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A prospective, multidisciplinary approach to understanding sport-related head trauma : novel insights… Wright, Alexander David 2017

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A PROSPECTIVE, MULTIDISCIPLINARY APPROACH TO UNDERSTANDING SPORT-RELATED HEAD TRAUMA: NOVEL INSIGHTS INTO THE EFFECTS ON MYELIN AND CEREBROVASCULAR FUNCTION by  Alexander David Wright  B.Sc. (Kinesiology), Simon Fraser University, 2009 M.Sc. (Kinesiology), University of Waterloo, 2011  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  May 2017  © Alexander David Wright, 2017   ii Abstract Sport-related concussion occurs at an alarmingly high rate, affecting millions each year. Concern is growing over the effects of repetitive subconcussive head trauma towards the development of long-term neurological deficits. There are calls within sports medicine to shift from symptom-based assessments towards reliable, objective tools to improve identification and management of dangerous levels of sport-related head trauma. The overall objective across the five studies of this thesis was to elucidate the roles of brain myelination and cerebrovascular dysfunction within this context. In study 1, myelin water imaging permitted the first direct evaluation of the effect of sport-related head trauma on myelin integrity. While transient post-concussion disruptions in myelin were observed for at least 2-weeks in multiple brain areas, no myelin changes were observed as a consequence of repetitive subconcussive trauma. Study 2 used transcranial Doppler ultrasound to assess the effects of concussion on indices of dynamic cerebral autoregulation (CA), demonstrating a delay in the CA response to blood pressure alterations persisting beyond symptom resolution that is suggestive of autonomic dysregulation of the cerebrovasculature; deficits did not appear to be cumulative across multiple injuries. Study 3 revealed detrimental effects of one season of contact sport participation on both the timing and magnitude of CA responses related to the degree of exposure to repetitive subconcussive head trauma. Study 4 assessed the effect of concussion on neurovascular coupling (NVC) dynamics within the artery supplying the occipital cortex following visual stimulation, and revealed delays in achieving peak response rate in concert with an elevated response magnitude acutely post-injury with resolution by 1-month; deficits did not appear to accumulate across multiple injuries. Study 5 revealed no changes in NVC dynamics as a function of exposure to one season of participation in contact or non-contact sport, suggesting subconcussive trauma may not impair   iii NVC. Collectively, these results suggest sport-related head trauma can impair myelin integrity and cerebrovascular function; the potential role for autonomic dysregulation towards these findings is discussed. While the effect of repetitive subconcussive trauma on susceptibility to injury remains unclear, the disruptions observed following acute concussion highlight the emerging distinction between clinical and physiological recovery.     iv Lay Abstract Lessening the health risks of sport-related head trauma requires a better characterization of the disruptions it causes to the brain, including microstructural structural damage and control of brain blood flow. Study 1 of this thesis showed concussions cause disruptions to the myelin sheath that surrounds brain fibers lasting at least two weeks after the injury. Studies 2-5 in this thesis show concussions, as well as exposure to head hits experienced just by playing hockey and football, may disrupt two important mechanisms controlling blood flow to the brain. Some disruptions in physiology after concussion may last longer than symptoms and / or outwardly observable behaviour, suggesting clinical and physiological recovery may be distinct. The potential role towards these findings for alterations in autonomic nervous system behaviour is discussed.      v Preface Chapter 2 is based on work conducted at the UBC MRI Research Centre by Dr. A. Rauscher and has been published: Wright AD, Jarrett M, Vavasour I, Shahinfard E, Kolind S, van Donkelaar P, Taunton J, Li D, Rauscher A (2016) Myelin water fraction is transiently reduced after a single mild traumatic brain injury – a prospective cohort study in collegiate hockey players. PLoS ONE 11(2): e0150215. AR, JT and DL designed the study. AR and DL designed the imaging protocol. MJ, ADW, IV, ES and SK performed data analysis under the supervision of AR. All authors interpreted the data. ADW, MJ and AR wrote the manuscript. ADW, MJ, and AR completed all revisions following reviewers’ comments and completed the final version accepted for publication. This study was approved by the University of British Columbia Clinical Research Ethics Board (H11-00423). Copyright approval was obtained from the Public Library of Science for reproduction of figures and text.     The methods used in Chapters 3-6 of this thesis were approved by the Clinical Research Ethics Board at the University of British Columbia, as part of a larger multidisciplinary study assessing the physiological effects of sport-related head trauma involving a variety of methods and hypotheses (H14-02996).  Data were collected at the University of British Columbia (Kelowna, BC) by Alexander D. Wright, Kelsey Bryk, Krista Fjeld, Jillian Dierijck, Kevin Bouliane, and Jonathan D. Smirl. In-season impact sensor data were collected by Alexander D. Wright and Kelsey Bryk.  A version of Chapter 3 has been submitted and is currently under review: Wright AD, Smirl JD, Bryk K, Fraser SK, van Donkelaar P (2017). A transcranial Doppler ultrasound-based evaluation   vi of the acute and cumulative effects of sport-related concussion on indices of dynamic cerebral autoregulation. This chapter describes work conducted in Kelowna, BC at the UBC Sport Concussion Research Lab. ADW and PvD designed the study. ADW, JDS, and KB performed data collection, and ADW, JDS, and SF performed the analyses. ADW and JDS interpreted the data. ADW wrote the manuscript. All authors had full access to the data, and helped to critically revise the manuscript before reviewing and approving the final version.    A version of Chapter 4 has been submitted and is currently under review: Wright AD, Smirl JD, Bryk K, Fraser SK, Jakovac M, van Donkelaar P (2017). A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on indices of dynamic cerebral autoregulation. This chapter describes work conducted in Kelowna, BC at the UBC Sport Concussion Research Lab. ADW and PvD designed the study. ADW, JDS, and KB performed data collection, and ADW, JDS, SF, and MJ performed the analyses. All authors interpreted the data. ADW wrote the manuscript. All authors had full access to the data, and helped critically revise the manuscript before reviewing and approving the final version.     A version of Chapter 5 has been submitted and is currently under revision: Wright AD, Smirl JD, Bryk K, van Donkelaar P (2017). A prospective transcranial Doppler ultrasound-based evaluation of the acute and cumulative effects of sport-related concussion on dynamics of the neurovascular coupling response. This chapter describes work conducted in Kelowna, BC at the UBC Sport Concussion Research Lab. ADW and PvD designed the study. ADW, JDS, and KB performed data collection. ADW performed the analyses, interpreted the data, and wrote the   vii manuscript. All authors had full access to the data, and helped critically revise the manuscript before reviewing and approving the final version.    A version of Chapter 6 has been submitted and is currently under review: Wright AD, Smirl JD, Bryk K, Jakovac M, van Donkelaar P (2017). A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on neurovascular coupling dynamics. This chapter describes work conducted in Kelowna, BC at the UBC Sport Concussion Research Lab. ADW and PvD designed the study. ADW, JDS, and KB performed data collection, and ADW and MJ performed the analyses. ADW interpreted the data and wrote the manuscript. All authors had full access to the data, and helped critically revise the manuscript before reviewing and approving the final version.        viii Table of Contents  Abstract .......................................................................................................................................... ii	Lay Abstract ................................................................................................................................. iv	Preface .............................................................................................................................................v	Table of Contents ....................................................................................................................... viii	List of Tables ................................................................................................................................ xv	List of Figures ............................................................................................................................. xvi	Glossary ...................................................................................................................................... xix	Acknowledgements .................................................................................................................... xxi	Dedication .................................................................................................................................. xxii	Chapter 1: Introduction to sport-related concussion .................................................................1	1.1	 Scope of the problem ......................................................................................................... 1	1.2	 Historical perspective ......................................................................................................... 3	1.2.1	 Earliest descriptions of concussive injury ................................................................... 3	1.2.2	 Defining and classifying concussion – evolution of the grading system era .............. 4	1.2.3	 Concussion in Sport Group meetings ......................................................................... 6	1.2.4	 Current working definition of sport-related concussion ............................................. 9	1.3	 Pathophysiology of sport-related concussion .................................................................. 10	1.3.1	 Biomechanical insult – the inciting force ................................................................. 10	1.3.1.1	 Repetitive head trauma and subconcussion ....................................................... 11	1.3.2	 Neurometabolic cascade of concussion .................................................................... 13	1.3.3	 White matter alterations following sport-related head trauma ................................. 14	  ix 1.3.3.1	 Limitations of diffusion tensor imaging ............................................................ 17	1.3.3.2	 Myelin water imaging ........................................................................................ 18	1.3.4	 Cerebral blood flow .................................................................................................. 21	1.3.4.1	 Anatomy of the cerebrovasculature ................................................................... 23	1.3.4.1.1	 Principles of transcranial Doppler ultrasound ............................................. 25	1.3.4.2	 Cerebrovascular reactivity to carbon dioxide .................................................... 29	1.3.4.2.1	 Alterations in CO2 reactivity following sport-related head trauma ............ 30	1.3.4.3	 Cerebral perfusion pressure and cerebral autoregulation ................................... 31	1.3.4.3.1	 CA disruptions in acquired brain injury / moderate-severe TBI ................. 33	1.3.4.3.2	 Alterations in CA following sport-related head trauma .............................. 33	1.3.4.3.3	 Transfer function analysis for characterizing dynamic CA ........................ 34	1.3.4.4	 Neurovascular coupling ..................................................................................... 36	1.3.4.4.1	 Multiple mechanisms contribute to the NVC response .............................. 38	1.3.4.4.2	 Characterizing NVC dynamics using transcranial Doppler ultrasound ...... 39	1.3.4.4.3	 Alterations in NVC dynamics following sport-related head trauma .......... 40	1.3.4.5	 Autonomic factors in cerebral blood flow regulation ........................................ 42	1.3.4.5.1	 Autonomic dysregulation following sport-related head trauma ................. 44	1.4	 Thesis objectives and summary of studies ....................................................................... 45	1.4.1	 Specific aims and hypotheses ................................................................................... 45	1.4.1.1	 Study 1 (Chapter 2) ............................................................................................ 45	1.4.1.2	 Study 2 (Chapter 3) ............................................................................................ 45	1.4.1.3	 Study 3 (Chapter 4) ............................................................................................ 46	1.4.1.4	 Study 4 (Chapter 5) ............................................................................................ 46	  x 1.4.1.5	 Study 5 (Chapter 6) ............................................................................................ 47	1.4.2	 Presentation ............................................................................................................... 47	Chapter 2: Myelin water fraction is transiently reduced after a single mild traumatic brain injury – a prospective cohort study in collegiate hockey players ............................................49	2.1	 Summary .......................................................................................................................... 49	2.2	 Introduction ...................................................................................................................... 50	2.3	 Methods............................................................................................................................ 54	2.3.1	 Study design .............................................................................................................. 54	2.3.2	 Myelin water imaging and processing ...................................................................... 55	2.3.3	 Statistical analysis ..................................................................................................... 56	2.4	 Results .............................................................................................................................. 57	2.5	 Discussion ........................................................................................................................ 61	2.6	 Conclusions ...................................................................................................................... 69	Chapter 3: A transcranial Doppler ultrasound-based evaluation of the acute and cumulative effects of sport-related concussion on indices of dynamic cerebral autoregulation ..............................................................................................................................70	3.1	 Summary .......................................................................................................................... 70	3.2	 Introduction ...................................................................................................................... 71	3.3	 Methods............................................................................................................................ 73	3.3.1	 Study design .............................................................................................................. 73	3.3.2	 Instrumentation ......................................................................................................... 74	3.3.3	 Experimental protocols ............................................................................................. 75	3.3.4	 Data processing and transfer function analysis ......................................................... 75	  xi 3.3.5	 Statistical analyses .................................................................................................... 76	3.3.5.1	 Effect of acute concussion ................................................................................. 76	3.3.5.2	 Cumulative effects of multiple previous concussions ....................................... 78	3.4	 Results .............................................................................................................................. 78	3.4.1	 Effect of acute concussion ........................................................................................ 78	3.4.2	 Cumulative effects of multiple previous concussions .............................................. 81	3.5	 Discussion ........................................................................................................................ 83	3.5.1	 Cerebral blood flow alterations post-concussion ...................................................... 83	3.5.2	 CA impairments in traumatic brain injury ................................................................ 84	3.5.3	 Possible mechanisms for CA impairments following concussion ............................ 85	3.5.4	 Limitations ................................................................................................................ 86	3.6	 Conclusion ....................................................................................................................... 88	Chapter 4: A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on indices of dynamic cerebral autoregulation ....89	4.1	 Summary .......................................................................................................................... 89	4.2	 Introduction ...................................................................................................................... 90	4.3	 Methods............................................................................................................................ 91	4.3.1	 Study design .............................................................................................................. 91	4.3.2	 Instrumentation ......................................................................................................... 92	4.3.3	 Experimental protocols ............................................................................................. 93	4.3.4	 Data processing ......................................................................................................... 94	4.3.5	 Impact monitoring ..................................................................................................... 96	4.3.6	 Statistical analyses .................................................................................................... 97	  xii 4.4	 Results .............................................................................................................................. 97	4.4.1	 Effect of exposure to repetitive subclinical head impacts ........................................ 98	4.5	 Discussion ...................................................................................................................... 101	4.5.1	 Physiological disruptions following repetitive subconcussive trauma ................... 102	4.5.2	 Disruptions in control of cerebral blood flow following subconcussive trauma .... 103	4.5.3	 Autonomic role for subconcussion-induced impairments in CA ............................ 104	4.5.4	 Evidence linking head impact exposure with physiological disruption .................. 105	4.5.5	 Limitations .............................................................................................................. 106	4.6	 Conclusion ..................................................................................................................... 107	Chapter 5: A prospective transcranial Doppler ultrasound-based evaluation of the acute and cumulative effects of sport-related concussion on dynamics of the neurovascular coupling response .......................................................................................................................108	5.1	 Summary ........................................................................................................................ 108	5.2	 Introduction .................................................................................................................... 109	5.3	 Methods.......................................................................................................................... 111	5.3.1	 Study design ............................................................................................................ 111	5.3.2	 Instrumentation ....................................................................................................... 112	5.3.3	 Experimental protocols ........................................................................................... 113	5.3.4	 Data processing ....................................................................................................... 113	5.3.5	 Statistical analyses .................................................................................................. 114	5.3.5.1	 Effect of acute concussion ............................................................................... 116	5.3.5.2	 Cumulative effects of multiple previous concussions ..................................... 116	5.4	 Results ............................................................................................................................ 116	  xiii 5.4.1	 Effect of acute concussion ...................................................................................... 116	5.4.2	 Cumulative effects of multiple previous concussions ............................................ 120	5.5	 Discussion ...................................................................................................................... 123	5.5.1	 Cerebral blood flow alterations following sport-related concussion ...................... 124	5.5.2	 Mechanisms underlying the neurovascular coupling response ............................... 125	5.5.3	 Functional magnetic resonance imaging in concussion .......................................... 126	5.5.4	 Possible mechanisms for observed effects of acute concussion ............................. 128	5.5.5	 Limitations .............................................................................................................. 129	5.6	 Conclusion ..................................................................................................................... 130	Chapter 6: A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on neurovascular coupling dynamics .................131	6.1	 Summary ........................................................................................................................ 131	6.2	 Introduction .................................................................................................................... 132	6.3	 Methods.......................................................................................................................... 134	6.3.1	 Study design ............................................................................................................ 134	6.3.2	 Instrumentation ....................................................................................................... 135	6.3.3	 Experimental protocols ........................................................................................... 136	6.3.4	 Data processing ....................................................................................................... 136	6.3.5	 Impact monitoring ................................................................................................... 137	6.3.6	 Statistical analyses .................................................................................................. 138	6.4	 Results ............................................................................................................................ 138	6.5	 Discussion ...................................................................................................................... 143	6.5.1	 Mechanisms underlying the neurovascular coupling response ............................... 144	  xiv 6.5.2	 Evidence of functional changes following subconcussive trauma ......................... 145	6.5.3	 Biomechanical characteristics of subconcussive trauma ........................................ 146	6.5.4	 Limitations .............................................................................................................. 147	6.6	 Conclusions .................................................................................................................... 148	Chapter 7: Conclusion. ..............................................................................................................150	7.1	 Overview ........................................................................................................................ 150	7.2	 Future directions ............................................................................................................ 157	7.3	 Conclusion and significance .......................................................................................... 161	Bibliography ...............................................................................................................................163	   xv List of Tables Table 1-1. Comparison of four main definitions of mild traumatic brain injury ............................ 5	Table 1-2. Summary of three primary concussion-grading scales .................................................. 6	Table 2-1. Demographic characteristics of all athletes undergoing myelin water imaging .......... 58	Table 3-1. Participant characteristics: demographics, SCAT3 performance, and resting physiological parameters during each test session for acutely concussed athletes ........... 74	Table 4-1. Participant characteristics: demographics, SCAT3 performance, and resting physiological parameters for contact sport and control (non-contact sport) athletes at preseason and post-season ................................................................................................ 93	Table 4-2. Summary of biomechanical variables describing head impact exposure in contact sport athletes across one athletic season ........................................................................... 99	Table 5-1. Participant characteristics: demographics, SCAT3 performance, return-to-play duration, and resting physiological parameters during each test session for acutely concussed athletes. .......................................................................................................... 112	Table 5-2. Summary of responses to visual stimulation for secondary physiological variables 120	Table 6-1. Participant characteristics: demographics, SCAT3 performance, and resting physiological parameters for contact sport and control (non-contact sport) athletes at preseason and post-season .............................................................................................. 135	Table 6-2. Summary of biomechanical variables describing head impact exposure in contact sport athletes across one athletic season ......................................................................... 140	Table 6-3. Summary of responses to visual stimulation for secondary physiological variables. 143	  xvi List of Figures Figure 1-1. Diagram outlining the acute cellular processes proposed to occur during the neurometabolic cascade of concussion ............................................................................. 14	Figure 1-2. Schematic representation of fiber orientation in four hypothetical voxels illustrating the insensitivity of diffusion tensor imaging metrics ........................................................ 18	Figure 1-3. T2 distribution from human white matter ................................................................... 19	Figure 1-4. Example of a myelin water fraction map in a healthy brain obtained using T2-relaxation based myelin water imaging ............................................................................ 21	Figure 1-5. Three-dimensional cutaway schematic showing a cervical ICA loop and the intracranial course of the ICA ........................................................................................... 24	Figure 1-6. Schematic of the cerebral arterial system ................................................................... 26	Figure 1-7. Picture of the TCD face showing depth of blood velocity signals oriented towards and away from the probe, velocity profile at selected depth ............................................ 27	Figure 1-8. Schematic demonstrating insonation of left posterior cerebral artery and right middle cerebral artery ................................................................................................................... 28	Figure 1-9. Schematic illustration of the components of the neurovascular unit from the level of capillaries to pial arterioles ............................................................................................... 37	Figure 2-1: Representative myelin water fraction maps from a concussed athlete at baseline and two weeks post-injury ....................................................................................................... 59	Figure 2-2. Relative myelin water fraction change post-concussion ............................................ 60	Figure 2-3. Brain areas with significantly reduced myelin water fractionin athletes with concussion at two weeks post-injury ................................................................................ 61	  xvii Figure 3-1. Representative time-series profiles for blood pressure, middle cerebral artery blood velocity, and expired carbon dioxide during squat-stand manoeuvres performed at 0.05 Hz and 0.10 Hz .................................................................................................................. 77	Figure 3-2. Normalized power spectra for mean arterial pressure and middle cerebral artery blood velocity during squat-stands at 0.05 Hz and 0.10 Hz at: preseason and post-concussion preseason; presesaon in subjects with zero versus three or more previous concussions ....................................................................................................................... 79	Figure 3-3: Summary of transfer function analysis outcomes in acutely concussed athletes. ...... 80	Figure 3-4. Summary of preseason autoregulatory outcomes from transfer function analysis for athletes with zero versus three or more previous concussions .......................................... 82	Figure 4-1. Representative time-series profiles for blood pressure, middle cerebral artery blood velocity, and expired carbon dioxide during squat-stand manoeuvres performed at 0.05 Hz and 0.10 Hz .................................................................................................................. 95	Figure 4-2. Photo of a participant wearing an impact sensor on the right mastoid process ......... 96	Figure 4-3. Normalized power spectra for mean arterial pressure and middle cerebral artery blood velocity during squat-stands at preseason and post-season in contact sport athletes and non-contact sport control athletes .............................................................................. 98	Figure 4-4. Effects of subconcussive trauma on autoregulatory outcomes derived from transfer function analysis during squat-stand manoeuvres performed at 0.05 Hz and 0.10 Hz ... 100	Figure 5-1. Representative traces of changes in posterior cereral artery blood velocity, middle cerebral artery blood velocity, mean arterial pressure, and end-tidal partial pressure of CO2 during one trial of the neurovascular coupling task ................................................ 115	  xviii Figure 5-2. Time-series profiles of physiological variables – averaged across subjects – at each pre- and post-concussion time point following visual stimulation ................................. 117	Figure 5-3. Summary of posterior cerebral artery neurovascular coupling responses to visual stimulation at preseason and each post-concussion time point ....................................... 118	Figure 5-4. Summary of middle cerebral artery neurovascular coupling responses to visual stimulation at preseason and each post-concussion time point. ...................................... 119	Figure 5-5. Preseason time-series profiles for changes in physiological variables following visual stimulation – averaged across participants with zero versus three or more prior concussions ..................................................................................................................... 121	Figure 5-6. Summary of preseason posterior cerebral artery neurovascular coupling responses to visual stimulation across participants with zero versus three or more prior concussions122	Figure 5-7. Summary of preseason middle cerebral artery neurovascular coupling responses to visual stimulation across participants with zero versus three or more prior concussions123	Figure 6-1. Representative traces of changes in posterior cerebral artery blood velocity, middle cerebral artery blood velocity, mean arterial presure, and end-tidal partial pressure of CO2 to visual stimulation during one trial of the neurovascular copuling task ...................... 139	Figure 6-2. Average time-series profiles for changes in physiological variables to visual stimulation at preseason and post-season in contact and non-contact sport athletes ...... 140	Figure 6-3. Summary of posterior cerebral artery neurovascular coupling responses to visual stimulation at preseason and post-season in contact and non-contact sport athletes ...... 141	Figure 6-4. Summary of middle cerebral artery neurovascular coupling responses to visual stimulation at preseason and post-season in contact and non-contact sport athletes ...... 142	   xix Glossary Symbol Definition (units) ∆ Delta, change in the suffixed parameter AD Axial diffusivity ANOVA Analysis of variance ASL Arterial spin labelling AUC25 Area-under-the-curve to 25 seconds (cm) BESS Balance error scoring system BMI Body mass index (kg/m2) BOLD Blood oxygen level dependent BP Blood pressure CA Cerebral autoregulation 95%CI 95% confidence interval CBF Cerebral blood flow CBFv Cerebral blood flow velocity (cm/s) CC Corpus callosum CO2 CSF Carbon dioxide Cerebrospinal fluid cPLA Cumulative peak linear acceleration (g) cPRA Cumulative peak rotational acceleration (rad/s2) CT Computed tomography DAI Diffuse axonal injury DLPFC Dorsolateral prefrontal cortex DTI Diffusion tensor imaging ECG Electrocardiogram FA Fractional anisotropy fMRI Functional magnetic resonance imaging HIC Head injury criterion HITS Head Impact Telemetry System™ HR Heart rate (beats/min) ICA Internal carotid artery   xx ICP Intracranial pressure (mmHg) LF:HF Low frequency to high frequency power ratio MAP Mean arterial pressure (mmHg) MBP Myelin basic protein MCA  Middle cerebral artery MCAv Middle cerebral artery blood velocity (cm/s) MD Mean diffusivity MRI Magnetic resonance imaging mTBI Mild traumatic brain injury MWF Myelin water fraction (%) MWI Myelin water imaging NAA N-acetyl-aspartate NVC Neurovascular coupling O2 Oxygen PCA  Posterior cerebral artery PCAv Posterior cerebral artery blood velocity (cm/s) PCO2 Partial pressure of carbon dioxide (mmHg) PCS Post-concussion syndrome PETCO2 End-tidal partial pressure of carbon dioxide (mmHg) PLA Peak linear acceleration (g) PRA Peak rotational acceleration (rad/s2) RD Radial diffusivity SAC Standardized Assessment of Concussion™ SCAT Sport Concussion Assessment Tool™ SD Standard deviation SEM Standard error of the mean SRC Sport-related concussion  TBI Traumatic brain injury TBSS Tract-based spatial statistics TCD Transcranial Doppler ultrasound TFA vmax Transfer function analysis    xxi Acknowledgements Despite the fact that my name alone is listed on the title page, this thesis would not have been possible without many others. I offer my enduring gratitude to all members of the Sport Concussion Research Lab, with particular thanks to Jonathan Smirl, Mike Kennefick, and Kelsey Bryk for their contributions to this work and to my overall doctoral experience. Thank you to all of the teams with whom we have worked, especially Mike Bois and the West Kelowna Warriors. I am grateful to have received substantial financial support during my doctoral program from the Vanier Canada Scholarship Program, the Canadian Institutes for Health Research, the O’Brien Foundation, the UBC Faculty of Medicine, and the UBC MD/PhD Program. I must also thank Jane Lee, Virginia Grossman, Carri Folk, as well as Drs. L Raymond and V. Duronio for your practical and emotional support in navigating the challenges of being the first student completing the MD/PhD program outside of Vancouver. I owe many thanks to my supervisory committee – Drs. C. Wellington, A. Rauscher, P. Ainslie, and P. van Donkelaar – for your mentorship and support, for providing coherent answers to my oft-incoherent questions, and for enlarging my vision of science and academic medicine. My success thus far is a function of the love, guidance, and emotional and financial support provided by my family. My mother, father, and sister have always supported my pursuits, academic and otherwise, without hesitation or question. You often tell me of how proud you are, but I too am so proud to be able to call you family. To my daughter, Ella, your kind soul and adventurous spirit are contagious; coming home to you each day fills my world in ways you cannot yet understand. I am so excited to watch you grow into a strong and beautiful woman. To my wife, Kari, I owe you endless gratitude for your love, support, and patience over the past 8 years. Amazingly, we are still but at the beginning of our exciting journey together, Gallivanting through life as partners-in-crime. I love you.   xxii Dedication For Ella Be a free thinker and don’t accept everything you hear as truth – be critical and evaluate what you believe in. - Aristotle      1 Chapter 1: Introduction to sport-related concussion Concussion has existed for centuries as a clinical entity, but scientific understanding and public awareness around this complex traumatic brain injury (TBI) has dramatically accelerated over the last decade. Sport-related head injury remains one of the most poorly understood injuries in the fields of sports medicine and neuroscience (1,2). Only recently has the perfect storm been set: the combination of intense public interest, advanced clinical techniques, and more comprehensive research approaches have shaped today’s “collective cultural focus on sports concussion” (3). Despite this widespread attention, many questions remain; the research question that guides this thesis is: what are the roles for disruptions to brain myelination and to control of cerebral blood flow towards the symptoms and deficits in neurocognitive function observed with exposure to sport-related head trauma?   1.1 Scope of the problem Sport-induced head trauma occurs at an alarmingly high rate – recent reports estimate the annual incidence of sport-related concussion at 1.1-1.8 million in US youth alone (4). According to the Centers for Disease Control and Prevention, the concussion problem has reached epidemic levels (5). Estimates of the prevalence of sport-related concussion in adolescent contact sport athletes range from 10-25% (6,7). Concerningly, these estimates are thought to drastically underrepresent the true injury burden as the majority of concussed individuals do not report for medical attention; for example, it has been estimated that up to 53% of high school football players do not report concussion symptoms (8) and consequently go undocumented.    2 Management of concussion is based primarily on resolution of athlete-reported symptoms (9). The Canadian Paediatric Society has outlined the need for more objective tools to improve initial diagnoses, guide management, and inform decisions regarding appropriate timing for athletes to return-to-learn and return-to-play (10). Intentional underreporting of symptoms in order to expedite return-to-play increases the risk for further concussions and longer-term consequences associated with repetitive head trauma (11-14). While 80-90% of concussions resolve in 7-10 days, a subset of individuals battle persistent disability for months to years (9). Emerging evidence also suggests a link between clinically-manifest concussions, repetitive sub-clinical head impacts, and the development of long-term neurodegeneration termed chronic traumatic encephalopathy (15). Furthermore, there is a growing evidence base supporting a link between repetitive subconcussive trauma specifically, and impairments in various aspects of brain structure and function including learning (16), cerebral blood flow regulation (17-19), functional brain connectivity (20-22), gray matter density and volume (23), and diffusion properties in white matter tracts (24-26). Long-lasting effects of sport-related head trauma may include problems with affect regulation, attention, memory, and depression (15). Collectively, the persistent physiological effects of sport-related head trauma in combination with the heavy reliance on symptom reporting for patient management emphasize the pressing need to develop objective techniques to identify, treat, and manage dangerous levels of head trauma towards minimizing the burden of injury at an individual and population level. Despite the recent surge in clinical, academic, and public attention to concussion, the problem is a historical one.     3 1.2 Historical perspective 1.2.1 Earliest descriptions of concussive injury The earliest clinical description of concussion as a mild brain injury characterized by an alteration in physiologic state rather than more severe structural brain injury was proposed by the Persian physician Rhazes (AD 850-923) in the 10th century, representing a “critical turning point in … the understanding of [concussion]” (27). Lanfrancus (d. 1306) made particular note of the transient nature of concussion symptoms, hypothesizing them to be a consequence of a functional paralysis caused by the brain being shaken. In doing so, he was the first to distinguish between commotio cerebri (shaking of the brain) and contusio cerebri (involving structural damage). In the early 1500s, Berengario da Carpi postulated commotio cerebri caused cortical tissue to be pressed against the solid skull (da Carpi 1535, Abbott 1961, and Flamm 1996 in (27)), an idea that was expanded upon by Ambroise Paré in his Workes in which he extensively described “the moving or concussion of the brain” and considered “commotion” to be a disorder of brain movement (Paré 1579 in (27)). Many clinical insights were documented over the subsequent ~100 years, including descriptions of lethargy, vertigo, tinnitus, as well as disturbances of balance, sleep, and emotions following concussive injury (27). Queyrat (17th century) furthered the commotio cerebri hypothesis, adding that concussion was not the result of a single brain movement, but rather from oscillatory movement of the brain within the skull (Queyrat 1657 in (27)). The invention of the microscope in 1694 permitted the earliest hypotheses into the pathological consequences of concussion, which ranged from vascular causes to neuronal shock. A case study reported by Littre in 1705 generated the first hypothesis that concussion caused circulatory failure and cerebral venous congestion, ultimately irritating the brain. His observations led to the theory that head impacts causing deformation of the skull could   4 redistribute blood and lead to an underperfusion (“anemia”) in the underlying gray matter (Littre 1705 in (27)). Despite many theories, the prevailing view on concussions by the late 1700s entailed that such injuries were not accompanied by structural brain injury – an idea that has only been challenged in the 21st century.  1.2.2 Defining and classifying concussion – evolution of the grading system era The term concussion remains poorly defined in both clinical and research realms, and debate continues as to whether the term can and / or should be used interchangeably with mild traumatic brain injury (mTBI).  The earliest proposal for a consensus definition of concussion or mTBI came in 1966, when the Congress of Neurological Surgeons defined concussion as “a clinical syndrome characterized by immediate and transient impairment of neural functions, such as alteration of consciousness, disturbance of vision, equilibrium, etc. due to mechanical forces.” (28). Four definitions of mTBI have subsequently been adopted by groups including the American Congress of Rehabilitation Medicine (ACRM) (29), the American Academy of Pediatrics (AAP) (30), the Centers for Disease Control and Prevention (CDC) (31), and the World Health Organization (WHO) (32). Each of these definitions places emphasis – to differing degrees – on loss of consciousness (LOC), post-traumatic amnesia (PTA), mental status, and neurological signs (Table 1-1).        5 Table 1-1 Comparison of four main definitions of mild traumatic brain injury. Source Etiology LOC PTA Mental Status Neurological Signs Other ACRM A traumatically induced physiological disruption of brain function ≤ 30 mins ≤ 24 h Any alteration in mental status at time of injury May or may not be transient Initial GCS of 13-15 CDC Injury to the head resulting from blunt trauma or acceleration / deceleration ≤ 30 mins Observed / self-reported dysfunction of memory around the time of injury Observed / self-reported transient confusion, disorientation, or impaired consciousness Observed signs of other neurological or neuropsychological dysfunction (seizures, irritability, lethargy, nausea / vomiting) Not specified WHO An acute brain injury resulting from mechanical energy to the head from external physical forces ≤ 30 mins ≤ 24 h Confusion and disorientation Transient neurological abnormalities (focal signs, seizure, intracranial lesion not requiring surgery) GCS 13-15 after 30 minutes must not be due to drugs / alcohol / medications / other injuries AAP Not specified ≤ 1 min Not specified Normal mental status at time of initial evaluation None at exam, but may have seizures, emesis, headache, lethargy immediately following injury No evidence of skull fracture ACRM = American Congress of Rehabilitation Medicine; CDC = Center for Disease Control and Prevention; WHO = World Health Organization; AAP = American Academy of Pediatrics; LOC = loss of consciousness; PTA = post-traumatic amnesia; GCS = Glasgow coma scale  As a diagnostic term, “concussion” is unsurprisingly used more frequently in the sports medicine community, while “mTBI” may be preferred by other medical specialties (33). For the purposes of this thesis, concussion will be as assumed to represent a variant at the mildest end of the mTBI spectrum.     6 Within the sports medicine setting, three prominent grading systems evolved during the late 20th century in an effort to stratify concussions based on acute injury characteristics. These scales – the Cantu Evidence-based Grading System (34), the Colorado Medical Society Guidelines (35), and the American Academy of Neurology Guidelines (36) – all described concussion as a transient abnormality of neurological function and relied heavily on LOC and PTA to classify injury severity (Table 1-2). Each of these scales also permitted concussed athletes to return-to-play on the same day in certain situations.   Table 1-2. Summary of three primary concussion-grading scales Severity Colorado Medical Society (1991) Cantu Grading System (2001) American Academy of Neurology (1999) Grade 1 (mild) • Transient mental confusion • No PTA • No LOC • No LOC • Either PTA or post-concussion SSx clear in ≤ 30 mins • NO LOC • Transient confusion • Post-concussion SSx clear in ≤ 15 mins Grade 2 (moderate) • No LOC • Confusion with PTA • LOC lasting ≤ 1min and PTA or • Post-concussions SSx > 30 mins but ≤ 24 hrs • No LOC • Post-concussion SSx > 15 mins Grade 3 (severe) • Any LOC, however brief • LOC > 1 min • PTA > 24 hrs • Post-concussion SSx > 7 days • Any LOC, either brief or prolonged PTA = post-traumatic amnesia; LOC = loss of consciousness; SSx = signs and symptoms  1.2.3 Concussion in Sport Group meetings In 2001, the first meeting of the International Consensus Group on Concussion in Sport (CISG) was held in Vienna. This meeting brought together an international panel of experts in basic and clinical science, epidemiology, cognitive assessment, protective equipment, research methods, and injury management and prevention, with the expressed aim of providing recommendations for improving the health and safety of athletes who suffer concussions (37). This landmark   7 meeting led to a new definition of concussion as well as the first widely accepted concussion protocol to be followed by those caring for concussed athletes on the basis of tolerance to graded physical exertion guided by symptom exacerbation. Existing concussion grading scales were acknowledged and abandoned based on limited evidence relating injury severity with the number / duration of acute symptoms and / or degree of impairment on neuropsychological testing (37). Importantly, the CISG recommended an individualized management approach to assess injury severity and tailor return-to-play decisions based on the specific patient profile, with an emphasis on the importance of neuropsychological testing as a cornerstone of concussion evaluation (37). An important idea that was raised included the potential that concussion does not follow a linear spectrum of injury severity, but rather there may exist multiple subtypes of concussion, including differences in clinical manifestation, anatomical localization, biomechanical impact profile, genetic phenotype, and structural versus no structural injury (37).  The second CISG meeting was held in Prague in 2004 and led to the development of the Sport Concussion Assessment Tool (SCAT), a standardized form to be used for patient education and sideline injury screening (38). The concussion protocol was modified to include “cognitive rest” to limit mental exertion while symptomatic. The major change evolving from this meeting entailed the classification of “simple” versus “complex” concussions for management purposes, distinguished primarily by the presence of persistent symptoms, prolonged LOC, or prolonged cognitive impairment. It was suggested that management of complex concussions include formal neuropsychological testing in a multidisciplinary setting, whereas it was not regarded as important in evaluating simple concussions. This meeting also marked the first formal   8 recommendation that baseline cognitive and symptom evaluation be performed prior to participation, regardless of age of performance level.   Major changes in recommendations from the 3rd meeting of the CISG, held in Zurich in 2008, included abandoning the complex versus simple classification scheme, after it was found that such terminology was not adequately descriptive (39). For the first time, a range of modifying factors were formally identified that may influence management and prognostic expectations for concussed patients, including the frequency and timing of multiple concussive injuries, decreasing impact threshold required to cause additional concussions, progressively slower recovery from additional injury, age, prolonged LOC, and psychiatric pre-/co-morbidities. The SCAT was amended to include an assessment of balance using the modified Balance Error Scoring System (BESS), as well as an upper limb motor coordination task.   The first unanimous agreement that return-to-play should not occur on the same day as concussive injury arose at the 4th CISG meeting in 2012. Additional attention was dedicated to concussion in children, with the first suggestion that the child/adolescent athlete must first successfully return-to-school before being allowed to return-to-play. Furthermore, the first child SCAT was introduced for use in individuals aged 5-12.   A noticeable trend that has developed across the various CISG meetings entails recommendations that are gradually more cautious and conservative towards the management of concussion at all levels, based on the growing understanding that structural and physiological deficits may occur with subconcussive trauma and may persist even after symptoms and   9 cognitive deficits have resolved clinically (40-45). At the most recent CISG meeting – held in October 2016 (statement not yet published) – an entire session was devoted to discussing the importance and timeline of physiological recovery. Indeed, the field is calling for a shift away from symptom-based concussion assessments towards structured physical examinations rooted in evaluations of physiologic function (46).  1.2.4 Current working definition of sport-related concussion The operational definition of sport-related concussion used in this thesis was adopted from the 4th International Consensus Statement on Concussion in Sport, which defined concussion as a brain injury representing a “complex pathophysiological process affecting the brain, induced by biomechanical forces”, and describes several common features (9): “1. Concussion may be caused either by a direct blow to the head, face, neck or elsewhere on the body with an ‘impulsive’ force transmitted to the head.  2. Concussion typically results in the rapid onset of short-lived impairment of neurological function that resolves spontaneously. However, in some cases, symptoms and signs may evolve over a number of minutes to hours.  3. Concussion may result in neuropathological changes, but the acute clinical symptoms largely reflect a functional disturbance rather than a structural injury and, as such, no abnormality is seen on standard structural neuroimaging studies.  4. Concussion results in a graded set of clinical symptoms that may or may not involve loss of consciousness. Resolution of the clinical and cognitive symptoms   10 typically follows a sequential course. However, it is important to note that in some cases symptoms may be prolonged. The majority of concussions are thought to resolve clinically in a 7-10 day period, though a subset of individuals may experience symptoms and dysfunction for months to years.”  1.3 Pathophysiology of sport-related concussion Concussions and other forms of TBI are thought to involve primary, secondary, and tertiary injury phases. The primary injury phase is characterized by the translation of kinetic energy to the head, either directly or indirectly, at the moment of impact. The secondary injury phase describes the subsequent pathophysiological processes occurring within the brain and includes immediate and delayed cellular events. The tertiary injury phase entails the growing appreciation for the persistent abnormalities in cerebral structure and function that may accompany sport-related head trauma (40).  1.3.1 Biomechanical insult – the inciting force As outlined in the working definition in Section 1.2.4, concussions are the result of a direct or indirect biomechanical insult to the head, and myriad studies have attempted to delineate a relationship between the characteristics of concussion-causing head impacts and clinical outcomes. Though the exact pathway between mechanical insult and subsequent pathology is not definitively known, forces imparted on the head cause acceleration-deceleration of the brain within the rigid cranium, creating diffuse tensile, compressive, and shear strains in the brain tissue. Finite element modeling studies have shown peak strains during concussive impacts to   11 occur at the level of the brainstem, with suggestions that forces imparted to the mesencephalon, corpus callosum, and fornix may be responsible for concussion symptoms (47). Much of the biomechanical research on concussion has focused on defining thresholds for predicting injury diagnosis on the basis of the severity of concussive impacts, often characterized by peak linear and rotational acceleration of the head following impact (47-50). However, these approaches have proven unfruitful, as concussions frequently occur well below proposed thresholds (51,52), and repetitive lower severity, subconcussive head trauma can also lead to progressive impairments in brain function (further described in Section 1.3.1.1). In a prospective study of 88 collegiate American football players over 5 seasons, no relationships were observed between impact magnitude or location and diagnosed concussion, changes in postural stability, cognitive performance, or symptom-reporting (52). Declines in performance on neuropsychological tests acutely post-injury were not correlated with any biomechanical variables describing impact exposure, including the total number of impacts, peak or cumulative linear acceleration, peak or cumulative rotational acceleration, time from game start until injury, or time from previous impact (51). Overall, it is clear that the role of biomechanical parameters describing head impact exposure towards predicting concussion diagnosis is not straightforward, and may be influenced by exposure to repetitive lower severity trauma (48).    1.3.1.1 Repetitive head trauma and subconcussion Recently, increasing concern has been raised over the potential for repetitive concussive and subconcussive head trauma to impart long-term neurological consequences including chronic traumatic encephalopathy (CTE) (15,40,53-55). As many as 16% of pathologically confirmed cases of CTE occurred in individuals with no reported history of concussion (15,53). In a recent   12 study of deceased amateur athletes and controls, a history of involvement in contact sports was reported as the greatest risk factor for CTE neuropathology (54). While a direct cause-and-effect relationship between repetitive head trauma and CTE has not yet been established, these findings nevertheless highlight the reason for growing concern over the potential long-term risks of subconcussive trauma.  Subconcussive head impacts are defined as trauma not resulting in signs or symptoms typical of a concussion (40,56), although their effects on the vulnerability of the brain to concussive injury and long-term neurodegenerative changes is unclear. Clinically, various metrics describing head impact exposure have been linked to later-life disturbances in cognitive and neurobehavioural function, including age of first exposure to American football (57,58), duration of participation in contact sports (15,59,60), and concussion history (61-64). Multiple studies have shown repetitive subconcussive trauma can induce deficits in brain structure and function that are associated with the degree of impact exposure (20,22,25,26,65-72). Human and animal studies have reported cumulative subconcussive impacts to be associated with axonal injury and damage to the blood-brain barrier (22,59,66,73-77).   Limited evidence exists to suggest head impact thresholds may exist for elevated risk of long-term changes in brain structure and function (25,72). A recent study demonstrated a threshold dose-response relationship between estimated cumulative head impact exposure from playing high school or collegiate American football and risk for later-life deficits in cognition, executive function, depression, anxiety, apathy, and behavioral dysregulation (72). Clinically meaningful impairments across all domains were elevated after a threshold of ~2000 hits, and increased   13 linearly with every ~1000 hits thereafter – equating to roughly two seasons of participation. Lipton and colleagues similarly estimated a threshold of 1800 head impacts in the context of soccer heading toward elevated risk of memory impairment (25). However, the threshold for alterations in white matter microstructure were much lower, ranging from 885-1550 hits depending on the brain region, suggesting structural changes may accrue prior to overtly manifest cognitive and behavioural impairments. It is clear that repetitive subconcussive head impacts have the potential to detrimentally affect the brain. The pathophysiological mechanisms underlying such changes are not clear, but likely are similar to those involved in clinically manifest concussion.   1.3.2 Neurometabolic cascade of concussion Current paradigms describing the underlying pathophysiology of concussion depict a complex post-injury series of events contributing to secondary and tertiary injury mechanisms. This “neurometabolic cascade” involves indiscriminate glutamate release and ionic flux, leading to a state of elevated glycolytic demand in an attempt to preserve ionic gradients (Figure 1-1). The ensuing hypermetabolic state is thought to lead to an energy crisis, involving failure of ATP pumps, mitochondrial dysfunction, and sequestration of calcium, ultimately leading to cytoskeletal damage (78,79). While primary axotomy is often observed following high magnitude head impacts associated with more severe traumatic brain injuries, the axonal pathology observed following concussion is thought to develop over days to weeks following the initial insult (78,80,81).    14  Figure 1-1. Diagram outlining the acute cellular processes proposed to occur during the neurometabolic cascade of concussion. Fig 1 in (79). Image reproduced with permission from Neurosurgery.  1.3.3 White matter alterations following sport-related head trauma Although concussions have long been regarded as a strictly functional disturbance of the brain without any concomitant structural brain damage (Section 1.2.1), recent evidence has challenged this assumption. Myelin is becoming recognized as an important player in the pathophysiology of TBI, though its role is poorly understood (82-84). Myelin plays a fundamental role in the health and function of axons, serving as a primary determinant of conduction velocity during propagation of action potentials. It has been estimated myelinated axons are up to 70 times more   15 metabolically efficient than unmyelinated axons (85), highlighting an important role for myelin in neuronal metabolism. Furthermore, recent work has implicated an important role for oligodendrocyte precursor cells in promoting blood-brain barrier integrity (86). Glutamate excitotoxicity, intracellular calcium overload, mitochondrial dysfunction, oxidative stress, and inflammation –all components of the post-concussion neurometabolic cascade (Section 1.3.2) – have all been recognized as significant causes of damage to both myelin integrity and oligodendrocytes (84,87).   Increasingly, evidence suggests damage to either myelin or the axon can lead to subsequent damage to the other (84,88). Impaired axonal transport after concussive injury leads to swellings within the axon containing organelles and other transport materials, creating a ripe environment for secondary axonal disconnection and Wallerian degeneration (78,89). Histopathologically, these processes have been documented in brain slices as axonal bulbs, irregular tortuous axonal varicosities, and small globoids of degraded myelin sheath (82,90,91). Experimental work has demonstrated that accumulative oxidative stress in the context prolonged cerebral hypoperfusion – which evidence suggests may occur following concussion (Section 1.3.4) – suppresses the differentiation of oligodendrocyte precursor cells to oligodendrocytes and leads to reduced myelin content (92). Thus, loss of oligodendrocytes and corresponding demyelination of affected axons is anticipated following traumatic injury (83,84,93). Whether the result of direct, multifocal primary traumatic axonal injury or secondary axotomy, subsequent axonal degeneration is a possible outcome. However, axonal damage and myelin disruption may be reversible (82,83). In contrast to situations where strain is focally applied (e.g. at anatomic boundaries), strains distributed more diffusely along the length of an axon create an elongated   16 pattern of axonal swelling, which may be more amenable to intrinsic repair mechanisms (78). Finite element models have implicated tensile elongation as a primary mechanism of traumatic axonal injury (94). While various studies in animal models have outlined myelin fragmentation and degradation following traumatic axonal injury (82,95), dynamic in-vivo myelin changes have not been directly observed in the concussed human brain.  Advanced MRI-based neuroimaging techniques like diffusion tensor imaging (DTI) have provided valuable insight into the effects of sport-related head trauma on white matter microstructure. DTI is sensitive to diffusion properties of the various tissues within the brain, and has frequently been used as an indirect marker of myelin integrity in concussion research. Within cortical white matter, the highly ordered nature of neurofibrils, axonal membrane, and myelin sheath cause water to preferentially diffuse along the length of the axons as opposed to perpendicularly. This asymmetrical pattern of water movement is termed anisotropic diffusion (96) and is quantifiable on a voxel-wise basis using DTI as fractional anisotropy (FA). While a multitude of reports have demonstrated diffusivity changes following sport-related head trauma (reviewed in (97-99)), results have been equivocal and difficult to interpret physiologically. Many studies have reported decreases in FA following mTBI (100-102) indicative of less restricted diffusion and interpreted to reflect axonal / myelin damage. However, numerous other studies have also demonstrated increases in FA post-injury (103-105), perhaps illustrating inflammation and / or edema, while others have observed no changes in FA (106,107) or changes in both directions (24,105). Despite these discrepancies, a number of cortical structures are consistently implicated and show alterations in white matter microstructure following   17 concussion, including the cingulum, anterior corona radiata, uncinate fasciculus, corpus callosum, posterior limb of the internal capsule, and superior longitudinal fasciculus (97-99).   1.3.3.1 Limitations of diffusion tensor imaging While at least part of the inconsistencies observed across DTI studies in concussion may be related to inconsistent injury-to-scan intervals, methodological constraints of this imaging technique permit limited insight into the physiological relevance of these findings. Many authors have reported changes in DTI metrics following concussion to reflect alterations in white matter and, more specifically, myelin integrity (108). However, such interpretations must be made cautiously, as evidence shows myelin changes are neither necessary nor sufficient to effect changes in metrics of anisotropic diffusion (96,109). This highlights the fundamental limitation of using DTI to gain insight into pathophysiological mechanisms: that is, its inability to distinguish between multiple factors that influence water diffusion within white matter tracts, including fiber diameter, fiber density, fiber orientation, membrane permeability, edema, and demyelination (Figure 1-2) (110). DTI metrics reflect fibre coherence; therefore, factors such as inflammation, gliosis, and axonal loss can quickly confound interpretation (109).     18  Figure 1-2. Schematic representation of fiber orientation in four hypothetical voxels. Despite dramatically different configurations, the fiber orientational density function obtained using diffusion tensor imaging would be identical. Fig 1 in (110). Image reproduced with permission from NeuroImage.  Consequently, DTI lacks the specificity required for accurate interpretation of the underlying physiological mechanisms at play following sport-related head trauma. In contrast, newer MRI-based techniques using decomposition of T2-weighted decay curves – termed myelin water imaging – directly evaluate myelin content in the brain, and have been validated histopathologically (111-114).  1.3.3.2 Myelin water imaging The first study in this thesis (Chapter 2:) uses T2 relaxation-based MWI to provide insight into tissue characteristics that are not observable using DTI or standard MR imaging techniques (114). Although it is often assumed that each voxel in a MRI-generated image (~1-5 mm3) represents homogeneous tissue, this notion is inaccurate, especially in the brain. Structural features of myelinated tissue cause the protons on water molecules – which provide the source for H1-MRI signals – to experience different local environments that affect T2 decay time. Consequently, decomposition of the T2 relaxation curve within each voxel reveals multiple   19 components, the shortest of which is specific to water molecules trapped with myelin bilayers (Figure 1-3). The myelin water fraction (MWF) can be calculated voxel-wise as the ratio of the area in the T2 distribution arising from myelin water (T2 time = ~10-40 ms) to the entire area of the T2 distribution (114). With recent technological advancements, whole-brain MWF images can be acquired in less than 10 minutes (Figure 1-4) (114,115).    Figure 1-3. T2 distribution from human white matter. Insert shows locations of myelin water versus intra/extracellular water on an electron micrograph of myelinated tissue (adapted from Fig 2 in (114)).  It has been suggested that myelin water imaging may be the best imaging technique to distinguish between myelination and inflammation in vivo (112,116-118). Post-mortem studies correlating MRI and histopathological findings in both central (111) and peripheral nervous tissue (119) have demonstrated strong relationships between T2 relaxation-derived MWF and histological staining for myelin. Myelin water imaging was shown to have high reproducibility in   20 healthy brains, both longitudinally and between imaging sites using the same scanner type and the same protocol (120,121). Moreover, MWF in the normal appearing white matter of people with multiple sclerosis was also shown to be stable over at least six months (122). In a guinea pig model of demyelination (experimental allergic encephalomyelitis), the observed decrease in the short T2 component (i.e. myelin water) was consistent with histological myelin loss (116). While other imaging methods are sensitive to myelin content, such as magnetization transfer, T2-relaxation based MWI has been suggested as the technique of choice for evaluating myelin dynamics (114). Indeed, investigations have used MWI to further our understanding of many clinical conditions, including multiple sclerosis (123-128), autism (129), and stroke (130). As such, this approach was chosen to evaluate the influence of sport-related head trauma on myelin, as presented in Chapter 2:.    21  Figure 1-4. Example of a myelin water fraction map in a healthy brain obtained using T2-relaxation based myelin water imaging.  1.3.4 Cerebral blood flow In addition to structural damage to white matter, recent research has also implicated an important role for compromised cerebrovascular function in the disturbances associated with sport-related head trauma (131-133). Despite comprising only 2% of total body weight, the brain accounts for ~15% of total cardiac output and ~20% of total oxygen consumption at rest, illustrating its high metabolic demands. The brain is highly reliant on glucose as a substrate for energy production – almost all adenosine triphosphate production in the brain occurs via oxidative glucose   22 metabolism (134) – yet has a remarkably low capacity for energy storage (135), necessitating effective and tightly controlled mechanisms to maintain blood flow.   Metabolic disruptions resulting from the post-concussion neurometabolic cascade (Section 1.3.2) occur during periods of altered cerebral blood flow. Transient disruptions in CBF following concussion have repeatedly been demonstrated (2,43,136,137). In the earliest post-mTBI phase (<48 hours), a period of acute hyperemia occurs with CBF peaking at 24-hours (138), although this may be age-dependent (139,140). Subsequently, evidence shows global and regional reductions in CBF, both sub-acutely (2,43,141) and chronically (142,143). This has been demonstrated in both paediatric (2) and young adult (43,141) athlete populations. Brain blood flow recovers to near-healthy athlete levels by ~30 days, although this may take longer in adolescents (2), and may be related to symptom resolution (43,137). Despite this finding, when compared to athletes whom had never sustained prior concussions, arterial spin labeling studies have shown those with a history of concussion display chronically reduced fronto-temporal CBF, influenced by the number of previous concussions (141,144). Patients often report symptom exacerbation with increased physical and cognitive demand, suggesting a potential mismatch between cerebral metabolic demand and CBF delivery may partly explain the clinical manifestations of concussive sequelae (132).  To understand the underlying reasons for post-concussion CBF disturbances, it is pertinent to consider the effects of sport-related head trauma on the mechanisms controlling CBF. Regulation of CBF involves a spectrum of mechanisms that work complementarily to alter resistance within the cerebral blood vessels, adjusting CBF to provide an adequate supply of oxygen and nutrients   23 based on situational demands (145). The cerebrovasculature adapts to regional metabolic requirements associated with neural activity (neurovascular coupling), to changes in perfusion pressure (cerebral autoregulation), and to changes in arterial blood gases (cerebrovascular reactivity) with particular sensitivity to carbon dioxide (145). Although recent studies using MRI-derived parameters of CBF – including arterial spin labeling (43,137,142,144,146,147), phase contrast angiography (2,143), and functional MRI (45,148,149) – have provided valuable insight into the effects of concussion on CBF, these techniques lack the temporal resolution required to optimally evaluate the dynamics of CBF control mechanisms (150). Conversely, transcranial Doppler ultrasound (TCD) has been suggested as an ideal modality for evaluating cerebrovascular function following concussion due to its high temporal resolution, portability, relative affordability, lack of radiation, and non-invasive nature (151). However, accurate use of TCD requires an understanding of cerebrovascular anatomy (150).   1.3.4.1 Anatomy of the cerebrovasculature Blood flow is supplied to the brain via two primary routes: the internal carotid artery (ICA) supplying ~70% of total CBF (anterior circulatory system), and the vertebrobasilar system supplying the remainder (posterior circulatory system).  The anterior circulatory system supplies the majority of the frontal, temporal, and parietal lobes, and originates from the common carotid arteries at the aortic arch / brachiocephalic trunk. The ICA originates at the bifurcation of the common carotid artery, enters the skull at the foramen lacerum, and courses through the carotid canal before entering the cranial cavity in the cavernous   24 sinus. The cavernous segment of the ICA abruptly bends superiorly and posteriorly to penetrate the dura matter at the proximal dural ring (Figure 1-5).    Figure 1-5. Three-dimensional cutaway schematic showing a cervical ICA loop and the intracranial course of the ICA. Adapted from (152). Image reproduced with permission from Neurosurg Clin N Am.  After giving rise to the ophthalmic artery at the distal dural ring, the posterior communicating artery branches from the ICA and passes posteromedially to join the posterior cerebral artery (PCA) as part of the Circle of Willis. The ICA bifurcates into the middle cerebral artery (MCA) and anterior cerebral artery (ACA). The MCA courses antero-laterally within the Sylvian fissure before turning sharply in the postero-superior direction (the genu), reaching the surface of the insula and giving rise to many perforating branches. The anterior cerebral artery (ACA) arises as the medial terminal branch of the ICA, and connects with the contralateral ACA in the interhemispheric fissure via the anterior communicating artery (Figure 1-6).    25 In the majority of healthy individuals, the posterior circulatory system arises from the vertebral arteries that branch from the subclavian arteries. After giving rise the branches that serve the cervical spinal cord, the vertebral arteries converge to form the basilar artery at the level of the pontomedually junction. A number of arteries branch from the basilar artery to supply the cerebellum and pons before it terminates as a bifurcation, giving rise to two posterior cerebral arteries that course laterally and then loop posteriorly to supply the occipital lobes (Figure 1-6).   1.3.4.1.1 Principles of transcranial Doppler ultrasound Transcranial Doppler provides a real-time index of CBF by using ultrasound probes to emit 1-2-MHz sound waves. Insonation of intracerebral arteries is possible through the thin regions of the temporal bone, referred to as acoustic windows (150). Using a transtemporal approach, three acoustic windows may be observed, including the posterior window (directly anterior to the ear, above the zygomatic arch), anterior window (superior to the anterior process of the zygomatic arch), and middle window (between anterior and posterior windows). Emitted  sound waves reflect off erythrocytes travelling within the insonated vessel and are detected by the transducer (Figure 1-7). The Doppler-shift between emitted and received signals is proportional to the velocity of the moving blood cells:  Equation 1.1:   Doppler Shift = 2 • ƒt • v • cos(θ) / C Where ƒt is the transmitted ultrasound frequency (2 MHz); v is the velocity of the reflector (erythrocytes); θ is the angle of insonation; and C is the speed of sound in the blood (1540 m/s)    26  Figure 1-6. Schematic of the cerebral arterial system. (Left) Coronal section through the head and neck; (Middle) Looking up through the base of the brain; (Right) Vessels of the vertebrobasilar system feeding into the circle of Willis. Adapted from (153). Reproduced with permission from NMR in Biomedicine.  27  Figure 1-7. Picture of the TCD interface. A) Depth of blood velocity signals oriented towards the probe (red) and away from the probe (blue) – note the bifurcation of the ICA visible at ~60 mm as a demarcation between blood flowing in the MCA (red) and ACA (blue); B) Velocity profile at selected depth (54 mm).  It is important to note that the diameter of the insonated vessel cannot be determined using TCD. As such, the main limitation of this technique is its inability to measure volumetric flow; rather TCD provides estimates of blood flow velocity under the assumption that vessel diameter remains constant.   Using TCD, the bifurcation of the ICA can typically be insonated through the anterior or middle temporal window at a depth of 55-65 mm, providing an important landmark for locating other vessels and standardizing insonation. The anatomical distribution of the MCA typically allows for direct insonation of the M-1 segment through the anterior temporal window – with near-zero   28 insonation angle – at depths between 20-60 mm. The P-1 segment of the PCA can be found posterior and deep to the ICA bifurcation at depths of ~60-70 mm (Figure 1-8).   Figure 1-8. Schematic demonstrating insonation of left posterior cerebral artery (right side of picture) and right middle cerebral artery (left side of picture). Image modified from Fig 3 in (150). Image reproduced with permission from Journal of Neuroscience Methods.  A recent review has highlighted the “considerable utility” of TCD in providing an efficient, cost-effective tool towards the comprehensive assessment of cerebrovascular function in physiological and pathological states for both research and clinical purposes (150). Indeed, TCD has been used to gain insights into a variety of clinical populations including vasospasm (154), spinal cord injury (155,156), Alzheimer’s diesease (157), ageing (158), stroke (159), and severe   29 TBI (160). Specifically, TCD represents an excellent tool to assess the integrity of the primary mechanisms controlling cerebral blood flow: CO2 reactivity, cerebral autoregulation, and neurovascular coupling (150).   1.3.4.2 Cerebrovascular reactivity to carbon dioxide Across the entire length of the cerebrovascular tree, cerebral blood vessels are highly sensitive to the arterial partial pressure of carbon dioxide (PaCO2), although resistance modulation is thought to occur primarily at the level of pial arterioles (145,161-164). While changes in CBF are linked to alterations in PaCO2, the true vasoactive stimulus is a change in extravascular pH, resulting from the diffusion of non-polar CO2 molecules across the blood-brain barrier into the extravascular environment (165-167). Once in the extracellular fluid, CO2 dissociates via the bicarbonate buffer system into H+ and HCO3-, generating substantial changes in pH. Increased PaCO2 leads to a decrease in pH and induces relaxation of vascular smooth muscle cells, leading to vessel dilation (up to 40% in pial arteries) and increased CBF (167). Conversely, hypocapnia yields an increase in pH, enhancing vascular tone and decreasing flow (168). The cerebrovascular response to altered CO2 occurs with a ~6 second delay and is critical to regulate and maintain central pH (168). Sensitivity to CO2 appears to differ in hyper- versus hypocapnic ranges (169), whereby hypercapnic stimuli result in CBF increases of ~2-5%/mmHg and hypocapnic stimuli elicit CBF reductions of ~1-2%/mmHg (162,170,171). Data suggests that CO2 reactivity is greater in grey matter than in white matter, likely due to relative differences in vascularization (172,173). While CBF is also sensitive to oxygen content within the blood, particularly at very low levels, the effect is dependent on the prevailing PaCO2 (174).     30 1.3.4.2.1 Alterations in CO2 reactivity following sport-related head trauma Of the primary mechanisms controlling CBF, the one that has received the most research attention in the context of sport-related head trauma is CO2 reactivity; multiple studies have used TCD or blood oxygen level dependent (BOLD) MRI in athletic populations and have shown trauma-induced alterations in the sensitivity of cerebral blood vessels to CO2 (reviewed in (175) and (132)). In acutely concussed young adult athletes (primarily hockey players) and contact sport athlete controls, TCD has demonstrated concussion-induced impairments in CO2 reactivity that resolved within 5 days post-injury (176,177). BOLD-based CO2 reactivity impairments have been shown in a small sample of concussed adolescent athletes and persisted beyond clinical recovery (45). At a whole brain level, BOLD-based CO2 reactivity was not different between concussed adults and normal controls, although patient-specific alterations were observed in both symptomatic and asymptomatic patients that were not present in controls (178). In a longitudinal case study of a single mTBI patient, Chan and colleagues (148) reported asymmetries in whole brain CO2 reactivity 2-months following injury that normalized on follow-up assessment 1-year later. Militana reported regional increases in CO2 reactivity in acutely concussed patients (3-6 days post-injury) that were correlated with functional connectivity in the hippocampus (179). Chronically, adolescent patients suffering persistent post-concussion symptoms demonstrated reduced CO2 reactivity compared to normal controls despite no differences in global mean CBF (149). Further work has been proposed towards generating an ultrasonographic index of CO2 reactivity to assist in the diagnosis and management of concussion (151).   Impairments in CO2 reactivity have also been demonstrated in the context of repetitive subconcussive trauma. In one TCD study, professional boxers exhibited substantial alterations in   31 CO2 reactivity when compared to controls that were negatively correlated with number of rounds fought (17). Impairments in CO2 reactivity have been reported in high school American football players compared to non-contact sport controls during the first half of the season, but resolved by end-of-season (18). Female high school soccer players exhibited CO2 reactivity impairments that were associated with cumulative impact exposure and persisted for up to 4-5 months post-season (19). It is evident that sport-related head trauma induces alterations in cerebrovascular sensitivity to CO2; however, much less is known regarding the effects on other mechanisms controlling CBF, including cerebral autoregulation and neurovascular coupling.   1.3.4.3 Cerebral perfusion pressure and cerebral autoregulation Cerebral perfusion pressure is the driving force for blood flow to the brain – equal to the difference between mean arterial pressure (MAP) and intracranial pressure (ICP). The importance of perfusion pressure in the regulation of CBF has been recognized for over a century: in 1895 Bayliss, Hill, and Gulland reported that “In all physiological conditions a rise in arterial pressure accelerates the flow of blood through the brain, and a fall slackens it” (180). This concept evolved in the late 1950s when Lassen plotted data from seven studies in 11 patient groups of average steady-state blood pressure and total brain blood flow, and revealed a range of MAP (~60 – 150 mmHg) across which CBF appeared to be stable (181). Coined static cerebral autoregulation (CA), this observation indicates reflexive adjustments in cerebrovascular resistance to changes in blood pressure. As perfusion pressure falls there is a consequent vasodilation and reduction in cerebrovascular resistance to support CBF; the reverse occurs in response to elevations in perfusion pressure. It is accepted that CA acts to adjust resistance at the level of the cerebral arterioles and pial vessels (182), though animal data exists to support   32 potential contributions from large intracranial and extracranial arteries (183-185). Subsequent human research has determined that the within-subject steady-state MAP-CBF relationship is not flat through the broad range of blood pressures originally described by Lassen, but encompasses a ~10 mmHg window (186). Furthermore, the slope of the pressure-passive regions of the CA curve differs in hypertensive versus hypotensive ranges, suggesting a greater buffering capacity against surges in pressure relative to reductions in pressure (145).   While classical definitions of CA were derived from evaluations of the pressure-flow relationship during steady-state conditions (static CA), research has increasingly focused on the influence of dynamic changes in MAP – for example, during changes in posture – on CBF (dynamic CA). The advent of TCD allowed for improved temporal resolution, indexing CBF in major intracranial blood vessels on a beat-by-beat basis. Following rapid transient hypotension induced by the release of inflated thigh occlusion cuffs, the earliest study of dynamic CA demonstrated a similar drop between MAP and CBFv, but a quicker recovery of the CBFv, suggesting relative rather than absolute buffering (187). Contemporary views of CA hold that the cerebrovasculature behaves as a high-pass filter, whereby higher frequency (> 0.20 Hz) changes in blood pressure are passed linearly into the cerebral blood vessels, and lower frequency changes are more extensively buffered (188,189). The frequency-dependent behaviour of CA is known to involve autonomic and myogenic contributions, which appear to operate at different frequencies (190-194). Characterization of dynamic CA has provided valuable clinical information, allowing differentiation of cerebrovascular responses to fluctuations in blood pressure occurring at different durations and amplitudes observed during everyday life (195,196).    33  1.3.4.3.1 CA disruptions in acquired brain injury / moderate-severe TBI Autoregulatory mechanisms appear sensitive to trauma, as disruptions to the cerebral-pressure flow relationship are well documented following moderate and severe TBI. Across multiple studies, 49-87% of severe TBI patients exhibit absent or impaired CA (197-199), while recovery of CA is delayed in some cases beyond 2 weeks (199). Disruptions in CA are predictive of outcome in acquired brain injury populations: in severe TBI, acutely compromised CA is a significant predictor or poor outcome (200,201); in patients with Fabry disease, impaired CA is thought to increase risk of stroke (202); following subarachnoid haemorrhage, CA dysfunction is among the primary factors predisposing patients to delayed cerebral ischemia and vasospasm at an individual level (203-205); impaired CA is also an established independent risk factor for stroke (159). However, evidence for CA impairments in cases of mild head trauma is not as robust.  1.3.4.3.2 Alterations in CA following sport-related head trauma Despite widespread postulation that disruptions in CA play an important role in the pathophysiology of sport-related concussion (9,131,206,207) – including an assertion of responsibility for persistent post-concussion symptoms (206) – no studies to-date have explicitly evaluated autoregulatory function in the context of sport-related concussion.  In one small study, a subset of hospitalized mTBI patients – eight of 29, the majority of whom also exhibited structural damage on CT – demonstrated impaired CA (208). One other case study reports impaired CA in a hospitalized mTBI patient (209). In the only study evaluating CA in the context of sport-related head trauma, Bailey and colleagues reported impairments in an index of   34 CA relative to control subjects in a cohort of professional boxers that correlated with combat volume (17). Apart from this study, very little is known to what extent the dynamic, frequency-dependent relationship between BP and CBF is affected by sport-related concussion and repetitive subconcussive trauma (99). As such, Chapter 3: and Chapter 4: of this thesis entail the first prospective evaluations of CA function via driven MAP oscillations and a widely-used technique known as transfer function analysis (TFA)(196), recently suggested as a gold-standard for evaluating the cerebral pressure-flow relationship (210).   1.3.4.3.3 Transfer function analysis for characterizing dynamic CA Whereas classical methods of indexing CA (namely, the rate of regulation (RoR) (187), autoregulatory index (ARI) (195), autoregressive-moving average ARI (211)) evaluate information in the time domain of CBF velocity and blood pressure signals, TFA also considers data contained within the frequency domain. This is pertinent to the evaluation of CA, as the pressure-flow relationship is frequency dependent (described in Section 1.3.4.3). The TFA approach models CA as a simplified linear control system, using a Fourier decomposition to describe the relationship between oscillations in input (MAP) and output (CBFv) signals at different frequencies (212). The frequency-dependent transfer function H(ƒ) between MAP and CBFv signals is calculated as:  Equation 1.2    H(ƒ) = SMAP-CBFv(ƒ)/SMAP-MAP(ƒ)  where SMAP-MAP(ƒ) is the autospectrum of the BP signal and SMAP-CBFv(ƒ)  is the cross-spectrum between the MAP and CBFv signals. The squared Coherence function is estimated as:   35  Equation 1.3      MSC(ƒ) = | SMAP-CBFv (ƒ) |2/ ⋅{SMAP-MAP(ƒ)  SCBFv-CBFv (ƒ)}  Similar to a correlation coefficient, Coherence describes the proportion of variance in the output signal (CBFv) explained by the input signal (MAP), and may have values between 0 and 1. A high coherence improves within-subject reliability of Gain | H(ƒ) | and Phase | φ(ƒ) |(212,213), which are calculated using the real HR(ƒ) and imaginary HI(ƒ) components of the complex transfer function:  Equation 1.4      | H(ƒ) | = {HR(ƒ)2 + HI(ƒ)2} Equation 1.5       φ(ƒ) = tan-1{HI(ƒ) / HR(ƒ)}  Phase represents the timing offset between input and output oscillations and is indicative of the time to change in cerebrovascular resistance following a change in MAP. Gain provides a ratio of output amplitude to input amplitude. In the setting of intact CA, higher Phase indicates more rapid adjustment of cerebrovascular resistance to changing MAP. Low gain indicates low magnitudes of MAP oscillation transferred to the cerebrovasculature (i.e. greater buffering) (210). Dynamic CA function has been evaluated using TFA in a variety of clinical conditions, including autonomic failure (214), Alzheimer’s disease (215); heart transplantation (216), and schizophrenia (217), and has shown clinical value; a recent study demonstrated that less effective CA acutely post-ischemic stroke (in the form of reduced TFA phase) was associated with elevated risk of hemorrhagic transformation and cerebral edema (218). No published studies to date have used TFA to evaluate the influence of sport-related head trauma on CA function.   36  1.3.4.4 Neurovascular coupling Regional increases in neural activity – and the associated elevation in metabolism – require appropriate and coordinated responses by the neurovascular unit to modulate local cerebrovascular resistance and direct nutrient-rich blood to active cortical regions. For over 100 years, it has been appreciated that local neural and metabolic activity within the cortex are tightly coupled with regional perfusion (219), though the exact mechanisms underlying this relationship in humans are still debated. The coupling between cortical activity and CBF is a characteristic of the neurovascular unit, a term describing the functional and anatomical relationship between neurons, supporting glial cells (astrocytes, pericytes, oligodendroglia), vascular smooth muscle cells, and endothelial cells (Figure 1-9). Multiple pathways have been proposed to contribute to the NVC response, including local accumulation of vasoactive metabolic by-products (e.g. CO2, nitric oxide (NO), adenosine, arachidonic acid metabolites), direct neural control of the cerebrovasculature, pericyte-mediated changes in capillary tone, and astrocyte-mediated vasosignaling (reviewed in: (145,220)). Ultimately, gap junctions between adjacent vascular smooth muscle cells are thought to facilitate intramural propagation of vascular signals to yield vasoactivity in remote pial arterioles up-stream of the signal origin (221-223).    37  Figure 1-9. Schematic illustration of the components of the neurovascular unit from the level of capillaries to pial arterioles. At the capillary level (Level 1), the neurovascular unit is comprised of endothelial cells, pericytes, astrocytes and neurons. At the parenchymal arteriole level (Level 2), the neurovascular unit consists of a single layer of vascular smooth muscle cells, pericytes (not illustrated) astrocytic end-feet, and neuron processes. At the pial arteriole level (Level 3), the endothelium is surrounded by multiple layers of smooth muscle, astrocyte processes, and perivascular nerve endings originating from peripheral ganglia. Fig 1 in (224). Image reproduced with permission from Elsevier.      38 1.3.4.4.1 Multiple mechanisms contribute to the NVC response Neural control of the cerebral microvasculature plays an important role in the NVC response. The entire cerebrovascular tree is innervated with sympathetic and parasympathetic fibres and growing evidence supports a role for autonomic activity in modulating CBF via its effects on cerebrovascular resistance (145,225,226). Indeed, the fast initial rise in CBF following cortical activation is thought to result from sympathetic activation within the cortex (145,213,220). Furthermore, increased extracellular glutamate activates N-methyl-D-aspartate (NMDA) receptors to stimulate neuronal NO synthase and the subsequent release of NO onto nearby parenchymal arterioles (227). When ATP levels are low in neurons, adenosine is also released locally to exert a vasodilatory effect (228).   Mounting evidence supports a role for pericytes in initiating the NVC response, wherein neuronal activation may modulate pericyte / capillary resistance with subsequent upstream signal propagation (229). In fact, models have estimated pericytes, and their effect on capillary tone, may contribute 16% to 70% of resistance within the parenchyma (230,231). Glutamate has been shown to induce dilation, whereas norepinephrine induces constriction of pericytes in brain slice preparations (230).   Astrocytes form a critical component of the neurovascular unit, acting as a bridge between neurons and cerebral blood vessels with end-feet that envelope penetrating arterioles. Excitatory and inhibitory neurons synapse on both astrocytes and GABAergic interneurons that are closely associated with astrocytic end-feet. Astrocytes are thought to contribute to a slow-onset (3-4 seconds) neurovascular coupling response, but may play a lesser role in the immediate   39 hyperemic effect (< 1 second) following neural activation (232). Glutamate released from active neurons triggers metabotropic receptor-mediated calcium uptake into neighbouring astrocytes (reviewed in: (232)). The resulting change in calcium concentration initiates a signaling cascade leading to the release of arachidonic acid (vasoconstrictory) and its metabolic derivatives including epoxyeicosatrienoic acid (EET) and prostaglandins (vasodilatory) onto arteriolar smooth muscle cells and vascular endothelial cells (233-236). Inhibitory interneurons communicating with neurons, astrocytes, and microvessels play a role in integrating local signals and releasing vasoactive substances (e.g. NO, acetylcholine, neuropeptide-Y, vasoactive intestinal peptide) to precisely regulate CBF (237,238). Interestingly, recent work has suggested reciprocal communication from blood vessels to astrocytes to neurons – a so-called vasculo-neuronal coupling (239).  Although our understanding of exact mechanisms governing neurovascular coupling – and certainly vasculo-neuronal coupling (239) – remains incomplete, it is clear that multiple overlapping pathways exist to ensure CBF is appropriately altered in response to changes in local neural activity (220).   1.3.4.4.2 Characterizing NVC dynamics using transcranial Doppler ultrasound A robust NVC response can be observed in-vivo using TCD to record blood velocity in the PCA before and after activation of the occipital cortex, typically achieved by having patients close and open their eyes to a visual stimulus such as reading (156,213,240-244). After stimulus onset, the canonical NVC response exhibits a brief delay followed by an increase in PCAv to 15-20% above eyes-closed baseline velocities, dependent on stimulus intensity (145,220,240-246). Flow   40 velocity in the PCA then tends to plateau for the duration of visual stimulation, reflecting a matching of CBF to metabolic demand. Whereas this phenomenon is maintained at rest (156,240-242,244,245), during moderate exercise (242), and throughout healthy human aging (247,248), impairments in NVC have been revealed across a variety of clinical conditions. For example, patients with autonomic dysfunction have shown altered neurogenic regulation of NVC responses (156,249); in high-level spinal cord injury patients, NVC dysfunction persisted even after correcting blood pressure pharmacologically (156); oxidative stress consequent to ß-amyloid plaques in the brains of Alzheimer patients is thought to directly inhibit NVC responses (250,251). It has been proposed that neuronal damage and astrocytic scar formation precludes normal NVC responses in severe TBI patients, with some of these individuals exhibiting inverse NVC responses (252,253). Mechanistically, biophysical models of TBI have estimated increased heterogeneity in CBF transit time across capillaries – secondary to capillary compression by astrocytic end-feet – to cause relevant reductions in oxygen availability (254). However, effects of mild sport-related head trauma on NVC dynamics are currently unknown.   1.3.4.4.3 Alterations in NVC dynamics following sport-related head trauma To-date, no studies have been conducted using techniques with sufficient temporal resolution to evaluate the dynamics of NVC responses in the context of sport-related head trauma. Insights may be gleaned from the various functional MRI studies that have been conducted, though the interpretation of results is not straightforward. The majority of task-based fMRI studies have used tasks probing frontal lobe/executive function. Typically, increases in cortical activation in mTBI patients relative to healthy controls have been reported across multiple brain regions (reviewed in (67)) and may be related to symptom severity, often despite no differences in task   41 performance between groups (255-257). However, other fMRI studies have concluded concussions cause hypoactivation, particularly in individuals with persistent symptoms, though task performance was not always equal between groups (258-261). A recent prospective study demonstrated global hyperactivation that gradually declined in extent during the recovery process, with BOLD responses measured at 3-days, 2-weeks, and 2-months post-injury (257). One study has suggested an association between the degree of hyperactivation and prolonged recovery (262). Participants reporting more post-concussion syndrome symptoms (persisting >1 year post-injury) exhibited greater activation in attention-related areas but reduced activation in task-irrelevant areas as cognitive load was increased during a top-down attentional task (263). Elevation of task-based BOLD responses in mTBI patients have been interpreted to reflect recruitment of additional neural resources to compensate for cognitive and/or attentional deficits (257,264). Only one study has considered the potential for mTBI to alter the dynamics of hemodynamic responses, and reported greater activation in the visual cortex of mTBI patients presenting to the emergency department relative to controls, particularly in the 2-4 second window after stimulus onset, suggesting a shorter time-to-peak response (265). Although inconsistency across fMRI studies may be partly attributed to methodological differences and injury heterogeneity across samples (266), a recent meta-analysis of fMRI findings in mTBI observed hyperactivation during continuous tasks and hypoactivation during tasks requiring discrete periods of working memory (267).   It remains unclear if multiple concussions in combination with repetitive subconcussive trauma are detrimental to NVC over the course of a career. Multiple recent task-based fMRI studies in high-school American football athletes have demonstrated changes in hemodynamic response   42 patterns to cortical activation as a function of head impact exposure across a single season (20,22,69,76,268). During in-season assessments, athletes performing abnormally on tests of cognition showed reduced temporal and occipital cortex BOLD responses and experienced higher numbers of impacts to the top-front of the head relative to subjects performing normally (22). Relative to preseason scans, within-subject visual BOLD responses were much more variable during periods of the season with high contact volume, although these deficits tended to normalize with cessation of contact (69). Altered BOLD responses were more likely to persist after the end of the athletic season in athletes receiving 50+ hits per week during the season (268). Whereas a history of multiple concussions may not detrimentally affect hemodynamic responses to cortical activation in otherwise healthy young adult athletes (269,270), multiple concussions have been shown to negatively affect cortical recruitment patterns in the relational memory network of former professional football players (271). Thus, multiple studies have reported changes in BOLD responses following repetitive subconcussive trauma. However, the extent to which NVC dynamics are affected by sport-related head trauma may be better estimated by obtaining pre-injury data using techniques providing better temporal resolution, such as TCD.  1.3.4.5 Autonomic factors in cerebral blood flow regulation The entire cerebrovascular tree is extensively innervated by autonomic fibers. Extrinsic perivascular neurons from both sympathetic and parasympathetic origins innervated extracranial arteries (ICA/VA), large arteries of the brain (MCA/PCA) and pial arteries on the brain surface, while intrinsic fibres innervate parenchymal arterioles and astrocytes (272). Vascular tone in pial arterioles is sensitive to neurotransmitters including norepinephrine, whereas parenchymal   43 arterioles do not respond as effectively (273). Rather, in vitro work suggests signaling from intrinsic neurons causes a release of vasoactive mediators that exert constrictory or dilatory effects on local endothelial cells, astrocytes, and upstream vascular smooth muscle (reviewed in: (226,272)). However, determining the functional role of intrinsic cerebrovascular innervation in humans has proved challenging (145).   Extrinsic postganglionic autonomic fibres arise from three sources, including the sphenopalatine ganglion, superior cervical ganglion, and the trigeminal ganglion (145,226). A role for sympathetic modulation of CBF is directly supported by observations in of increases in CBF following cervical ganglionectomy (274-277) and following pharmacological blockade of cervical ganglion (278-281). Indeed, it is thought that sympathetic activity plays a protective role in preventing cerebral hyper-perfusion by increasing vessel tone, particularly during changes in perfusion pressure (226,282-286). For a given rise in MAP, sympathetic ganglion blockade (287) and α-adrenoreceptor block (288) both led to larger increases in CBF and caused increases in transfer function gain and decreases in phase, indicative of impaired CA (191,289). The influence of parasympathetic activity is more poorly understood, though it is thought to counteract sympathetically-mediated vasoconstriction through activation of the trigeminal nerves (226). While the precise role of autonomic innervation in the regulation of CBF remains controversial (286), it is clear that the autonomic nervous system has the capacity to modulate cerebral hemodynamics.       44 1.3.4.5.1 Autonomic dysregulation following sport-related head trauma Autonomic dysregulation has been repeatedly documented following sport-related concussion, most often in the form of altered heart rate variability. Generally, parasympathetic activation slows heart rate and increases heart rate variability, whereas sympathetic activation yields opposite effects. Reduced heart rate variability is thought to reflect an impaired ability of the autonomic nervous system to respond dynamically to the environment, and has been associated with poorer outcome in a variety of clinical scenarios; for example, decreased variance in R-R intervals as well as decreased power in the very low and low frequency ranges have been found to be independently predictive of mortality in myocardial infarction patients (290). In severe TBI, HRV metrics have shown acute cardiac autonomic dysfunction to be directly associated with high mortality rates in TBI patients (291). Some groups have suggested that central autonomic dysregulation may at least partly explain the observed increase in long-term mortality in persons with a history of mTBI (292-295). Associations reported in recent studies from Sung and colleagues suggest altered cardiac autonomic function may contribute to enduring emotional dysfunction following mTBI, particularly in female patients (296,297). Following sport-related concussion, various cross-sectional studies have outlined reductions in heart rate variability suggestive of elevated sympathetic and / or reduced parasympathetic outflow that may persist beyond clearance for clinical recovery, particularly during activity (298-306). Concussion-induced increases in sympathetic drive have been shown to induce a transient “stiffening” of peripheral blood vessels (300). Given the extensive autonomic innervation of the cerebrovasculature (272), alterations in autonomic drive could contribute to altered cerebral hemodynamics following sport-related head trauma, though no evidence currently exists to support this idea.   45 1.4 Thesis objectives and summary of studies The specific objective of this proposal was to use a prospective, longitudinal cohort study design to test the hypothesis that sport-related head trauma leads to quantifiable changes in brain myelination, neurovascular coupling dynamics, and the MAP-CBF relationship. Secondary objectives were to evaluate relationships between changes in cerebrovascular function and biomechanical metrics of head impact exposure. The results of this work will be incorporated within a broader investigation of the physiological effects of head trauma in sport, towards an evidence base that will aid in the development of objective tools to be used to prevent, identify, and manage dangerous levels of exposure to sport-related head trauma.  1.4.1 Specific aims and hypotheses 1.4.1.1 Study 1 (Chapter 2) Primary Aim: To investigate how myelin content in the in-vivo human brain is influenced by concussion, as well as exposure to repetitive subconcussive head trauma. Hypothesis 1a: Brain myelin content will be reduced following a concussion. Hypothesis 1b: Brain myelin content will be reduced following a season of exposure to repetitive subconcussive head trauma.  1.4.1.2 Study 2 (Chapter 3) Primary Aim: To investigate how metrics of dynamic cerebral autoregulation are influenced by sport-related concussion, both acutely and as a function of multiple previous concussions. Hypothesis 2a: Dynamic cerebral autoregulation will be temporarily impaired following acute concussion. Hypothesis 2b: The dynamic cerebral pressure-flow relationship will be impaired in otherwise healthy athletes with a history of three or more concussions relative to those with no   46 history of concussion. Hypothesis 2c: Greater impairment in CA will correlate with higher symptom severity scores, as well as with degree of impairment in neurocognitive function.  1.4.1.3 Study 3 (Chapter 4) Primary Aim: To investigate how metrics of dynamic cerebral autoregulation are influenced by exposure to repetitive subconcussive head trauma in elite athletes. Hypothesis 3a: Dynamic cerebral autoregulation will be impaired following one season of participation in contact sports. Hypothesis 3b: The dynamic cerebral pressure-flow relationship will be unaffected following one season of competition in elite athletes who experience little-to-no head trauma (i.e. non-contact sports). Hypothesis 3c: Higher degrees of head impact exposure will be associated with higher degrees of impairment in cerebral autoregulation.  1.4.1.4 Study 4 (Chapter 5) Primary Aim: To investigate how the dynamics of the neurovascular coupling response are influenced by sport-related concussion, both acutely and as a function of multiple previous concussions. Hypothesis 4a: NVC dynamics will be temporarily altered following a single sport-related concussion. Hypothesis 4b: NVC dynamics will be altered in otherwise healthy athletes with a history of three or more concussions relative to those with no history of concussions. Hypothesis 4c: Larger alterations in NVC dynamics will be related to higher symptom severity scores, as well as the degree of impairment in neurocognitive function post-injury.    47 1.4.1.5 Study 5 (Chapter 6) Primary Aim: To investigate how the dynamics of the NVC response are influenced by exposure to repetitive subconcussive head trauma in elite athletes. Hypothesis 5a: NVC dynamics will be altered following one season of participation in contact sports. Hypothesis 5b: NVC dynamics will be unaffected following one season of competition in elite athletes who experience little-to-no head trauma (i.e. non-contact sports). Hypothesis 5c: Higher degrees of head impact exposure will be associated with larger alterations in NVC dynamics.  1.4.2 Presentation The current dissertation contains six additional chapters. Following this overview chapter, Chapter 2: entails an original research study into the effects of sport-related head trauma on the integrity of the myelin sheath using a novel MRI-based imaging technique. The fraction of total water content in the brain attributable to myelin was evaluated at preseason in collegiate ice hockey athletes, with repeat evaluations occurring at three post-concussion time-points as well as after completion of the competitive season. In a similar longitudinal design, Chapter 3: assessed the effects of acute and multiple prior concussions on indices of dynamic CA using a hemodynamic challenge commonly experienced in everyday life – shifts in posture from squatting to standing. Chapter 4: extends from the findings in Chapter 3 but with a focus on the effects of exposure to repetitive subconcussive head trauma through comparison of pre- and post-season CA function in contact and non-contact sport athletes. Chapter 5: presents an evaluation of the within-subject effects of sport-related concussion on dynamics of the NVC response in the PCA using a visual stimulation paradigm. Chapter 6:details the effects of repetitive subconcussive trauma on NVC dynamics in the PCA. Finally, Chapter 7: summarizes   48 the five studies in this thesis, provides an interpretation of their collective conclusions, and identifies important avenues for future research.    49 Chapter 2: Myelin water fraction is transiently reduced after a single mild traumatic brain injury – a prospective cohort study in collegiate hockey players  2.1 Summary Impact-related mild traumatic brain injuries (mTBI) are a major public health concern, and remain as one of the most poorly understood injuries in the field of neuroscience. Currently, the diagnosis and management of such injuries are based largely on patient-reported symptoms. An improved understanding of the underlying pathophysiology of mTBI is urgently needed in order to develop better diagnostic and management protocols. Specifically, dynamic post-injury changes to the myelin sheath in the human brain have not been examined, despite “compromised white matter integrity” often being described as a consequence of mTBI.   In this preliminary cohort study, myelin water imaging was used to prospectively evaluate changes in myelin water fraction, derived from the T2 decay signal, in two varsity hockey teams (45 players) over one season of athletic competition. 11 players sustained a concussion during competition, and were scanned at 72 hours, 2 weeks, and 2 months post-injury. Results demonstrated a reduction in myelin water fraction at 2 weeks post-injury in several brain areas relative to preseason scans, including the splenium of the corpus callosum, right posterior thalamic radiation, left superior corona radiata, left superior longitudinal fasciculus, and left posterior limb of the internal capsule. Myelin water fraction recovered to pre-season values by 2   50 months post-injury. These results may indicate transient myelin disruption following a single mTBI, with subsequent remyelination of affected neurons. Myelin disruption was not apparent in the athletes who did not experience a concussion, despite exposure to repetitive subconcussive trauma over a season of collegiate hockey. These findings may inform many of the metabolic and neurological deficits observed clinically following mTBI.   2.2 Introduction Impact-related mTBI are a growing public health concern globally, with major causes including sports, motor vehicle accidents, falls, and assaults. The Centers for Disease Control and Prevention estimate that approximately 1.6 - 3.8 million mTBI occur annually in the United States alone (307). Symptoms of concussion, a form of mTBI, are thought to result from mild diffuse axonal injury (DAI) that is not detectable on conventional computed tomography or magnetic resonance imaging (MRI). Currently, the diagnosis and management of this broadly defined and poorly understood injury are based on clinical observation and patient-reported symptoms, despite numerous recent efforts towards the development of objective tools to link functional deficits with quantifiable structural changes. While the majority (80-90%) of individuals with mTBI symptoms recover in 7-10 days, a subset of individuals are left with persistent disability for months to years (9). Furthermore, emerging evidence has suggested a possible link between clinically manifest concussions, as well as repetitive sub-clinical head impacts, and the development of long-term neurodegenerative changes, termed chronic traumatic encephalopathy (15). The long-lasting effects of single and repetitive mTBI may include serious cognitive and behavioural deficits, such as problems with affect regulation, attention, memory, and depression (15). Given these concerns, it is imperative that techniques be developed to   51 provide a more thorough understanding of precisely how mild traumatic brain injuries affect the brain.  Myelin is thought to be an important player in the pathophysiology of TBI, though its role is poorly understood (82,83); increasingly, evidence implicates that damage to either myelin or the axon can lead to subsequent damage to the other (84,88). In the case of sport-related head trauma, biomechanical forces imparted on the head cause linear and rotational acceleration-deceleration of the brain within the rigid cranium, which creates diffuse shear strains in the brain tissue. Due to the viscoelastic nature of this tissue, the rate at which such strains are applied is an important factor towards the resultant tissue damage. While primary axotomy is generally observed following high magnitude impacts associated with more severe traumatic brain injuries, it is thought that the axonal pathology observed in mTBI develops over days to weeks following the initial insult (78,80,81). Current theories describe a post-traumatic neurometabolic cascade involving ionic flux and indiscriminate glutamate release, leading to mitochondrial dysfunction and calcium sequestration, and a subsequent energy crisis with cytoskeletal damage (78,79). Intracellular calcium overload has been recognized as a significant cause of damage to both myelin and oligodendrocytes (87). Impaired axonal transport leads to swellings within the axon containing organelles and other transport materials, creating the potential for a sequence of secondary axonal disconnection and Wallerian degeneration (78,89). Prolonged global and regional reductions in cerebral blood flow have also been reported following concussion, and were related to recovery duration (2,43); experimental work has demonstrated that accumulative oxidative stress in the context prolonged cerebral hypoperfusion suppresses both the differentiation of oligodendrocyte precursor cells to oligodendrocytes as well as myelin staining   52 (92). Thus, loss of oligodendrocytes and corresponding demyelination of affected axons is anticipated (83,84,93). Histopathologically, this has been observed as axonal bulbs, irregular tortuous axonal varicosities and small globoids of degraded myelin sheath (82,90,91). While various reports have implicated that myelin fragmentation and degradation occurs following axonal injury (82,90,95,308-310), dynamic in vivo myelin changes have not been directly observed in the human brain. Whether the result of direct, multifocal primary traumatic axonal injury or secondary axotomy, subsequent axonal degeneration is a possible outcome of mild DAI, but axon damage and myelin disruption may be reversible (82,83). In contrast to situations where strain is focally applied (e.g. at anatomic boundaries), strains distributed more diffusely along the length of an axon create an elongated pattern of axonal swelling, which may be more amenable to intrinsic repair mechanisms (78).   Our current understanding of the pathophysiology of mTBI is derived primarily from post-mortem studies and animal models. While post-mortem studies are useful for exploring histopathological changes in the brain following mTBI, by definition they are unable to provide information on the dynamic post-injury changes explained using animal models. However, it is recognized that the substantial mass and inertia of the human brain play an important role in the development of diffuse axonal injury (78), highlighting an inherent challenge in the development of valid rodent models of mTBI (311). A non-invasive method for objective, in-vivo evaluation of the pathophysiological changes associated with concussion is currently one of the primary goals in mTBI research. Specifically, the dynamic effects of acute mTBI on myelin in the human brain represent a major gap in our understanding of these injuries.    53 Here, we use myelin water imaging (MWI (115)) to quantify metrics associated with changes in myelin after mTBI. It has previously been identified that decomposing the T2 decay signal results in three components. They include a very long component (~2 seconds) that corresponds to cerebrospinal fluid, an intermediate component (~80 ms) derived from intracellular and extracellular water, as well as a short component (~20 ms) from water that is within the myelin bilayers (111,312). As such, the fraction of total brain water attributable to myelin can be estimated, and is termed the myelin water fraction (MWF). Recent advances in myelin water imaging have enabled rapid exploration of myelin damage across the whole brain (115). Previous work has demonstrated a good quantitative relationship between MWF, as derived from MR images, and histological staining for myelin in tissue from both the central nervous system (111) and peripheral nervous system (119). Being the only technique that has been validated by histopathology, T2-relaxation based myelin water imaging has provided novel insights in demyelinating diseases, such as multiple sclerosis research (313), but has never been used in the context of mTBI to evaluate post-injury myelin dynamics. In this prospective study, we followed a group of individuals at high risk of sustaining a concussion, comprised of two varsity hockey teams, for one athletic season. This is the first study to directly evaluate myelin changes following mTBI in the in vivo human brain, assessing myelin water fraction in the context of sport-related head trauma.  Accordingly, our objectives in the current study were to observe changes in myelin water fraction, relative to baseline, at acute, sub-acute, and chronic post-mTBI time points in a group of individuals at high-risk of sustaining a mTBI. We hypothesized that a reduction in myelin water fraction would be observed following concussion, with recovery to near-baseline values by   54 two months post-injury.  2.3 Methods 2.3.1 Study design 25 male and 20 female college-aged (mean age 21.2 ± 3.1 years) amateur hockey players from two ice hockey teams participated. All players underwent baseline MRI scanning and neuropsychological testing (Sport Concussion Assessment Tool version 2 (SCAT2, (39)) before the beginning of the hockey season. Players who were diagnosed with a concussion by an independent physician, based on criteria outlined in the 3rd Consensus Statement on Concussion in Sport (39), underwent additional scans and testing at 72-hours, 2-weeks, and 2-months after injury. End of season scans were also completed for the non-concussed cohort. The sample size for this preliminary study was determined from previous cross-sectional literature reports on expected incidence of concussions. Cross-sectional imaging studies have found effects of concussion with less than 15 subjects each (103). The incidence of concussion in competitive contact sports such as Varsity ice hockey was estimated at 25% or higher (6). The rationale was then to work with two varsity ice hockey teams where one could expect eight to 12 concussions within a season, sufficient for a preliminary prospective study with pre-injury data from the same brains. Exclusion criteria included a history of severe cognitive impairment, psychiatric or other central neurological disorder, pacemaker use, previous eye surgery, or having worked in an environment likely to expose the participants to the risk of metal fragments being embedded in their eyes. No participants were excluded from this study on these grounds. All participants provided written informed consent prior to participation in the study, which was approved by the University of British Columbia Clinical Research Ethics Board (H11-00423).    55  2.3.2 Myelin water imaging and processing MRI data were acquired on a Philips Achieva 3T scanner equipped with Quasar Dual Gradients and an eight-channel SENSE head coil. A 32 echo T2 scan (14 minutes, 22 seconds) was acquired for myelin assessment (TR=1000 ms, TE=10, 20, … , 310, 320 ms,  flip angle=90°, acquisition matrix=232x192, acquired voxel size 0.99 x0.99 x 5mm, reconstructed voxel size=0.96 x 0.95 x 2.5mm). The T2 decay was decomposed using a non-negative least squares fit with an extended phase graph algorithm and flip angle optimization (115). MWF was calculated as T2 signal from 0-40ms divided by the total T2 signal. Other scans acquired during the scanning session included: (a) sagittal 3D T1-weighted scan (TR=8.1 ms, TE=3.7 ms, flip angle=6 degrees, acquisition matrix= 256 x 256 x 160, field of view=256 x 256 x 160 mm3, acquired voxel size=1 x 1 x 1 mm3, reconstructed voxel size=1 x 1 x 1 mm3, SENSE factor of 2 along the left-right direction), (b) sagittal 3D fluid attenuated inversion recovery (FLAIR) (TR= 8000 ms, TI = 2400 ms, TE=337 ms, flip angle=6 degrees, acquisition matrix= 256 x 256 x 160 , field of view=256 x 256 x 160 mm3, acquired voxel size=1 x 1 x 1 mm3 , reconstructed voxel size=1 x 1 x 1 mm3, SENSE factor of 2 along the left-right direction and 2.5 along the anterior-posterior direction),  (c) multi echo susceptibility weighted imaging (SWI) using an axial 3D gradient echo scan (TR=36  ms, TE=6/12/18/24/30 ms, flip angle= 17 degrees, acquisition matrix= 440 x 222 x 64 , field of view=220 x 166 x 128 mm3, acquired voxel size=0.5 x 0.5 x 2 mm3 , reconstructed voxel size=0.5 x 0.5 x 1 mm3, SENSE factor of 1.2 along the left-right direction), and (d) diffusion tensor imaging (DTI) scan (TR=7015 ms, TE=60 ms, flip angle=90 degrees, acquisition matrix=100 x 99, field of view=224 x 224 x 154 mm3, acquired voxel size=2.2 x 2.2 x 2.2 mm3, reconstructed voxel size=2  x 2 x 2.2 mm3, SENSE factor of 2.1 along the  anterior-  56 posterior direction, b0 = 0, b1 = 700 sec/mm2, 60 noncolinear directions). Total data acquisition time was 48 minutes. Results from the conventional scans are reported elsewhere (314).   2.3.3 Statistical analysis Myelin water fraction changes were evaluated through comparison of concussed athletes’ baseline scans to those acquired at 72 hours, 2 weeks, and 2 months post-injury. Impact-related mTBI is a very heterogeneous injury (266). However, in the current preliminary study, the intent was to prospectively investigate myelin dynamics after mTBI without making any clinical predictions on an individual basis, let alone correlate clinical measures with imaging measures. Voxelwise statistical analysis of the data was performed using tract-based spatial statistics (TBSS) (315), part of the Functional MRI of the Brain Software Library (FSL (316)), which creates a white matter skeleton for each participant’s brain using fractional anisotropy (FA) maps obtained from diffusion tensor images. First, FA images were created by fitting a tensor model to the raw diffusion data using FDT, and then brain-extracted using BET. All subjects' FA data were then aligned into a common space using the nonlinear registration tool FNIRT, which uses a b-spline representation of the registration warp field. Next, the mean FA image was created and thinned to create a mean white matter skeleton that represents the centres of all tracts common to the group. MWF maps were then registered into DTI space and projected onto the white matter skeleton. Voxelwise statistics were carried out using the randomise tool in FSL for 5000 permutations with threshold-free cluster enhancement to assess differences in myelin water fraction at each post-injury time point compared to baseline, while controlling for, as explanatory variables, age, gender, SCAT2 results, and whether scans were acquired before or after an upgrade to the scanner's gradient system occurred. The locations of significant voxels were   57 identified anatomically using the John’s Hopkins University standard white matter atlas. No outliers were excluded from analysis, as possible “outliers” may well be within the normal spectrum of mTBI. Corrected level of significance was set at α = 0.05. These methods were chosen explicitly to examine diffuse changes in brain structure, without a priori assumptions as to where such changes would occur, while compensating for multiple comparisons. This approach effectively restricts analysis to areas that are injured in the majority of subjects, and follows the myelin signal in these brain areas. Analysis of the data was performed by non-supervised algorithms. The study had a conventional imaging component as well, which required the reading of MRI data by radiologists. These data will be reported elsewhere.  2.4 Results 11 players (six female) sustained a concussion during the ice hockey season (Table 2-1). When comparing baseline scans between concussed and non-concussed athletes, voxelwise TBSS revealed no significant differences in myelin water fraction. Within the non-concussed cohort, no significant differences were identified between pre-season and post-seasons scans. Eight out of 11 concussed subjects were able to complete scanning at 72 hours post-injury, 10 out of 11 athletes were scanned at 2 weeks, and nine out of 11 were scanned at 2 months post-injury (Figure 2-1).        58 Table 2-1: Demographic characteristics of all athletes Subject Concussed (Y/N) Sex Age 1 Y M 22 2 Y M 21 3 Y F 21 4 Y F 19 5 Y F 22 6 Y F 21 7 Y M 22 8 Y M 24 9 Y F 19 10 Y F 19 11 Y M 23 12 N F 23 13 N M 21 14 N F 18 15 N F 20 16 N F 18 17 N F 18 18 N M 21 19 N M 24 20 N F 21 21 N M 22 22 N M 25 23 N M 22 24 N M 21 25 N F 19 26 N F 18 27 N M 22 28 N M 20 29 N M 21 30 N M 21 31 N F 20 32 N M 22 33 N F 18 34 N M 23 35 N F 17 36 N M 20 37 N F 19 38 N F 17 39 N M 21 40 N M 23 41 N F 36 42 N M 18 43 N M 22 44 N M 23 45 N M 26    59  Figure 2-1: Representative myelin water fraction maps. Myelin water fraction maps from a concussed athlete at baseline (left) and two weeks post-injury (right). Myelin water fraction is measured as the T2 signal from 0-40 ms divided by the total T2 signal. A region of the corpus callosum with a visible reduction in MWF post-injury is highlighted by the red arrow. Fig 1 from (317). Image reproduced with permission from PLoS ONE.  Within the concussed cohort, TBSS showed clusters of voxels with significantly reduced myelin water fraction at two weeks post-injury, relative to baseline (Figure 2-2). Across all significant voxels, this represented a 5.9% ±	1.2% (mean ± standard error)	reduction in MWF from baseline to 2 weeks. A decrease in MWF was observed at 72 hours post-injury in these voxels, but this did not achieve statistical significance (p=0.076). No significant MWF changes were observed between baseline and 2 months post-injury.     60  Figure 2-2. Relative myelin water fraction change post-injury. Change scores for myelin water fraction, relative to baseline, plotted against time for each subject with a mild traumatic brain injury in all significant voxels A) across the whole brain; B) in the splenium of the corpus callosum (a structure most commonly affected in mild TBI). Dots represent data points for each injured athlete (mean ± standard error plotted in grey). Note: time zero refers to baseline. Fig 2 in (317). Image reproduced with permission from PLoS ONE.   These voxel clusters were located in the splenium of the corpus callosum, right posterior thalamic radiation, left superior corona radiata, left superior longitudinal fasciculus, and left posterior limb of the internal capsule (as shown in Figure 2-3).    61  Figure 2-3. Brain areas with significantly reduced myelin water fraction. Areas of significantly reduced myelin water fraction in athletes with concussion at two weeks post-injury, superimposed on a standard brain. These areas include the splenium of the corpus callosum, right posterior thalamic radiation, left superior corona radiata, left superior longitudinal fasciculus, and left posterior limb of the internal capsule. Fig 3 from (317). Image reproduced with permission from PLoS ONE.  2.5 Discussion  In the current preliminary report, we present the first prospective study on myelin water fraction in the context of mTBI in the human brain, and demonstrate significant post-injury reductions. In contrast, tract-based spatial statistics of post-season MWF maps demonstrated no differences from pre-season scans in athletes who did not sustain a concussion. Myelin water fraction, derived from the T2 decay signal, is a direct marker of myelin content in the brain. These data may indicate a process of transient myelin disruption following mTBI in areas of the brain   62 previously shown to exhibit diffusivity changes (reviewed in (97)). Furthermore, MWF recovered to near-baseline values by 2 months post-injury. Although significantly reduced MWF values were observed at the 2-week time point only, there was a trend towards decreased MWF at 72 hours post-injury (p = 0.076). That no differences were seen between pre- and post-season for non-concussed athletes is encouraging, given recent concern over the effect of exposure to repetitive sub-clinical trauma (318).  The exact time course of myelin alterations following sport-related concussion cannot be determined from this exploratory study. As the subjects were acutely concussed and enduring the worst phase of their symptoms, only eight of the 11 subjects were able to complete the 72 hour scan; it is possible that the reduced sample size at this time point may have obviated statistical significance from being achieved. Previous work has demonstrated that peak concentrations of myelin basic protein in the cerebrospinal fluid (CSF) occur at 48-72 hours following severe TBI, where primary axotomy likely occurred (319). In milder forms of TBI such as concussion, where primary axotomy does not occur, myelin degradation (as a downstream effect of the post-injury neurometabolic cascade and subsequent neuroinflammation) may take longer to occur, which may also explain the why the MWF reduction at 72 hours post-injury did not achieve statistical significance. It is important to point out that, although we observed a significant reduction in MWF at 2 weeks post-injury, peak reductions in myelin content may have occurred earlier or later. Indeed, significant loss of myelin for up to 21 days following injury has been reported following fluid percussion injury in rats (93), although this injury model is recognized to be of greater severity than sport-related concussion. Maxwell and colleagues demonstrated that optic nerve fibre degeneration may be initiated days to weeks after a mechanical stretch injury (81).   63 Using closed-skull impacts in mice (an injury model more similar to concussion), Mierzwa et al. (82) reported markers of neuroinflammation localized to areas of axon and myelin pathology for up to 6 weeks. Similarly, true recovery of MWF to baseline values may have occurred earlier or later than two months following injury. Myelin debris is known to stimulate neuroinflammatory processes (82,95). In the context of Wallerian degeneration, myelin debris has been reported to remain for several months before full clearance by macrophages (320), while previous work has shown myelin fragments contained within activated microglia for up to 4 weeks after fluid percussion injury (321). Remyelination of multiple sclerosis lesions has also been observed within 2 months (322). The exact time course of myelination dynamics following mTBI in humans is not currently known. Nevertheless, the authors of the current preliminary article postulate that myelin fragmentation and degeneration led to the observed reductions in MWF, with the recovery of MWF by two months post-injury likely due to remyelination of the affected axons by oligodendrocytes.    We are inferring that changes in myelin water fraction are indicative of true changes in myelination within the brain. T2 relaxation-based MWI provides insight into tissue characteristics that are not observed using standard MR imaging techniques. Numerous studies have supported that the short component of the multicomponent T2 relaxation distribution is specific to myelin, and have suggested this as the best imaging technique to distinguish between myelination and inflammation (112,116-118). Post-mortem MRI-pathology correlation studies in both CNS (111) and animal peripheral nerve (119) have demonstrated good quantitative and qualitative relationships between MR-derived MWF and histological staining for myelin. Myelin water imaging was shown to have high reproducibility in healthy brains, both longitudinally and   64 between imaging sites using the same scanner type and the same protocol (120,121). Moreover, MWF in the normal appearing white matter of people with multiple sclerosis was also shown to be stable over at least six months (122). In a guinea pig model of demyelination (experimental allergic encephalomyelitis), a decrease in the short T2 component was observed, which was consistent with histological myelin loss (116). As such, it is reasonable to conclude that the MWF changes observed in the current study are indeed reflective of transient reductions in myelin content following mTBI.  The current results provide the first direct, in-vivo demonstration of myelin damage following sport-related mTBI in humans, a notion that is supported by previous work in different models. Experimental models have implicated myelin disruption and subsequent remyelination to be major components of the degeneration and recovery process in white matter following mTBI (82,83). Multiple mTBI studies using closed-skull impacts in mice have shown significant demyelination distributed across intact axons using electron microscropy and histological staining techniques. Donovan and colleagues observed structural abnormalities in rats that experienced controlled cortical impacts, including separation of myelin from the axon, as well as decompaction and fragmentation of the myelin sheath following repetitive mTBI, compared to sham injury (323). Both single and repetitive injuries have been shown to lead to significant reductions in the thickness of myelin surrounding axons (82,323). Observations of increased Luxol fast blue staining (a histological stain for myelin) within the cytoplasmic compartment of cells following traumatic brain injury has supported the role of myelin degeneration and subsequent active phagocytosis of myelin fragments (308). Reports of acute decreases in axial diffusivity following experimental closed-skull mTBI, measured using diffusion tensor imaging,   65 followed by delayed increases in radial diffusivity also imply that axonal damage may be followed by myelin damage (323,324). Myelin disruption slows signal conduction, thereby desynchronizing circuitry within the brain (325) that may contribute to the observed neurological deficits that accompany mTBI, such as reduced information-processing speed. Accordingly, demyelination has been proposed to explain significantly slower interhemispheric transfer times (a measure of conduction speed through the corpus callosum) in paediatric human TBI patients, who also exhibited lower fractional anisotropy and higher mean diffusivity values in at least 13 out of 18 white matter tracts that were evaluated (108).   Transient reductions in the myelination status of axons following mTBI, as observed in the current study, may also help to explain the observation of a ‘temporal window of vulnerability’ following concussion (42), by which the brain is more sensitive to additional trauma during the recovery period. Magnetic resonance spectroscopy findings have demonstrated significant reductions in N-acetyl-aspartate (NAA) in the brain (42,326), a marker recently shown to be localized in the myelin of adult brains (327). Such NAA changes largely resolved within 30 days, but they did not coincide with clinical resolution of symptoms, implying a period of acute metabolic imbalance during the post-mTBI recovery process (42,326). Interestingly, MR spectroscopy studies in multiple sclerosis patients have also detected significant NAA reductions in the absence of any visible lesions (328). The integrity of axonal neurofilaments is dynamically regulated by the influence of myelin on kinase and phosphatase activity. From a developmental perspective, myelin increases phosphorylation of neurofilaments, enabling lateral extension of these structural proteins, which correspondingly increases axonal calibre and conduction velocity (329). Animal studies have shown that demyelination leads to a reduction in neurofilament   66 phosphorylation and consequent axon calibre (330,331). While the role of the myelin sheath in facilitating propagation of electrical impulses is well known, its pivotal role in neuronal metabolism is highlighted by estimates that myelinated axons are up to 70 times more metabolically efficient than unmyelinated axons (85). Myelin may also modulate the activity of the enzyme that hydrolyzes NAA into aspartate and acetate (involved in the production of coenzyme A) (332). As such, post-mTBI metabolic disturbances may at least partly be explained by changes in myelination (84). Moreover, previous research has suggested that unmyelinated axons may be more vulnerable to trauma, demonstrating greater electrophysiological impairment than their myelinated counterparts (333,334). It is possible that myelination changes after concussion may sensitize axons to further damage if exposed to additional trauma (309).  In evaluating changes in myelination within the brain, neuroimaging techniques that enable us to reliably observe pathophysiological changes behind an intact blood-brain barrier, such as myelin water imaging, are more appropriate than measurement of blood and CSF biomarkers. An important clinical limitation of using CSF for biomarker analysis is the invasive nature of acquiring such samples, which requires a lumbar puncture. While acquiring blood samples is less invasive, the blood-brain barrier, which is thought to remain intact following mTBI (335,336), attenuates the ability of biomarkers to enter the blood. Some biomarkers may be bound to carrier proteins or undergo degradation in the blood, further decreasing their measurable concentration, while extracerebral sources of some biomarkers also exist. Consequently, it has been difficult to identify reliable blood markers for mTBI (337). With specific regards to the evaluation of myelin, myelin basic protein (MBP) is the best available fluid biomarker of myelin integrity. No studies are currently available regarding the effects of mTBI on MBP levels in the CSF. While   67 the specificity of MBP in the blood for TBI appears to be adequate (96%), this marker lacks the sensitivity (44%) required to be clinically useful (338). In contrast, myelin water imaging enables us to reliably observe pathophysiological reductions in myelin behind a potentially intact blood-brain barrier, and thus appears to be a more appropriate in-vivo method towards answering research questions related to changes in myelination.  Myelin water imaging is a preferable technique to diffusion tensor imaging (DTI) for the evaluation of myelin integrity following mTBI (112). DTI is sensitive to diffusion properties of the various tissues within the brain, and has often been used as an indirect marker of myelin integrity in mTBI research. In white matter, the neurofibrils, axonal membrane, and myelin sheath promote water diffusion axially (along the length of the axons) relative to perpendicular flow, a phenomenon termed anisotropic diffusion (96) and quantified as fractional anisotropy (FA). Reports on diffusivity changes following mTBI have been equivocal, and have been reviewed in detail previously (97-99). While many studies have reported a decrease in FA following mTBI (100-102), numerous other studies have demonstrated an increase in FA (103-105), while other studies have reported no changes (106,107), or FA changes in both directions (24,105). At least part of these discrepancies may be related to inconsistent injury-to-scan intervals across studies, as the time course of changes in FA post-injury is not fully understood. Nevertheless, many studies infer that changes in DTI metrics reflect compromises in white matter and, more specifically, myelin integrity (108). Such interpretations must be made with caution, however, as myelin changes are not necessary or sufficient to yield changes in metrics of anisotropic diffusion (96). In fact, a fundamental limitation of interpreting changes in DTI metrics is the inability of this technique to distinguish between multiple factors that influence   68 them, including fiber diameter and density, fiber orientation, membrane permeability, edema, and demyelination (110). In contrast, T2 relaxation-based myelin water imaging directly evaluates myelin content in the brain, and has been validated histopathologically (111-113).  There are several limitations to the current preliminary study. Firstly, the sample size of concussed athletes is relatively small, which precludes an in-depth analysis of any differences between male and female athletes, or the relationship between myelin water fraction and neuropsychological scores. The prospective nature of this preliminary study limited the sample size but allowed us to directly compare intra-individual changes before and after injury. Nevertheless, the authors feel that this approach is preferable to a cross-sectional case-control design with a higher sample size. By definition, the specificity of the myelin water imaging technique to myelin comes at the expense of a decreased signal-to-noise ratio, as myelin water accounts for only ~15% of total brain water content (Sled et al. 2004 in (112)). Further, different individuals have different degrees of myelination within their white matter. As such, it is imperative to obtain pre-injury data when using this imaging approach to mitigate the effects of inter-individual variation. Unfortunately, not all subjects completed all MRI scans. However, the statistical power is similar at all time points with eight out of 11 concussed subjects scanned at 72 hours, 10 out of 11 scanned at two weeks, and nine out of 11 scanned at two months. An upgrade to the MRI scanner gradient system occurred during the course of the study, which included a replacement of the gradient coil. The exact date of this upgrade was known and was included as a covariate in the statistical analysis, but did not alter the results. Furthermore, monthly scans of a geometry phantom were acquired during this study, which were evaluated for field distortions due to gradient non-linearities; no such distortions were found in the phantom   69 data. Our statistical approach (TBSS) is exploratory in nature, unable to elucidate subject-specific MWF changes as it limits analysis to the central cores of large WM tracts common across all subjects. Therefore, TBSS also does not examine the grey matter-white matter junction, where traumatic axonal injury also occurs. Nevertheless, the fact that significant MWF changes are seen in a preliminary study with a small sample size emphasizes the need for more in-depth prospective investigations into the effects of mTBI on myelin dynamics, including analytical approaches to assess within-subject changes (24,266).   2.6 Conclusions In order to mitigate both the incidence and severity of concussive-type mild traumatic brain injuries, a better understanding of their neurobiological underpinnings is needed. This will facilitate the development of objective tools to improve the detection and management of these injuries. Although not currently appropriate for clinical application, myelin water imaging appears to be a promising approach to understanding the role of myelin following sport-related concussion. In this exploratory study, we detected significant reductions in myelin content in the brain of concussed athletes 2 weeks following injury, which recovered by 2 months. While validation is required in a larger number of subjects, the results of this preliminary study may indicate a process of transient myelin disruption following mTBI, and encourage the development of additional investigation into the effects of repetitive concussive and subclinical head impacts on the time course of myelination changes in the brain. Furthermore, exploration of the relationships between age, sex, and myelination on susceptibility to injury, as well as between myelin status and neurocognitive performance, is warranted.    70 Chapter 3: A transcranial Doppler ultrasound-based evaluation of the acute and cumulative effects of sport-related concussion on indices of dynamic cerebral autoregulation  3.1 Summary Sport-related concussion is a global public health concern, with the Centers for Disease Control and Prevention considering the injury at epidemic levels. The objective of the current prospective cohort study collected between September 2013 and December 2016 was to determine the acute and cumulative effects of sport-related concussion on indices of dynamic cerebral autoregulation. 179 elite, junior-level (age 19.6 ± 1.5 years) contact sport (ice hockey, American football) athletes were recruited for preseason testing, 42 with zero prior concussions and 31 with three or more previous concussions. 18 athletes sustained a concussion during the competitive season, and completed follow-up testing at 72-hours, 2-weeks, and 1-month post-injury. Beat-by-beat mean arterial pressure (MAP) and middle cerebral artery blood velocity (MCAv) were recorded using finger photoplethysmography and transcranial Doppler ultrasound, respectively. Five minutes of repetitive squat-stand manoeuvres induced MAP oscillations at 0.05 Hz and 0.10 Hz. The MAP-MCAv relationship was quantified using transfer function analysis to estimate Coherence (correlation), Gain (amplitude ratio), and Phase (response latency). Repeated-measures ANOVA indicated 0.10 Hz Phase was reduced (mean difference ± SE) following acute concussion, compared to preseason, by 23% (-0.136 ± 0.033 rads) at 72-hours and by 18% (-0.105 ± 0.029 rads) at 2-weeks post-injury, and was related to performance on the Standardized Assessment of Concussion; recovery occurred by 1-month. Symptoms   71 resolved by 2-weeks, and athletes were cleared for return-to-play in a median of 14 days, implying physiologic dysfunction persisted beyond clinical recovery in many cases. When comparing autoregulatory behaviour between athletes with three or more prior concussions and those with zero, no differences were observed despite persistent concussion-like symptoms. Acute sport-related concussion induces transient impairments in the capacity of the cerebrovascular pressure-buffering system that may persist beyond clinical recovery, and may be due to a period of autonomic dysregulation. Athletes with a history of three or more concussions did not exhibit impairments relative to those with zero prior concussions, suggesting recovery of function over time. Findings from this preliminary study support the potential need to consider physiological recovery in deciding when patients should return-to-play following a concussion.    3.2 Introduction Sport-related concussions (SRC) are a public health concern; recent reports estimate 1.1 to 1.9 million occur each year in US youth alone (4). Whereas the majority of patients recover clinically within two weeks (9), concussions are characterized by a period of increased cerebral vulnerability to additional trauma (9,42,339). Additional research has shown the effects of SRC may be cumulative, with reports demonstrating collegiate athletes with a history of three or more concussions exhibit a three-fold increased risk of a subsequent concussion (11).   The increased cerebral vulnerability observed post-SRC might reflect a distinction between physiological and clinical recovery, the latter being heavily based on symptom resolution to guide return-to-learn/return-to-play decisions. Alterations in physiological parameters persist far   72 beyond the typical 7-10 days to clinical recovery: among other physiological markers, cortical connectivity (340), myelin content (Chapter 2:)(317), cardiac autonomic function (303,305), and cerebral blood flow (CBF) (2,43,136,137) have demonstrated recovery profiles on the order of 30+ days. In both paediatric and adult patients, local and global reductions in CBF have been reported following SRC that may persist beyond 30 days (2,43,136). Meier et al. (43) report regional reductions in CBF at 1-month in slower-to-recover athletes that were related to initial symptom severity (43). Contrastingly, Barlow and colleagues reported reduced CBF in asymptomatic subjects at 1-month post-injury, whereas symptomatic participants displayed increased CBF compared to controls (137). Despite demonstrated CBF alterations following concussion in the literature, surprisingly little work has focused on the effects of SRC on CBF control mechanisms.    Concussion-induced CBF disturbances may arise from disruptions in cerebral autoregulation (CA) – the ability of the cerebral blood vessels to buffer blood pressure (BP) changes (189). Normally, CA behaves as a high-pass filter, whereby higher frequency BP oscillations (>0.20 Hz) are transferred to the cerebrovasculature, while lower frequency oscillations are dampened (189). Myogenic, neurogenic, and metabolic mechanisms are involved in CA, functioning to protect against BP surges during periods of relative hypertension and against ischemia during hypotensive episodes (190,341). Disrupted CA may be a mechanism underlying persistent post-concussive symptoms (206). Impairments in CA are a significant predictor of poor outcome acutely following moderate and severe traumatic brain injury (TBI) (342,343). Impaired CA has also been observed in a small number of hospitalized mild TBI patients, the majority of whom also exhibited abnormal intracranial findings on CT (208,209). However, little is known to what   73 extent the dynamic, frequency-dependent relationship between BP and CBF is affected by SRC (131,175).   Accordingly, our objectives in the current study were to obtain pre- and post-injury data to provide the first evaluation of acute and cumulative effects of SRC on indices of dynamic CA. Towards this end, we sought to examine the effects of: i) acutely diagnosed SRC, and; ii) multiple (3+) previous SRC in otherwise healthy athletes.   3.3 Methods 3.3.1 Study design 179 male (mean age 19.6 ± 1.5 years) elite junior hockey (n=90) and American football (n=89) players were recruited. All participants underwent preseason baseline testing. Upon enrolment, 42 players had experienced zero concussions (Hx-) while 31 had sustained three or more concussions (Hx3+). Athletes diagnosed with a concussion (n=18) by an independent physician based on criteria in the 4th Consensus Statement (9) repeated testing at 72-hours, 2-weeks, and 1-month post-injury. Prior to physiological testing, participants completed the Sport Concussion Assessment Tool (SCAT3) (9), a concussion screening tool comprised of symptom characterization, the Standardized Assessment of Concussion (SAC) that probes orientation, immediate and delayed recall, and concentration, as well as performance on the modified Balance Error Scoring System (BESS) (Table 3-1). No participants were excluded based on a priori exclusion criteria of significant history of cardiorespiratory, cerebrovascular, neurological, or severe neurodevelopmental disorder. All subjects underwent familiarization of testing procedures, and abstained from exercise, caffeine, and alcohol for 12+ hours prior to testing. All   74 participants provided written informed consent, approved by the University of British Columbia Clinical Research Ethics Board.   Table 3-1. Participant characteristics. Demographics, SCAT3 performance, and resting physiological parameters during each test session for acutely concussed athletes. Data are presented as mean (SD) unless otherwise noted. Metric Concussion History Concussed (n=18) 0 (n=42) 3+ (n=31) Preseason 72 Hour 2 Week 1 Month Age (years) 19.0 (1.4) 19.6 (1.9) 18.6 (1.5) BMI (kg/m2) 27.6 (5.1) 27.5 (4.3) 25.5 (3.1) RTP (days) N/A (preseason only) median = 14, range 7-35 days # Symptoms 2.2 (2.7) 4.7 (4.3) 2.0 (3.6) 11.2 (5.5) 2.8 (3.0) 1.1 (2.1) Symptom Severity 3.4 (4.7) 9.3 (12.0) 3.6 (3.6) 25.1 (19.0) 3.6 (3.5) 1.3 (2.3) SAC Score (/30) 27.1 (1.7) 26.7 (1.8) 26.8 (1.7) 26.5 (2.0) 26.9 (2.9) 28.1 (1.3) BESS Score (/10) 3.5 (3.2) 3.5 (3.3) 2.6 (2.6) 4.2 (3.1) 3.0 (2.3) 2.0 (2.0) MCAv (cm/s) 55.1 (9.0) 55.6 (9.3) 53.8 (7.0) 53.5 (8.7) 53.3 (9.5) 53.2 (7.8) MAP (mmHg) 95.0 (13.6) 94.1 (12.4) 92.3 (20.1) 90.4 (18.2) 92.0 (16.5) 91.2 (15.9) PETCO2 (mmHg) 37.7 (2.8) 38.1 (2.5) 37.7 (3.2) 37.6 (3.7) 37.9 (4.1) 37.6 (4.5) HR (bpm) 75.1 (9.8) 73.6 (8.7) 79.4 (8.3) 79.7 (12.2) 82.1 (15.9) 79.5 (10.2) SCAT3 = Sport Concussion Assessment Tool version 3; BMI = body mass index; RTP = return-to-play duration; SAC = Standardized Assessment of Concussion; BESS = Balance Error Scoring System;  MAP = mean arterial pressure; MCAv = middle cerebral artery blood velocity; PETCO2 = end-tidal partial pressure of carbon dioxide; HR = heart rate  3.3.2 Instrumentation Participants were equipped with a three-lead electrocardiogram (ECG). Transcranial Doppler (TCD) ultrasound (ST3, Spencer Technologies, Seattle, WA) recorded blood velocity in the middle cerebral artery (MCAv). After the vessel was identified and signal optimized according to depth, waveform, and velocity, the ultrasound probe was locked in place with a fitted head frame (Spencer Technologies, Seattle, WA). Our research group has demonstrated this method of indexing CBF to be highly reliable and reproducible in a similarly aged population, with within-  75 subject coefficient of variations reported to be 2-3% (210). Beat-to-beat BP was recorded with finger photoplethysmography (Finometer PRO, Finapres Medical Systems, Amsterdam, Netherlands). End-tidal partial pressure of carbon dioxide (PETCO2) was monitored using an online gas analyzer (ML206, AD Instruments, Colorado Springs, CO). All data were sampled at 1000 Hz (PowerLab 8/30 ML880, AD Instruments) and stored for offline analysis using commercially available software (LabChart version 7.1, AD Instruments).   3.3.3 Experimental protocols All visits to the laboratory occurred at the same time of day (344) and involved a hemodynamic challenge protocol (repetitive squat-stand manoeuvres) (210). Resting data were recorded during five-minutes of quiet stance. During squat-stands, subjects started from standing, squatted and held a ~90˚ knee angle, and returned to standing at a pace dictated by a metronome. Squat-stands were performed for five minutes at two different frequencies – 0.05 Hz and 0.10 Hz – thought to reflect myogenic and autonomic contributions towards CA, respectively (191-193).   3.3.4 Data processing and transfer function analysis Beat-to-beat mean arterial pressure (MAP) and MCAv were determined from each R-R interval. All data were analyzed with custom-designed software in LabView 14 (National Instruments, Austin, TX), as outlined previously (210). MAP and MCAv data were spline interpolated and resampled at 4 Hz. In accordance with best-practice guidelines for transfer function analysis (212), each 5-min recording was divided into five successive windows with 50% overlap. Data within each window were linearly detrended and passed through a Hanning window prior to fast   76 Fourier transform. Transfer function analysis involved determining the cross-spectrum between MAP and MCAv, divided by the MAP autospectrum, in order to derive transfer function Coherence, Phase, and normalized Gain. Similar to a correlation coefficient, Coherence describes the proportion of variance in the output signal (MCAv) explained by the input signal (MAP); a high coherence improves within-subject reliability of Phase and Gain (210). Phase represents the timing offset between input and output oscillations, whereas Gain provides a ratio of output amplitude to input amplitude. In the setting of intact CA, higher Phase indicates more rapid adjustment of cerebrovascular resistance to changing MAP. Low gain indicates low magnitudes of MAP oscillation transferred to the cerebrovasculature (i.e. greater buffering) (210). Metrics were sampled at 0.05 and 0.10 Hz; phase wraparound was not present for any point-estimates.  3.3.5 Statistical analyses All statistical analyses were performed using SPSS Statistics for Macintosh (Version 22.0, IBM Corp., Armonk, NY). Shapiro-Wilks tests were used to assess for normality, while Mauchly’s test was used to evaluate sphericity. Where sphericity was violated, Greenhouse-Geiser epsilon was used to adjust degrees-of-freedom for the primary F-test. Significance was determined a priori to achieve an experiment-wide α = 0.05.  3.3.5.1 Effect of acute concussion A 2 (frequency: 0.05 and 0.10 Hz) by 4 (time: preseason, 72-hours, 2-weeks and 1-month) two-way repeated-measures ANOVA was used to evaluate the effect of acute SRC on dependent variables. When omnibus tests indicated significant main effects, pre-planned t-tests    77  Figure 3-1. Representative traces. Representative time-series profiles showing oscillations in blood pressure (BP, top) elicited during 60 seconds of squat-stand manoeuvres performed at 0.05 Hz (left) and 0.10 Hz (right); oscillations are also observed in middle cerebral artery blood velocity (MCAv, middle); expired carbon dioxide (PCO2, bottom) is less affected.  were used to evaluate each post-injury time point relative to preseason. For variables exhibiting a significant effect of time, secondary exploratory analyses were conducted to estimate the relationship between change in CA metrics and change in SCAT3 performance. Specifically, Pearson or Spearman correlation coefficients were calculated between acute change scores in the dependent variable and changes in symptom number, symptom severity, performance on the   78 SAC and BESS, and time to independent medical clearance for full return-to-play (RTP).  3.3.5.2 Cumulative effects of multiple previous concussions The cumulative effect of concussions on transfer function metrics was evaluated using a 2 (frequency) x 2 (Hx- versus Hx3+) two-way mixed ANOVA.   3.4 Results Demographic characteristics, SCAT3 performance, RTP durations and resting physiological data across are outlined in Table 3-1. Concussed athletes were cleared by their team physician to return to full-contact game participation a median 14 days post-injury. At preseason, Hx3+ participants reported a greater number (p = 0.033) and severity of symptoms (p = 0.013) than Hx- participants. Physiological variables did not differ between groups (p > 0.05). Representative traces of MAP, MCAv, and PETCO2 are shown in Figure 3-1. Squat-stand manoeuvres increased power in MAP and MCAv signals at the desired point frequencies (Figure 3-2).  3.4.1 Effect of acute concussion Two-way RM-ANOVA indicated significant main effects of frequency for Coherence and Gain (Figure 3-3). Coherence (F1,17=35.6, p<0.001) and Gain (F1,17=172.1, p<0.001) were significantly higher at 0.10 Hz than at 0.05 Hz, suggesting preserved high-pass filter behaviour of the cerebrovasculature following injury. Interaction terms between frequency and time were significant for Phase (F3,51=4.715, p=0.007), but not for Coherence (F2.02,34.31=0.416, p=0.665) or Gain (F3,51=1.654, p=0.189). Simple effects revealed an effect of time for 0.10 Hz Phase (F3,51=8.061, p<0.001). Relative to preseason, planned contrasts revealed significant Phase   79 reductions (mean difference ± SEM) of 27% at 72 hours (-0.158 ± 0.028 rads, p<0.001) and 20% at 2-weeks (-0.117 ± 0.023 rads, p<0.001), suggesting a slower CA response post-SRC. By 1-month, Phase had recovered to near-preseason values (-0.024 ± 0.029 rads, p=0.42).    Figure 3-2. Normalized power spectra. Normalized values of power spectrum densities for mean arterial pressure (MAP; a,c) and middle cerebral artery blood velocity (MCAv; b,d) for preseason and post-concussion squat-stands at 0.05 Hz (a,b) and 0.10 Hz (c,d); preseason squat-stands in subjects with zero (Hx-) versus three or more (Hx3+) previous concussions (e,f). The frequencies at which power spectra reached peak amplitude (either 0.05 Hz or 0.10 Hz) were used in sampling point estimates for Coherence, Phase, and Gain.    80  Figure 3-3: Summary of transfer function analysis outcomes describing CA function in acutely concussed athletes. Coherence (top), Phase offset (middle), and normalized Gain (bottom) during squat-stand manoeuvres assessed at preseason and each post-injury time point in athletes who suffered a concussion during the season. † represents significant main effect of frequency (p all <0.01), * denotes significant simple effect of time (p all < 0.001). Data presented as mean ± 95% CI.   81 A significant correlation was observed between ∆Phase0.10Hz from preseason to 72-hours, and ∆SAC composite score (r=0.549, p=0.018). However, correlations were not significant between ∆Phase0.10Hz and change in symptom number (r=-0.197, p=0.434), symptom severity (ρ=-0.168, p=0.504), headache (ρ=-0.113, p=0.656), “pressure in the head” (ρ=-0.011, p=0.967), or performance on the BESS (r=-0.133, p=0.600).  3.4.2 Cumulative effects of multiple previous concussions Two-way mixed ANOVA did not reveal main effects of concussion history for Coherence (F1,71=1.808, p=0.184), Phase (F1,71=0.005, p=0.944), or Gain (F1,71=0.832, p=0.365) (Figure 3-4). Significant main effects of frequency were observed for all variables (p<0.001), while interaction terms were non-significant (p=0.311, 0.398, 0.973 for Coherence, Phase, and Gain, respectively). As expected, Coherence (+1.74%, 95%CI = 0.008 – 0.026) and Gain (+50.4%, 95%CI = 0.398 – 0.533 %/%) were higher, while Phase was lower (-37.9%, 95%CI = -0.372 – -0.256 rads) at 0.10 Hz relative to 0.05 Hz, indicating intact high-pass filter behaviour.    82  Figure 3-4. Summary of preseason autoregulatory outcomes from transfer function analysis for athletes with zero (Hx-) and three or more (Hx3+) previous concussions. Coherence (top), Phase offset (middle), and normalized Gain (bottom) during squat-stand manoeuvres assessed at preseason in athletes with zero and three or more previous concussions. † represents significant main effect of frequency (p all <0.001). Data presented as mean ± 95% CI.    83 3.5 Discussion  In the current report, we provide the first prospective study to evaluate the capacity of the cerebral blood vessels to modulate CBF in response to changes in BP after SRC. Transient impairments in the CA response were observed at 0.10 Hz, a frequency associated with sympathetic contributions to CA (191,345). At a within-subject level, more substantial CA impairments were related to poorer performance on the SAC, a brief cognitive screen for SRC. These impairments in pressure-buffering persisted beyond medical clearance for return-to-play in many cases, highlighting an important discrepancy between clinical (median 14 days) and physiological recovery (~30 days). However, when comparing preseason CA function in contact sport athletes with three or more previous concussions to those with zero, no differences were observed despite persistent concussion-like symptoms. These data support a process of transient SRC-induced autonomic dysfunction that does not appear to exert cumulative, lasting effects on the cerebrovasculature.   3.5.1 Cerebral blood flow alterations post-concussion Transient disruptions in CBF following concussion have been reported previously (2,43,136,137). In the earliest post-mTBI phase (<48 hours), a period of acute hyperemia occurs with CBF peaking at 24-hours (346), although this may be age-dependent (139,140). Subsequently, global and regional reductions in CBF are reported both sub-acutely (2,43,136) and chronically (142,143), in both paediatric (2) and young adult (43,136) athlete populations. In both age groups, blood flow often recovers to near-healthy levels by ~30 days (2), and may be related to symptom resolution (43,137). Nevertheless, arterial spin labeling has shown those with a history of concussion consistently display reduced fronto-temporal CBF, independent of the   84 number of previous concussions (136,144). In the current study, we did not observe significant reductions in resting MCAv as a function of concussion (Table 3-1). This may be due to differences in sensitivity and spatial resolution between MRI and TCD to subtle changes in flow, with MRI providing higher spatial resolution. Despite the existence of CBF alterations following SRC, a paucity of evidence exists documenting effects on mechanisms controlling CBF. A comprehensive evaluation of cerebrovascular functioning should consider reactivity to CO2, the neurovascular coupling response, and an assessment of the cerebral pressure-flow relationship (145).   3.5.2 CA impairments in traumatic brain injury Autoregulatory mechanisms appear sensitive to acquired brain injury, as CA disruptions are well documented following moderate and severe TBI, with one small study suggesting similar deficits in a subset (8/29) of hospitalized mild TBI patients (208). Across multiple studies, 49-87% of severe TBI patients exhibit absent or impaired CA (197,199), with recovery of CA after severe TBI delayed in some cases beyond 2 weeks (199). CA evaluation has predictive value in acquired brain injury populations: in severe TBI, acutely compromised CA is a significant predictor or poor outcome (200,201); following subarachnoid haemorrhage, CA dysfunction predisposes patients to delayed cerebral ischemia and vasospasm (203-205); impaired CA is an established independent risk factor for stroke (159). The findings of the current study indicate that even comparatively mild brain injuries, such as SRC, disrupt the capacity of the brain to regulate CBF in the face of changing BP.    85 3.5.3 Possible mechanisms for CA impairments following concussion The current observation of reduced 0.10 Hz Phase for at least two weeks implies altered autonomic regulation of the cerebrovasculature causing a delayed change in vascular resistance in response to a BP challenge. This complements previous reports of SRC-induced cardiovascular autonomic dysfunction, providing the first evidence that autonomic dysregulation affects cerebral hemodynamics. Concussion alters cardiac autonomic function, particularly during exercise; altered heart rate variability patterns – associated with resting CBF (347) – suggest increased sympathetic and / or lowered parasympathetic tone for at least 10 days post-injury (298-301). The cerebrovascular tree is richly innervated by sympathetic fibres (272), and mounting evidence points to the importance of sympathetic innervation in the dynamic regulation of BP variability (190). Pharmacological studies in healthy young adults have shown sympathetic activation reduces Phase at frequencies including 0.10 Hz (191,345). In accordance with the suggestion that progressive impairment of CA likely affects response latency (Phase) before affecting efficiency (Gain) (195), we observed significant changes in Phase only. These results indicate SRC induces autonomic dysregulation affecting cerebral hemodynamics for at least 2-weeks, but suggest no cumulative effects of multiple injuries.   The mechanism by which SRC alters autonomic function, CA, and CBF remains unclear. It is not definitively known whether vascular dysfunction precedes neuronal dysfunction, or results from primary neuronal dysfunction (348), preclinical rodent TBI models have shown reductions in the number and diameter of capillaries at the injury site (349), while impaired CA has been associated with cerebral white matter damage (350). Specifics underlying sympathetic modulation of cerebrovascular resistance remain poorly defined, but brain injury models show   86 lateralized control of cardiac autonomic outflow, wherein left insular efferents exert parasympathetic effects and right insular efferents generate sympathetic responses (351-353). Disruption to the corpus callosum – the white matter structure consistently reported to show damage following concussion (99,317) – could compromise balance between sympathetic and parasympathetic outflow (301). Furthermore, damage to prefrontal areas within the central autonomic network could exert a disinhibition of the central nucleus of the amygdala, causing a net increase in sympathetic activity through subsequent disinhibition of sympathoexcitatory neurons in the ventrolateral medulla (354). Increased sympathetic drive has been shown to effect a transient “stiffening” of intracerebral vessels following concussion (300), which would effectively cause a delay in vessel responsiveness and explain the observed reduction in Phase, although this remains speculative.   3.5.4 Limitations There are several limitations to the current study. First, clinical guidelines for SRC management during the study period dictate physical and cognitive rest post-injury. The potential detraining influence of strict rest on CA cannot be discounted; however, CA has previously been shown to be preserved or even improved following prolonged bed rest (355). Recruiting a control group of healthy uninjured elite athletes to undergo a post-concussion rest and return-to-play protocol would allow insight, but is pragmatically unrealistic. Second, concussion remains a clinical diagnosis. As we recruited from multiple teams, three different physicians provided official concussion diagnoses, potentially magnifying the omnipresent heterogeneity within our sample. Third, we tested only male athletes, representing a significant shortcoming in the generalizability of our findings, as females are reported to sustain higher rates of SRC and longer recovery times   87 than males (356). Fourth, evaluation of acute effects of SRC benefitted from a repeated-measures design. Insight into the cumulative effects of multiple concussions may be better gleaned using a similar prospective approach; our between-subjects design may have precluded differences between Hx- and Hx3+ groups due to substantial variability in the normal range of Phase and Gain. Despite the widespread use of TFA within the CA research community (212), this approach models the MAP-CBF relationship as a linear system with one input and one output. As such, the inherent non-linearity of the autoregulatory system is not captured by this analysis technique, representing an important limitation of this approach. In effort to maximize the reliabilty of our MAP-CBF characterization, we had participants complete repetitive squat-stand manoeuvres to “linearize” the system and amplify signal-to-noise ratio. Nevertheless, though the analysis parameters used followed recommendations from the international CA research network (CARNet), it is possible that using only 5 data windows within our TFA may have inflated estimates of coherence; however, coherence would still be sufficiently high to enable reliable interpretation of Phase and Gain (210). Lastly, TCD provides an index of CBF by measuring the velocity of red blood cells – that this relationship holds true requires the diameter of insonated vessel to remain constant, which cannot be verified. However, there are ongoing debates surrounding the influences of MCA diameter changes on evaluation of cerebral hemodynamics (357,358). Effects of PCO2 on MCA diameter are assumed to have been minimal in the current study, as end-tidals were tightly maintained (Figure 3-1) (359). Nevertheless, that significant CA impairments were observed in a small sample emphasizes the need for in-depth prospective investigations into the effects of SRC on CBF control mechanisms.    88 3.6 Conclusion In order to mitigate the incidence and severity of concussive-type mild TBI, a better understanding of their neurobiological underpinnings is needed. Although not currently appropriate for clinical management, this TCD-based assessment shows significant reductions in the pressure-buffering capacity of cerebral blood vessels in concussed athletes for at least 2-weeks that were related to performance on a cognitive screening test. While validation is required in a larger sample, these results indicate SRC induces a transient disruption in autonomic cerebrovascular function that may outlast symptom resolution and clinical recovery. Development of further prospective investigations into the effects of SRC on mechanisms controlling CBF – including relationships with age, sex, impact biomechanics, and susceptibility to injury – are warranted.    89 Chapter 4: A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on indices of dynamic cerebral autoregulation  4.1 Summary Recent literature has raised concern over detrimental effects of repetitive subconcussive head trauma experienced during participation in contact sport. The objective of the current prospective cohort study collected between September 2013 and December 2016 was to determine the effect of repetitive sub-concussive head trauma on indices of dynamic cerebral autoregulation. 179 elite, junior-level (age 19.6 ± 1.5 years) contact sport (ice hockey, American football) athletes recruited for pre-season testing. 52 non-concussed athletes returned for post-season testing. 15 non-contact sport athletes (age 20.4 ± 2.2) also completed pre- and postseason testing. Beat-by-beat mean arterial pressure (MAP) and middle cerebral artery blood velocity (MCAv) were recorded using finger photoplethysmography and transcranial Doppler ultrasound, respectively. MAP oscillations were induced during five minutes of repetitive squat-stand manoeuvres at 0.05 Hz and 0.10 Hz. The MAP-MCAv relationship was quantified using transfer function analysis to estimate Coherence (correlation), Gain (response amplitude), and Phase (response latency). In contact sport athletes, 0.10 Hz Phase was reduced and Gain was increased at post-season compared to pre-season, indicating impairment in both the latency and magnitude of the autoregulatory response to changing blood pressure. These changes were associated with increased reporting of headache and pressure in the head. Changes in Phase were greater in athletes experiencing a higher number and severity of head impacts. Gain increases were   90 correlated to elevations in sympathetic tone, estimated from resting heart rate variability. Contrastingly, non-contact sport controls displayed no changes in autoregulatory behaviour from pre- to post-season. Repetitive subconcussive head trauma, as experienced during one season of participation in contact sport, induces exposure-dependent impairments in the capacity of the cerebrovascular pressure-buffering system, and may be due to autonomic dysregulation. It is unknown how long these deficits persist or if they accumulate year-over-year.   4.2 Introduction Sport-related concussion is a global public health issue, with growing concern over the effects of repetitive subconcussive head trauma (55). Subconcussion can be defined as head trauma that does not elicit signs or symptoms typical of clinical concussion (40,56). Numerous studies have demonstrated repetitive subconcussive trauma can cause deleterious alterations in brain structure and function that may be associated with the degree of subconcussive exposure (20,25,26,65-68,71,72), potentially altering the brain’s susceptibility and contributing to injury risk.  Alterations in cerebral blood flow (CBF) play an important role in the pathophysiology underlying concussion, but the effects of subconcussive trauma on CBF are poorly understood. Although the brain comprises only 2% of total body weight, it accounts for 15-20% of cardiac output (145), underscoring the importance of maintaining adequate perfusion. Comprehensive evaluation of cerebrovascular function need consider the multiple controllers of CBF, including reactivity to carbon dioxide (CO2), the neurovascular coupling response, and the blood pressure (BP) buffering system (145). In the face of changing BP, resistance within the cerebrovascular tree is altered to maintain CBF. The ability of the cerebral blood vessels to buffer changes in BP   91 – commonly referred to as cerebral autoregulation (CA) (189,360) – serves as an important marker of cerebrovascular function, and involves myogenic, neurogenic, and metabolic mechanisms (190,341). Disrupted CA has been demonstrated acutely post-concussion (Chapter 3:) and has been hypothesized as a mechanism underlying persistent post-concussion symptoms (206).  Disruptions in CBF have been demonstrated following sport-related head trauma. In both adult and paediatric populations, concussion has been shown to induce CBF changes that may be related to symptom recovery (2,43,137,141). Multiple studies have demonstrated alterations in reactivity of the cerebrovasculature to CO2 following concussion (45,176,178,361). Recently, impairments in CO2 reactivity have also been shown in asymptomatic high school football and soccer players that were not observed in non-collision athletes (18,19), and were attributed to repetitive subconcussive head trauma. While we have previously demonstrated transient CA impairments in acutely concussed athletes (Chapter 3:), it is currently unknown if subconcussive hits also affect CA.  Accordingly, our objective was to prospectively evaluate the effect of repetitive subconcussive head trauma on indices of dynamic CA, with the hypothesis that deficits would be observed at post-season relative to pre-season in a group of young adult elite contact sport athletes.   4.3 Methods 4.3.1 Study design 179 male (mean age 19.6 ± 1.5 years) junior hockey (n=90) and football (n=89) were recruited to   92 the study, in addition to 15 non-contact sport controls (mean age 20.4 ± 2.2 years; 12 cross-country running, 1 ultimate, 2 basketball). All participants underwent baseline laboratory testing prior to the beginning of the athletic season (preseason). Testing was repeated within two weeks of the end-of-season (post-season) for a subset of contact sport participants who did not sustain a concussion during the season (n=52), as well as the non-contact sport controls. Prior to physiological testing, all participants completed the Sport Concussion Assessment Tool, version 3 (SCAT3)(9). The SCAT3 is a concussion screening tool comprised of a graded symptom checklist (7-point Likert scale to characterize burden of 22 symptoms), the Standardized Assessment of Concussion (SAC) that probes orientation, immediate and delayed recall, and concentration, as well as the Balance Error Scoring System (BESS). No participants were excluded based on predefined criteria including a significant history of cardiorespiratory, cerebrovascular, neurological, or severe neurodevelopmental disorder. All subjects underwent familiarization of testing procedures, and abstained from exercise, caffeine, and alcoholic beverages for 12+ hours prior to testing. Written informed consent was obtained prior to participation, as approved by the University of British Columbia Clinical Research Ethics Board.   4.3.2 Instrumentation Participants were equipped with a three-lead electrocardiogram (ECG) for measurement of R-R intervals and heart rate. Cerebral blood flow velocity was recorded in the middle cerebral artery (MCAv) using transcranial Doppler ultrasound (ST3, Spencer Technologies, Seattle, WA). Vessels were identified and signals optimized according to depth, waveform, and velocity, and ultrasound probes were locked in place with a fitted headframe (Spencer Technologies). Beat-to-beat BP was recorded with finger photoplethysmography (Finometer PRO, Finapres Medical   93 Systems, Amsterdam, The Netherlands), while partial pressure of expired CO2 (PETCO2) was monitored using an online gas analyzer (ML206, AD Instruments, Colorado Springs, CO). All data were sampled at 1000 Hz (PowerLab 8/30 ML880, AD Instruments) and stored for offline analysis using commercially available software (LabChart version 7.1, AD Instruments).   Table 4-1. Participant characteristics. Demographics, SCAT3 performance, and resting physiological parameters for contact sport and control (non-contact sport) athletes at preseason and post-season; data are presented as mean (SD). Metric Contact Sport (n=52) Control (n=15) Preseason Post-season Preseason Post-season Age (years) 19.6 (1.5) 20.4 (2.2) BMI (kg/m2) 28.2 (4.9) 22.6 (3.0) Test Interval (days) 109.2 (25.8) 100.1 (23.8) # of Symptomsa 3.7 (3.6) 5.4 (5.0) 5.5 (5.0) 5.7 (3.3) Symptom Severitya 6.7 (7.8) 9.6 (10.1) 8.1 (8.3) 8.2 (7.2) SAC Scorea 26.6 (1.9) 26.6 (1.8) 27.7 (1.5) 27.9 (1.4) BESS Scorea 3.7 (3.3) 2.9 (3.2) 2.7 (2.4) 2.6 (3.6) MCAv (cm/s) 54.5 (9.3) 53.8 (7.5) 55.6 (14.4) 57.3 (14.3) MAP (mmHg) 92.2 (12.2) 92.6 (12.7) 93.9 (13.8) 91.3 (9.7) PETCO2 (mmHg) 38.0 (3.0) 37.1 (2.6) 37.9 (1.8) 37.9 (1.3) HR (bpm) 74.5 (10.0) 78.3 (11.9) 71.0 (9.9) 72.8 (13.8) SCAT3 = Sport Concussion Assessment Tool version 3; SAC = Standardized Assessment of Concussion; BESS = Balance Error Scoring System; MAP = mean arterial pressure; MCAv = middle cerebral artery velocity; PETCO2 = end-tidal partial pressure of carbon dioxide; HR = heart rate   4.3.3 Experimental protocols All testing occurred at the same time of day (344) and involved a hemodynamic challenge protocol (repetitive squat-stand manoeuvres) (210). First, spontaneous fluctuations in physiological metrics were recorded while standing quietly for five minutes. During squat-stand   94 manoeuvres, subjects began in a standing position, squatted to a knee angle of ~90˚, and returned to standing at a pace dictated by a metronome. Squat-stands were performed for five minutes at each of two frequencies, including 0.05 Hz and 0.10 Hz – thought to reflect myogenic and autonomic contributions towards CA, respectively (191-193) (Figure 4-1).   4.3.4 Data processing Beat-to-beat mean arterial pressure (MAP) and MCAv were determined from each R-R interval. All data were processed and analyzed with custom-designed software in LabView 14  (National Instruments, Austin, TX), as outlined previously (210). Beat-to-beat MAP and MCAv data were spline interpolated and resampled at 4 Hz. In accordance with recently published best-practice guidelines for transfer function analysis (212), each five-minute recording was divided into five successive windows with 50% overlap. Data within each window were linearly detrended and passed through a Hanning window prior to fast Fourier transform. The transfer function H(ƒ) between the MAP and MCAv signals was calculated as: H(ƒ) = SMAP-MCAv(ƒ)/SMAP-MAP(ƒ) where SMAP-MAP(ƒ) is the autospectrum of the MAP signal and SMAP-MCAv(ƒ)  is the cross-spectrum between the two signals. The squared Coherence function was estimated as: MSC(ƒ) = | SMAP-MCAv(ƒ) |2/ ⋅{SMAP-MAP(ƒ)  SMCAv-MCAv(ƒ)} The real HR(ƒ) and imaginary HI(ƒ) components of the complex transfer function were used to calculate Gain | H(ƒ) | and Phase | φ(ƒ) |: | H(ƒ) | = {HR(ƒ)2 + HI(ƒ)2} φ(ƒ) = tan-1{HI(ƒ) / HR(ƒ)}   95 Coherence, Phase, and normalized Gain were sampled at the point estimate of the driven frequency (0.05 or 0.10 Hz), falling within the very low frequency (VLF; 0.02- 0.07 Hz) and low frequency (LF; 0.07- 0.20 Hz) ranges where CA is believed to be operant (189). Phase wraparound was not present for any point-estimates.   Figure 4-1. Representative traces. Representative time-series showing oscillations in blood pressure (BP, top) elicited during 60 seconds of squat-stand manoeuvres performed at 0.05 Hz (left) and 0.10 Hz (right); oscillations are also observed in middle cerebral artery blood velocity (MCAv, middle); expired carbon dioxide (PCO2, bottom) is less affected.     96 4.3.5 Impact monitoring During the season, impact sensors (xPatch, X2 Biosystems, Seattle, WA) were attached to the right mastoid in a subset of players (n=29) to estimate linear and rotational accelerations experienced by the head during each game played (Figure 4-2). Acceleration profiles were recorded for 100 ms at 1000 Hz when translational acceleration exceeded a 10 g threshold. Following each game, data were downloaded using the Head Impact Monitoring System software (X2 Biosystems). Features within the software provide estimates of peak linear (PLA) and peak rotational (PRA) acceleration for each detected impact event. Only acceleration events exceeding a 20 g threshold were used in an effort to focus analysis to head accelerations most likely to result from direct impacts to the head or body, as opposed to hard stops or cuts (19,362,363). Estimates of cumulative exposure to linear (cPLA) and rotational (cPRA) acceleration by summing across all impacts for the season. Non-contact sport athletes were not monitored for head acceleration events during their competitive season.   Figure 4-2. Photo of a participant wearing an impact sensor on the right mastoid process (Permission to reproduce photo obtained; credit: GreystokePhoto.com).   97 4.3.6 Statistical analyses Effects of exposure to repetitive subconcussive head trauma during the course of a competitive season were estimated using a 2 (group: contact sport versus control) x 2 (time: preseason versus post-season) x 2 (frequency: 0.05 versus 0.10 Hz) three-way mixed ANOVA. Secondary exploratory analyses were conducted using independent samples t-tests to explore differences in change scores from pre- to post-season for Phase (∆Phase) and Gain (∆Gain) between high and low quartiles for estimated impact exposure variables (Hits/season, cPLA, cPRA) and. Spearman’s correlation coefficients were calculated between ∆Phase/∆Gain and change in symptom, SAC, and BESS scores from pre- to post-season.  All statistical analyses were performed using SPSS version 22.0 for Macintosh (IBM, Wherever, USA). Significance was determined a priori to achieve an experiment-wide α = 0.05.  4.4 Results Demographic characteristics, SAC and BESS performance, and resting physiological data are outlined in Table 4-1. Representative traces of MCAv, MAP, and PETCO2 at both squat-stand frequencies are provided in Figure 4-1. These manoeuvres substantially increased power in MCAv and MAP signals at the target frequencies (Figure 4-3).   Biomechanical descriptions of impact exposure in the subset of participants wearing sensors are presented in Table 4-2. Relative to football players, ice hockey players experienced fewer hits per game, but greater cumulative number of hits due to the differences in the length of season (62 games in hockey versus 10 games in football). Individual impacts were similar in PLA   98 magnitude across sports, but football players experienced greater PRA/hit than hockey players.    Figure 4-3. Normalized power spectra. Normalized power spectrum densities for mean arterial pressure (MAP, top) and middle cerebral artery blood velocity (MCAv, bottom) for preseason and post-season squat-stands in contact sport athletes (red, left) and in non-contact sport control athletes (blue, right). The frequency at which PSD reached peak amplitude (either 0.05 Hz or 0.10 Hz) was used for sampling point estimates for Coherence, Phase, and Gain.  4.4.1 Effect of exposure to repetitive subclinical head impacts The three-way interaction term (frequency*time*group) was non-significant for Coherence (F1,65=2.415, p=0.125), Phase (F1,65=1.494, p=0.226), and Gain (F1,65=0.007, p=0.931). Significant two-way interactions existed for Gain between frequency and time (F1,65=7.577, p=0.008, partial eta2=0.104), and between group and time (F1,65=5.898, p=0.018, partial   99 eta2=0.083), and for Phase between frequency and time (F1,65=3.982, p=0.049, partial eta2=0.059). Subsequent analysis of simple effects revealed a 12.4% relative increase in 0.10 Hz Gain (95%CI= +0.096 – 0.238 %MCAv/%MAP, p<0.001) and a 9.0% relative decrease in 0.10 Hz Phase (95%CI= -0.005 – -0.096 rads, p=0.027) from pre- to post-season in contact sport athletes (Figure 4-4), suggestive of autonomic dysfunction. No changes were observed at 0.10 Hz in control athletes (Figure 4-4) for Gain (95%CI= -0.079 – 0.115 %/%, p=0.696) or Phase (95%CI= -0.103 – 0.029 rads, p=0.247). No significant changes were observed for 0.05 Hz Gain or Phase (p > 0.05).   Table 4-2. Summary of head impact exposure in contact sport athletes. Median (IQ range) for head impact exposure variables across subset of hockey (n=10) and football (n=19) players wearing impact sensors during the season; p-values reflect results of Mann-Whitney U-tests comparing across sport. Metric Hockey Football p Hits / game (#) 8.2 (6.1 - 11.2) 16.6 (8.7 - 21.2) 0.003 Hits / season (#) 353.5 (295.0 - 587.3) 166 (63.5 - 212) 0.002 PLA / hit (g) 36.3 (35.4 - 37.4) 36.6 (34.5 - 40.2) 0.448 cPLA (g) 11920.5 (10788.3 - 21570.6) 5794.2 (2507.5 - 7117.7) 0.002 PRA / hit (rad/s2) 5036.1 (4772.3 - 5510.8) 6601.8 (6104.0 - 7441.0) <0.001 cPRA (rad/s2) 2016603.5 (11592.6 - 24322.9) 1057691.6 (486976.2 - 1376735.9) 0.003 PLA = peak linear acceleration; PRA = peak rotational acceleration; cPLA/cPRA = cumulative PLA/PRA    100  Figure 4-4. Effects of subconcussive trauma on autoregulatory outcomes derived from transfer function analysis. Transfer function analysis outcomes presented as mean ± SD for Coherence (top), Phase offset (middle), and normalized Gain (bottom) during squat-stand manoeuvres performed at 0.05 Hz (left) and 0.10 Hz (right), assessed at preseason and postseason in contact sport (solid red lines) and non-contact sport control (dashed blue lines) athletes. * indicates significant simple effects of time in the contact sport group; no significant changes were observed in control athletes.   101  Comparing high-to-low quartiles for total number of hits experienced per season in the subgroup of players who wore impact sensors, significant differences in ∆Phase were observed – players experiencing fewer hits exhibited a mean ± SD increase in Phase of 0.092 ± 0.108 rads from pre- to post-season, whereas those experiencing a higher number of hits exhibited an average decrease in Phase (i.e. impairment) of 0.070 ± 0.067 rads (t12=2.366, p=0.036). Similarly, ∆Phase differed between high and low quartiles based on estimated cPLA, wherein players exposed to lower cumulative linear acceleration exhibited a Phase increase of 0.092 ± 0.108 rads, while those in the highest cPLA quartile exhibited a Phase decrease of 0.043 ± 0.107 rads (t12=3.381,p=0.005). Significant Spearman’s correlations were observed between ∆Phase and symptom scores for “pressure in the head” (rho = -0.305, p = 0.047), and between ∆Gain and headache scores (rho = -0.398, p = 0.008).  To further characterize the role of autonomic dysfunction following subconcussive trauma, we estimated sympathovagal balance by calculating the ratio between low frequency (0.04-0.15 Hz) and high frequency (0.15-0.40 Hz) power (LF:HF) in the ECG signal (Kubios v2.2, Biosignal Analysis and Medical Imaging Group, Finland). A significant positive correlation was observed between ∆LF:HF and ∆Gain (r=0.334, p=0.031), indicating increases in sympathetic output (i.e. elevated LF:HF) were associated with increased CA Gain.   4.5 Discussion  In the current report, we present the first prospective study of dynamic cerebral autoregulation in the context of repetitive subconcussive head trauma. Transcranial Doppler ultrasound data   102 revealed: 1) an impairment in both the Gain and Phase of the cerebral pressure-flow relationship in contact sport athletes who had not sustained a concussion, suggesting a delayed change in vascular resistance in response to a change in BP that lead to a greater magnitude change in CBF for a given BP shift; 2) athletes exposed to a higher number of hits and higher cumulative linear acceleration exhibited greater deficits in CA function than those exposed to lower levels of head trauma; 3) CA alterations from pre- to post-season were related to sympathovagal balance, as estimated from heart rate variability; 4) in contrast, non-contact sport athletes exhibited no change in CA function over the course of one season. Although the permanence of the observed CA impairments cannot been established, the current data suggest the potential for subconcussive trauma to impair cerebrovascular function in response to a common BP challenge.   4.5.1 Physiological disruptions following repetitive subconcussive trauma A number of studies have reported minimal or no detrimental effects of subconcussive trauma (60,364-367), particularly on clinical measures of behaviour / neuropsychological function (reviewed in (368)). Despite exposure to more than 1000 impacts on average, one season of participation in collegiate football did not meaningfully impair scores on a computerized neuropsychological test battery (369), SAC (60,369), the Sensory Organization Test (60), BESS (60), or symptom severity (60). However, a higher number of years of collegiate playing experience was associated with worse performance on the Sensory Organization Test. It is possible that sequelae of subconcussive trauma may require more time to develop than a single season, or that these measures of neurological function may not be sensitive enough to detect subtle dysfunction. Findings to date suggest that any effect of subconcussive blows on neuropsychological performance is likely to be small and perhaps only evident in a subset of   103 individuals on select measures (368).   In contrast to clinical neuropsychological evaluations, more advanced techniques have revealed multiple detrimental effects of subconcussive hits. A body of evidence exists to suggest repetitive head trauma can, in the absence of symptoms, disrupt various aspects of brain structure and function, including white matter microstructure (24-26,65,66,370-372), cerebral metabolism (67,68,70,364) cortical activation patterns (20,69), vestibular function (373), functional connectivity (21,71), and blood-brain barrier integrity (66,77). For example, collegiate soccer players exhibited gray matter atrophy in anterior temporal regions compared to non-soccer playing controls (23); at baseline, resting-state fMRI revealed hyperconnectivity in the default mode network of high-school football players compared to controls that increased over one season (71); both American football and soccer players have shown disrupted white matter microstructure on diffusion tensor imaging (24,25). The current results – obtained using Transcranial Doppler – support the potential for subconcussive trauma to impair physiological function following only one season of play, including the integrity of cerebral blood flow control. Overall, however, the long-term functional and clinical implications of the outlined changes remain unclear.  4.5.2 Disruptions in control of cerebral blood flow following subconcussive trauma Although acute and chronic disruptions in CBF have been well-documented following concussions (2,43,141), our understanding of the consequences of subconcussive head trauma on cerebral perfusion is comparatively scant. Only three other studies to-date have examined the effect of subconcussive trauma on mechanisms controlling CBF. Svaldi and colleagues   104 demonstrated impairments in reactivity of the cerebrovasculature to CO2 in collegiate football players following the onset of the season (18). Similar deficits in CO2 reactivity were reported in soccer players beginning in the second half of the season that persisted for at least 3-4 months after the end of the season (19). While the subconcussive nature of head trauma in professional boxing is debatable, Bailey and colleagues reported impairments in CO2 reactivity that were related to the volume and intensity of sparring but not the frequency of knock-outs suffered or number of rounds fought (17). Considered alongside the current data these findings are concerning, as the underlying mechanisms governing CO2 reactivity and CA are though to represent distinct processes (158,374), suggesting repetitive subconcussive trauma may induce deficits to multiple aspects of cerebrovascular control.   4.5.3 Autonomic role for subconcussion-induced impairments in CA An impaired CA response to changes in MAP occurring at 0.10 Hz implies dysregulation in the autonomic control of the cerebrovasculature (191,192). Increasingly, the rich sympathetic innervation of the cerebrovascular tree is recognized to play an important role in the dynamic regulation of BP variability (190). Numerous lines of evidence have outlined the detrimental effects of concussion on autonomic function (298-301). To further characterize autonomic dysfunction in our contact sport athletes, ECG signals were used to calculate the low to high frequency power ratio – reflective of sympathovagal balance (290). The observed increase in CA Gain correlated significantly with increased sympathetic-to-vagal output, providing an additional line of support for autonomic contributions towards the observed cerebrovascular dysfunction. In a related study, our group demonstrated acute concussion imparts a ~20% reduction in the latency (Phase) of the CA response that persists for at least two weeks post-injury (Chapter 3:).   105 Disruptions were observed in both the latency and magnitude of the CA response following subconcussive trauma, indicating that even mild repetitive head trauma may incrementally disrupt the capacity of the cerebral blood vessels to regulate CBF in the face of changing BP. Additional research is warranted to further clarify the underlying mechanisms of cerebrovascular dysfunction, which may be influenced by age, sex, neck strength, previous impact exposure, and baseline autonomic function.  4.5.4 Evidence linking head impact exposure with physiological disruption Prior work has demonstrated relationships between sport-related head impact exposure and outcomes on functional MRI (20-22,76,375), white matter diffusion (26,376,377), balance (60), ocular near point of convergence (56), and cerebral metabolism (70). For example, in non-concussed high school football players, Talavage and colleagues demonstrated pre-to-post season changes in cortical activation on fMRI during a working memory task that correlated with the total number of head impacts experienced during the season (22). In collegiate football and ice hockey players, McAllister et al. noted changes in fractional anisotropy (a metric describing water diffusion patters reflective of white matter microstructure) in multiple brain regions that was associated with head impact exposure, including total number of hits across the season and exposure to linear acceleration (26). Recent work in collegiate football players has demonstrated the time between subconcussive hits may influence the effects on white matter diffusivity metrics (377). While it has been established that no true biomechanical threshold exists towards the incidence of concussion (48,52), data suggest subconcussive trauma may influence injury risk. Reports indicate football players sustain a higher number and severity of head impacts on days of diagnosed concussion than on days without, suggesting incremental changes occur   106 following subconcussive impacts that may lower the injury threshold (378). The current findings associating change in CA function with impact exposure should be considered preliminary, and further study is warranted to investigate potential long-term consequences of repetitive hits on cerebrovascular and neurologic function. However, these data reinforce the hypothesis that the effects of repetitive blows to the head are cumulative, with repeated exposure contributing to pathologically altered neurophysiology.  4.5.5 Limitations There are several limitations to the current preliminary study. Transcranial Doppler ultrasound measures the velocity of red blood cells, rather than CBF explicitly. For velocity to approximate flow in this scenario, the diameter of the insonated vessel must remain constant, which cannot be verified. However, debate continues over the importance of diameter changes in evaluating cerebral hemodynamics, particularly when PCO2 is held stable (357-359), as in this study (Figure 4-1). While previous research has demonstrated head impact exposure is typically greater during games than practices (49,379), impact data were collected during games only and therefore underestimate absolute exposure. Furthermore, the skin-worn impact sensors used in this study have recently been shown to exhibit substantial in-vivo overestimation error when compared to mouthguard-based sensors due to non-rigid skull coupling (380). Consistent overestimation of the severity of individual impacts likely did not affect the comparisons made within this study, however. Nevertheless, that significant CA impairments were observed in a small sample of contact sport athletes, but not in non-contact control athletes, emphasizes the need for in-depth prospective investigations into the effects of subconcussive trauma on CBF control mechanisms.    107 4.6 Conclusion There is growing concern that even low-magnitude, subconcussive head impacts can cause lasting neurological injury. While behavioural changes in response to subconcussive trauma have been difficult to identify, this exploratory study suggests the cerebral autoregulatory system is vulnerable to repetitive head trauma. Our data provide evidence of cumulative impairment in the CA response of contact sport athletes associated with exposure to repetitive head trauma. Non-contact athletes exhibited no such changes in CA integrity. Future prospective cohort studies in a larger number of subjects are warranted to investigate the clinical relevance of CA changes induced by subconcussive impacts towards injury susceptibility and long-term outcomes.     108 Chapter 5: A prospective transcranial Doppler ultrasound-based evaluation of the acute and cumulative effects of sport-related concussion on dynamics of the neurovascular coupling response  5.1 Summary Sport-related concussion has been shown to alter cerebral blood flow (CBF) both acutely and chronically, with suggestions that effects may be cumulative across multiple injuries. Such dysfunction may be mediated by trauma-induced deficits to CBF control mechanisms, though our understanding of such effects is limited, including the dynamics of the neurovascular coupling (NVC) response (i.e. CBF responses to neurologic demand). 179 junior-level contact sport athletes completed preseason testing – 42 had never experienced a concussion (Hx-) and 31 had endured three or more (Hx3+). 18 athletes suffered concussions during the study period and were re-tested 3-days, 2-weeks, and 1-month post-injury. NVC dynamics were estimated by measuring blood flow velocity in the posterior (PCAv) and middle (MCAv) cerebral arteries during cycles of 20-s eyes-closed and 40-s eyes-open to a visual stimulus (reading). Acutely following concussion, peak rate of PCAv increase during the activation phase was delayed by over 50%, and the magnitude of the PCAv response elevated by over 30% compared to preseason, although these alterations were largely resolved by 2-weeks. Independent medical clearance for full return-to-play was inversely related to the magnitude of increase in the NVC response. No changes in MCAv, blood pressure, or end-tidal carbon dioxide responses to visual stimulation were observed following concussion. No differences in NVC dynamics were observed between Hx- and Hx3+ groups at preseason. Via multiple potential mechanisms, acute   109 sport-related concussion induces transient impairments in the dynamics of the NVC response that may be related to clinical recovery. Such effects do not appear to accumulate across multiple injuries.  5.2 Introduction Sport-related concussion is a global public health concern, with recent reports estimating incidences of 1.1 to 1.9 million injuries each year in US youth alone (4). Defined as a “complex pathophysiological process affecting the brain, induced by biomechanical forces” (9), concussions are characterized by a period of increased cerebral vulnerability during which normal metabolism within the brain is disrupted, leading to heightened sensitivity to additional trauma during the recovery period (9,42,79). Cerebral metabolism is critically dependent on the regulation of cerebral blood flow (CBF). In both paediatric and adult patients, it has been demonstrated that the brain exhibits local and global reductions in CBF following sport-related concussion (2,43,141). Animal models have shown concussive-type injuries to reduce the number and diameter of capillaries, both adjacent and distal to the injury site (349). As such, alterations in cerebral blood flow (CBF) are thought to play an important role the pathophysiology underlying concussion (131), though effects on mechanisms controlling CBF are poorly understood.   Comprehensive assessment of cerebrovascular function should include evaluation of the cerebrovascular reactivity to carbon dioxide (CO2), the cerebral pressure-flow relationship, as well as the neurovascular coupling response (145). Neurovascular coupling (NVC), a concept first proposed in the late 1800’s, describes alterations in CBF in response to changes in neuronal   110 activity. Although direct microvascular measurements of CBF are challenging to obtain in humans in vivo, NVC can be characterized indirectly using transcranial Doppler ultrasound (TCD) to measure CBF velocity (CBFv) in the posterior cerebral artery (PCA) – the primary source of blood supply to the visual cortex – during visual stimulation protocols such as reading (156,213,241,242,381). Neurovascular coupling is also the basis for the blood oxygen level-dependent (BOLD) signal obtained using functional MRI (fMRI), which is a function of the ratio of oxy-to-deoxyhemoglobin, CBF, and cerebral blood volume.   In the context of sport-related concussion, transient impairments in cerebrovascular function have been observed following injury, including reduced capacity of the cerebrovasculature to buffer changes in blood pressure (Chapter 3:) and altered reactivity to CO2 (132). Concussion-induced CBF disturbances may also be affected by alterations in the ability of cerebral blood vessels to respond to changes in cortical activation (131). Multiple fMRI studies have shown concussed brains recruit additional cortical resources to successfully perform working memory and attentional tasks (255-257); however, these studies have typically derived a single parameter to estimate the magnitude of the BOLD response, which assumes the shape of the hemodynamic response is unaltered by injury. Only one study has considered whether NVC dynamics are affected by mTBI, reporting increased activation in the visual cortex of mTBI patients during a visual-auditory sensorimotor task, particularly during the earliest (2-4 seconds) response phase (265). Furthermore, fMRI studies have largely used case-control designs without pre-injury data, precluding insights into the magnitude of within-subject effects. The extent to which the dynamics of the neurovascular coupling response are affected by concussive head trauma may be better estimated by obtaining pre-injury data in a prospective cohort design with techniques   111 providing better temporal resolution, such as TCD.   Accordingly, our objectives in the current study were to prospectively evaluate the effects of sport-related concussion on the dynamics of the neurovascular coupling response using TCD ultrasound. Towards this end, we sought to examine: i) the effect of clinically diagnosed concussion, and; ii) whether effects are cumulative across multiple (3+) previous concussions in otherwise healthy and fully-recovered athletes on the neurovascular coupling response.   5.3 Methods 5.3.1 Study design 179 male (mean age 19.6 ± 1.5 years) elite junior hockey (n=90) and American football (n=89) players were recruited. All participants underwent preseason baseline testing. Upon enrolment, 42 players had experienced zero prior concussions (Hx-) while 31 had sustained three or more (Hx3+: mean (SD) = 4.5 (2.4), range = 3-12). Athletes diagnosed with a concussion by an independent physician during the competitive season (n=18), based on criteria in the 4th Consensus Statement (9), repeated testing at 72-hours, 2-weeks, and 1-month post-injury. Prior to physiological testing, participants completed the Sport Concussion Assessment Tool (SCAT3) (9), a concussion screening tool comprised of a graded symptom checklist, the Standardized Assessment of Concussion (SAC) – probing orientation, immediate and delayed recall, and concentration – as well as performance on the modified Balance Error Scoring System (BESS) (Table 5-1). No participants were excluded based on a-priori criteria including significant history of cardiorespiratory, cerebrovascular, neurological, or severe neurodevelopmental disorder. All participants provided written informed consent, abstained from exercise, caffeine,   112 and alcohol for 12+ hours, and were familiarized with testing procedures prior commencing this study, approved by the University of British Columbia Clinical Research Ethics Board.   Table 5-1. Participant characteristics. Demographics, SCAT3 performance, return-to-play duration, and resting physiological parameters during each test session for acutely concussed athletes. Metric Concussion History Concussed (n=18) 0 (n=42) 3+ (n=31) Preseason 72 Hour 2 Week 1 Month Age (years) 19.0 (1.4) 19.6 (1.9) 18.6 (1.5) BMI (kg/m2) 27.6 (5.1) 27.5 (4.3) 25.5 (3.1) RTP (days) N/A (preseason only) median = 14, range 7-35 days # Symptoms 2.2 (2.7) 4.7 (4.3) 2.0 (3.6) 11.2 (5.5) 2.8 (3.0) 1.1 (2.1) Symptom Severity 3.4 (4.7) 9.3 (12.0) 3.6 (3.6) 25.1 (19.0) 3.6 (3.5) 1.3 (2.3) SAC Score 27.1 (1.7) 26.7 (1.8) 26.8 (1.7) 26.5 (2.0) 26.9 (2.9) 28.1 (1.3) BESS Score 3.5 (3.2) 3.5 (3.3) 2.6 (2.6) 4.2 (3.1) 3.0 (2.3) 2.0 (2.0) PCAv (cm/s) 35.8 (4.9) 35.7 (5.8) 35.4 (3.5) 35.3 (8.2) 34.8 (5.3) 34.9 (6.2) MCAv (cm/s) 55.1 (9.0) 55.6 (9.3) 53.8 (7.0) 53.5 (8.7) 53.3 (9.5) 53.2 (7.8) MAP (mmHg) 95.0 (13.6) 94.1 (12.4) 92.3 (20.1) 90.4 (18.2) 92.0 (16.5) 91.2 (15.9) PETCO2 (mmHg) 37.7 (2.8) 38.1 (2.5) 37.7 (3.2) 37.6 (3.7) 37.9 (4.1) 37.6 (4.5) HR (bpm) 75.1 (9.8) 73.6 (8.7) 79.4 (8.3) 79.7 (12.2) 82.1 (15.9) 79.5 (10.2) BMI = body mass index; RTP = return-to-play; SAC = Standardized Assessment of Concussion; BESS = Balance Error Scoring System; PCAv = posterior cerebral artery blood velocity; MCAv = middle cerebral artery blood velocity; MAP = mean arterial pressure; PETCO2 = end-tidal partial pressure of CO2; HR = heart rate  5.3.2 Instrumentation Participants were equipped with a three-lead electrocardiogram (ECG). Cerebral blood flow was indexed using TCD (ST3, Spencer Technologies, Seattle, WA) to record CBF velocities in the right middle (MCAv) and left posterior (PCAv) cerebral arteries. After vessels were identified and signals optimized according to depth, waveform, velocity, and response to carotid compression / visual stimulation tests, ultrasound probes were locked in place with a fitted head   113 frame. Beat-to-beat blood pressure was recorded using finger photoplethysmography with a brachial cuff to adjust for height differences between the finger and the brachial artery (Finometer PRO, Finapres Medical Systems, Amsterdam, The Netherlands), while partial pressure of expired carbon dioxide (PETCO2) was monitored using an online gas analyzer (ML206, AD Instruments, Colorado Springs, CO). All data were sampled at 1000 Hz (PowerLab 8/30 ML880, AD Instruments) and stored for offline analysis using commercially available software (LabChart version 7.1, AD Instruments).   5.3.3 Experimental protocols All visits to the laboratory occurred at the same time of day during which the NVC response was evaluated in the PCA using a visual stimulation paradigm, as outlined previously (213). Resting physiological data were recorded while sitting quietly for one-minute. Participants were seated 50-60 cm from the visual screen (27” Apple iMac) with a 50 cm x 35 cm visual field. Subjects completed five cycles of 20 seconds eyes-closed, 40 seconds eyes-open to a visual stimulus (reading an article of interest to the participant), consistent with other NVC research (241,242,244,247,381); all visual stimuli were presented in the centre of the visual field, with screen brightness set to maximum and unchanged across participants or test sessions.  5.3.4 Data processing All data were processed using a custom-written script in the Matlab environment (vR2013a, Mathworks, Natick, MA). Beat-to-beat values of systolic and diastolic BP, MCAv, and PCAv were determined from each R-R interval and used to calculate mean arterial pressure (MAP) and   114 mean velocity traces. Breath-to-breath peak expired CO2 values were extracted to measure PETCO2. All signals were visually inspected for artifacts and corrected by cubic spline interpolation. Data were then filtered with a dual-pass, 4th order digital Butterworth filter with a 2 Hz cutoff frequency. Time-series profiles for each trial were time-aligned to stimulus onset (eyes open) and all trials averaged within-participant to generate a representative NVC response for that session (Figure 1). To account for the unknown insonation angle of the TCD probes, relative changes in CBF velocity were calculated relative to the average velocity during the 3-5 second window before stimulus onset. Responses to visual stimulation were quantified by calculating the maximum slope of the activation phase (slopemax), time to slopemax (tslopemax), peak relative change in CBFv (vmax), time-to-peak-change (tvmax), and area-under-the-curve during the first 25 seconds after stimulus onset (AUC25) (Figure 5-1).   5.3.5 Statistical analyses All statistical analyses were performed using SPSS version 22.0 for Macintosh (IBM, Wherever, USA).  Shapiro-Wilks tests were used to assess for normality, while Mauchly’s test was used to evaluate sphericity. In cases where the assumption of sphericity was violated, Greenhouse-Geiser epsilon was used to adjust degrees-of-freedom for the primary F-test. Significance was determined a priori to achieve an experiment-wide α = 0.05.   115  Figure 5-1. Representative traces of changes in physiological variables during one trial of the neurovascular coupling task. a) change posterior cerebral artery velocity (PCAv) – outcome metrics include timing and magnitude of peak slope during activation phase (tslopemax, slopemax), timing and magnitude of peak relative change in PCAv (tvmax, vmax), and area-under-the-curve over the first 25 seconds of eyes open (AUC25); b) change in middle cerebral artery velocity (MCAv); c) mean arterial pressure (MAP); and d) end-tidal partial pressure of CO2 (PETCO2); vertical green dashed lines indicates stimulus onset (eyes-open).        116 5.3.5.1 Effect of acute concussion A one-way (time) repeated-measures ANOVA was used to evaluate the effect of acute sport-related concussion on NVC metrics. Where omnibus tests indicated significant main effects, pre-planned t-tests were used to evaluate specific pairwise contrasts (i.e. each post-injury time point relative to preseason).   5.3.5.2 Cumulative effects of multiple previous concussions The effect of multiple prior concussions on NVC metrics was evaluated using independent samples t-tests (Hx- versus Hx3+).   5.4 Results Demographic characteristics, SCAT3 performance, return-to-play durations and resting physiological data across are outlined in Table 5-1. Concussed athletes were cleared by their team physician to return to full-contact game participation a median 14 days post-injury. At preseason, Hx3+ participants reported a greater number (p = 0.033) and severity of symptoms (p = 0.013) than Hx- participants. Physiological variables did not differ between groups (p > 0.05). Representative traces for PCAv, MCAv, MAP, and PETCO2 are shown in Figure 5-1.  5.4.1 Effect of acute concussion Time-series profiles for each primary physiological measure, averaged across subjects, are presented in Figure 5-2.   117  Figure 5-2. Time-series profiles of physiological variables – averaged across subjects – at each pre- and post-concussion time point following visual stimulation for a) change posterior cerebral artery velocity (∆PCAv); b) change in middle cerebral artery velocity (∆MCAv); c) mean arterial pressure (∆MAP); and d) change in end-tidal partial pressure of CO2 (PETCO2); vertical black dashed lines at t=5s indicates stimulus onset (eyes-open); error bars represent 95% confidence intervals – note: not all error bars are shown for purposes of visual clarity.  Evaluating the NVC response in the PCA, repeated measures-ANOVA indicated a significant main effect of time for tslopemax (F2.48,42.14=3.157, p=0.043, partial eta2=0.157), vmax (F3,51=4.172, p=0.01, partial eta2=0.197) and AUC25 (F3,51=2.924, p=0.043, partial eta2=0.147). As outlined in Figure 5-3, post-hoc analyses revealed an absolute increase in PCA-tslopemax of 1.2 seconds (56.6% slower) at 72-hours post-injury (95%CI=0.01-2.42 seconds, adjusted p=0.049) and a   118 trend towards a 1.1 second increase at 2-weeks (95%CI=-0.16-2.36 seconds, p=0.08), but returned to near-preseason levels by 1-month.   Figure 5-3. Summary of neurovascular coupling metrics in the posterior cerebral artery (PCA) to visual stimulation at preseason and each post-concussion time point; a) eyes-closed PCA blood velocity (Baseline PCAv); b) maximum PCAv slope (slopemax), and c) time to maximum (tslopemax) PCAv slope during activation phase; d) peak relative change (vmax), and e) time to peak relative change (tvmax) in PCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); unless pairwise comparisons are indicated, p-values represent main effect of time; error bars represent 95% confidence intervals.   Absolute PCA-vmax increased by 6.5% – a 45.6% relative increase – at 72-hours (95%CI=2.2–  119 10.8%, adjusted p=0.015) and 3.6% at 2-weeks post-injury (95%CI=0.4–6.7%, adjusted p=0.084); PCA-vmax did not differ from preseason by 1-month post-injury.  Similarly, PCA-AUC25 was elevated by 31.1% at 72-hours (95%CI=10.9–43.0 cm, adjusted p=0.009), but did not differ from preseason at 2-weeks or 1-month post-injury.    Figure 5-4. Summary of neurovascular coupling response metrics to visual stimulation in the middle cerebral artery (MCA) at preseason and each post-concussion time point (error bars represent 95% confidence intervals): a) eyes-closed MCA blood velocity (Baseline MCAv); b) maximum MCAv slope (slopemax), and c) time to maximum (tslopemax) MCAv slope during activation phase; d) peak relative change (MCAvmax), and e) time to peak relative change (tMCAvmax) in MCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); p-values represent main effect of time from repeated measures ANOVA.     120 An association was observed between ∆PCA-vmax and time to clearance for return-to-play (RTP) (Spearman’s rho = -0.491, p=0.05), indicating those who exhibited the greatest increases in PCA-vmax immediately following injury relative to preseason responses recovered more quickly on clinical grounds. Concussion did not significantly affect MCAv, MAP, or CO2 responses to visual stimulation (Figure 5-4, Table 5-2).   Table 5-2. Summary of responses to visual stimulation for secondary physiological variables. Metric Concussion History Concussed (n=18) Hx- (n=42) Hx3+ (n=31) p Preseason 72 Hour 2 Week 1 Month p MAPbase (mmHg) 90.1 (8.6) 91.3 (13.1) 0.669 93.9 (14.0) 92.5 (13.0) 91.4 (17.5) 91.1 (11.5) 0.603 ∆MAPmax (%)  4.1 (3.1) 6.1 (3.8) 0.013* 4.3 (2.9) 3.3 (3.0) 3.7 (2.5) 4.5 (2.2) 0.459 PETCO2base (mmHg) 35.6 (8.7) 37.0 (6.9) 0.211 38.7 (0.7) 37.3 (1.1) 36.1 (1.4) 36.9 (0.9) 0.102 ∆PETCO2max (mmHg) 1.7 (2.7) 1.3 (1.3) 0.447 1.0 (1.0) 1.2 (1.5) 1.3 (1.1) 1.1 (1.1) 0.611 HRbase (bpm) 64.6 (9.9) 65.1 (9.6) 0.853 62.9 (1.9) 63.8 (1.9) 65.5 (2.4) 65.2 (2.0) 0.563 ∆HRmax (bpm) 5.0 (3.8) 5.4 (3.4) 0.687 4.8 (3.1) 5.0 (2.8) 6.3 (4.0) 5.9 (3.2) 0.258 MAPbase = baseline MAP (eyes-closed); ∆MAPmax = peak relative change in MAP following stimulus onset; PETCO2base = baseline end-tidal PCO2 (eyes-closed); ∆PETCO2max = peak absolute change in PETCO2 following stimulus onset; HRbase = baseline heart rate (eyes-closed); ∆HRmax = peak absolute change in heart rate following stimulus onset; p-values for Concussion History reflect independent samples t-tests; p-values for Concussed reflect omnibus F-test from one-way repeated measures ANOVA; * indicates significant finding.  5.4.2 Cumulative effects of multiple previous concussions No significant differences were observed between Hx- and Hx3+ groups with respect to any NVC metric in either the PCA or MCA (Figure 5-5, Figure 5-6, Figure 5-7, Table 5-2).    121  Figure 5-5. Preseason time-series profiles – averaged across participants with zero (Hx-) versus three or more (Hx3+) prior concussions – following visual stimulation for a) change posterior cerebral artery velocity (∆PCAv); b) change in middle cerebral artery velocity (∆MCAv); c) mean arterial pressure (∆MAP); and d) change in end-tidal partial pressure of CO2 (PETCO2); vertical black dashed lines indicates stimulus onset (eyes-open); error bars represent 95% confidence intervals.  Statistically, participants in the Hx3+ group exhibited a significantly greater peak change in MAP following stimulus onset (t71 = -2.55, p=0.013), though the magnitude of the difference was only 2.0%.    122  Figure 5-6. Summary of preseason neurovascular coupling responses to visual stimulation in the posterior cerebral artery (PCA) across participants with zero (Hx-) versus three or more (Hx3+) prior concussions; a) eyes-closed PCA blood velocity (Baseline PCAv); b) maximum PCAv slope (slopemax), and c) time to maximum (tslopemax) PCAv slope during activation phase; d) peak relative change (vmax), and e) time to peak relative change (tvmax) in PCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); no differences were observed between groups; error bars represent 95% confidence intervals.    123  Figure 5-7. Summary of preseason neurovascular coupling responses to visual stimulation in the middle cerebral artery (MCA) across participants with zero (Hx-) versus three or more (Hx3+) prior concussions; a) eyes-closed MCA blood velocity (Baseline MCAv); b) maximum MCAv slope (slopemax), and c) time to maximum (tslopemax) MCAv slope during activation phase; d) peak relative change (vmax), and e) time to peak relative change (tvmax) in MCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); no differences were observed between groups.  5.5 Discussion  In this study, we present the first evaluation into the effects of sport-related concussion on the neurovascular coupling response to visual stimulation using transcranial Doppler ultrasound, and revealed three primary findings: i) activation of the blood flow response in the posterior cerebral artery to visual stimulation was delayed, and the magnitude of the response augmented, acutely following injury, but returned to preseason values by 1-month; ii) the magnitude of increase in blood flow response was inversely related to clinical recovery, as estimated by time to medical   124 clearance for return-to-play; and; iii) effects of acute concussion do not appear to be cumulative, wherein comparison of NVC responses at preseason revealed no differences between individuals who had never experienced a concussion versus those who had endured three or more prior concussions.  5.5.1 Cerebral blood flow alterations following sport-related concussion  The brain comprises only 2% of total body weight, yet receives 15-20% of cardiac output at rest, highlighting its high metabolic demand and the consequent importance of maintaining adequate CBF for proper functioning. Cerebral blood flow has repeatedly shown alterations following concussive injury (2,43,136,137,346). In the immediate post-injury phase CBF may be elevated (346), with evidence demonstrating subsequent reductions in global and regional CBF both sub-acutely (2,43,136) and chronically (142,143). Recovery of CBF to near-healthy levels occurs over ~30 days (2) and may be related to symptom resolution (43,137), although some studies have shown previous concussions may invoke chronic reductions in regional CBF (136,144). In the current study, we did not observe significant changes in resting PCAv or MCAv following injury (Table 5-1), although this may be heavily influenced by methodological differences between MRI- and TCD-derived estimates of CBF; the improved spatial resolution of MRI provides heightened sensitivity for subtle changes in flow, while TCD-indexed CBF is susceptible to changes in the diameter of the insonated vessel. However, TCD provides superior temporal resolution, allowing insights into CBF dynamics. Despite the known CBF alterations following concussion, our understanding of the effects of such injuries on mechanisms controlling CBF is comparatively lacking, including the dynamics of the neurovascular coupling response.   125  5.5.2 Mechanisms underlying the neurovascular coupling response Regional increases in neural activity – and the associated elevation in metabolism – require appropriate and coordinated responses by the neurovascular unit to modulate local cerebrovascular resistance and direct nutrient-rich blood to active cortical regions. Failure to appropriately match CBF with local metabolic demands may lead to neurological dysfunction. Multiple pathways have been proposed to contribute to the NVC response, including local accumulation of vasoactive metabolic by-products (e.g. CO2, nitric oxide (NO), adenosine, arachidonic acid metabolites), direct neural control of the cerebrovasculature, astrocyte-mediated vasosignaling, and pericyte-mediated changes in capillary tone (reviewed in: (145,220)). The entire cerebrovascular tree is innervated with sympathetic and parasympathetic fibres and growing evidence supports a role for autonomic activity in modulating CBF via its effects on cerebrovascular resistance (145,225,226). Indeed, the fast initial rise in PCAv in the current visual stimulation paradigm is thought to result from sympathetic activation within the visual cortex (145,213,220). Astrocytes are thought to contribute to a slow-onset (3-4 seconds) neurovascular coupling response, but may play a lesser role in the immediate hyperemic effect (< 1 second) following neural activation (232). Excitatory and inhibitory neurons synapse on both astrocytes and GABAergic interneurons that are closely associated with astrocytic end-feet enveloping penetrating arterioles. The release of glutamate from active neurons triggers metabotropic receptor-mediated calcium uptake into neighbouring astrocytes (reviewed in: (232)) and causes release of vasoactive modulators (adenosine, nitric oxide, prostaglandins and other arachidonic acid derivatives) onto arteriolar smooth muscle cells and vascular endothelial cells (234-236). Inhibitory interneurons communicating with neurons, astrocytes, and   126 microvessels play a role in integrating local signals and releasing vasoactive substances (e.g. NO, acetylcholine, neuropeptide-Y, vasoactive intestinal peptide) to precisely regulate CBF (237,238). Ultimately, gap junctions between adjacent vascular smooth muscle cells are thought to facilitate intramural propagation of vascular signals to yield vasoactivity in remote pial arterioles up-stream of the signal origin (221-223). Although our understanding of the precise mechanisms controlling the NVC response in humans remains incomplete, it is clear that multiple redundant pathways exist to ensure CBF is appropriately altered in response to changes in local neural activity (220).   5.5.3 Functional magnetic resonance imaging in concussion The majority of task-based functional MRI studies into the effects of concussion and mTBI on the hemodynamic response have used tasks related to frontal lobe/executive function, and have typically shown increases in cortical activation relative to healthy controls in multiple brain regions (reviewed in (67)). Cortical hyperactivation is demonstrated often despite no between-group differences in task performance, and may be related to symptom severity (255-257). The timeline to recovery of functional alterations following concussion is unclear; a recent prospective study demonstrated gradual reductions in the degree of global hyperactivation over time, showing elevated BOLD responses in multiple frontoparietal regions at three days post-injury, in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal lobe persisting for two weeks, and in the DLPFC only at two months (257). In a study of concussed high-school athletes in the first week post-injury, hyperactivation in Brodman’s Area 6 during a working memory task was associated with prolonged recovery (262); this contrasts the current findings in a slightly older population, wherein those who exhibited an augmented NVC response acutely   127 post-injury experienced shorter recovery times. However, the former study also reported higher activation associated with lower symptom scores (262). Further investigation is warranted to determine if this discrepancy is a function of age group or other clinical factors. In the only study to evaluate the effects of mTBI on the dynamics of the hemodynamic response, Mayer and colleagues reported greater activation in the visual cortex in mTBI patients presenting to the emergency department relative to controls, particularly in the 2-4 second window after stimulus onset, suggesting a shorter time-to-peak response (265). Our within-subject results similarly showed increased peak responses (vmax, Figure 5-3), but delayed response initiation (tslopemax) and no difference in time to peak response (tvmax, Figure 5-3). Nevertheless, elevated task-based activation in the brains of concussed patients has generally been interpreted as recruitment of additional neural resources to compensate for cognitive and/or attentional deficits to support task performance (257,264).   Other fMRI studies have demonstrated concussion-induced hypoactivation in similar areas to those mentioned above, particularly in individuals with persistent symptoms, though task performance was not always as equal between groups (258-261,382). Participants reporting more post-concussion syndrome symptoms (persisting > 1 year post-injury) exhibited reduced activation in task-irrelevant areas but greater activation in attention-related areas as cognitive load was increased during a top-down attentional task (263). Previous studies have observed, similar to our results, no cumulative effects of multiple previous concussions on the hemodynamic response to cortical activation in otherwise healthy young adult athletes (269,270). However, multiple previous concussions were shown to negatively affect recruitment patterns in the relational memory network of former professional football players (271), raising the   128 possibility that multiple concussions in addition to repetitive subconcussive trauma may be detrimental over the course of a long career. Although inconsistency across fMRI studies may be partly attributed to methodological differences and injury heterogeneity across samples (266), a recent meta-analysis of fMRI findings in mTBI observed hyperactivation during continuous tasks – similar to the current reading paradigm – and hypoactivation during tasks requiring discrete periods of working memory (267). Nevertheless, additional investigations are warranted to determine whether conflicting results are a function of task complexity or other clinical factors.   5.5.4 Possible mechanisms for observed effects of acute concussion Concussive injuries may alter the NVC response by multiple mechanisms. Concussions induce autonomic dysregulation in the form of elevated sympathetic and / or depressed parasympathetic tone (298,299,301,305) that affects the stiffness of peripheral arteries (300). Such autonomic dysfunction has previously been shown to delay the response of cerebral blood vessels to changes in blood pressure, though the magnitude of the response was unaffected (Chapter 3:). Neuronal damage caused by concussion, including disruptions in myelination (Chapter 2:)(317), is thought to reduce the speed and efficiency of signal processing within the brain. Taken together, these findings complement the current observation of a delay in achieving peak activation slope of the NVC response (Figure 5-3). Animal mTBI models have shown leukocyte invasion initially occurs across pial microvessels; elevated chemokine expression from astrocytes provides a chemotactic gradient for subsequent perivascular migration of leukocytes into brain parenchyma, suggesting a contributing role for astrocytes in the post-concussion neuroinflammatory response (383). Increased astrocyte signaling could also contribute to the   129 observed increase in the magnitude of the NVC response, given its role outlined above, though this remains speculative. Furthermore, concussion induces a decoupling between CBF and glutamate metabolism, followed by a more global reduction in cerebral metabolism (42,79,104). Consequently, the demand placed on neural networks involved in performing a given task may be elevated, requiring compensatory activation of additional neural resources (255). Indeed, the effects of acute concussion appear similar to observations in non-concussed healthy athletes of increases in PCA-vmax and PCA-AUC25 as the complexity of the visual stimulus increased (213). As mentioned previously, multiple redundant mechanisms are thought affect the NVC response in normal humans, and there are multiple ways in which concussive trauma may interfere with normal functioning. Taken alongside results from fMRI, the current data support a concussion-induced alteration in the CBF response to task-based cortical activation.  5.5.5 Limitations There are several limitations to the current study. First, our sample consisted exclusively of male athletes, representing a significant shortcoming in the generalizability of our findings as females sustain higher rates of SRC and endure longer recovery trajectories (356). Second, while TCD provides excellent resolution in the time domain, the spatial sensitivity of this technique is limited to measurement of blood velocity in major cerebral arteries; given the known heterogeneity in biomechanical and spatial localization of concussive injuries, this approach is unable to discern subtle regional damage and any impairments in NVC function at a microvascular level. Furthermore, our sample was drawn from multiple athletic teams with different medical staff; the clinical nature of concussion diagnosis raises the possibility of magnifying the heterogeneity of injuries across participants. Third, TCD does not measure blood   130 flow, but rather CBF velocity; for this index to accurately represent flow requires the diameter of insonated vessels to remain unchanged, which cannot be verified. However, any effects of CO2 on vessel diameters are presumed to have been minimal as end-tidals were largely unchanged (Figure 5-2, Figure 5-5). Lastly, clinical guidelines outlining appropriate management of concussed patients dictate a period of physical and cognitive rest post-injury. As such, the potential effect of inactivity on our results cannot be discredited. Nevertheless, significant alterations in the dynamics of the NVC response were revealed in a small sample of concussed young adult athletes, encouraging further prospective investigations into the effects of sport-related head trauma on CBF control mechanisms.  5.6 Conclusion A better understanding of the pathophysiological underpinnings of concussion is needed to limit the burden of these injuries at an individual and population level. Although not appropriate for clinical decision-making, this TCD-based evaluation revealed acute alterations in the neurovascular coupling response in the posterior cerebral artery of concussed athletes that were related to clinical recovery. However, it appears that such effects are transient in nature and do not accumulate with multiple injuries. These findings add to our growing appreciation for the detrimental effects of sport-related concussion on multiple aspects of cerebrovascular function. Development of further prospective investigations in larger samples towards delineating the effects of concussion on mechanisms controlling CBF – including relationships with age, sex, biomechanical exposure, and susceptibility to injury – are warranted.     131 Chapter 6: A prospective transcranial Doppler ultrasound-based evaluation of the effects of repetitive subconcussive head trauma on neurovascular coupling dynamics  6.1 Summary Recent research has implicated repetitive subconcussive head trauma towards short- and long-term deficits in brain structure and function, including changes in the integrity of mechanisms controlling cerebral blood flow (CBF). However, the degree to which dynamics of the neurovascular coupling (NVC) response (i.e. CBF response to neural activity) are altered following a season of contact sport participation is unknown. 179 junior-level contact sport athletes (ice hockey and football: age 19.6 ± 1.5 years) completed preseason testing – 52 returned for follow-up testing after completion of the athletic season. 15 age- and education-matched non-contact sport athletes (primarily cross-country running) also completed pre- and post-season testing. NVC dynamics were estimated during cycles of 20-s eyes-closed and 40-s eyes-open to a visual stimulus (reading) by measuring blood flow velocity in the posterior (PCA) and middle (MCA) cerebral arteries using transcranial Doppler ultrasound. No significant differences in NVC dynamics in the PCA or MCA were observed between pre- and post-season in either athlete group. Furthermore, no significant relationships were found between change scores in NVC metrics from pre- to post-season and estimates of cumulative head impact exposure as derived from skin-worn impact sensors. Within the context of growing concern over detrimental effects of repetitive subconcussive trauma, the current results suggest that the dynamics of NVC responses are not affected by one season of participation in junior-level ice   132 hockey or football.   6.2 Introduction There is growing concern over the effects of repetitive subconcussive head trauma towards long-term deficits in neurologic function (55). Subconcussion has been defined as trauma that does not result in signs or symptoms of concussion (40,56). Over the past five years, multiple studies have shown repetitive trauma to the head can induce deficits in brain structure and function associated with impact exposure (25,26,65-68,71,72), including metrics influenced by the cerebral blood flow (CBF) response to changes in neural activity (20,22).   Brain metabolism is critically dependent on the adequate supply of nutrients, accomplished via multiple mechanisms that contribute to the tight regulation of CBF (145). In addition to influences of blood pressure (cerebral autoregulation) and carbon dioxide (CO2 reactivity), CBF is also sensitive to regional neural activity through a process known as neurovascular coupling (NVC). The NVC phenomenon may be observed using transcranial Doppler (TCD) ultrasound to index blood flow in the posterior cerebral artery – the primary supplier of blood to the occipital cortex – during visual stimulation paradigms such as reading (156,213,241,242,381). Functional MRI (fMRI) also capitalizes on this hemodynamic response: local cortical activation elicits a relative excess of delivered blood, termed functional hyperemia, thereby altering the ratio of oxy-to-deoxyhemoglobin and thus providing the basis for the blood oxygen level-dependent (BOLD) signal obtained using fMRI.   Cerebral blood flow plays an important role in the pathophysiology of concussion (131), but the   133 effects of subconcussion on CBF are less well understood. Alterations in CBF have been repeatedly demonstrated following diagnosed sport-related concussion (2,43,136,137), with evidence also indicating changes in the integrity of CBF control mechanisms including cerebral autoregulation (Chapter 3:), CO2 reactivity (reviewed in (132)), and NVC dynamics (Chapter 5:)(265). Recently, impairments in CO2 reactivity (18,19) have also been attributed to repetitive subconcussive trauma in collegiate soccer and football, while deficits in cerebral autoregulation have been associated with number of head hits and cumulative exposure to linear acceleration over the course of one season of football or ice hockey (Chapter 4:). Importantly, these alterations in cerebrovascular function were not observed in non-contact athletes. Studies employing fMRI suggest subconcussive trauma may also alter NVC; for example, differences were observed in task-based BOLD signal in the occipital cortex were related to the number of head impacts experienced (20). However, fMRI studies have typically derived one parameter to estimate the magnitude of the BOLD response, which assumes the dynamics of the NVC response are unaltered by trauma (67). To probe this assumption, evaluation of NVC dynamics using techniques providing better temporal resolution, such as TCD, are required.  As such, our objective was to prospectively evaluate the effect of repetitive subconcussive head trauma on the dynamics of the NVC response, with the hypothesis that alterations would be observed at post-season relative to pre-season in a group of young adult elite contact sport athletes.     134 6.3 Methods 6.3.1 Study design 179 elite male (mean age 19.6±1.5 years) junior hockey (n=90) and football (n=89) athletes were recruited to the study, in addition to 15 non-contact sport controls (mean age 20.4±2.2 years: 12 cross-country running, 1 ultimate, 2 basketball). All participants completed baseline laboratory testing prior to the beginning of the athletic season (preseason). Testing was repeated within two weeks of the end-of-season (post-season) in a subset of contact sport participants who were not concussed during the season (n=52), as well as all non-contact sport controls (Table 6-1). Prior to testing, participants completed the Sport Concussion Assessment Tool, version 3 (SCAT3) (9). The SCAT3 is comprised of a graded symptom checklist (7-point Likert scale for 22 concussion symptoms), the Standardized Assessment of Concussion (SAC) probing orientation, concentration, and immediate and delayed recall, as well as a balance assessment in the form of the modified Balance Error Scoring System (BESS). Exclusion criteria included significant history of cardiorespiratory, cerebrovascular, neurological, or severe neurodevelopmental disorder, however no participants were excluded on these grounds. All subjects were familiarized with testing procedures and abstained from caffeine, exercise, and alcoholic beverages for at least 12 hours before testing. Written informed consent was obtained before participating in the study, which was approved by the University of British Columbia Clinical Research Ethics Board.    135 Table 6-1. Participant characteristics. Demographics, SCAT3 performance, and resting physiological parameters for contact sport and control (non-contact sport) athletes at preseason and post-season; data are presented as mean (SD). Metric Contact Sport (n=52) Control (n=15) Preseason Post-season Preseason Post-season Age (years) 19.6 (1.5) 20.4 (2.2) BMI (kg/m2) 28.2 (4.9) 22.6 (3.0) Test Interval (days) 109.2 (25.8) 100.1 (23.8) # of Symptomsa 3.7 (3.6) 5.4 (5.0) 5.5 (5.0) 5.7 (3.3) Symptom Severitya 6.7 (7.8) 9.6 (10.1) 8.1 (8.3) 8.2 (7.2) SAC Scorea 26.6 (1.9) 26.6 (1.8) 27.7 (1.5) 27.9 (1.4) BESS Scorea 3.7 (3.3) 2.9 (3.2) 2.7 (2.4) 2.6 (3.6) PCAv (cm/s) 34.6 (5.7) 36.1 (7.7) 35.9 (6.2) 37.0 (1.3) MCAv (cm/s) 54.5 (9.3) 53.8 (7.5) 55.6 (14.4) 57.3 (14.3) MAP (mmHg) 92.2 (12.2) 92.6 (12.7) 93.9 (13.8) 91.3 (9.7) PETCO2 (mmHg) 38.0 (3.0) 37.1 (2.6) 37.9 (1.8) 37.9 (1.3) HR (bpm) 74.5 (10.0) 78.3 (11.9) 71.0 (9.9) 72.8 (13.8) SCAT3 = Sport Concussion Assessment Tool version 3; SAC = Standardized Assessment of Concussion; BESS = Balance Error Scoring System; MAP = mean arterial pressure; PCAv = posterior cerebral artery blood velocity; MCAv = middle cerebral artery velocity; PETCO2 = end-tidal partial pressure of carbon dioxide; HR = heart rate   6.3.2 Instrumentation Participants wore a standard three-lead electrocardiogram (ECG). Cerebral blood flow velocity was recorded using 2 MHz TCD ultrasound probes (ST3, Spencer Technologies, Seattle, WA); the P-1 segment of the PCA was insonated on the left side of the head (PCAv), and the M-1 segment of middle cerebral artery (MCAv) was insonated on the right side. Vessels were identified and signals optimized according to depth, waveform, velocity, and response to carotid compression / visual stimulation tests (150), and ultrasound probes were locked in place with a fitted head frame (Spencer Technologies). Beat-to-beat blood pressure was recorded via finger   136 photoplethysmography and a brachial cuff to adjust for height differences between the finger and brachial artery (Finometer PRO, Finapres Medical Systems, Amsterdam, The Netherlands). Partial pressure of expired CO2 was recorded via an online gas analyzer (ML206, AD Instruments, Colorado Springs, CO) and used to measure end-tidal CO2 levels (PETCO2). Data were sampled at 1000 Hz (PowerLab 8/30 ML880, AD Instruments) and stored for offline analysis using commercially available software (LabChart version 7.1, AD Instruments).   6.3.3 Experimental protocols As outlined previously (Chapter 5:, 213) baseline physiological metrics were established during a one-minute resting trial prior to evaluating NVC dynamics using a visual stimulation paradigm (Table 1). The visual stimulation protocol entailed five cycles of 20 seconds eyes-closed followed by 40 seconds eyes-open and reading an article of interest to the participants, consistent with other neurovascular coupling research (213,241,242,244,247,381). Subjects were seated 50-60 cm from the computer monitor (27” Apple iMac) with a 50 cm x 35 cm visual field, with screen brightness set to maximum.   6.3.4 Data processing All data were processed using a custom program (Matlab vR2013a, Mathworks, Natick, MA). Beat-to-beat values of systolic and diastolic blood pressure, MCAv, and PCAv were determined from each R-R interval and used to calculate mean arterial pressure (MAP) and mean velocity traces. Breath-to-breath peak expired CO2 values were extracted to measure PETCO2. All signals were visually inspected for artifacts and corrected by cubic spline interpolation before filtering   137 with a dual-pass, 4th order digital Butterworth filter with a 2 Hz cutoff frequency. Trials were time-aligned to stimulus onset (eyes open) and averaged within-subject to generate a representative NVC trace for each session. Given the unknown insonation angle of the TCD probes, relative changes in CBF velocity were calculated as a percent change from the average velocity during the 3-5-second window prior to stimulus onset (244). Dynamics of the NVC response were quantified as peak rate of increase in CBF velocity during the activation phase (slopemax), time to slopemax (tslopemax), peak relative change in CBF velocity (vmax), time to vmax (tvmax), and area-under-the-curve to 25 seconds (AUC25) (Figure 6-1).   6.3.5 Impact monitoring During the season, a subset of contact sport participants who completed both pre- and post-season testing (n=29) wore impact sensors (xPatch, X2 Biosystems, Seattle, WA) on the right mastoid process to estimate linear and rotational acceleration profiles for each head impact experienced during games. Acceleration profiles were sampled for 100 ms (10 ms pre-impact, 90 ms post-impact) at 1000 Hz when translational acceleration exceeded a 10 g threshold. Data were uploaded using the Head Impact Monitoring System (X2 Biosystems) after each game. Peak linear (PLA) and peak rotational (PRA) acceleration were estimated for each detected impact. In an attempt to restrict analysis to head accelerations most likely to result from direct impacts rather than hard stops or cuts, only acceleration events exceeding a 20 g threshold were used (19,362,363). Cumulative exposure to linear (cPLA) and rotational (cPRA) acceleration were estimated by summing across all impacts for the season. Non-contact sport athletes did not wear impact sensors.     138 6.3.6 Statistical analyses Statistical analyses were performed in SPSS for Macintosh (v22.0, IBM Corp., Armonk, NY). Normality was evaluated using Shapiro-Wilks tests. Significance was determined a priori to achieve an experiment-wide α = 0.05. Effects of exposure to repetitive subconcussive trauma during the course of one competitive season were estimated via a 2 (contact versus non-contact sport) x 2 (pre-season versus post-season) two-way mixed ANOVA using type III sums of squares to account for unbalanced sample sizes across groups. Secondary exploratory analyses on the relationship between change scores in slopemax, tslopemax, vmax, tvmax, and AUC25 from pre- to post-season and cPLA and cPRA were conducted using Spearman’s correlation coefficients. Spearman’s correlation coefficients were also calculated between NVC change metrics and changes in symptom, SAC, and BESS scores from pre- to post-season.  6.4 Results Demographic characteristics, SCAT3 scores, and resting physiological metrics across testing sessions and groups are outlined in Table 6-1. Representative traces of PCAv, MCAv, MAP, and PETCO2 responses to visual stimulation are provided in Figure 6-1.    139  Figure 6-1. Representative traces of physiological responses to visual stimulation during one trial of the neurovascular coupling task a) change posterior cerebral artery velocity (PCAv) – outcome metrics include timing and magnitude of peak slope during activation phase (slopemax), timing and magnitude of peak relative change in PCAv (vmax), and area-under-the-curve over the first 25 seconds of eyes open (AUC25); b) change in middle cerebral artery velocity (MCAv); c) mean arterial pressure (MAP); and d) end-tidal partial pressure of CO2 (PETCO2); vertical green dashed lines indicates stimulus onset (eyes-open).  Biomechanical descriptors of impact exposure are presented in Table 6-2. Relative to football players, ice hockey players experienced fewer hits per game, but greater cumulative number of hits due to season length differences (62 games in hockey versus 10 games in football).     140 Table 6-2. Summary of biomechanical variables describing head impact exposure in contact sport athletes. Median (IQ range) for head impact exposure variables across subset of hockey (n=10) and football (n=19) players wearing impact sensors during the season; p-values reflect results of Mann-Whitney U-tests comparing across sport. Metric Hockey Football p Hits / game (#) 8.2 (6.1 - 11.2) 16.6 (8.7 - 21.2) 0.003 Hits / season (#) 353.5 (295.0 - 587.3) 166 (63.5 - 212) 0.002 PLA / hit (g) 36.3 (35.4 - 37.4) 36.6 (34.5 - 40.2) 0.448 cPLA (g) 11920.5 (10788.3 - 21570.6) 5794.2 (2507.5 - 7117.7) 0.002 PRA / hit (rad/s2) 5036.1 (4772.3 - 5510.8) 6601.8 (6104.0 - 7441.0) <0.001 cPRA (rad/s2) 2016603.5 (11592.6 - 24322.9) 1057691.6 (486976.2 - 1376735.9) 0.003 PLA = peak linear acceleration; PRA = peak rotational acceleration; cPLA/cPRA = cumulative PLA/PRA Averaged time-series profiles for physiological responses to visual stimulation are presented in Figure 6-2.   Figure 6-2. Average time-series profiles to visual stimulation across physiological variables a) posterior cerebral artery blood velocity (∆PCAv); b) middle cerebral artery blood velocity (∆MCAv); c) mean arterial pressure (∆MAP); and d) end-tidal partial pressure of CO2 (∆PETCO2); vertical black dashed lines indicates stimulus onset (eyes-open); note: error bars are note shown for purposes of visual clarity.    141 Two-way mixed ANOVA revealed no significant group-time interactions for any NVC metric in the PCA (Figure 6-3) or MCA (Figure 6-4), nor were any significant main effects found for group or time (p all >0.05).    Figure 6-3. Summary blood velocity responses to visual stimulation in the posterior cerebral artery (PCA) a) baseline resting PCA blood velocity (PCAv); b) maximum (slopemax), and c) time to maximum (tslopemax) PCAv slope during activation phase; d) peak relative change (vmax), and e) time to peak relative change (tvmax) in PCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); 2-way mixed ANOVA revealed no significant main or interaction effects for any variable; error bars represent 95% confidence intervals.     142  Figure 6-4. Summary of blood velocity responses to visual stimulation in the middle cerebral artery (MCA) a) baseline resting MCA blood velocity (MCAv); b) maximum (slopemax), and c) time to maximum (tslopemax) MCAv slope during activation phase; d) peak relative change (vmax), and e) time to peak relative change (tvmax) in MCAv; f) area-under-the-curve during the first 25 seconds after stimulus onset (AUC25); 2-way mixed ANOVA revealed no significant main effects of group or time, nor significant interactions for any variable (p > 0.05) ; error bars represent 95% confidence intervals.  As shown in Table 6-3, control subjects exhibited a lower heart rate than contact sport subjects during eyes-closed periods, but heart rate responses to visual stimulation did not differ. No significant correlations were observed between changes in NVC dynamics from pre- to post-season and any impact exposure metric, nor were there any significant relationships with change scores on components of the SCAT3 (p all >0.05).     143 Table 6-3. Summary of responses to visual stimulation for secondary physiological variables. Metric Contact Sport (n=52) Control (n=15) pinteraction ptime pgroup Preseason Post-season Preseason Post-season MAPbase (mmHg) 90.3 (9.8) 89.7 (10.5) 86.3 (19.0) 88.4 (10.4) 0.571 0.747 0.323 ∆MAPmax (%)  5.1 (3.6) 4.2 (3.7) 4.3 (4.6) 2.9 (2.1) 0.694 0.144 0.213 PETCO2base (mmHg) 37.7 (4.2) 38.4 (4.8) 40.1 (2.5) 39.0 (2.4) 0.213 0.757 0.160 ∆PETCO2max (mmHg) 1.5 (2.3) 1.1 (2.4) 0.8 (0.5) 1.3 (0.9) 0.361 0.895 0.131 HRbase (bpm) 64.9 (10.0) 66.2 (10.2) 58.7 (7.5) 59.3 (10.2) 0.791 0.509 0.020* ∆HRmax (bpm) 5.2 (3.8) 4.7 (3.6) 4.8 (3.5) 4.6 (3.4) 0.785 0.604 0.792 MAPbase = baseline MAP (eyes-closed); ∆MAPmax = peak relative change in MAP following stimulus onset; PETCO2base = baseline end-tidal PCO2 (eyes-closed); ∆PETCO2max = peak absolute change in PETCO2 following stimulus onset; HRbase = baseline heart rate (eyes-closed); ∆HRmax = peak absolute change in heart rate following stimulus onset; p-values reflect 2-way mixed ANOVA; * indicates significant finding.  6.5 Discussion  In the current study, the influence of repetitive sub-concussive head trauma – as experienced during one season of competitive athletic play – on indices of neurovascular coupling dynamics was examined using a visual stimulation paradigm in contact sport and non-contact sport athletes. It was hypothesized that the timing and amplitude of NVC responses in the posterior cerebral artery would be negatively influenced by repetitive head trauma, as described by five variables: (i) the peak rate of increase in PCAv following stimulus onset (slopemax); (ii) time between stimulus onset and peak PCAv slope (tslopemax); (iii) the peak elevation (vmax) and; (iv) time to peak elevation (tvmax) in PCAv; and (v) area-under-the-curve during the first 25 seconds after visual stimulation (Figure 6-1). The results did not support this hypothesis, with no statistically significant effects of group or time detected by two-way mixed ANOVA. Taken together, the results suggest that exposure to repetitive subconcussive trauma over the course of one season induces minimal effects on TCD-derived characteristics of the NVC response following visual stimulation.   144  6.5.1 Mechanisms underlying the neurovascular coupling response Cortical activation increases local cerebral metabolism, which requires a coordinated response of the neurovascular unit to modulate resistance within cerebral blood vessels to distribute blood to necessary areas. The dynamics of the NVC response likely involve a multitude of mechanisms, including accumulation of vasoactive metabolic by-products (e.g. CO2, nitric oxide (NO), adenosine, arachidonic acid metabolites), direct neural control of the cerebrovasculature, astrocyte-mediated vasosignaling, and pericyte-mediated changes in capillary tone (reviewed in: (145,220)). The entire cerebrovascular tree is directly innervated with autonomic fibres, implicating a role for autonomic activity in modulating cerebrovascular resistance and thus CBF (145,225,226). Astrocytes with end-feet that envelope penetrating arterioles are thought to play an important role in the slow component to the NVC response (3-4 seconds), but may serve a limited role in the immediate hyperemic effect (< 1 second) following neural activation (232). Glutamate release from active neurons causes nearby astrocytes to uptake calcium ions and alter arteriolar smooth muscle tone following the release of vasoactive substances (adenosine, nitric oxide, prostaglandins and other arachidonic acid derivatives) (reviewed in: (232)). Inhibitory interneurons are pivotal in the precise regulation of CBF via their interactions with neurons, astrocytes, and microvessels to integrate signals and release vasoactive substances (e.g. NO, acetylcholine, neuropeptide-Y, vasoactive intestinal peptide) (237,238). Gap junctions between vascular smooth muscle cells enable signal propagation and vasoactivity in upsteam pial arterioles (221-223). While the extent to which each of these pathways regulate NVC dynamics in humans remains incompletely understood, multiple overlapping mechanisms exist to modulate cerebrovascular resistance and appropriately distribute CBF following changes in neural activity,   145 providing multiple avenues by which head trauma may influence NVC responses (220).   6.5.2 Evidence of functional changes following subconcussive trauma That subconcussive trauma can detrimentally alter brain structure and function has been established. Transient damage to the blood-brain barrier in the form of elevated serum levels of the astrocytic protein S100B has been observed as a function of the number of subconcussive hits in football players (66), while dynamic contrast enhanced MRI showed blood-brain barrier pathology in football players interpreted to result from subconcussive trauma (77). Multiple studies have established an association between subconcussive trauma and changes in white matter diffusion (24-26,65,370,372). Deficits in aspects of cerebrovascular function other than neurovascular coupling have been attributed to repetitive subconcussive trauma (Chapter 4:)(17-19). In the same sample of participants as the current study, impairments in the cerebrovascular response to changes in blood pressure were related to total number of head impacts and cumulative exposure to linear acceleration (Chapter 4:). Furthermore, these changes were related to alterations in sympathovagal balance from pre- to post-season (Chapter 4:). Alterations in CO2 reactivity in football and soccer players have been associated with cumulative impact exposure and persisted for up to 4-5 months post-season (18,19). Impairments in CO2 reactivity were related to the volume and intensity of sparring, but not the frequency of knock-outs suffered or number of rounds fought in a sample of professional boxers (17). Cerebral metabolism is affected by repetitive head hits, wherein the total number hits greater than 60 g in the week preceding evaluation was associated with alterations in a variety of metabolites; larger blows to the head yielded disrupted energy metabolism and damage to glial cells (70). Relationships with cerebral metabolites suggested high magnitude trauma induces an initial state of   146 hypermetabolism followed by hypometabolic responses that are influenced by the timing, number, magnitude, and location of hits to the head (70). Similar changes in cerebral metabolites were observed in retired professional soccer players without a history of concussion, suggesting the potential for chronic metabolic disturbances resulting from subconcussive trauma (68).   Multiple recent task-based fMRI studies in high-school football athletes have demonstrated changes in hemodynamic response patterns to cortical activation as a function of head impact exposure (20,22,69,76,268). During in-season assessments, those who performed abnormally on cognitive tests displayed reduced fMRI activity within temporal and occipital cortices, and experienced higher numbers of hits to the top-front of the head relative to subjects performing normally (22). Relative to preseason, scans during periods of the athletic season with high levels of contact revealed greater within-subject variation in visual working memory BOLD signal that tended to normalize after contact was ceased (69). fMRI changes persisting after the conclusion of the season were significantly more common in athletes receiving 50+ hits per week during the season (268); 80% of subjects who sustained > 900 cumulative hits were flagged for abnormal functional findings 2-5 months post-season, whereas those who received < 600 impacts were flagged 52% of the time. Thus, while the timing and magnitude of the NVC response multiple studies have reported changes in cortical activation as a result of subconcussive trauma.   6.5.3 Biomechanical characteristics of subconcussive trauma The lack of significant findings in the current study may be partly explained by differences in impact exposure from other studies. The average total number of hits per subject in this study (ranging from 5 to 677) was lower than has been reported in most studies (379,384-387), with   147 only five subjects (four hockey players, one football) sustaining at least 500 hits. In collegiate football players, cumulative impact numbers have averaged well over 500 per player (>14.4 g) (379,385,387). The average linear magnitude of impacts in the present study (Table 2) was higher than reported in other studies (379,384-387), but in line with those that have used a similar threshold (>20 g) for recording valid impacts (363). Nevertheless, subconcussive impacts may incrementally alter cerebral susceptibility to injury, with reports that football players were exposed to a higher magnitude and volume of head impacts on days of diagnosed concussion than on days without concussion (378). Other research has suggested individual playing style – and the influence on the spatial distribution of hits to the head – may influence the changes in hemodynamic responses to cortical activity (76); however, we did not assess relationships between impact location and NVC dynamics in the current study due to the known error of our impact sensors in this estimate (380). Another possible explanation for the observed lack of differences in NVC dynamics could relate to the sensitivity of the chosen outcome variables to the effects of head trauma. However, previous work has demonstrated NVC dynamics in the PCA are altered following acute concussion, including a within-subject delay in achieving peak rate of increase in PCAv (by ~50%) and elevations in the magnitude of the response (by over 30%) compared to preseason values (Chapter 5:). Thus, the chosen outcome parameters are sensitive to head trauma; however, exposure to repetitive trauma as experienced during the current study period did not significantly alter NVC dynamics.   6.5.4 Limitations The conclusions drawn from this study are subject to multiple limitations. This was a modest sample of contact sport athletes, but was drawn from a local setting of elite male athletes aged   148 17-24, limiting generalizability to other patient populations including females. Transcranial Doppler ultrasound provides excellent temporal resolution, allowing beat-by-beat analysis of CBF dynamics; however, the spatial resolution of this technique is limited to large cortical territories supplied by the major cerebral arteries that can be reliably insonated. As such, any potential changes in NVC dynamics restricted to focal occipital areas as a result of repetitive head trauma may have been masked. Nevertheless, NVC dynamics in the major upstream feeding vessels were not affected. Furthermore, TCD provides an index of CBF via measurement CBF velocity; this association holds true only so long as the insonated vessel does not appreciably change diameter, which cannot be confirmed, although any influences of CO2 and blood pressure on vessel diameter are presumed to have been minimal given the relative consistency of these measures during the task (Figures 1 & 2). It is pertinent to note that impact sensors were worn during games only, thereby underestimating true impact burden. The number and magnitude of hits have repeatedly been shown to be higher in games than practices (50,387), and between-subject trends in exposure based on individual playing style and position are likely still captured in the current data set. The error in estimates of impact exposure is compounded by recent reports demonstrating substantial in-vivo overestimation bias using skin-worn impact sensors when compared to mouthguard-based sensors due to non-rigid skull coupling (380). Consistent overestimation of the severity of individual impacts is unlikely to affect the conclusions drawn from the current data.  6.6 Conclusions There is growing concern over the potential short- and long-term effects of contact sports and repetitive subconcussive head impacts. While deficits in other aspects of cerebrovascular   149 function have been reported as a consequence of subconcussive trauma, this exploratory study suggests the dynamics of the neurovascular coupling response are unaltered following a single season of contact sport participation. Non-contact sport athletes also exhibited no changes in NVC dynamics. Future prospective cohort studies in a larger number of subjects with greater impact exposure are warranted to confirm the current findings.     150 Chapter 7: Conclusion. 7.1 Overview The global motivation underlying my doctoral research was to elucidate physiological changes that occur following sport-related head trauma towards facilitating the development of novel and objective methods to improve the identification, management, and treatment protocols for sport-related head injury. Sport-induced concussion occurs at an alarmingly high rate, affecting millions each year, with estimates of the prevalence in adolescent athletes reaching 10-25% (6,7). Despite vastly increased attention to the issue over recent years, sport-related head injury remains one of the most poorly understood injuries in the fields of sports medicine and neuroscience. Clinical management of concussion is based heavily on resolution of patient-reported symptoms (9), highlighting the pressing need for more objective identification and management techniques. Intentional underreporting of symptoms – in the hopes of avoiding being withdrawn from play, or to expedite return-to-play – is a well-established problem that increases risk for further concussions as well as longer-term consequences associated with repetitive head trauma (8,12-14).  Emerging evidence also suggests a link between repetitive subconcussive head impacts, multiple clinically manifest concussions, and the development of long-term neurodegeneration termed chronic traumatic encephalopathy (15). There is a growing evidence base supporting a link between repetitive subconcussive trauma specifically, and impairments in learning (16), alterations in functional brain connectivity (20-22), changes in gray matter density and volume (23), and altered diffusion in white matter tracts (24-26). Long-lasting effects of sport-related head trauma may include problems with affect regulation, attention, memory, and depression,   151 though the physiological changes underlying such effects remain poorly understood. It is imperative that we achieve a more thorough understanding of the precise mechanisms by which sport-related head trauma affects the brain.  Though concussions have been traditionally thought to represent a functional disturbance in the brain rather than a structural injury, recent research has challenged this assumption, including data presented in Chapter 2: of this thesis. Myelin is increasingly regarded as an important player in TBI pathophysiology, though its role is poorly understood (83). Clinical deficits following concussion have been associated with regional microstructural white matter changes observed using diffusion tensor imaging (103,104,388-390). However, the inability of this technique to provide information on the underlying reason for changes in water diffusion (e.g. demyelination versus increased membrane permeability versus overlapping axons) (110) has contributed to inconsistent findings across studies (97,99). While various animal models have implicated myelin fragmentation and degradation following traumatic injury (82,95), the initial study in this thesis provides the first direct, in-vivo assessment of myelin integrity following sport-related concussion (and mTBI more broadly) in humans. The axonal pathology observed in concussion is thought to evolve over days to weeks following traumatic insult, and this notion is supported by our findings of reductions in myelin water content at 3-days and 2-weeks post-injury. Given the foundational role of myelin towards enhancing the speed and efficiency of signal conduction, these results also support the proposition that demyelination may be responsible for slower interhemispheric transfer times associated with reduced fractional anisotropy (FA) in the corpus callosum of pediatric mTBI patients (108) and might partly explain the cognitive deficits observed post-concussion (e.g. reduced processing speed). Myelin disruptions were observed in   152 several areas, including the corpus callosum and posterior limb of the internal capsule – tracts known to be involved in the communication of autonomic information. Interestingly, recent animal work has suggested that myelin precursor cells contribute to the integrity of the blood-brain barrier (86); as such, it is possible to the disruptions in myelin content observed in Chapter 2: could also contribute to increased blood-brain barrier permeability that has been observed with head trauma (66,77), though this remains speculative. Myelin content returned to near-preseason levels by 2-months post-injury, suggesting remyelination may occur; however, the potential for disruptions in myelin to outlast clinical recovery raises concern that – under current management protocols – athletes may be returned to play during a period when the brain is not yet recovered structurally or physiologically. Further research is warranted to directly investigate the influence of myelin disruptions on cerebral metabolism, autonomic function, and cerebral susceptibility to injury.   Recent work has also delineated an important role for compromised cerebrovascular function in the disturbances associated with concussion (131). Cerebral metabolism is critically dependent on the regulation of CBF. Concussed patients have consistently exhibited global and regional alterations in CBF (2,43,136,137), with some studies suggesting sport-related head trauma can yield impairments in the mechanisms controlling CBF (17,19,177,179). Although they represent key components in the assessment of cerebrovascular function (150), no studies prior to those presented herein have used techniques with sufficient temporal resolution to explicitly evaluate the dynamics of CA or NVC responses in concussed athletes or in athletes exposed to a high frequency of subconcussive trauma. The aim of Chapters 3-6 was to prospectively determine how these CBF control mechanisms are affected by sport-related concussion and repetitive   153 subconcussive trauma. To address this question, these two aspects of cerebrovascular function were evaluated using TCD ultrasound in a cohort of individuals with a high likelihood of enduring repetitive head trauma and sustaining concussions – namely, contact sport athletes.   Chapter 3: presents a TCD-based assessment of autoregulatory function following concussion, and revealed delays in the cerebrovascular response to a common blood pressure challenge – change in posture – that persisted for at least 2-weeks and appear to be autonomically-mediated. These deficits were related to poorer performance on a cognitive screening test, but do not appear to be cumulative based on comparison of athletes with a history of 3+ concussions to concussion-naïve individuals. Physiologically, cerebral autoregulation is a multiple input system that likely exhibits features of non-stationarity and non-linearity (391). Despite the widespread use of TFA within the CA research community (212), this approach models the MAP-CBF relationship as a linear system with one input and one output. As such, the inherent complexity of autoregulation is not captured within this analysis technique, representing an important limitation of this approach. In effort to maximize the reliabilty of our MAP-CBF characterization, we had participants complete repetitive squat-stand manoeuvres to “linearize” the system and amplify signal-to-noise ratio (210). While validation is still required in a larger sample, the results suggest concussion induces transient disruptions in autonomic cerebrovascular function that may outlast symptom resolution and clinical recovery, highlighting the emerging notion that physiological recovery and clinical recovery may not equate.   Chapter 4: extends from the findings in Chapter 3, and demonstrates impairments in the latency and magnitude of autoregulatory responses following exposure to one season of repetitive   154 subconcussive trauma during contact sport. The degree to which autoregulatory capacity was impaired was directly related to: i) the total number and cumulative linear magnitude of head impacts experienced during the season, as well as; ii) the relative increase in sympathetic:parasympathetic output observed post-season. Non-contact sport athletes exhibited no such changes in autoregulatory or autonomic function. The clinical relevance of these autoregulatory changes – which also appear to be autonomically mediated – towards rendering the brain more susceptible to injury remains unknown. Furthermore, any cumulative, year-over-year effects are not discernable from this data. Despite multiple published hypotheses that CA disruptions play a pivotal role in the persistence of post-concussion symptoms (131,133,206), these studies provide the first direct, prospective evidence of dysfunction in cerebral autoreglatory behaviour in the context of sport-related head trauma.   In addition to alterations in CO2 reactivity and cerebral autoregulation, CBF is highly sensitive to cortical activity. In Chapter 5:, alterations in PCAv response dynamics following visual stimulation were apparent at 3-days post-injury in concussed athletes. The rise in PCAv during the early activation phase – thought to be mediated by autonomic activity (213) – was delayed by over 50% compared to preseason. This increased response latency was accompanied by a >30% increase in the magnitude of the response that was inversely related to the time until medical clearance for return-to-play. Such effects appear to be transient, largely resolving by 2-weeks post-injury, and were not cumulative across multiple concussions in otherwise healthy athletes. These findings add to the growing understanding that acute sport-related concussion exerts detrimental effects on multiple aspects of cerebrovascular function, possibly via effects of autonomic modulation of CBF dynamics.   155  Despite reported deficits in other aspects of cerebrovascular function following exposure to repetitive subconcussive trauma – including CO2 reactivity (17-19) and cerebral autoregulation (Chapter 4:) – the data presented in Chapter 6: suggest the dynamics of NVC responses in the PCA are unaltered following exposure to one season of repetitive subconcussive trauma. Non-contact sport athletes also exhibited no change in NVC dynamics. Considered in conjunction with the observed effects of subconcussive trauma on indices of cerebral autoregulation in the same participant pool (Chapter 4:), these results highlight the importance of comprehensive evaluations of cerebrovascular function with the understanding that the three major CBF control mechanisms (CO2, blood pressure, NVC) reflect different and uncorrelated aspects of cerebrovascular control (158).   Autonomic nervous system dysfunction is increasingly recognized as a major contributing factor to the effects of sport-related head trauma, and this theme resonates throughout the current thesis. Multiple reports have outlined the effects of concussion on cardiac autonomic function, consistently demonstrating reduced heart rate variability in ways that suggest elevated sympathetic and / or reduced parasympathetic outflow – particularly in physically active states – that may persist beyond clinical recovery, (298-306). The results presented in Chapters 3-5 provide the first evidence supporting a role for autonomic dysregulation in the control of CBF in the context of sport-related head trauma. Specifics underlying the autonomic modulation of cerebrovascular resistance in healthy humans, let alone post-concussion, remain poorly defined (190). However, brain injury models suggest a lateralized control of autonomic outflow wherein left insular efferents exert parasympathetic effects and right insular efferents generate   156 sympathetic responses (351-353). It has been demonstrated that altered white matter microstructure in the corpus callosum and posterior limb of the internal capsule contribute to paroxysmal sympathetic hyperactivity (392). Damage to these regions – both of which exhibited disruptions in myelin integrity in Chapter 2: – could compromise balance between sympathetic and parasympathetic outflow (301). Damage to prefrontal areas within the central autonomic network could further exert a disinhibition of the central nucleus of the amygdala, causing a net increase in sympathetic activity through subsequent disinhibition of sympathoexcitatory neurons in the ventrolateral medulla (354). Increased sympathetic drive has been shown to effect a transient “stiffening” of peripheral blood vessels following concussion (300); if also true in the cerebrovasculature, this would explain the increased latencies in cerebrovascular responses outlined in Chapters 3-5. Reduced compliance in cerebral vessels secondary to trauma-induced autonomic dysregulation could subject the microvasculature to higher mechanical forces as a result of elevated pulsatile flow (393) and potentially contribute to microvascular damage and transient disruptions in blood-brain barrier permeability that have previously been reported (66,77).   Beyond providing a theoretical mechanism for trauma-induced disruptions in cardiac and cerebrovascular function, alterations in autonomic function may have direct clinical implications in the setting of sport-related head trauma. In patients with a history of mTBI, early autonomic dysfunction is thought to contribute to enduring emotional dysfunction, particularly in female patients (296,297). It has also been suggested that autonomic dysfunction may contribute to the increased mortality in patients with a history of mTBI (292-295). In more severe injuries, direct associations have been demonstrated between acute cardiac autonomic dysfunction and high   157 mortality rates in TBI patients (291). Further research is warranted to determine what contribution, if any, is made by alterations in autonomic behaviour towards the development of long-term neurodegenerative changes and clinical outcomes following a lifetime of contact sport participation.   7.2 Future directions This thesis describes the effects of head trauma, both concussive and subconcussive, on myelin content in the brain and on mechanisms controlling blood flow to the brain. Though the techniques described in this thesis represent promising avenues for future research with the potential for integration into clinical decision making, the results presented herein provide multiple avenues for future research that have yet to be thoroughly addressed experimentally.  1. When is it safe for concussed athletes to return-to-play? In addition to the results presented in Chapter 2: and Chapter 3:, other avenues of research continue to document disruptions in physiological function that persist well beyond symptom resolution and clinical recovery (42,44,45). The obvious question that arises pertains to the safety of relying on symptom reports to guide clinical decision-making, and whether physiological recovery need be considered to avoid placing athletes at undue risk by prematurely approving return-to-play. Indeed, there are calls within the field for a shift away from symptom-based assessments of sport-related head trauma towards structured physical examinations rooted in evaluations of physiologic function (46). Clearly, the clinical relevance of various persistent physiological disruptions –   158 including those reported in this thesis – towards injury susceptibility needs to be established.    2. What is the role of autonomic dysregulation of cerebrovascular function in patients who develop persistent post-concussion syndrome? While recent research has increasingly suggested the deficits of acute concussion are mediated by alterations in cerebrovascular function, the extent to which these alterations also underlie the clinical manifestations of post-concussion syndrome is unknown. It will be of great clinical value to compare the structural and functional imaging patterns in patients with PCS to those in patients who recover spontaneously and in more typical timeframes. Pioneering work from the group at the University of Buffalo has sought to stratify PCS patients into operational sub-types on physiological grounds, using graded exercise and other clinical tests to evaluate the presence of global physiological dysfunction versus isolated dysfunction of particular neurological sub-systems (133). In their schema, “physiological post-concussion disorder” (PCD) is posited to be mediated by a persistence of the same biochemical, autonomic, and cerebrovascular alterations that characterize acute concussion. Techniques used in the current thesis will enable insight into these mechanisms and not only enhance our understanding of the mechanisms underlying the various proposed subtypes of PCD, but also complement and facilitate the individualized assessment and targeted treatment of these patients based on documented physiological deficits.    159  3. What is the potential role for rehabilitating autonomic dysfunction following injury, including the role for exercise? The relationship between exercise intolerance and CBF dysregulation post-concussion is poorly understood, but may be mediated by altered autonomic function. As such, autonomic function may represent a potential therapeutic target for intervention and rehabilitation of patients suffering from post-concussion sequelae, similar to the emerging pattern in management of stroke patients (394). Indeed, the suggested mainstay of treatment for physiological PCD is tailored sub-maximal aerobic exercise (133). Evidence suggests exercise therapy may improve autonomic function by increasing vagal tone and decreasing sympathetic activity (reviewed in (290)), potentially through effects on angiotensin II and nitric oxide, both of which have potent effects on CBF. Exercise training has been shown to increase central arterial compliance and consequently reduce pulsatile flow in the middle cerebral artery (393). Along a similar line of reasoning, the potential for direct therapeutic modulation of autonomic activity following concussion is intriguing. Indeed, optimizing parasympathetic nervous system activation has shown neuroprotective effects in preclinical models of stroke – including increased CBF and improved neurogenesis (395) – and has been successful in the treatment of other brain disorders including depression and epilepsy (396,397). Excitotoxicity may be mitigated by vagal nerve stimulation, reducing extracellular glutamate levels within 15-20 minutes after 5 minutes of experimental transient global ischemia (395,398). Numerous autonomic structures are located in an area of the pterygopalatine fossa that is accessible via minimally invasive neuromodulation techniques. Neuromodulation of autonomic   160 fibres has been suggested as a promising approach in the management of headache disorders, stroke, and cerebral vasospasm (399). One case report has recently been published outlining the successful treatment of refractory chronic posttraumatic headache in a concussed high school football player using sphenopalatine ganglion block (400).   4. What are the differences, if any, in physiological responses to sport-related head trauma between sexes and across age groups? Perhaps the biggest limitation of this thesis (particularly Chapters 3-6) involves the exclusive examination of males – a problem not limited to the current studies but one that plagues the entire field of research in sport and exercise science (401). Although this outcome was not intended during planning of the current thesis, it will be especially important to evaluate the role of cerebrovascular and autonomic dysfunction in females considering the evidence suggesting females tend to fair more poorly than males with respect to post-concussive symptoms and recovery trajectories (356). Importantly, the physiological underpinnings for such sex-specific differences, and whether the underlying brain pathology is different between men and women with concussion, remain unknown (98). Differential responses to trauma may also occur across age groups, particularly in the developing brains of children who reportedly experience worse symptoms and longer recoveries than their adult counterparts (402,403). Answering these questions will be especially important as children participate in organized sport in greater numbers and at younger ages.    161 5. To what extent might the observed deficits in autoregulatory function contribute to the development of long-term neurodegenerative changes such as chronic traumatic encephalopathy? Interestingly, the pathological hallmarks of CTE include perivascular deposition of hyperphosphorylated tau (15); though it remains entirely speculative, trauma-induced impairments in CA would subject the microvasculature to higher mechanical forces as a result of elevated pulsatile flow, conceivably contributing to the blood-brain barrier disruption that has been observed with concussive and subconcussive trauma. Over the course of a long playing career in contact sports, repetitive exposure of the brain to traumatic insults could ostensibly contribute to the pattern of pathology observed in CTE. Large, longitudinal, multi-disciplinary studies are warranted to better elucidate a cause and effect relationship between repetitive head trauma and CTE.  7.3 Conclusion and significance A better understanding of the pathophysiological underpinnings of concussion and subconcussive trauma is needed to objectively and reliably identify and manage dangerous levels of sport-related head trauma, thereby limiting the burden of sport-related head injuries at an individual and population level. Although not yet appropriate for clinical use, the methods described in this thesis provide tremendous opportunity to further investigate physiological dysfunction following head trauma. In particular, the utility of ultrasound as a portable tool to characterize cerebrovascular function in athletes is by no means exhausted. This thesis provides valuable insights into the capacity of sport-related head trauma to induce structural and functional disturbances in the brains of young adult contact sport athletes, demonstrating   162 disruptions in both myelin integrity and mechanisms controlling CBF following concussive and subconcussive trauma. That such disruptions persisted in some cases beyond symptom resolution and clinical recovery suggests the need to consider the relevance of clinical versus physiological recovery. All of the deficits observed post-concussion resolved within 1-2 months and did not appear to accumulate across multiple injuries. Large prospective cohort studies using a multidisciplinary approach in subjects representing a variety of contact and non-contact sports are warranted to further delineate the short- and long-term clinical utility of these findings.     163 Bibliography 1. Thompson J, Sebastianelli W, and Slobounov S. 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