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The development of the corticospinal tract in premature newborns : impact of early brain injury Adams, Elysia 2009

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THE DEVELOPMENT OF THE CORTICOSPINAL TRACT IN PREMATURE NEWBORNS: IMPACT OF EARLY BRAIN INJURY by Elysia Adams B. A. (Hons), The University of British Columbia, 2007  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate Studies (Neuroscience)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2009  © Elysia Adams, 2009  Abstract Early brain abnormalities, including white matter injury, intraventricular hemorrhage and ventriculomegaly are associated with abnormalities of early motor functioning in premature neonates. Similarly, an increased risk of neurodevelopmental impairment is found in neonates with postnatal infections. The mechanism by which these factors impair motor functioning is largely unknown, but may result from altered development of white matter motor tracts. The purpose of this study was to evaluate the impact of brain abnormalities and neonatal illness on corticospinal tract (CST) development in premature neonates serially studied with diffusion tensor tractography (DTT). Fifty-five premature neonates between 24 and 32 weeks gestation at birth were scanned 2-4 weeks after birth, and again at termequivalent age. Moderate to severe brain abnormalities (abnormal-MRI) were characterized by at least one of: moderate or severe white matter injury, moderate or severe intraventricular hemorrhage, or ventriculomegaly. CST DTT was performed using DTIStudio with seeding in the posterior limb of the internal capsule and filtering at the precentral gyrus and cerebral peduncle. This yielded CST diffusion parameters (fractional anisotropy; FA and average diffusivity; Dav), indicators of microstructural development. The effect of abnormal-MRI and neonatal illness on CST FA and Dav was assessed. Twenty-one neonates (38%) had abnormal-MRI on at least 1 of 2 scans. In neonates with normal MRIs, FA increased by 0.011 per week; Dav decreased by 1.9x10-5 mm2/sec (both P<0.001). In neonates with abnormal-MRI, however, FA increased at a significantly slower rate of 0.008 per week (interaction term P=0.05); Dav was 1.5x10-5 mm2/sec higher for any given age at scan (P<0.001). Changes in FA resulted from a decrease in radial, rather than axial, diffusivity. Radial diffusivity was higher in neonates with abnormal-MRI. Additionally, 23 neonates (42%) were exposed to a postnatal clinical infection. FA increased more slowly in neonates with postnatal infection (interaction term P=0.04), with a borderline slower rate of decrease in Dav (interaction term P=0.08). These results demonstrate that CST microstructural development, including maturation of the glial cells surrounding the axon, is impaired in premature neonates with abnormal-MRI. Maturation of the CST is also impaired in neonates with postnatal infections, independent of these abnormalities.  ii  Table of Contents Abstract ..................................................................................................................................... ii  Table of Contents ..................................................................................................................... iii  List of Tables ............................................................................................................................ v  List of Figures .......................................................................................................................... vi  Abbreviations .......................................................................................................................... vii  Acknowledgements ................................................................................................................ viii  Dedication ................................................................................................................................ ix  CHAPTER I: INTRODUCTION .............................................................................................. 1  1.1 Problem of Prematurity .................................................................................................. 1  1.2 Neurological Outcomes of Prematurity .......................................................................... 2  1.3 Corticospinal Tract Anatomy and Postnatal Development ............................................. 3  1.3.1 Anatomy................................................................................................................... 3  1.3.2 CST Development in Newborns .............................................................................. 4  1.4 Neonatal Brain Abnormalities and Development ........................................................... 5  1.4.1 White Matter Injury ................................................................................................. 6  1.4.2 Intraventricular Hemorrhage .................................................................................... 8  1.4.3 Ventriculomegaly ................................................................................................... 10  1.4.4 Impaired Brain Development ................................................................................. 10  1.4.5 Neonatal Illness and Brain Abnormalities ............................................................. 10  1.5 Magnetic Resonance Techniques .................................................................................. 11  1.5.1 Diffusion Tensor Imaging ...................................................................................... 11  1.5.2 Diffusion Tensor Tractography.............................................................................. 17  1.6 Conclusions and Objectives .......................................................................................... 20  1.7 References ..................................................................................................................... 22  CHAPTER II: TRACTOGRAPHY-BASED QUANTITATION OF CORTICOSPINAL TRACT DEVELOPMENT IN PREMATURE NEONATES ................................................ 28  2.1 Introduction ................................................................................................................... 28  2.2 Methods......................................................................................................................... 29  2.2.1 Study Population .................................................................................................... 29  2.2.2 Clinical Data Collection ......................................................................................... 29  2.2.3 Magnetic Resonance Imaging Studies ................................................................... 30  2.2.4 Diffusion Tensor Tractography (DTT) .................................................................. 30  2.2.5 Data Analysis ......................................................................................................... 31  2.3 Results ........................................................................................................................... 32  2.3.1 Study Subjects........................................................................................................ 32  2.3.2 MRI Findings ......................................................................................................... 32  iii  2.3.3 Quantitation of Normal CST Development using DTT ......................................... 32  2.3.4 Effect of Moderate to Severe MRI Abnormalities on CST Development ............. 33  2.3.5 Effect of WMI and IVH on CST Development ..................................................... 33  2.3.6 Effect of Clinical Risk Factors on CST Development ........................................... 33  2.3.7 ROI-based Quantitation and Moderate to Severe Abnormalities .......................... 34  2.3.8 Reliability Comparison of CST Diffusion Parameters on DTT and ROI .............. 34  2.4 Discussion ..................................................................................................................... 34  2.4.1 CST Development in the Premature Neonate ........................................................ 34  2.4.2 CST Development and Brain Abnormalities ......................................................... 35  2.4.3 Clinical Risk Factors and CST Development using DTT ...................................... 36  2.4.4 Comparison of ROI and DTT Measurements of CST Development..................... 37  2.4.5 Limitations ............................................................................................................. 38  2.5 Conclusions ................................................................................................................... 38  2.6 References ..................................................................................................................... 46  CHAPTER III: CONCLUSIONS ........................................................................................... 50  3.1 Research Questions Answered ...................................................................................... 50  3.1.1 Development of the CST in Healthy Premature Neonates .................................... 50  3.1.2 The Impact of Early Brain Abnormalities on CST Development.......................... 51  3.1.3 The Impact of Neonatal Illnesses on CST Development ....................................... 51  3.2 Strengths and Limitations of the Current Study ........................................................... 52  3.2.1 Strengths ................................................................................................................ 52  3.2.2 Limitations ............................................................................................................. 53  3.3 Proposals for New Ideas ............................................................................................... 55  3.4 Significance of the Problem .......................................................................................... 55  3.5 Future Directions .......................................................................................................... 56  3.6 References ..................................................................................................................... 57  Appendix I: Comparison of FA and D av trajectories from first to second scan in neonates with and without moderate to severe MRI abnormalities ........................................ 60  Appendix II: University of British Columbia Research Ethics Board Certificate of Approval ................................................................................................................................. 61   iv  List of Tables Table 2.1 Descriptive statistics of the premature neonates enrolled in the study ................ 39  Table 2.2 Distribution of brain abnormality findings on MRI ............................................. 40  Table 2.3 Clinical features of the premature neonates with and without moderate to severe MRI abnormalities .................................................................................... 41  Table 2.4 Intra-rater reliability measurements for the repeated quantification of CST FA and Dav using the diffusion tensor tractography and region of interest methods ................................................................................................................ 42   v  List of Figures Figure 1.1 White matter injury on MRI................................................................................... 7 Figure 1.2 Intraventricular hemorrhage and ventriculomegaly on MRI ................................. 9 Figure 1.3 DTI diffusion tensor ellipsoid .............................................................................. 13 Figure 1.4 Brain development from early in premature life to term-equivalent age ............. 15 Figure 1.5 Tractography of the corticospinal tract using diffusion tensor tractography ....... 18 Figure 1.6 Placement of regions of interest to delineate the corticospinal tract.................... 19 Figure 2.1 Diffusion tensor tractography of the corticospinal tract in a premature newborn studied serially ...................................................................................... 43 Figure 2.2 Developmental trajectory of CST diffusion parameters obtained from serial DTT scans in premature newborns with and without moderate to severe MRI abnormalities (abnormal-MRI).................................................................... 44 Figure 2.3 Developmental trajectory of CST fractional anisotropy and average diffusivity from serial DTT scans in premature newborns with and without postnatal clinical infection. .................................................................................. 45   vi  Abbreviations Abnormal-MRI ADHD CI CLD CP CST Dav DTI DTT FA FACT ICC IQR IVH MR MRI OL PDA PLIC Pre-OL RA RDS ROI PROM PVL SNAP-PE TBSS VM WMI  Moderate to severe MRI abnormalities Attention deficit/hyperactivity disorders Confidence interval Chronic lung disease Cerebral palsy Corticospinal tract Average diffusivity Diffusion tensor imaging Diffusion tensor tractography Fractional anisotropy Fiber assignment by continuous tracking Intraclass coefficient Interquartile range Intraventricular hemorrhage Magnetic resonance Magnetic resonance imaging Oligodendrocyte Patent ductus arteriosis Posterior limb of the internal capsule Late OL progenitor Relative anisotropy Respiratory distress syndrome Region of interest Prolonged rupture of membrane Periventricular leukomalacia Score for neonatal acute physiology- perinatal extension Tract-based spatial statistics Ventriculomegaly White matter injury  vii  Acknowledgements I would like to acknowledge the wealth of support that has been available to me throughout this master’s program, as well as throughout my entire life. My success is the product of all of your contributions throughout the years. Thank you to Dr. Steven Miller and Dr. Vann Chau for their critical review of this thesis. I am very grateful to have had the opportunity over the last few years to work with Dr. Miller, whom I have the greatest respect for, at the BC Children’s Hospital. His mentorship, support and patience were integral to my success throughout this program; his passion for research inspired me at both the undergraduate and now at the graduate level. I also owe my gratitude to Dr. Vann Chau for all his contributions to this project and for his expert advice, both as a colleague and as a friend. Thank you also to the members of my supervisory committee; Dr. Ruth Grunau, Dr. Alex McKay and Dr. Joanne Weinberg, for their time and guidance. Thanks to my family and friends who maintained stability in my life and always understood when my school work had to come first. I could not have gotten through the successes and stresses without you all. Special thanks to Mike, who mentally held my hand each step of the way and gave me the courage to take chances and succeed even when the odds were against me. Also my parents who always believed in me, and taught me to ski down the mountain of obstacles that we need to overcome to achieve our dreams. Finally, I would like to acknowledge the financial contributions of the Canadian Institutes of Health Research (CIHR), Michael Smith Foundation for Health Research (MSFHR) and from Dr. Miller, who have helped put a roof over my head during the course of this program.  viii  Dedication  This is dedicated to the memory of my grandmother, who was, and will always be, one of the strongest women I have ever known.  ix  CHAPTER I: INTRODUCTION 1.1 Problem of Prematurity Premature birth is a problem of important consideration to our society. In British Columbia, approximately 8% of infants born each year are premature (less than 37 weeks gestational age at the time of birth) (BC Vital Statistics Agency, 2006). Due to their immaturity, these newborns are at high risk of several postnatal complications such as respiratory distress syndrome (RDS), patent ductus arteriosis (PDA), chronic lung disease (CLD) and postnatal infections (Witter and Keith, 1993; Ward and Beachy, 2003). Furthermore, brain abnormalities, such as white matter injury (WMI), intraventricular hemorrhage (IVH) and ventriculomegaly (VM), are prevalent in the premature population (Volpe, 2001). Such consequences have traditionally resulted in early mortality or in adverse long-term outcomes in survivors. Surviving infants have demonstrated impairments in areas of motor, cognitive, visual and everyday functioning (Piecuch et al., 1997; Vohr et al., 2000; Vohr et al., 2003). Underlying these global developmental deficits in the motor, cognitive and visual domains may be acquired focal or multifocal brain injuries or abnormal development of damaged white matter tracts, such as the corticospinal tract (CST). Non-cystic WMI, one of the most common cerebral abnormalities apparent in premature neonates, may result in these deficits in white matter development, and is associated with diffuse abnormalities in early motor and cognitive functioning (Miller et al., 2005; Woodward et al., 2006). The focus of this master’s thesis is to first examine the normal trajectory of CST development in premature neonates. The novel question we will then address is how the maturation of the CST is affected by early brain injury (e.g. WMI) and clinical risk factors. This is accomplished using diffusion tensor tractography (DTT), an advanced magnetic resonance imaging (MRI) technique. The cohort studied consists of very premature neonates (under 32 weeks gestational age) as they are at an increased risk of adverse neurodevelopmental outcome. Early identification of abnormal CST development may allow the prediction of delays in motor functioning as the infant enters childhood. This will lead to the early initiation of appropriate interventions to ameliorate or prevent these delays.  1  1.2 Neurological Outcomes of Prematurity Advances in neonatal intensive care have contributed to an increase in survival rates compared with previous neonatal mortality rates (Richardson et al., 1998). This decline in mortality is especially pronounced in the youngest neonates that are born prior to term age. Despite these declining mortality rates, however, these infants still account for the majority (66% in 2005) of infant deaths under one year of age. Presently, 85% of premature neonates survive beyond their first year. As a consequence of this improved survival rate, the incidence of motor and cognitive deficits in these infants appears to be rising (Volpe, 2001). These deficits are especially prevalent during the school-age years. Of the 85% of surviving premature infants, up to 50% exhibit cognitive deficits that are manifested in many different forms (Volpe, 2001). Studies have shown a higher incidence of autism spectrum disorders, attention deficit/hyperactivity disorders (ADHD), reduction in IQ and impairments in executive functioning at school age in ex-premature children in comparison with those born at term (Astbury et al., 1987; Harvey et al., 1999; Luciana et al., 1999; Marlow et al., 2005; Limperopoulos et al., 2008). Additionally, an increased risk of learning impairments is associated with prematurity. This was demonstrated in a recent study in which over half (56%) of the cohort of ex-premature children required special educational assistance, failed a grade or were in special education classes (van Baar et al., 2005). Further developmental disabilities are seen in the 5-10% of premature survivors who exhibit cerebral palsy (CP) in childhood (Volpe, 2001). This percentage may be even higher, as recent studies have consistently demonstrated the prevalence to be between 10-17% within their respective cohorts of premature infants (Vohr et al., 2000; Marlow et al., 2005; van Baar et al., 2005). The incidence of CP greatly increases as gestational age at birth decreases. This severe developmental disorder is characterized by motor developmental delays and abnormalities of tone, movement, posture and reflexes. The form of CP that is most often associated with prematurity is spastic diplegia, which is marked by the tightening and contracting of muscles in the extremities, more often affecting the lower limbs than the upper  2  limbs (Volpe, 1997b; Bracewell and Marlow, 2002). CP is the most common major impairment consequential of prematurity (Witter and Keith, 1993). Minor motor impairments are even more common in premature children, and are apparent at an early age in three categories of movement: fine motor, static and dynamic balance and ball skills (Bracewell and Marlow, 2002). Approximately 40% of premature infants go on to have problems with motor coordination (Goyen and Lui, 2008). One particular disorder, developmental coordination disorder, is commonly recognized in previously preterm children (Holsti et al., 2002; Davis et al., 2007). Developmental coordination disorder is characterized by delays in achieving developmental milestones, as well as impairments in the development of motor coordination which cause significant problems for the child’s daily functions and academic performance (American Psychiatric Association, 2000). These minor impairments in motor functioning are frequently co-morbid with the cognitive deficits that are prevalent during childhood for these infants. 1.3 Corticospinal Tract Anatomy and Postnatal Development 1.3.1 Anatomy During early post-natal life, the brain undergoes marked structural development including that of white matter pathways such as the corticospinal tract. The CST is one of the major white matter pathways in the brain and is the principle motor system responsible for voluntary motor control. The tract is characterized in each hemisphere by a bundle of axons projecting from the frontal lobe of the cerebral cortex, crossing the midline at the medulla, and running down to the spinal cord to innervate the opposite side of the body. The majority of the cell bodies for these corticospinal neurons are located within the precentral gyrus (primary motor cortex), with the remainder arising from motor association areas or the parietal lobe (Blumenfeld, 2002). The CST fibres originate from these cell bodies and enter the upper part of the cerebral white matter, the corona radiata, descending toward the posterior limb of the internal capsule (PLIC). At the level of the PLIC, the projection fibres, including the CST, become densely packed into a smaller region, in sharp contrast to the less dense fan-like structure of the corona radiata (Nolte, 2002). From the PLIC, the tract continues into the midbrain cerebral peduncles. Specifically, the tract passes through the  3  middle one-third of the most anterior portion of the midbrain, the cerebral peduncles, or even more specifically the crus cerebri (Blumenfeld, 2002). Once the CST reaches the pons, it becomes intermixed with the transverse pontocerebellar fibres and pontine nuclei, and then collects to form the medullary pyramids in the ventral medulla. Towards the rostral medulla, as the transition begins from brain to spinal cord, the CST begins its decussation to the contralateral side of the body. At this point, 85-90% of the tract decussates to the opposite side and descends as the lateral corticospinal tract in the lateral white column of the spinal cord (Blumenfeld, 2002). The remaining 10-15% of the corticospinal fibres continue on the ipsilateral side of the body and descend as the anterior corticospinal tract through the ventral part of the spinal cord. When the corticospinal axons reach their target level in the spinal cord, they synapse onto the lower motor neurons in the anterior horn which innervate the various muscles of the body (Squire et al., 2003). 1.3.2 CST Development in Newborns White matter development proceeds in an organized way, with the myelination of brain regions beginning in the fifth month of gestation and continuing throughout life (Barkovich, 2000). Myelination is the process in which axons are ensheathed in myelin, thereby speeding up the velocity of action potential conduction (Squire et al., 2003). In the central nervous system, myelin is synthesized by oligodendrocytes (OL), a specialized type of glial cell which forms this lipid layer surrounding axons (Squire et al., 2003). Caudal areas of the brain are myelinated first, progressing to rostral regions; dorsal regions are myelinated before more ventral areas (Barkovich, 2000). The CST, however, is myelinated rostrocaudally, beginning with the corona radiata and progressing toward the spinal cord (Sarnat, 2003). This motor tract is one of the earliest white matter pathways to undergo this maturational process, beginning prenatally after approximately 30 weeks of gestation. Unlike the brainstem motor systems, myelination is not fully completed at the time of birth (Martin, 2005). This process of CST maturation commences with the proliferation and differentiation of the precursor cells, OLs, which underlie the production of myelin (Volpe, 2001; Sarnat, 2003). Rapid tract myelination, therefore, continues into the early post-natal period. Evidence of myelination of the CST has been shown histologically by the age of 36 weeks (Counsell et  4  al., 2002). Maturation of the pathway is completed around two years of age and is defined by the acquisition of specialized myelin membrane around axons (Sarnat, 2003). The commencement of CST maturation towards the end of the third trimester suggests that the corticospinal tract is especially underdeveloped at the time of birth in premature newborns. Mechanisms associated with this relative immaturity of the CST at the time of birth and during early life may relate to the increased vulnerability of human perinatal white matter to early injury (Back et al., 2002). Indeed, prematurity has been associated with disturbances in the developmental events that precede myelination, such as disruption of OL lineage progression (Back et al., 2001; Volpe, 2001). Progression of the OL lineage occurs in stages; the late OL progenitors (pre-OLs), the immature OLs and the mature OLs, which progress between midgestation and term birth as the cerebral white matter prepares for myelination (Back et al., 2001). It is the mature OLs, appearing after term-equivalent age, that are responsible for the myelination of axonal processes. Disruption of the OL lineage, therefore, may result in further disruptions in myelination and subsequent impairments, or delays, in CST development. Delays in the development of the corticospinal system have been associated with delayed motor development in childhood (Martin, 2005). Thus, the motor deficits seen in premature infants may relate to a maturational impairment of this white matter pathway. 1.4 Neonatal Brain Abnormalities and Development Early brain abnormalities in premature neonates have been associated with widespread disruptions in white matter development (Huppi et al., 2001; Miller et al., 2002). Focal and multifocal brain injuries such as white matter injury and intraventricular hemorrhage are common in the premature population (Miller et al., 2005). It is also important to note that other brain abnormalities such as ventriculomegaly, the enlargement of the ventricles, often coexist with these focal/multifocal injuries. These brain abnormalities, identified most readily on MRI scans of the brain, are associated with diffuse abnormalities of early motor and cognitive function at 18 and 24 months of life (Miller et al., 2005; Woodward et al., 2006; Counsell et al., 2008). How these focal or multifocal brain injuries relate to these “diffuse” neurodevelopmental deficits is largely unknown. Recent evidence  5  from advanced brain imaging studies suggest that focal injuries, such as WMI on MRI, are associated with more diffuse impairments of white matter development that are not evident on conventional MRI, but may be detected with quantitative neuroimaging such as DTI. Motor deficits, therefore, may result from damage to the CST or alterations in CST development, caused by early brain abnormalities such as WMI or IVH. 1.4.1 White Matter Injury Periventricular leukomalacia (PVL) was once considered to be the major form of brain injury in the premature infant. PVL results in injury to the cerebral white matter and is characterized by a focal component involving necrotic lesions and subsequent cyst formation, as well as a more diffuse component (Volpe, 1997c; Volpe, 2001). More recently the incidence of PVL has dramatically declined and now accounts for less than 5% of cases of white matter injury (Hamrick et al., 2004). This decline in PVL has been linked to improvements in neonatal intensive care such as a reduction in the days of mechanical ventilation used for premature neonates. While PVL is well recognized on ultrasound, with the increasing use of MRI, focal non-cystic WMI has emerged as the predominant pattern of injury in the premature neonate (Volpe, 2005). The prevalence of WMI in the premature population is even higher than had been previously suspected based on ultrasonography results; this type of early injury was exhibited on MRI in over half of premature infants studied (Inder et al., 2003a; Miller et al., 2003; Miller et al., 2005). The diffuse or focal noncystic lesions that define this type of brain injury can be found throughout the cerebral white matter, and are reliably identified on MRI as focal areas of signal abnormalities (Figure 1.1) (Volpe, 2003; Miller et al., 2005; Volpe, 2005). The severity of WMI is determined according to the number and size of the lesions present in the white matter.  6  Figure 1.1 White matter injury on MRI White matter injury (arrows) has a broad spectrum of severity as shown by these sagittal T1-weighted images. It ranges from minimal (grade 1), moderate (grade 2) and severe (grade 3). A) Minimal WMI in a premature neonate delivered at 31.6 weeks gestational age and imaged with MRI at 32.3 weeks postmenstrual age. Note the two areas of abnormal T1 hyperintensity on the periventricular white matter (arrow) typical of minimal WMI B) Moderate WMI in a premature neonate delivered at 28.6 weeks gestational age and imaged with MRI at postmenstrual age 31.4 weeks. Note the multiple areas of abnormal T1 hyperintensity on the periventricular white matter (arrow) typical of moderate WMI C) Severe WMI in a premature neonate delivered at 29.7 weeks gestational age and imaged with MRI at 34.1 weeks postmenstrual age. Note the extensive areas of abnormal T1 hyperintensity as well as areas of T1hypointensity (cysts) characteristic of severe WMI  WMI is characterized by a loss of differentiating oligodendrocytes, astrogliosis (proliferation of the astroglial cells) and impairment in myelination (Haynes et al., 2003). The etiology of these lesions has been recognized as being related to the selective vulnerability of the late oligodendrocyte progenitor cells, the predominant cell type during the high-risk period for WMI in the premature neonate, to hypoxic-ischemic injury (Back et al., 2001; Back et al., 2002). It has been proposed that the vulnerability in premature neonates may be the result of maturation-dependent factors, leading to episodes of hypoxia-ischemia, such as (a) arterial border and end zones within white matter and (b) impaired autoregulation of cerebral blood flow (Volpe, 1997b). It is, however, the downstream mechanisms of hypoxia-ischemia (excitotoxicity and oxidative stress) that are specifically thought to result in the death of the vulnerable pre-OLs and subsequent white matter lesions (Volpe, 2001). More recently, a maturational arrest of pre-OL differentiation has been demonstrated in cerebral white matter lesions of the immature brain due to hypoxia-ischemia (Segovia et al., 7  2008). This resulting disruption of the OL lineage may contribute to a failure in myelination, as well as render the brain susceptible to subsequent episodes of hypoxia-ischemia. Animal models of preterm hypoxia-ischemia have demonstrated that the disruption of the OL lineage results in hypertonia and abnormalities in motor control that are consistent with those characteristic of CP (Derrick et al., 2004). This suggests, therefore, that disruption of the OL lineage by hypoxia-ischemia may influence the onset of myelination, which may result in the developmental impairment of white matter pathways such as the CST, and may lead to CP. Ultimately, this impairment in white matter development may prove to be the link between WMI and deficits in motor functioning. 1.4.2 Intraventricular Hemorrhage Premature neonates have been found to be at an increased risk of other severe brain abnormalities such as intraventricular hemorrhage (Volpe, 2001). IVH is characterized by the rupture of the capillaries located at the germinal matrix, as well as the spread of blood into the lateral ventricles and subsequently throughout the ventricular system (Figure 1.2). The risk of IVH is inversely proportional to gestational age; the greatest risk occurring in infants born at 24-25 weeks gestational age and decreasing thereafter (Kuban et al., 1999). Furthermore, the severity of IVH is greater in lower birth weight babies. The onset of IVH is relatively early, on the first day of life for 50% of affected infants, and by 72 hours 90% of the affected infants will exhibit the lesions characteristic of IVH (Volpe, 2001). The occurrence of IVH is typically at the subependymal germinal matrix, the site containing the glial precursor cells that ultimately give rise to the myelin-forming oligodendrocytes (Volpe, 2001; Inder, 2006). There is some suggestion that a loss of these precursor cells, due to IVH, may be involved in the reduction in gray matter volume observed on high resolution volumetric MRI (Vasileiadis et al., 2004).  8  Figure 1.2 Intraventricular hemorrhage and ventriculomegaly on MRI Representative axial T2-weighted MRI images from premature neonates illustrating the spectrum of intraventricular hemorrhage and ventriculomegaly A. Premature neonate delivered at 29 weeks gestation and scanned at 32 weeks postmenstrual age. In this normal MR image, note the clear delineation of the cerebral cortex, white matter, and basal nuclei (basal ganglia and thalamus). The lateral ventricle size in this neonate is normal. B. Premature neonate delivered at 25 weeks gestation and scanned at 34 weeks postmenstrual age. Note the area of abnormal T2 hypointensity adjacent to germinal matrix at the level of the Foramen of Monro, in a distribution typical of a subependymal hemorrhage (Grade 1 IVH). The lateral ventricle size in this premature neonate is normal. C. Premature neonate delivered at 28 weeks gestation and scanned at 30 weeks postmenstrual age. Note the areas of abnormal T2 hypointensity in the lateral ventricles bilaterally, indicated intraventricular hemorrhage (Grade 2 IVH). Note the borderline enlargement of the lateral ventricles bilaterally. D. Premature neonate delivered at 28 weeks gestation and scanned at 32 weeks postmenstrual age. Note the areas of abnormal T2 hypointensity in the left lateral ventricle originating from the subependymal germinal matrix (Grade 2 IVH). Note the mild enlargement of the lateral ventricle on this side.  9  1.4.3 Ventriculomegaly Ventriculomegaly is a brain abnormality that can be characterized by a loss of tissue or increased obstruction of cerebrospinal fluid flow, as can occur with IVH (Figure 1.2). It is recognized on MRI as the enlargement of the lateral ventricles to greater than 8mm in width (Miller et al., 2005). The pathophysiology of VM remains poorly defined, however, the severity of VM is strongly associated with the severity of the cognitive and motor deficits seen when the infants reach childhood (Ment et al., 1999; Miller et al., 2005). 1.4.4 Impaired Brain Development Injuries of the cerebral white matter, such as WMI and IVH, lead to impairments in subsequent brain development. The primary impact of these abnormalities is a loss of brain tissue (Volpe, 1997c). However, as these abnormalities occur prior to or during the period of rapid brain development from preterm birth to term-equivalent age, they result in further abnormalities and developmental changes in brain structure. These changes are apparent on MRI and can be manifested in many ways. Structural changes occurring in premature infants may include impaired gyral development, enlargement of the subarachnoid spaces, increased ventricular size and a decrease in basal ganglia volumes (Volpe, 1997a; Inder et al., 2003b; Srinivasan et al., 2007). Furthermore, cerebral cortical gray matter, as well as myelinated white matter volumes, have been found to be reduced at term age in premature infants with previous moderate to severe WMI in comparison with normal infants (Inder et al., 1999; Inder et al., 2005). These structural changes in brain development in children born prematurely have also been associated with an adverse neurodevelopmental outcome (Peterson et al., 2000). 1.4.5 Neonatal Illness and Brain Abnormalities Altered brain development and impairments in motor and cognitive functioning may also result from neonatal illnesses that are common amongst premature neonates. Outcome studies have demonstrated significant motor and cognitive impairments in premature infants with postnatal infection and CLD (Singer et al., 1997; Stoll et al., 2004; Miller et al., 2005). This suggests that brain development has been altered by these illnesses. The mechanisms by which this occurs, however, are still unknown. Treatments for these illnesses have also been shown to cause brain abnormalities in term-born infants. For example, infants treated with  10  dexamethasone for CLD demonstrated reduced cerebral cortical gray matter volume (Murphy et al., 2001). Furthermore, suggestive of patent ductus arteriosis as a risk factor for WMI, prolonged indomethacin treatment for PDA was associated with a reduction in the occurrence of WMI (Miller et al., 2006). Brain abnormalities are also present in premature infants with postnatal infections. Previous research has demonstrated an increased risk of white matter abnormalities, including WMI, in infants exposed to postnatal infections (Graham et al., 2004; Shah et al., 2008). These postnatal infections may also render the white matter susceptible to acquiring more focal or multifocal white matter lesions (Glass et al., 2008). The mechanisms underlying the relationship between postnatal infections and white matter abnormalities remain to be elucidated. In other studies, postnatal infections in premature neonates, such as sepsis or necrotizing enterocolitis, have been associated with an increased risk of later neurodevelopmental impairments, including cerebral palsy (Murphy et al., 1997; Stoll et al., 2004; Shah et al., 2008). Shah et al. (2008) have proposed that these neurodevelopmental consequences are mediated by white matter abnormalities in these infants exposed to infection, suggesting impairment in the white matter pathways relaying motor and cognitive functions. Conventional MRI allows for the ability to image changes in brain development due to early brain abnormalities or neonatal illnesses at a macroscopic level. Microstructural changes, however, are not apparent on conventional imaging. Therefore, in order to really understand how brain injury and illness affect brain development at a microstructural level, advanced magnetic resonance (MR) techniques, such as diffusion tensor imaging (DTI) and diffusion tensor tractography, are required. 1.5 Magnetic Resonance Techniques 1.5.1 Diffusion Tensor Imaging Advances in magnetic resonance imaging, such as diffusion tensor imaging, provide an unprecedented window into the developing brain. DTI is a magnetic resonance technique that enables the measurement of the diffusion of water molecules within brain tissues, thereby producing images that reflect anatomical and microstructural connectivity. Two 11  types of information conveyed by DTI include the extent of diffusion anisotropy and the orientation of the anisotropy (Mori and van Zijl, 2002). The basis of DTI relies on the principle that water diffusion in the nervous system is highly anisotropic. In this way, diffusion within a voxel of a MR image can be described by the shape of an ellipsoid, diffusing preferentially in the direction of one axis (the primary eigenvalue) (Beaulieu, 2002). This is in contrast to isotropic diffusion where diffusion occurs equally, or spherically, in all directions. Changes in water diffusion, as measured by DTI, are caused by the maturation of microstructural components within the axon, as well as in extracellular space (Beaulieu, 2002; Mori and van Zijl, 2002). Within the axon, the motion of water molecules is restricted by the longitudinally-oriented neurofilament bundles and microtubules, the axon membrane, and eventually the myelin sheath surrounding the axon. Extracellularly, within the white matter, diffusion is hindered by the densely packed axons, as well as glia and other cells inhabiting the extracellular space. Water diffusion becomes restricted perpendicularly to these microstructural elements. DTI, therefore, is especially useful in examining the development of cerebral white matter by measuring the alterations in water diffusion caused by these processes (Neil et al., 1998; Partridge et al., 2004). Diffusion parameters obtained by DTI analysis describe the amount and anisotropy of water diffusion in each voxel contained in the cerebral white matter structures on these DTI images. Parameters of water diffusion and the developing brain DTI yields a diffusion tensor which describes a diffusion ellipsoid in space. The size, shape and orientation of the ellipsoid are characterized by the diffusion constants (the eigenvalues λ1, λ2, λ3), which represent the three principal axes of the diffusion tensor and describe the magnitude of water diffusion (Figure 1.3) (Partridge et al., 2004). The primary eigenvalue λ1 reflects axial diffusion, such as that parallel to organized white matter tracts. The other two eigenvalues, λ2 and λ3, reflect radial diffusion, perpendicular to the white matter tracts.  12  λ2  λ1 λ3 Isotropic Diffusion  λ2 λ1  λ3 Anisotropic Diffusion  Figure 1.3 DTI diffusion tensor ellipsoid The eigenvalues (λ1, λ2, λ3) describe the size, shape and orientation of the ellipsoid. λ1 represents diffusion in the direction parallel to the fibre bundles (axial diffusion); λ2 and λ3 represent diffusion perpendicular to the white matter tracts (radial diffusivity). This schematic demonstrates the expected changes in diffusion in a white matter voxel with a decrease in average diffusivity (Dav) and an increase in directionality of water diffusion (increased anisotropic diffusion; FA) with increasing age.  Average diffusivity (Dav) reflects the mean of the eigenvalues and characterizes the overall amount of water diffusion in a voxel (Partridge et al., 2004; Berman et al., 2005). Dav is calculated using the formula: Equation 1. Mathematical Definition of Average Diffusivity  Fractional anisotropy (FA) reflects the variance of the eigenvalues (higher FA with increasing variance) and is a measure of the degree of directionality of diffusion (Partridge et 13  al., 2004; Berman et al., 2005). FA is expressed as a scaled number between 0 (highly isotropic) and 1 (highly anisotropic) and is calculated by the formula: Equation 2. Mathematical Definition of Fractional Anisotropy  Another index that is less commonly used to describe the pattern of water diffusion in the brain is relative anisotropy (RA) (Partridge et al., 2004). RA reflects the ratio of anisotropic to isotropic diffusion, and is defined as the quotient of the standard deviation of the eigenvalues of the diffusion tensor and Dav. FA is more often used to measure anisotropy in neonatal brain studies because of its increased sensitivity to regions of low anisotropy, as in neonates, in comparison with RA. Furthermore, RA fails to capture the underlying microstructural factors resulting in the observed changes in anisotropy (Suzuki et al., 2003). FA, therefore, allows for a more detailed characterization of white matter tracts. In a relatively immature brain, such as that of a premature infant after birth, there is a large extracellular free water content which decreases with age as the brain structures begin to develop (Figure 1.4) (Dobbing and Sands, 1973). Early on, the movement of water molecules is not as hindered by microstructural components, which are still underdeveloped. Diffusion, therefore, is more isotropic at a young age and can be characterized by high Dav values and low FA values (Miller et al., 2002; Partridge et al., 2004; Berman et al., 2005). In a more mature brain, such as at term equivalent age (40 weeks), microstructural maturational processes hinder the free diffusion of water molecules (Beaulieu, 2002). Barriers to free water diffusion include the development of microstructural components such as microtubules and neurofilaments, as well as the axonal membrane and the maturation of the OL cells (Beaulieu, 2002; Drobyshevsky et al., 2005). As the brain matures, therefore, axial and radial diffusion decrease due to the restriction of free water diffusion from microstructural development (Suzuki et al., 2003; Berman et al., 2005). Radial diffusion, however, decreases at a higher rate than axial diffusion thereby resulting in an increase in FA and decrease in Dav with increasing age. 14  Figure 1.4 Brain development from early in premature life to term-equivalent age Axial T2 weighted and color coded fractional anisotropy maps in a premature neonate delivered at 28 weeks gestation and scanned at 30 weeks postmenstrual age and again at 39 weeks. On the T2 weighted images note the dramatic increase in gyration of the cerebral cortex and early myelination in the posterior limb of the internal capsule. The color coded fractional anisotropy maps represent the “directionality” of water diffusion, with brighter areas indicating more directionality (higher FA). Water diffusion in the right-left plane is coloured red, superior-inferior in blue, and anterior –posterior in green. The corticospinal tracts (blue region in the posterior limb of the internal capsule) are more clearly delineated with higher FA at term-equivalent age.  15  Findings on abnormal development using DTI Most premature neonates do not have the dramatic white matter abnormalities that can be detected using conventional MRI (Inder et al., 2003b). DTI is therefore needed to examine more subtle changes in brain development. Using DTI, studies have also looked at how early brain injury affects subsequent white matter development. Miller et al. (2002) have demonstrated that early brain injury results in widespread abnormalities in brain development that are not apparent on conventional MRI. Using an advanced DTI method, diffusion tensor tractography, maturational FA changes from the CST were shown to be reduced in term-age congenital heart disease infants with brain injury (Partridge et al., 2006). This is suggestive of microstructural impairment, but needs further investigation. Through the in vivo quantification of water diffusion, therefore, DTI has greatly contributed to our ability to understand the trajectory of white matter maturation, and how it is affected by brain injury, during the period of rapid brain development that occurs in premature neonates from birth to term age. Methods of DTI analysis Recent advances in MRI hardware and software have allowed improved DTI acquisition and analysis. For example, DTI may be optimized with improved image acquisition, such as increased MR field strength, an increased number of diffusion encoding directions and the use of a broader range of b values. Furthermore, the analysis of DTI images has been optimized with the advent of new software techniques and analysis tools, such as DTT. These new techniques are used to measure the diffusion parameters of specific white matter tracts obtained with DTI. Earlier DTI studies on white matter development utilized the manual region of interest (ROI) technique to obtain measures of diffusion from white matter regions including the frontal, posterior and occipital white matter (Huppi et al., 2001; Miller et al., 2002). In this method, ROIs of various shapes and sizes are systematically placed on a DTI image according to predefined anatomical landmarks throughout the cerebral white matter. This measures the diffusion parameters within a voxel in the selected anatomical locations at a particular level of the brain. A similar method is tract-based ROI measures, which has been used to measure diffusion parameters from a specific tract, such as the CST, but at only one level of the brain (Partridge et al., 2004). These tract-based DTI techniques have only been validated in premature neonates at term-equivalent age and had 16  limited sample sizes. Moreover, the problem with these methods is that they do not measure diffusion over the entire tract; diffusion is measured at distinct locations (Partridge et al., 2005). This is problematic because regions along a tract may differ in degree of anisotropy. This is the case at the PLIC where the tightly bound bundles of fibres show greatly increased anisotropy in comparison with other less compact regions of the CST (Partridge et al., 2006). Furthermore, ROI-based techniques have been shown to be less reliable in comparison with the newer DTI techniques, and are less sensitive to the effects of brain abnormalities (Partridge et al., 2005; Partridge et al., 2006). Newer techniques, therefore, allow for a more detailed analysis of white matter tract development, especially in premature infants with brain abnormalities. One relatively newer DTI technique is tract-based spatial statistics (TBSS), a method designed to improve the sensitivity, objectivity and ability to compare DTI parameters across groups (Smith et al., 2006). This is a relatively user independent method which enables the estimation of localized changes in FA by comparing images to a standardized template. This allows for group comparisons without the need for a user to manually place or trace ROIs. Although it has been previously used to investigate differences in brain microstructure in premature infants at term, this technique is not yet sufficiently developed to evaluate white matter tract maturation during the period from premature birth to term age, due to important changes in brain size and shape across this age range (Anjari et al., 2007). DTT overcomes some of the limitations of the ROI and TBSS techniques and allows for the measurement of diffusion changes across the developmental trajectory from premature life to term-equivalent age. 1.5.2 Diffusion Tensor Tractography DTI diffusion parameters can also be used to reconstruct 3D images, allowing the visualization of fibre tracts, using diffusion tensor tractography (Figure 1.5). DTT is a more sophisticated way to process and analyze the DTI data to measure diffusion parameters from specific white matter tracts (Berman et al., 2005; Partridge et al., 2005). This technique can be used as an indirect measurement of microstructural development and white matter tract maturation.  17  Figure 1.5 Tractography of the corticospinal tract using diffusion tensor tractography Three-dimensional reconstruction of the right corticospinal tract at 29 weeks postmenstrual age, passing through the posterior limb of the internal capsule. Note that the tract was seeded in the PLIC with filtering through the precentral gyrus and cerebral peduncles (See Figure 1.6).  There are several different approaches to the reconstruction of 3D fibre tracts. One such approach used by some DTT software packages such as DtiStudio (John Hopkins University, Baltimore, MD) is the deterministic fiber assignment by continuous tracking (FACT) method (Mori et al., 1999; Jiang et al., 2006). This is a line propagation technique where 3D virtual “fibres” are reconstructed from 3D vector fields originating from a seed point (ROI). This is based on the assumption that the primary eigenvalue (λ1) aligns with the orientation of the predominant fibre within a MRI voxel (Mori and van Zijl, 2002). Starting from the centre of the seed voxel, the tracking proceeds in the direction of the vector (the direction of λ1) and enters into the neighbouring voxel (Mori et al., 1999). In the neighbouring voxel, a new orientation of the fibre is calculated according to the direction of the vector in that pixel, and continues so forth. Limits are also put in place to restrict the propagation of the line to reduce noise. Such limits include termination of propagation if the extent of anisotropy meets a predetermined threshold, or if there is a sharp angle during the  18  transition of the propagated line from one voxel to the next (Mori and van Zijl, 2002). These are the basic principles behind the reconstruction of virtual fibres using the FACT method. Specific white matter tracts are isolated by placing ROIs at locations on various levels of the brain through which the tract is known to pass. To isolate the corticospinal tract, for example, ROIs can be placed at the level of the PLIC, at the precentral gyrus and at the cerebral peduncle (Figure 1.6). Once the pathway has been isolated, diffusion parameters for the entire tract can be obtained. This added advantage of DTT, the averaging of diffusion parameters over the entire tract, allows for more precise characterization of the selected pathway by taking into consideration the variation of diffusion at its different levels. This is in contrast to traditional DTI techniques which characterize white matter pathways by obtaining diffusion parameters at one level of the tract.  Figure 1.6 Placement of regions of interest to delineate the corticospinal tract Regions of interest (ROI; in white) are placed on the axial colour map to isolate the corticospinal tract. A seeding ROI is placed at the level of the posterior limb of the internal capsule (centre). The tract is further defined by placing a limiting ROI above at the precentral gyrus (right) and below at the cerebral peduncle (left).  Another computationally intensive DTT approach, probabilistic tractography, is used to estimate global connectivity and characterize white matter pathways (Behrens et al., 2003). This technique is optimized to examine regions with low FA as well as those with 19  crossing fibres, which are limitations of deterministic tractography. The utilization of probabilistic tractography has been demonstrated in ex-premature children to map cortical connections to the thalamus (Counsell et al., 2007). The findings resulting from this new technique were found to be consistent when compared with deterministic tractography in the examination of pyramidal tract maturation (Berman et al., 2005). As the advantages of probabilistic tractography become more apparent at higher-field strengths, and with tracts of lower mean FA than the CST, this technique will likely be more widely applied with the greater use of 3 Tesla MRI scanning and for investigating less mature white matter tracts. The advent of DTT has been a valuable tool for the characterization of patterns of brain development in the premature neonate. Maturational changes in white matter regions and tracts in premature neonates with and without brain injury was previously studied using manual ROI measurements (Miller et al., 2002; Partridge et al., 2004). These methods were unable to characterize the entire tract, so were not sensitive to changes in white matter development from premature to term age. More recently, DTT has been validated and used to measure CST development in healthy preterm and term neonates (Berman et al., 2005; Partridge et al., 2005). Furthermore, this technique has been used to show that early brain injuries such as stroke impair CST development in term infants, even when this tract appears normal on conventional MRI (Partridge et al., 2006). Limitations of these studies, however, include limited sample size and that not all infants were serially imaged. The success of this technique in characterizing normal brain development in premature neonates warrants further studies to determine how brain injury affects its development. DTT, therefore, will be a key player in elucidating the consequences of early brain abnormalities such as WMI, IVH and VM on CST development in the premature neonate. 1.6 Conclusions and Objectives Prematurity results in a multitude of developmental problems including cognitive and motor deficits. Early neonatal brain abnormalities, including white matter injury, intraventricular hemorrhage and ventriculomegaly as well as certain neonatal illnesses, have been shown to be associated with these neurodevelopmental deficits. How these brain abnormalities give rise to such widespread neurodevelopmental deficits, however, is largely  20  unknown. Correlations of motor impairment and microstructural changes in the corticospinal tract have previously been demonstrated in children with congenital hemiplegia (Glenn et al., 2007). Motor impairments may therefore arise from abnormal maturation of the corticospinal tract, resulting from early brain abnormalities or illness. With the advent of DTI and DTT we are now in a position to address how these possible mechanisms result in the motor deficits seen in the premature population. The objective of this thesis is to examine how early brain abnormalities affect corticospinal tract maturation using diffusion tensor tractography. The primary hypothesis we will address is that early brain abnormalities impair corticospinal tract development in premature neonate, as indicated by lower FA and higher Dav values. We will also explore the effect of neonatal illness on corticospinal tract development to test the hypothesis that early neonatal illnesses, often risk factors of early brain injury, also impair corticospinal tract development.  21  1.7 References American Psychiatric Association (2000) Diagnostic and Statistical Manual - Text Revision, 4th Edition. Washington, DC: American Psychiatric Association. Anjari M, Srinivasan L, Allsop JM, Hajnal JV, Rutherford MA, Edwards AD, Counsell SJ (2007) Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants. Neuroimage 35:1021-1027. Astbury J, Orgill A, Bajuk B (1987) Relationship between two-year behaviour and neurodevelopmental outcome at five years of very low-birthweight survivors. Dev Med Child Neurol 29:370-379. Back SA, Luo NL, Borenstein NS, Levine JM, Volpe JJ, Kinney HC (2001) Late oligodendrocyte progenitors coincide with the developmental window of vulnerability for human perinatal white matter injury. J Neurosci 21:1302-1312. Back SA, Han BH, Luo NL, Chricton CA, Xanthoudakis S, Tam J, Arvin KL, Holtzman DM (2002) Selective vulnerability of late oligodendrocyte progenitors to hypoxiaischemia. J Neurosci 22:455-463. Barkovich AJ (2000) Pediatric Neuroimaging, 3rd Edition. Philadelphia, PA: Lippincott Williams & Wilkins. BC Vital Statistics Agency BMoH (2006) Selected Vital Statistics and Health Status Indicators Annual Report. Beaulieu C (2002) The basis of anisotropic water diffusion in the nervous system - a technical review. NMR Biomed 15:435-455. Behrens TE, Woolrich MW, Jenkinson M, Johansen-Berg H, Nunes RG, Clare S, Matthews PM, Brady JM, Smith SM (2003) Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med 50:1077-1088. Berman JI, Mukherjee P, Partridge SC, Miller SP, Ferriero DM, Barkovich AJ, Vigneron DB, Henry RG (2005) Quantitative diffusion tensor MRI fiber tractography of sensorimotor white matter development in premature infants. Neuroimage 27:862871. Blumenfeld H (2002) Neuroanatomy Through Clinical Cases. Sunderland, MA: Sinauer Associates, Inc. Bracewell M, Marlow N (2002) Patterns of motor disability in very preterm children. Ment Retard Dev Disabil Res Rev 8:241-248. Counsell SJ, Maalouf EF, Fletcher AM, Duggan P, Battin M, Lewis HJ, Herlihy AH, Edwards AD, Bydder GM, Rutherford MA (2002) MR imaging assessment of myelination in the very preterm brain. AJNR Am J Neuroradiol 23:872-881. Counsell SJ, Edwards AD, Chew AT, Anjari M, Dyet LE, Srinivasan L, Boardman JP, Allsop JM, Hajnal JV, Rutherford MA, Cowan FM (2008) Specific relations between neurodevelopmental abilities and white matter microstructure in children born preterm. Brain 131:3201-3208. 22  Counsell SJ, Dyet LE, Larkman DJ, Nunes RG, Boardman JP, Allsop JM, Fitzpatrick J, Srinivasan L, Cowan FM, Hajnal JV, Rutherford MA, Edwards AD (2007) Thalamocortical connectivity in children born preterm mapped using probabilistic magnetic resonance tractography. Neuroimage 34:896-904. Davis NM, Ford GW, Anderson PJ, Doyle LW (2007) Developmental coordination disorder at 8 years of age in a regional cohort of extremely-low-birthweight or very preterm infants. Dev Med Child Neurol 49:325-330. Derrick M, Luo NL, Bregman JC, Jilling T, Ji X, Fisher K, Gladson CL, Beardsley DJ, Murdoch G, Back SA, Tan S (2004) Preterm fetal hypoxia-ischemia causes hypertonia and motor deficits in the neonatal rabbit: a model for human cerebral palsy? J Neurosci 24:24-34. Dobbing J, Sands J (1973) Quantitative growth and development of human brain. Arch Dis Child 48:757-767. Drobyshevsky A, Song SK, Gamkrelidze G, Wyrwicz AM, Derrick M, Meng F, Li L, Ji X, Trommer B, Beardsley DJ, Luo NL, Back SA, Tan S (2005) Developmental changes in diffusion anisotropy coincide with immature oligodendrocyte progression and maturation of compound action potential. J Neurosci 25:5988-5997. Glass HC, Bonifacio SL, Chau V, Glidden D, Poskitt K, Barkovich AJ, Ferriero DM, Miller SP (2008) Recurrent postnatal infections are associated with progressive white matter injury in premature infants. Pediatrics 122:299-305. Glenn OA, Ludeman NA, Berman JI, Wu YW, Lu Y, Bartha AI, Vigneron DB, Chung SW, Ferriero DM, Barkovich AJ, Henry RG (2007) Diffusion tensor MR imaging tractography of the pyramidal tracts correlates with clinical motor function in children with congenital hemiparesis. AJNR Am J Neuroradiol 28:1796-1802. Goyen TA, Lui K (2008) Developmental coordination disorder in 'apparently normal' school children born extremely preterm. Arch Dis Child. Graham EM, Holcroft CJ, Rai KK, Donohue PK, Allen MC (2004) Neonatal cerebral white matter injury in preterm infants is associated with culture positive infections and only rarely with metabolic acidosis. Am J Obstet Gynecol 191:1305-1310. Hamrick SE, Miller SP, Leonard C, Glidden DV, Goldstein R, Ramaswamy V, Piecuch R, Ferriero DM (2004) Trends in severe brain injury and neurodevelopmental outcome in premature newborn infants: the role of cystic periventricular leukomalacia. J Pediatr 145:593-599. Harvey JM, O'Callaghan MJ, Mohay H (1999) Executive function of children with extremely low birthweight: a case control study. Dev Med Child Neurol 41:292-297. Haynes RL, Folkerth RD, Keefe RJ, Sung I, Swzeda LI, Rosenberg PA, Volpe JJ, Kinney HC (2003) Nitrosative and oxidative injury to premyelinating oligodendrocytes in periventricular leukomalacia. J Neuropathol Exp Neurol 62:441-450. Holsti L, Grunau RV, Whitfield MF (2002) Developmental coordination disorder in extremely low birth weight children at nine years. J Dev Behav Pediatr 23:9-15.  23  Huppi PS, Murphy B, Maier SE, Zientara GP, Inder TE, Barnes PD, Kikinis R, Jolesz FA, Volpe JJ (2001) Microstructural brain development after perinatal cerebral white matter injury assessed by diffusion tensor magnetic resonance imaging. Pediatrics 107:455-460. Inder TE (2006) Neurodevelopmental impact of low-grade intraventricular hemorrhage in very preterm infants. J Pediatr 149:152-154. Inder TE, Wells SJ, Mogridge NB, Spencer C, Volpe JJ (2003a) Defining the nature of the cerebral abnormalities in the premature infant: a qualitative magnetic resonance imaging study. J Pediatr 143:171-179. Inder TE, Anderson NJ, Spencer C, Wells S, Volpe JJ (2003b) White matter injury in the premature infant: a comparison between serial cranial sonographic and MR findings at term. AJNR Am J Neuroradiol 24:805-809. Inder TE, Warfield SK, Wang H, Huppi PS, Volpe JJ (2005) Abnormal cerebral structure is present at term in premature infants. Pediatrics 115:286-294. Inder TE, Huppi PS, Warfield S, Kikinis R, Zientara GP, Barnes PD, Jolesz F, Volpe JJ (1999) Periventricular white matter injury in the premature infant is followed by reduced cerebral cortical gray matter volume at term. Ann Neurol 46:755-760. Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S (2006) DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Programs Biomed 81:106-116. Kuban K, Sanocka U, Leviton A, Allred EN, Pagano M, Dammann O, Share J, Rosenfeld D, Abiri M, DiSalvo D, Doubilet P, Kairam R, Kazam E, Kirpekar M, Schonfeld S (1999) White matter disorders of prematurity: association with intraventricular hemorrhage and ventriculomegaly. The Developmental Epidemiology Network. J Pediatr 134:539-546. Limperopoulos C, Bassan H, Sullivan NR, Soul JS, Robertson RL, Jr., Moore M, Ringer SA, Volpe JJ, du Plessis AJ (2008) Positive screening for autism in ex-preterm infants: prevalence and risk factors. Pediatrics 121:758-765. Luciana M, Lindeke L, Georgieff M, Mills M, Nelson CA (1999) Neurobehavioral evidence for working-memory deficits in school-aged children with histories of prematurity. Dev Med Child Neurol 41:521-533. Marlow N, Wolke D, Bracewell MA, Samara M (2005) Neurologic and developmental disability at six years of age after extremely preterm birth. N Engl J Med 352:9-19. Martin JH (2005) The corticospinal system: from development to motor control. Neuroscientist 11:161-173. Ment LR, Vohr B, Allan W, Westerveld M, Katz KH, Schneider KC, Makuch RW (1999) The etiology and outcome of cerebral ventriculomegaly at term in very low birth weight preterm infants. Pediatrics 104:243-248. Miller SP, Mayer EE, Clyman RI, Glidden DV, Hamrick SE, Barkovich AJ (2006) Prolonged indomethacin exposure is associated with decreased white matter injury detected with  24  magnetic resonance imaging in premature newborns at 24 to 28 weeks' gestation at birth. Pediatrics 117:1626-1631. Miller SP, Cozzio CC, Goldstein RB, Ferriero DM, Partridge JC, Vigneron DB, Barkovich AJ (2003) Comparing the diagnosis of white matter injury in premature newborns with serial MR imaging and transfontanel ultrasonography findings. AJNR Am J Neuroradiol 24:1661-1669. Miller SP, Vigneron DB, Henry RG, Bohland MA, Ceppi-Cozzio C, Hoffman C, Newton N, Partridge JC, Ferriero DM, Barkovich AJ (2002) Serial quantitative diffusion tensor MRI of the premature brain: development in newborns with and without injury. J Magn Reson Imaging 16:621-632. Miller SP, Ferriero DM, Leonard C, Piecuch R, Glidden DV, Partridge JC, Perez M, Mukherjee P, Vigneron DB, Barkovich AJ (2005) Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr 147:609-616. Mori S, van Zijl PC (2002) Fiber tracking: principles and strategies - a technical review. NMR Biomed 15:468-480. Mori S, Crain BJ, Chacko VP, van Zijl PC (1999) Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol 45:265-269. Murphy BP, Inder TE, Huppi PS, Warfield S, Zientara GP, Kikinis R, Jolesz FA, Volpe JJ (2001) Impaired cerebral cortical gray matter growth after treatment with dexamethasone for neonatal chronic lung disease. Pediatrics 107:217-221. Murphy DJ, Hope PL, Johnson A (1997) Neonatal risk factors for cerebral palsy in very preterm babies: case-control study. Bmj 314:404-408. Neil JJ, Shiran SI, McKinstry RC, Schefft GL, Snyder AZ, Almli CR, Akbudak E, Aronovitz JA, Miller JP, Lee BC, Conturo TE (1998) Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. Radiology 209:57-66. Nolte J (2002) The Human Brain. An Introduction to its Functional Anatomy, 5th Edition. St. Louis: Mosby. Partridge SC, Mukherjee P, Berman JI, Henry RG, Miller SP, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2005) Tractography-based quantitation of diffusion tensor imaging parameters in white matter tracts of preterm newborns. J Magn Reson Imaging 22:467-474. Partridge SC, Vigneron DB, Charlton NN, Berman JI, Henry RG, Mukherjee P, McQuillen PS, Karl TR, Barkovich AJ, Miller SP (2006) Pyramidal tract maturation after brain injury in newborns with heart disease. Ann Neurol 59:640-651. Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2004) Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. Neuroimage 22:1302-1314.  25  Peterson BS, Vohr B, Staib LH, Cannistraci CJ, Dolberg A, Schneider KC, Katz KH, Westerveld M, Sparrow S, Anderson AW, Duncan CC, Makuch RW, Gore JC, Ment LR (2000) Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. Jama 284:1939-1947. Piecuch RE, Leonard CH, Cooper BA, Sehring SA (1997) Outcome of extremely low birth weight infants (500 to 999 grams) over a 12-year period. Pediatrics 100:633-639. Richardson DK, Gray JE, Gortmaker SL, Goldmann DA, Pursley DM, McCormick MC (1998) Declining severity adjusted mortality: evidence of improving neonatal intensive care. Pediatrics 102:893-899. Sarnat HB (2003) Functions of the corticospinal and corticobulbar tracts in the human newborn. Journal of Pediatric Neurology 1:3-8. Segovia KN, McClure M, Moravec M, Luo NL, Wan Y, Gong X, Riddle A, Craig A, Struve J, Sherman LS, Back SA (2008) Arrested oligodendrocyte lineage maturation in chronic perinatal white matter injury. Ann Neurol 63:520-530. Shah DK, Doyle LW, Anderson PJ, Bear M, Daley AJ, Hunt RW, Inder TE (2008) Adverse neurodevelopment in preterm infants with postnatal sepsis or necrotizing enterocolitis is mediated by white matter abnormalities on magnetic resonance imaging at term. J Pediatr 153:170-175, 175 e171. Singer L, Yamashita T, Lilien L, Collin M, Baley J (1997) A longitudinal study of developmental outcome of infants with bronchopulmonary dysplasia and very low birth weight. Pediatrics 100:987-993. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TE (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:14871505. Squire LR, Bloom FE, McConnell SK, Roberts JL, Spitzer NC, Zigmond MJ (2003) Fundamental Neuroscience, 2nd Edition. San Diego, CA: Academic Press. Srinivasan L, Dutta R, Counsell SJ, Allsop JM, Boardman JP, Rutherford MA, Edwards AD (2007) Quantification of deep gray matter in preterm infants at term-equivalent age using manual volumetry of 3-tesla magnetic resonance images. Pediatrics 119:759765. Stoll BJ, Hansen NI, Adams-Chapman I, Fanaroff AA, Hintz SR, Vohr B, Higgins RD (2004) Neurodevelopmental and growth impairment among extremely low-birthweight infants with neonatal infection. Jama 292:2357-2365. Suzuki Y, Matsuzawa H, Kwee IL, Nakada T (2003) Absolute eigenvalue diffusion tensor analysis for human brain maturation. NMR Biomed 16:257-260. van Baar AL, van Wassenaer AG, Briet JM, Dekker FW, Hok JH (2005) Very Preterm Birth is Associated with Disabilities in Multiple Developmental Domains. Journal of Pediatric Psychology 30:247-255.  26  Vasileiadis GT, Gelman N, Han VK, Williams LA, Mann R, Bureau Y, Thompson RT (2004) Uncomplicated intraventricular hemorrhage is followed by reduced cortical volume at near-term age. Pediatrics 114:e367-372. Vohr BR, Allan WC, Westerveld M, Schneider KC, Katz KH, Makuch RW, Ment LR (2003) School-Age Outcomes of Very Low Birth Weight Infants in the Indomethacin Intraventricular Hemorrhage Prevention Trial Pediatrics 111:e340-e346. Vohr BR, Wright LL, Dusick AM, Mele L, Verter J, Steichen JJ, Simon NP, Wilson DC, Broyles S, Bauer CR, Delaney-Black V, Yolton KA, Fleisher BE, Papile LA, Kaplan MD (2000) Neurodevelopmental and functional outcomes of extremely low birth weight infants in the National Institute of Child Health and Human Development Neonatal Research Network, 1993-1994. Pediatrics 105:1216-1226. Volpe J (2001) Neurology of the Newborn, 4th Edition. Philadelphia: W.B. Saunders. Volpe JJ (1997a) Brain injury in the premature infant. Neuropathology, clinical aspects. MRDD Res Rev 3:3-12. Volpe JJ (1997b) Brain injury in the premature infant--from pathogenesis to prevention. Brain Dev 19:519-534. Volpe JJ (1997c) Brain injury in the premature infant. Neuropathology, clinical aspects, pathogenesis, and prevention. Clin Perinatol 24:567-587. Volpe JJ (2003) Cerebral white matter injury of the premature infant-more common than you think. Pediatrics 112:176-180. Volpe JJ (2005) Encephalopathy of prematurity includes neuronal abnormalities. Pediatrics 116:221-225. Ward RM, Beachy JC (2003) Neonatal complications following preterm birth. Bjog 110 Suppl 20:8-16. Witter FR, Keith LG (1993) Textbook of Prematurity: Antecedents, Treatments, and Outcome. Boston: Little, Brown, and Co. Woodward LJ, Anderson PJ, Austin NC, Howard K, Inder TE (2006) Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. N Engl J Med 355:685-694.  27  CHAPTER II: TRACTOGRAPHY-BASED QUANTITATION OF CORTICOSPINAL TRACT DEVELOPMENT IN PREMATURE NEONATES1 2.1 Introduction The incidence of neurodevelopmental deficits in children born very premature remains significant: 5-10% of surviving infants have major motor deficits, while 40% have problems with motor co-ordination (Goyen and Lui, 2008), and 50% exhibit cognitive deficits (Volpe, 2001) that are frequently co-morbid with motor and academic difficulties (Holsti et al., 2002; Marlow et al., 2007). Early brain abnormalities such as white matter injury (WMI), intraventricular hemorrhage (IVH) and ventriculomegaly recognized on magnetic resonance imaging (MRI) are associated with impairments in early motor and cognitive function (Miller et al., 2005). How these brain injuries impact the motor pathways in the developing brain is largely unknown. Diffusion tensor imaging (DTI) enables the in vivo visualization and quantification of the microstructural development of these white matter pathways by measuring the overall extent (average diffusivity; Dav) and directionality (fractional anisotropy; FA) of water diffusion (Huppi et al., 1998; Neil et al., 1998; Partridge et al., 2004). With increasing age in the developing brain, white matter Dav decreases and FA increases. Previous DTI studies suggest that early brain injury impairs white matter development, even in brain regions that are normal on conventional MRI (Huppi et al., 2001; Miller et al., 2002). However, the region of interest (ROI) based approach used in these studies may not be optimally sensitive to changes in a specific white matter functional pathway. Diffusion tensor tractography (DTT) is a more sophisticated DTI technique for the 3D reconstruction of specific white matter tracts (Mori et al., 1999; Mori and van Zijl, 2002; Jiang et al., 2006). DTT can be used to reconstruct the corticospinal tract (CST), the primary pathway for voluntary motor control. DTT has been used to quantify CST tract-specific diffusion measurements in premature neonates with normal MRIs (Berman et al., 2005). More recently, DTT has been used to show that focal brain injuries (e.g. stroke) in term neonates with heart disease are associated  1  A version of this chapter will be submitted for publication. Adams E, Chau V, Poskitt KJ, Grunau RE, Synnes A and Miller SP. Tractography-based quantitation of corticospinal tract development in premature neonates.  28  with impaired CST development (Partridge et al., 2006). The impact of early brain injury in the premature neonate on DTT measures of CST development has not yet been addressed. The objective of this study is to evaluate the impact of early brain injury and neonatal illness on corticospinal tract development in premature neonates serially studied with DTT. We hypothesized that brain abnormalities in the premature neonates are associated with impaired CST development as neonates develop from early-life to term-equivalent age. 2.2 Methods 2.2.1 Study Population This prospective cohort study enrolled premature neonates, born at 24-32 weeks gestation, and delivered at or transferred to the Children’s & Women’s Health Centre of British Columbia (April 2006 to April 2008). Exclusion criteria included: (1) congenital malformation or syndrome, (2) antenatal congenital infection, or (3) large parenchymal hemorrhagic infarction on ultrasound (>2 cm) (Papile et al., 1978). Informed consent was obtained from a parent or legal guardian. This study was approved by the University of British Columbia Clinical Research Ethics Board. Of the eligible neonates, 80 consented for the study (59%) with serial DTT obtained in 55 (20 not scanned serially, 5 inadequate quality DTT due to patient motion). 2.2.2 Clinical Data Collection Data regarding pre- and postnatal factors thought to be associated with brain injury were obtained by detailed chart review. The severity of illness in the first 24 hours of life was summarized using the score for neonatal acute physiology-perinatal extension (SNAP-PE) (Richardson et al., 1993). Prolonged premature rupture of membrane (PROM) was defined as rupture of membrane >18 hours. Chronic lung disease (CLD) was diagnosed if the infant required oxygen after 36 weeks. In the absence of a universally accepted definition, hypotension was diagnosed if neonates were treated with saline boluses or vasopressors for low blood pressure (Dempsey and Barrington, 2007). Postnatal clinical infections were defined according to Stoll et al. (2004); given the sample size, a summary variable of “any clinical infection” was analyzed (Table 2.1).  29  2.2.3 Magnetic Resonance Imaging Studies Neonates were imaged twice on a 1.5 Tesla Siemens Avanto MRI (VB 13A software): (1) in the first weeks of life (when clinically stable), and (2) at term-equivalent age. Scans were completed safely, without pharmacological sedation using an MR-compatible isolette (Lammers Medical Technology) and specialized neonatal head coil (Advanced Imaging Research). Brain MRI included: (1) 3D coronal volumetric T1-weighted images (TR 36/TE 9.2/FOV 200 mm/Slice thickness 1mm/No gap), (2) axial fast spin echo T2-weighted images (TR 4610/TE 107/ FOV 160/ Slice thickness 4mm/ Gap 0.2mm), and (3) Diffusion tensor imaging (DTI) for full brain coverage was acquired with single-shot multirepetition echo planar sequence with 12 gradient directions (TR 4900/TE 104/3 repetitions/FOV 160mm/Slice thickness 3mm/No gap), in-plane resolution of 1.3 mm, using 2 diffusion weightings (b, 600 and 700 mm2/s), and a baseline image without diffusion weighting (b0) (Partridge et al., 2004). An experienced pediatric neuroradiologist blinded to the clinical history, reviewed the MRIs for WMI, IVH, and ventriculomegaly as described previously (Miller et al., 2005). WMI, scored from minimal to severe, was defined by white matter foci of abnormal T1 hyper-intensity without marked T2 hypo-intensity, or low intensity foci on T1-weighted images (cysts) (Miller et al., 2005). IVH was graded according Papile et al. (1978). Moderate to severe MRI abnormalities (abnormal-MRI) were defined as one or more of: moderate or severe WMI, grades 3 or 4 IVH, or any degree of ventriculomegaly, on either scan. The definition of “Moderate to severe MRI abnormalities” accounts for the frequent overlap in brain abnormalities in this population and is predictive of adverse neurodevelopmental outcome (Miller et al., 2005). Twenty random MRIs were re-scored: intra-rater reliability of WMI, IVH and ventriculomegaly was high (Kappa 0.94-0.97). 2.2.4 Diffusion Tensor Tractography (DTT) With DTI, the diffusion tensor describes an ellipsoid in space characterized by the diffusion constants (eigenvalues λ1, λ2 and λ3) in the three orthogonal directions and their corresponding eigenvectors. In brain white matter, axial diffusivity [primary eigenvalue (λ1)] is oriented along the direction of the main tracts. Radial diffusivity [intermediate and minor eigenvalues (λ2 and λ3)] is oriented perpendicular to these tracts. Average diffusivity (Dav)  30  reflects the mean of these eigenvalues. Fractional anisotropy (FA) reflects the variance of the eigenvalues, ranging from 0 (isotropic diffusion) to 1 (anisotropic). DTI images were transferred offline for CST tracking by a single investigator using DTIStudio (http://cmrm.med.jhmi.edu) (Jiang et al., 2006), based on the Fiber Assignment by Continuous Tracking (FACT) method (Mori et al., 1999). CST fibre tracking was initiated with a seeding region of interest (ROI) in the posterior limb of the internal capsule at the level of the Foramen of Monro on colour-coded FA maps, tracking all fibres that pass through this ROI (Figure 2.1A). The starting threshold for tracking was an FA >0.15; tracks were terminated if FA dropped below 0.03 or the angle between the primary eigenvectors of consecutive voxels exceeded 50° (Partridge et al., 2005). The CST was filtered with two limiting ROIs at the precentral gyrus and cerebral peduncle: fibres not passing through these regions were excluded from calculations (Figure 2.1B). Consistent with previous studies, tract-based diffusion statistics were calculated: FA, Dav, axial (λ 1) and radial diffusivity [(λ 2 + λ 3)/2] (Counsell et al., 2006). Given the sample size, as the CST diffusion parameters from the left and right hemisphere did not differ (all P>0.5), the mean value from both sides was analyzed. In order to compare DTT with an ROI-based DTI analysis, CST diffusion parameters at the level of the PLIC were obtained by placing a rectangular ROI on the axial colour FA maps at the level of the Foramen of Monro. 2.2.5 Data Analysis Statistical analyses were performed using Stata 9.1 (Stata Corporation, College Station, TX). Intra-rater reliability of DTT and ROI analyses was assessed in 30 random scans using intraclass correlation coefficient (ICC) and Bland-Altman limits of agreement (Bland and Altman, 1986). The clinical risk factors in neonates with and without abnormalMRI were compared using the Fisher’s exact test for categorical variables or a t-test assuming unequal variance for continuous/ordinal variables. DTT parameters were analyzed using multivariate regression for repeated measures (generalized estimating equation) to account for serial scans and examine the effect of abnormal-MRI, accounting for age at scan. To determine whether abnormal-MRI modified the change in DTT parameters over time, an interaction term of abnormal-MRI by age at scan was examined in the model. The individual impact of WMI and IVH severity (maximum on either scan) on CST diffusion parameters  31  was similarly examined. The effects of clinical variables associated with abnormal-MRI (P<0.1) on CST development were explored using multivariate regression for repeated measures accounting for age at scan. 2.3 Results 2.3.1 Study Subjects Fifty-five premature neonates delivered at a median gestational age of 27.6 weeks (range: 24-32) participated. Twelve neonates (22%) were delivered before 26 weeks gestation. The neonates were serially imaged at median postmenstrual age 32 weeks (range: 27.4 – 40.4) and again at median 40.3 weeks (range: 34.3 – 46.4). The first MR examination took place on median postnatal day 19 (range: 3 – 109) and the second scan on median postnatal day 89 (range: 47-150). 2.3.2 MRI Findings Of the 55 premature neonates included in this study, 21 (38%) exhibited moderate to severe MRI abnormalities (abnormal-MRI) on either the first or second scan: 15 (27%) on the first scan and 15 (27%) on the second (Table 2.2 A & B). In 9 neonates, the severity of WMI (n=5) or ventriculomegaly (n=4) was less apparent on the second scan; in 6 neonates moderate WMI (n=1), or ventriculomegaly (n=5) was only apparent on the second scan. Abnormalities of the CST were not apparent on the conventional MRI or average diffusivity images. Neonates with abnormal-MRI were more likely to be intubated for longer periods of time and to be exposed to prolonged ruptured membranes, with a trend to be more likely exposed to postnatal infections (Table 2.3). 2.3.3 Quantitation of Normal CST Development using DTT With increasing postmenstrual age in premature neonates without abnormal-MRI, there was a significant increase in CST FA [0.011 per week (95% confidence interval (CI): 0.009 – 0.014; P<0.001] and a decrease in Dav [1.9x10-5 mm2/sec per week (95% CI: 1.4x10-5 – 2.4x10-5; P<0.001)] (Figure 2.2 A & B). The increase in FA resulted because the decrease in axial diffusivity (λ1) [0.8x10-5 mm2/sec per week (95% CI: 0.27x10-5 – 1.3x10-5; P=0.003)]  32  was of lesser magnitude than the decrease in radial diffusivity (λ2 and λ3) [2.5x10-5 mm2/sec per week (95% CI: 1.9x10-5 – 3.1x10-5; P<0.001)] (Figure 2.2 C & D). 2.3.4 Effect of Moderate to Severe MRI Abnormalities on CST Development The rate of increase of CST FA was significantly slower in neonates with abnormalMRI (0.008 per week; 95% CI: 0.005 – 0.010), relative to those without these changes (interaction term P=0.05) (Figure 2.2 A). The lower rate of change of FA in neonates with abnormal-MRI over time is due to the significantly higher radial diffusivity (λ2 and λ3) [1.9x10-5 mm2/sec per week (95% CI: 1.3x10-5 – 2.5x10-5; P<0.001)] in neonates with abnormal-MRI, in the context of axial diffusivity (λ1) that is not significantly different [0.6x10-5 mm2/sec per week (95% CI: 0.08x10-5 – 1.3x10-5; P=0.09] (Figure 2.2 C & D). In contrast, the rate of change of Dav values over time did not significantly differ in neonates with abnormal-MRI (interaction term P=0.2). However, for any given postmenstrual age, Dav is 1.5x10-5 mm2/sec per week higher on average (95% CI: 0.8x10-5 – 2.0x10-5; P<0.001) in neonates with abnormal-MRI (Figure 2.2B). When examining neonates with FA values below the mean on the first scan, the proportion of neonates with values remaining below the mean on the second scan was similar in those with and without abnormal-MRI (P=0.7). When examining neonates with Dav values above the mean on the first scan, the proportion of neonates with values remaining above the mean on the second scan was similar to those with and without abnormal-MRI (P=0.4) (see Appendix I). 2.3.5 Effect of WMI and IVH on CST Development Severe WMI on its own was significantly associated with lower FA [0.1 per week (95% CI: 0.08 – 0.12; P<0.001)]. Additionally, severe WMI was associated with higher values of radial diffusion (λ2 and λ3) (P=0.007), but was not associated with a difference in axial diffusion (λ1) (P>0.05). IVH did not significantly affect FA or Dav (P>0.05). 2.3.6 Effect of Clinical Risk Factors on CST Development In multivariate models adjusting for age at scan, accounting for serial studies, neither PROM nor the duration of intubation were significantly associated with the DTI measures of CST development (P>0.05 for FA and Dav). In contrast, postnatal infection significantly 33  modified the effect of age at scan on the DTI parameters. In neonates with infection, CST FA increased more slowly (0.007 per week; 95% CI: 0.005 – 0.01) than in neonates without infection (0.011 per week; 95% CI: 0.008 – 0.014) (interaction term P=0.04) (Figure 2.3A). CST Dav decreased at a marginally slower rate in neonates with postnatal infection (1.3x10-5 mm2/sec per week; 95% CI: 0.8x10-5 – 1.8x10-5) relative to those without infection (1.9x10-5 mm2/sec per week; 95% CI: 1.4x10-5 – 2.5x10-5) (interaction term P=0.08) (Figure 2.3B). When abnormal-MRI was added to these models, the presence of infection remained associated with a slower increase in CST FA over time (P=0.03) and a marginally less rapid decline in Dav (P=0.08). Additionally, when adjusting for age at scan and accounting for serial studies, extreme prematurity (gestational age at birth <26 weeks) was not significantly associated with CST FA or Dav (both P>0.05). 2.3.7 ROI-based Quantitation and Moderate to Severe Abnormalities Consistent with DTT findings in neonates without abnormal-MRI, in the ROI-based analysis, FA increased consistently with increasing postmenstrual age [0.01 per week (95% CI: 0.007 – 0.012; P<0.001)]. In contrast with the DTT findings, the rate of change of FA was not significantly different in neonates with and without abnormal MRI (interaction term P=0.22). However, for any given postmenstrual age, FA was significantly lower (0.007 per week; 95% CI: 0.005 – 0.01) in neonates with abnormal-MRI (P=0.004). Dav, axial and radial diffusivity were not significantly different in premature neonates with abnormal-MRI compared to those without (P=0.1-0.9). 2.3.8 Reliability Comparison of CST Diffusion Parameters on DTT and ROI Intra-rater reliability was higher with DTT measures than ROI-based measures (Table 2.4). 2.4 Discussion 2.4.1 CST Development in the Premature Neonate In this study, premature neonates with moderate to severe MRI abnormalities were found to have impaired development of the corticospinal tract as they developed to termequivalent age, characterized by higher overall diffusion and a slower increase in diffusion directionality. Consistent with previous studies, premature neonates without moderate to 34  severe MRI abnormalities had robust CST development characterized by decreasing overall diffusion (Dav), increasing directionality of water diffusion (FA) and radial diffusion decreasing more rapidly than axial diffusion (Miller et al., 2002; Suzuki et al., 2003; Partridge et al., 2004; Berman et al., 2005; Counsell et al., 2006). These results of CST development in premature neonates with normal MRIs are also seen in neonatal animal models of white matter development, demonstrating an increase in diffusion anisotropy which coincides with the maturation of the oligodendrocyte lineage (Drobyshevsky et al., 2005). Thus, changes in water diffusion with increasing postmenstrual age are associated with pre-myelination events which can be measured by FA and Dav. 2.4.2 CST Development and Brain Abnormalities The novel use of DTT to assess CST maturation in premature neonates with brain injuries highlights the importance of serial imaging to assess altered brain development. WMI has been previously shown to attenuate white matter maturation in premature neonates studied with ROI-based DTI measures (Miller et al., 2002). In addition to affecting microstructural development, early brain injuries in premature neonates also impair macroscopic structural development of the cerebral cortex, basal ganglia and myelinated white matter (Volpe, 1997a; Inder et al., 1999; Inder et al., 2003b; Inder et al., 2005; Srinivasan et al., 2007). These early brain abnormalities and structural changes may contribute to an adverse neurodevelopmental outcome at later ages (Peterson et al., 2000; Miller et al., 2005). Together, these data indicate that early brain injury is associated with more widespread impairments of brain development beyond that visualized with conventional MRI. The normal increase in white matter FA and decrease in Dav during development from early in premature life to term-equivalent age has been attributed to the development of microstructural components of white matter (e.g. microtubules, neurofilaments) and the maturation of oligodendroglia (OL) progenitors to mature OLs (Beaulieu, 2002; Drobyshevsky et al., 2005). The pathogenesis of WMI is linked to a particular vulnerability of late-OL progenitors (Back et al., 2001; Back et al., 2002; Haynes et al., 2003). Recently, hypoxia-ischemia was shown to arrest the development of OL progenitors (Segovia et al., 2008). Thus, the slower rate of CST maturation in neonates with moderate to severe MRI  35  abnormalities, particularly the higher radial diffusivity (perpendicular to the axons), may reflect impaired maturation of the OL lineage. However, the resolution of DTT precludes a distinction at the cellular level of a loss of glial elements or their developmental arrest. The measurement of axial and radial diffusivity provides more insight into the impact of early brain injury at the cellular level. We and others have shown elevated radial diffusivity and unchanged axial diffusivity values with increasing white matter maturation in premature neonates with MRI abnormalities compared to those with normal MRIs (Counsell et al., 2006). These results are paralleled in animal models, thereby shedding light on cellular changes occurring during development. Changes in radial diffusivity are thought to reflect the events of myelination and pre-myelination (such as the maturation of oligodendrocytes) (Song et al., 2002; Song et al., 2003). This was demonstrated in a mouse model, showing an increase in radial diffusivity coinciding with the dysmyelination of various white matter regions (Song et al., 2002). In contrast, axial diffusivity remained unchanged in response to those changes in the events of myelination, and is thought to reflect the integrity of the axon and its internal components. Together these results suggest that the elevated radial diffusivity levels in premature neonates with MRI abnormalities reflects the impairment of the oligodendrocytes surrounding the axon, as opposed to intra-axonal processes, reducing the barriers to free water diffusion in the orientation perpendicular to the CST. 2.4.3 Clinical Risk Factors and CST Development using DTT Segovia et al. (2008) suggest a potential for ongoing white matter susceptibility in regions of arrested OL development. Progressive WMI is now recognized in some premature neonates, particularly those exposed to postnatal infections (Glass et al., 2008). In this DTT study we find that postnatal infections are associated with a delayed development of the CST: less rapid increase in FA and less rapid decline in Dav. These findings raise the hypothesis that postnatal infections in premature neonates increase the susceptibility to acquiring new white matter lesions by impairing white matter maturation, leaving an increased pool of vulnerable oligodendrocyte progenitor cells. The delayed CST development observed in neonates with infection is consistent with the increased risk of adverse outcomes in premature neonates exposed to postnatal infections (Stoll et al., 2004; Bassler et al., 2009). There is an increasing recognition of the adverse effects of systemic infection on the brain in  36  the premature neonate. It will be critical to determine how these brain changes relate to adverse neurodevelopmental outcomes and whether improving the treatment of infection, or preventing these infections, might improve the long-term outcomes of these vulnerable neonates. Other clinical risk factors, including extreme prematurity, were not in themselves sufficient to result in impaired CST development. This is consistent with previous work using volumetric MRI demonstrating that brain volumes are preserved in premature neonates in the absence of chronic lung disease (CLD) (Boardman et al., 2007). Although research has previously implicated a relationship between illnesses such as CLD and subsequent motor deficits, this impaired motor development may occur through the sensory or supplementary motor pathways, or basal ganglia structures (Singer et al., 1997; Hoon et al., 2002; Thomas et al., 2005). Specifically, Hoon et al. (2002) described the possible involvement of impaired sensory white matter tracts, independent from the CST, in the pathophysiology of motor disability in children with cerebral palsy. Given the more diffuse distribution of the sensorimotor pathways (Berman et al., 2005) and technical challenges in tracking these pathways, we specifically focused on the motor pathway. 2.4.4 Comparison of ROI and DTT Measurements of CST Development Consistent with the findings of Partridge et al. (2006), our observations show FA values from the PLIC to be systematically higher than those obtained from DTT; Dav values were lower. This highlights the variability of diffusion along the tract, where diffusion at one level is not representative of the entire tract. Our study demonstrates a high degree of reliability between repeated DTT measures of the CST, while ROI-based measures were slightly less reproducible with greater potential for inconsistent ROI placement. Recent advances in DTI analysis tools, such as tract-based spatial statistics, have enabled group comparisons without the need for manual ROI placement (Anjari et al., 2007). However, these techniques have not yet been validated across the age range from early premature life to term-equivalent age with the dramatic changes observed in brain size and shape. Despite the increased technical requirements relative to ROI analyses, DTT provides an important method of assessing abnormalities in brain maturation from early-life to term-equivalent age in specific white matter tracts.  37  2.4.5 Limitations Although this is the largest group of premature neonates studied serially with DTT of the CST, the sample size precludes the determination of the specific effects of individual types of brain injury. Given the frequent co-occurrence of these injuries, a composite score was used. While an effect of severe WMI was detected on CST microstructural development, neonates with milder forms of WMI often had other brain abnormalities, limiting our ability to detect differences. With a larger sample size, therefore, we would be able to distinguish between the effects of individual types of brain pathologies. Additionally, many brain injuries in this population were multifocal and bilateral. As such, we were unable to examine the effect of unilateral abnormalities on ipsilateral CST development. As this cohort is followed through childhood we will examine the association of microstructural CST development with motor outcomes. 2.5 Conclusions The current study demonstrates that corticospinal tract maturation is impaired in premature neonates with moderate to severe MRI abnormalities. The change in radial, as opposed to axial, diffusivity suggests a loss of glial cells around axons. This is consistent with experimental observations of an arrest in the developmental progression of the oligodendrocyte lineage with brain injury. Our findings also suggest that the vulnerability to acquiring new white matter injuries in neonates with postnatal infection (Glass et al., 2008) may be related to delayed white matter development.  38  Table 2.1 Descriptive statistics of the premature neonates enrolled in the study  Number Male Sex Prenatal Pregnancy Induced Hypertension Prolonged Ruptured Membrane Histological Chorioamnionitis Postnatal C-section Delivery Gestational Age at Birth Postnatal age (days) at MRI: MRI 1 MRI 2 Gestational age < 26 Weeks Score for Neonatal Acute Physiology- Perinatal Extension Patent Ductus Arteriosus Days Intubated Chronic Lung Disease Hypotension Postnatal Infection  Number (%) or Median (IQR) 55 25 (45%) 12 (22%) 12 (22%) 20 (38%) 30 (55%) 27.6 (26.4 – 30) 19 (3 – 109) 89 (47 – 150) 12 (22%) 19 (9 – 38.5) 23 (42%) 3 (0-25) 23 (42%) 15 (27%) 23 (42%)  39  Table 2.2 Distribution of brain abnormality findings on MRI A. Brain abnormalities present on the first scan  Number (%) IVH (Grades 1-2) Absent Present Ventriculomegaly Absent Present  White Matter Injury Moderate Normal Mild to severe  P-value  27 (66%) 14 (34%)  4 (80%) 1 (20%)  4 (44%) 5 (56%)  0.20  36 (85%) 5 (12%)  3 (60%) 2 (40%)  4 (44%) 5 (56%)  0.01  B. Brain abnormalities present on the scans at term-equivalent age  Number (%) IVH (Grades 1-2) Absent Present Ventriculomegaly Absent Present  White Matter Injury Moderate Normal Mild to severe  P-value  36 (77%) 11 (23%)  1 (33%) 2 (67%)  4 (80%) 1 (20%)  0.41  37 (79%) 10 (21%)  3 (100%) 2 (40%) 0 3 (60%)  0.13  40  Table 2.3 Clinical features of the premature neonates with and without moderate to severe MRI abnormalities  Number (%) or Median (IQR) Number Male Sex Prenatal Pregnancy Induced Hypertension Prolonged Ruptured Membrane Histological Chorioamnionitis Postnatal C-section Delivery Gestational Age at Birth Postnatal age (days) at MRI: MRI 1 MRI 2 Gestational age <26 Weeks Score for Neonatal Acute Physiology- Perinatal Extension Patent Ductus Arteriosus Days Intubated Chronic Lung Disease Hypotension Postnatal Infection  Moderate to Severe MRI Abnormalities No Yes 34 21 15 (44%) 10 (48%)  P-value  9 (26%) 4 (12%) 11 (33%)  3 (14 %) 8 (38%) 9 (45%)  0.34 0.04 0.56  17 (50%) 27.9 (26.7 – 30)  13 (62%) 26.9 (25.9 – 29.6)  0.42 0.22  16.5 (3 – 69) 82.5 (47 – 125) 6 (18%)  26 (3 – 109) 94 (59 – 150) 6 (29%)  0.14 0.04 0.50  17 (9 – 29.5)  20.5 (15.5 – 42.5)  0.14  12 (35%) 2 (1 – 9) 13 (38%) 7 (21%) 11 (32%)  11(52%) 12 (0 – 54) 10 (48%) 8 (38 %) 12 (57%)  0.27 0.01 0.58 0.22 0.09  41  Table 2.4 Intra-rater reliability measurements for the repeated quantification of CST FA and Dav using the diffusion tensor tractography and region of interest methods  Method DTT FA Dav ROI FA Dav  ICC  95% CI  Mean Difference  Bland Altman Limits of Agreement  0.99 0.97  0.98 – 0.99 0.95 – 0.99  -0.005 -0.3x10-5  -0.02 – 0.01 -9.4x10-5 – 8.8x10-5  0.91 0.88  0.84 – 0.97 0.80 – 0.96  0 -1.5x10-5  -0.06 – 0.06 -13.1x10-5 – 10.2x10-5  42  Figure 2.1 Diffusion tensor tractography of the corticospinal tract in a premature neonate studied serially Representative images from a premature neonate delivered at 27 weeks gestational age and studied with MRI at: (A) 29 weeks of postmenstrual age (B) and 45 weeks postmenstrual age. (Top) Axial diffusion tensor imaging encoded anisotropy color map illustrating the region of interest in the posterior limb of the internal capsule (in white). The color convention used to display the predominant diffusion direction has red representing right–left, green representing anterior-posterior, and blue representing superior-inferior anatomical directions (Partridge et al., 2004). (Bottom) 3D renderings of the DTT delineated corticospinal tract (CST) in red. A seeding ROI was first placed at the posterior limb of the internal capsule (Top, in white) and then limiting ROIs were placed at the precentral gyrus and cerebral peduncle to define the tract. Diffusion parameters were averaged over the entire length of the tract.  43  A  B  CST Fra ctio nal Anisotropy vs Age at Scan  CST Average Diffusivity vs A ge at Scan Higher in Infants w ith Moderate/Severe Abnormalities (Interaction P=0.2)  0  .00 0 8  .2  .00 1 2  .4  FA  D av  .6  .00 1 6  .8  1  .00 2  Diff ers in Newborns with Mod erate/Severe Abnorma lities (Interaction P= 0.05)  25  30  35 40 Ges tati o nal Age at MR I (W ee ks) Nor ma l MR I  C  45  25  30  A bn or mal MRI  35 40 Ge sta tio na l Ag e a t MR I ( We ek s) No rma l MR I  D  CST Axial Diffusivity vs Age at Scan  Ab no rma l MR I  CST Radia l Diffusivity vs Age at Scan Is Higher in Inf ants with Moderate/Severe Abnormalitie s (Interaction P=0.1)  .001  .0 00 5  R adi a l Di ffu sivi ty .0 00 8 .0 01 1 .0 01 4  A xi al D iffu si vity .001 5 .002 .002 5  .0 01 7  .003  No Change in Inf ants with Moderate/Severe Abnormalities (Interaction P=0.7)  45  25  30  35 40 Ge statio n al A ge a t MR I (We ek s) No rma l M RI  Abn o rma l MR I  45  25  30  35 40 Ge sta tio na l Age a t MR I (W e eks ) N o rma l MR I  45  Abn o rma l MR I  Figure 2.2 Developmental trajectory of CST diffusion parameters obtained from serial DTT scans in premature neonates with and without moderate to severe MRI abnormalities (abnormal-MRI). A. Fractional Anisotropy increases less rapidly in neonates with abnormal-MRI (P=0.05). B. Average Diffusivity is higher in neonates with abnormal-MRI (P=0.2). C. Axial diffusivity is not significantly different in neonates with abnormal MRI (P=0.7). D. Radial diffusivity is higher in neonates with abnormal MRI (P=0.1).  44  CST Fractional Anisotropy vs Age at Scan  B  CST Average Diffusivity vs Age at Scan Differs in Infants with Postnatal Infection (Interaction P=0.07)  0  .0008  .2  .0012  .4  FA  Dav  .6  .0016  .8  1  Differs in Infants with Postnatal Infection (Interaction P=0.04)  .002  A  25  30  35 40 Gestational Age at MRI (Weeks) No Infection  Infection  45  25  30  35 40 Gestational Age at MRI (Weeks) No Infection  45  Infection  Figure 2.3 Developmental trajectory of CST fractional anisotropy and average diffusivity from serial DTT scans in premature newborns with and without postnatal clinical infection. A. Fractional Anisotropy increases less rapidly in newborns with infection (P=0.04). B. Average Diffusivity decreases less rapidly in newborns with infection (P=0.07).  45  2.6 References Anjari M, Srinivasan L, Allsop JM, Hajnal JV, Rutherford MA, Edwards AD, Counsell SJ (2007) Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants. Neuroimage 35:1021-1027. Back SA, Luo NL, Borenstein NS, Levine JM, Volpe JJ, Kinney HC (2001) Late oligodendrocyte progenitors coincide with the developmental window of vulnerability for human perinatal white matter injury. J Neurosci 21:1302-1312. Back SA, Han BH, Luo NL, Chricton CA, Xanthoudakis S, Tam J, Arvin KL, Holtzman DM (2002) Selective vulnerability of late oligodendrocyte progenitors to hypoxiaischemia. J Neurosci 22:455-463. Bassler D, Stoll BJ, Schmidt B, Asztalos EV, Roberts RS, Robertson CM, Sauve RS (2009) Using a count of neonatal morbidities to predict poor outcome in extremely low birth weight infants: Added role of neonatal infection. Pediatrics 123:313-318 Beaulieu C (2002) The basis of anisotropic water diffusion in the nervous system - a technical review. NMR Biomed 15:435-455. Berman JI, Mukherjee P, Partridge SC, Miller SP, Ferriero DM, Barkovich AJ, Vigneron DB, Henry RG (2005) Quantitative diffusion tensor MRI fiber tractography of sensorimotor white matter development in premature infants. Neuroimage 27:862871. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307-310. Boardman JP, Counsell SJ, Rueckert D, Hajnal JV, Bhatia KK, Srinivasan L, Kapellou O, Aljabar P, Dyet LE, Rutherford MA, Allsop JM, Edwards AD (2007) Early growth in brain volume is preserved in the majority of preterm infants. Ann Neurol 62:185-192. Counsell SJ, Shen Y, Boardman JP, Larkman DJ, Kapellou O, Ward P, Allsop JM, Cowan FM, Hajnal JV, Edwards AD, Rutherford MA (2006) Axial and radial diffusivity in preterm infants who have diffuse white matter changes on magnetic resonance imaging at term-equivalent age. Pediatrics 117:376-386. Dempsey EM, Barrington KJ (2007) Treating hypotension in the preterm infant: when and with what: a critical and systematic review. J Perinatol 27:469-478. Drobyshevsky A, Song SK, Gamkrelidze G, Wyrwicz AM, Derrick M, Meng F, Li L, Ji X, Trommer B, Beardsley DJ, Luo NL, Back SA, Tan S (2005) Developmental changes in diffusion anisotropy coincide with immature oligodendrocyte progression and maturation of compound action potential. J Neurosci 25:5988-5997. Glass HC, Bonifacio SL, Chau V, Glidden D, Poskitt K, Barkovich AJ, Ferriero DM, Miller SP (2008) Recurrent postnatal infections are associated with progressive white matter injury in premature infants. Pediatrics 122:299-305. Goyen TA, Lui K (2008) Developmental coordination disorder in 'apparently normal' school children born extremely preterm. Arch Dis Child.  46  Haynes RL, Folkerth RD, Keefe RJ, Sung I, Swzeda LI, Rosenberg PA, Volpe JJ, Kinney HC (2003) Nitrosative and oxidative injury to premyelinating oligodendrocytes in periventricular leukomalacia. J Neuropathol Exp Neurol 62:441-450. Holsti L, Grunau RV, Whitfield MF (2002) Developmental coordination disorder in extremely low birth weight children at nine years. J Dev Behav Pediatr 23:9-15. Hoon AH, Jr., Lawrie WT, Jr., Melhem ER, Reinhardt EM, Van Zijl PC, Solaiyappan M, Jiang H, Johnston MV, Mori S (2002) Diffusion tensor imaging of periventricular leukomalacia shows affected sensory cortex white matter pathways. Neurology 59:752-756. Huppi PS, Maier SE, Peled S, Zientara GP, Barnes PD, Jolesz FA, Volpe JJ (1998) Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr Res 44:584-590. Huppi PS, Murphy B, Maier SE, Zientara GP, Inder TE, Barnes PD, Kikinis R, Jolesz FA, Volpe JJ (2001) Microstructural brain development after perinatal cerebral white matter injury assessed by diffusion tensor magnetic resonance imaging. Pediatrics 107:455-460. Inder TE, Wells SJ, Mogridge NB, Spencer C, Volpe JJ (2003) Defining the nature of the cerebral abnormalities in the premature infant: a qualitative magnetic resonance imaging study. J Pediatr 143:171-179. Inder TE, Warfield SK, Wang H, Huppi PS, Volpe JJ (2005) Abnormal cerebral structure is present at term in premature infants. Pediatrics 115:286-294. Inder TE, Huppi PS, Warfield S, Kikinis R, Zientara GP, Barnes PD, Jolesz F, Volpe JJ (1999) Periventricular white matter injury in the premature infant is followed by reduced cerebral cortical gray matter volume at term. Ann Neurol 46:755-760. Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S (2006) DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Programs Biomed 81:106-116. Marlow N, Hennessy EM, Bracewell MA, Wolke D (2007) Motor and executive function at 6 years of age after extremely preterm birth. Pediatrics 120:793-804. Miller SP, Vigneron DB, Henry RG, Bohland MA, Ceppi-Cozzio C, Hoffman C, Newton N, Partridge JC, Ferriero DM, Barkovich AJ (2002) Serial quantitative diffusion tensor MRI of the premature brain: development in newborns with and without injury. J Magn Reson Imaging 16:621-632. Miller SP, Ferriero DM, Leonard C, Piecuch R, Glidden DV, Partridge JC, Perez M, Mukherjee P, Vigneron DB, Barkovich AJ (2005) Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr 147:609-616. Mori S, van Zijl PC (2002) Fiber tracking: principles and strategies - a technical review. NMR Biomed 15:468-480. Mori S, Crain BJ, Chacko VP, van Zijl PC (1999) Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol 45:265-269. 47  Neil JJ, Shiran SI, McKinstry RC, Schefft GL, Snyder AZ, Almli CR, Akbudak E, Aronovitz JA, Miller JP, Lee BC, Conturo TE (1998) Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. Radiology 209:57-66. Papile LA, Burstein J, Burstein R, Koffler H (1978) Incidence and evolution of subependymal and intraventricular hemorrhage: a study of infants with birth weights less than 1,500 gm. J Pediatr 92:529-534. Partridge SC, Mukherjee P, Berman JI, Henry RG, Miller SP, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2005) Tractography-based quantitation of diffusion tensor imaging parameters in white matter tracts of preterm newborns. J Magn Reson Imaging 22:467-474. Partridge SC, Vigneron DB, Charlton NN, Berman JI, Henry RG, Mukherjee P, McQuillen PS, Karl TR, Barkovich AJ, Miller SP (2006) Pyramidal tract maturation after brain injury in newborns with heart disease. Ann Neurol 59:640-651. Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2004) Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. Neuroimage 22:1302-1314. Peterson BS, Vohr B, Staib LH, Cannistraci CJ, Dolberg A, Schneider KC, Katz KH, Westerveld M, Sparrow S, Anderson AW, Duncan CC, Makuch RW, Gore JC, Ment LR (2000) Regional brain volume abnormalities and long-term cognitive outcome in preterm infants. Jama 284:1939-1947. Richardson DK, Phibbs CS, Gray JE, McCormick MC, Workman-Daniels K, Goldmann DA (1993) Birth weight and illness severity: independent predictors of neonatal mortality. Pediatrics 91:969-975. Segovia KN, McClure M, Moravec M, Luo NL, Wan Y, Gong X, Riddle A, Craig A, Struve J, Sherman LS, Back SA (2008) Arrested oligodendrocyte lineage maturation in chronic perinatal white matter injury. Ann Neurol 63:520-530. Singer L, Yamashita T, Lilien L, Collin M, Baley J (1997) A longitudinal study of developmental outcome of infants with bronchopulmonary dysplasia and very low birth weight. Pediatrics 100:987-993. Song SK, Sun SW, Ju WK, Lin SJ, Cross AH, Neufeld AH (2003) Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. NeuroImage 20:1714-1722. Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH (2002) Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage 17:1429-1436. Srinivasan L, Dutta R, Counsell SJ, Allsop JM, Boardman JP, Rutherford MA, Edwards AD (2007) Quantification of deep gray matter in preterm infants at term-equivalent age using manual volumetry of 3-tesla magnetic resonance images. Pediatrics 119:759765.  48  Stoll BJ, Hansen NI, Adams-Chapman I, Fanaroff AA, Hintz SR, Vohr B, Higgins RD (2004) Neurodevelopmental and growth impairment among extremely low-birthweight infants with neonatal infection. Jama 292:2357-2365. Suzuki Y, Matsuzawa H, Kwee IL, Nakada T (2003) Absolute eigenvalue diffusion tensor analysis for human brain maturation. NMR Biomed 16:257-260. Thomas B, Eyssen M, Peeters R, Molenaers G, Van Hecke P, De Cock P, Sunaert S (2005) Quantitative diffusion tensor imaging in cerebral palsy due to periventricular white matter injury. Brain 128:2562-2577. Volpe J (2001) Neurology of the Newborn, 4th Edition. Philadelphia: W.B. Saunders. Volpe JJ (1997) Brain injury in the premature infant. Neuropathology, clinical aspects. MRDD Res Rev 3:3-12.  49  CHAPTER III: CONCLUSIONS In the research undertaken for this Master’s program, we first demonstrated that the normal developmental trajectory of the corticospinal tract in premature neonates is characterized by a consistent increase in FA and decrease in Dav with increasing age. We then demonstrated that this CST development is impaired by early brain abnormalities and postnatal infection. These results stem from the three questions that I set out to examine in this thesis: (1) How does the CST develop in healthy premature neonates? (2) What is the impact of early brain abnormalities on CST maturation in premature neonates? (3) Does systemic neonatal illness, such as infection, in premature neonates impact CST development? With the information afforded by our study we have begun to elucidate a piece of the mechanism underlying how focal brain abnormalities are associated with abnormal development. The next step is to determine whether these abnormalities underlie the motor deficits seen during development. 3.1 Research Questions Answered 3.1.1 Development of the CST in Healthy Premature Neonates The brain of a premature neonate undergoes rapid changes and increases in complexity during early postnatal life from birth to term-equivalent age (Huppi et al., 1998; Volpe, 2001). Changes occurring in the brain during this time period include the maturation of axonal elements and the myelination of specific white matter pathways, such as the CST. As maturation ensues, these factors contribute to an increased hindrance of water diffusion within the white matter. This is exemplified in a neonatal rabbit model, where an observed increase in FA coincides with the progression of the OL lineage, as OL progenitors mature to myelin-producing OLs (Drobyshevsky et al., 2005). This increase in FA is parallel to our observations of CST development in healthy premature neonates. This suggests that the consistent increase in FA and decrease in Dav observed with increasing age in premature neonates corresponds to the maturation of cellular microstructural components, including the OLs as they prepare for myelination. Our results are also consistent with other DTI and DTT studies, despite differences in acquisition and image analysis, demonstrating the robustness of this technique.  50  3.1.2 The Impact of Early Brain Abnormalities on CST Development Due to the nature of the critical period of active macro- and microstructural development between birth and term-equivalent age, cerebral white matter pathways are extremely vulnerable to injury. This is secondary to insults such as ischemia, inflammation and their downstream mechanisms of excitotoxicity and free-radical attack, which are involved in the pathogenesis of WMI (Volpe, 2009). A particular cellular target of these processes is the late OL progenitor (Back and Volpe, 1997; Back et al., 2001; Back et al., 2002). Particularly, WMI pathogenesis has been related to the maturational arrest of pre-OLs by hypoxia-ischemia (Segovia et al., 2008). The secondary consequence of this maturational arrest is a decrease in the pool of myelin-forming mature OLs, resulting in myelination disturbances. These findings in a neonatal rat model are paralleled in our study in the human premature neonate, with a slower rate of increase in FA and higher Dav values in those with MRI abnormalities or lower FA in neonates with severe WMI. Although DTT does not directly measure cellular development, from these results we can infer that CST microstructural development, i.e. the progression of the OL lineage, is impaired in premature neonates with moderate to severe MRI abnormalities. Does this lead to retained white matter vulnerability beyond the period we studied? 3.1.3 The Impact of Neonatal Illnesses on CST Development Despite our relatively large sample size, our ability to examine neonatal illness is limited. We therefore explored only those clinical factors associated with moderate to severe brain abnormalities on MRI. Our results indicate that CST maturation is impaired in premature neonates with postnatal infections. Previous studies have demonstrated an increased risk of white matter abnormalities in premature infants with postnatal infections (Graham et al., 2004; Shah et al., 2008). This is intriguing given that postnatal infections are also associated with neurodevelopmental deficits (Murphy et al., 1997; Stoll et al., 2004; Shah et al., 2008). Together these observations suggest that there is some mechanism involved with postnatal infections which impairs the white matter pathways underlying cognitive and motor functions.  51  A recent study investigating the cause of progressive WMI in premature neonates found an association with recurrent postnatal infections (Glass et al., 2008). Together with the findings of Back et al. (2002) demonstrating the vulnerability of pre-OLs to hypoxic-ischemic injury, these results are suggestive of a general inherent vulnerability of the white matter in these premature neonates. The white matter of a premature neonate may also be vulnerable to infection/inflammation, which may play an important role in the pathogenesis of injury in the developing brain. In response to infection in the premature neonate, an inflammatory response is initiated (Khwaja and Volpe, 2008). This results in the release of pro-inflammatory cytokines as well as the activation of microglia within immature white matter. In vivo neonatal rat studies have demonstrated that these pro-inflammatory cytokines are toxic to the vulnerable population of pre-OLs, resulting in inflammation-mediated injury (Pang et al., 2003). The association between postnatal infection and brain injury has not yet been clearly defined, however, this suggests that hypoxia-ischemia and inflammation may share a common pathway, through the disruption of the OL-lineage, resulting in injury to the white matter. This is consistent with our findings of impaired CST development in neonates with postnatal infections. This link between inflammation and brain injury may help explain mechanisms behind observed neurodevelopmental impairments in infants exposed to postnatal infections. 3.2 Strengths and Limitations of the Current Study 3.2.1 Strengths Our cohort was the largest group of serially imaged premature neonates that were analyzed using DTT. Inherent difficulties involved in studying such a fragile cohort have been overcome for this study and have greatly contributed to its strength. Our group has developed methods of safely transporting infants to and from the neonatal intensive care unit and the MRI scanner, in which safe ICU management has been established. This includes the use of a MR-compatible incubator. Furthermore, dedicated neonatal MR equipment, such as a neonatal head coil, have increased the signal-to-noise ratio to enable advanced quantitative MRI techniques such as DTT.  52  The use of DTT in this study has provided us with a unique opportunity to visualize alterations in white matter development from early premature life to termequivalent age. The detection of maturational impairments afforded by DTT cannot be as reliably found using conventional MRI or ROI-based techniques. This provides justification for the additional time required to fully track the CST in comparison to the relatively quick placement of a solitary ROI. Additionally, the use of DTT in our study led to very robust results and high intra-rater reliability. It is also important to note that diffusion parameters yielded by different DTT programs, such as DtiStudio, are reproducible; an important quality required for the use of DTT in clinical diagnosis and intervention. Using data from the present study, I recently evaluated the intra-method reliability of obtaining CST diffusion parameters. FA, Dav and the eigenvalues obtained in DtiStudio were compared to those obtained in another independent deterministic DTT program, MedINRIA (INRIA Sophia Antipolis) (Toussaint et al., 2007). This project demonstrated that CST diffusion parameters were remarkably consistent across different DTT programs. As it appears that diffusion parameters can be reliably obtained using different software, this allows for comparisons to be made between different institutions regarding patterns of brain development. This suggests that DTT may be a candidate for eventual use in a clinical setting. 3.2.2 Limitations This clinical research project has limitations that can be described in 2 domains: current technical limitations of DTT, and sample size and outcomes. The deterministic tractography approach utilized by DtiStudio is limited by the Gaussian Diffusion Assumption: that a single diffusion fibre population is sufficient to characterize each voxel (Descoteaux et al., 2009). This poses a problem because these methods do not account for the multi-directional architecture of fibres within a voxel. The resultant may be the amalgamation of two fibre bundles, heading in different directions, into one bundle or the premature ending of a fibre. This method, therefore, is not sensitive to crossing fibres at the centrum semiovale (cerebral white matter). As a result, the placement of an ROI at the PLIC or cerebral peduncle only reveals the motor fibre projections which go through these areas and branch to the medial portions of the primary motor cortex (Behrens et al., 2007). Projections to the lateral regions of the motor strip (e.g. those 53  projecting to areas responsible for arm movement) via the fan-like (crossing) fibres of the corona radiata, would not be accounted for. Similarly, using this deterministic approach, tracking performance is constrained to areas of high anisotropy and low uncertainty. This is potentially problematic for the study of the premature neonate brain; FA values may be misrepresented, as anisotropy is typically very low due to the immaturity of the white matter microstructure. There are fewer crossing fibres in the immature neonate brain, however, and since the CST is one of the earliest developing pathways, CST FA values are higher in comparison to other more immature tracts. Increased sensitivity to lower FA values and crossing fibres could be achieved through the use of a stronger magnetic field (3 Tesla MRI) for diffusion tensor acquisition, or the development of smaller multichannel head coils for the neonate brain. These improvements in sensitivity will enable more diffusion encoding directions and increase the signal-to-noise ratio. Other DTT methods, such as probabilistic tractography, might then be able to take advantage of this increased sensitivity. As described above, another limitation of the methodology used in this study is the size of our cohort. Our sample size was relatively large in comparison to similar studies in the area where the sample size ranged from 9 to 32 infants (Huppi et al., 2001; Miller et al., 2002; Partridge et al., 2004; Berman et al., 2005; Partridge et al., 2005; Partridge et al., 2006). In this size of a cohort, there was a limited number and severity of moderate to severe brain abnormalities described. With a larger sample size, we would be able to evaluate more systemic risk factors, validate our infection results, and be able to distinguish between the effects of individual types of brain pathologies (i.e. WMI or IVH). Finally, a lack of long term motor outcomes has prevented us from examining the link between the abnormalities in CST development demonstrated in our study, to later motor deficits. Follow-up examinations of these premature neonates are planned for older ages, and will be discussed in the future directions section.  54  3.3 Proposals for New Ideas We have shown that early neonatal illness and early brain injuries can impair the development of white matter pathways, such as the CST. Due to the vulnerability of the developing brain, this brings to light questions about how critical care practices may impact brain development. There has been some recognition that critical care therapies, as well as resuscitation measures used at birth, negatively impact brain development. For example, administration of corticosteroids for treatment of CLD has been associated with impaired brain growth as well as adverse cognitive and motor functioning in childhood (Murphy et al., 2001; Yeh et al., 2004). Recently, we have been collecting data on the impact of resuscitation strategies, and clinical characteristics during the resuscitation period immediately following delivery, on the risk of WMI (Adams et al., 2009). This follows in the theme of understanding how brain development, and subsequent neurodevelopmental deficits, is affected by factors during the early life of premature infants. Continuing efforts to elucidate the postnatal risks and mechanisms underlying abnormal neurodevelopmental outcomes in premature neonates will help improve the futures of these infants. 3.4 Significance of the Problem A better understanding of how early brain abnormalities impact subsequent development of the primary motor pathway will form a foundation for addressing how to maximize the brain’s potential for recovery. The ability to detect abnormalities in brain development using DTT technology will greatly contribute to the improvement of neurodevelopmental outcomes of infants and children born prematurely. Translated into clinical practice, these results will allow physicians to better anticipate neurological problems in ex-premature children with abnormal corticospinal tract development. Additionally, it will allow physicians to counsel parents more appropriately, and even to initiate appropriate rehabilitation interventions, such as physiotherapy, to ameliorate these deficits. Early intervention is critical in stimulating inherent compensatory mechanisms to minimize the consequences of brain abnormalities on neurodevelopmental  55  outcome during the critical period of brain development from early-life to termequivalent age. 3.5 Future Directions It is becoming increasingly established in the literature that moderate to severe MRI abnormalities, which we have identified in our study, are associated with diffuse abnormalities in subsequent motor functioning (Volpe, 2001; Miller et al., 2005; Woodward et al., 2006). In our study, we demonstrated that these brain abnormalities result in impairments in corticospinal tract maturation, and may underlie the motor deficits seen in toddlers and children born prematurely. Glenn et al. previously showed, using DTT, that alterations in CST diffusion parameters in children with cerebral palsy was correlated with the severity of motor dysfunction (Glenn et al., 2007). To be able to predict motor deficits from impairments in CST development seen in our cohort of premature neonates, follow-up examinations are required. Assessment of motor developmental outcome at 18 months of age for infants from our cohort is currently underway. Further follow-up studies for these infants at 3 years of age, and eventually 8 years, are planned. These follow-up studies will enable us to determine whether abnormal corticospinal tract development in infancy is predictive of later motor deficits in children. Early brain abnormalities are also associated with impairments in cognition and vision (Volpe, 2001; Miller et al., 2005; Woodward et al., 2006). Once the predictive capability of DTT is established for motor outcome, therefore, this technique can be utilized to quantify the development of cognitive and visual pathways, with the ultimate goal of predicting the full-spectrum of neurodevelopmental outcome. Neurodevelopmental deficits take time to manifest and therefore, identification and prediction of neonates at the highest risk of impairment is important so that rehabilitation can be introduced without delay. By quantifying brain development in the neonate period, we hope to develop a method that can be used readily by clinicians as a standard of care to assess the early impact of new and emerging brain protection strategies. The ultimate goal of this work is to improve the outcomes of premature neonates. 56  3.6 References Adams E, Chau V, Sherlock RL, Poskitt K, Synnes A, Soulikias W, Miller SP (2009) Risk factors for white matter injury during the resuscitation period in premature newborns. E-PAS 3868.283. Back SA, Volpe JJ (1997) Cellular and molecular pathogenesis of periventricular white matter injury. Ment Retard Dev Disabil Res Rev 3:96-107. Back SA, Luo NL, Borenstein NS, Levine JM, Volpe JJ, Kinney HC (2001) Late oligodendrocyte progenitors coincide with the developmental window of vulnerability for human perinatal white matter injury. J Neurosci 21:1302-1312. Back SA, Han BH, Luo NL, Chricton CA, Xanthoudakis S, Tam J, Arvin KL, Holtzman DM (2002) Selective vulnerability of late oligodendrocyte progenitors to hypoxiaischemia. J Neurosci 22:455-463. Behrens TE, Berg HJ, Jbabdi S, Rushworth MF, Woolrich MW (2007) Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage 34:144-155. Berman JI, Mukherjee P, Partridge SC, Miller SP, Ferriero DM, Barkovich AJ, Vigneron DB, Henry RG (2005) Quantitative diffusion tensor MRI fiber tractography of sensorimotor white matter development in premature infants. Neuroimage 27:862-871. Descoteaux M, Deriche R, Knosche TR, Anwander A (2009) Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans Med Imaging 28:269-286. Drobyshevsky A, Song SK, Gamkrelidze G, Wyrwicz AM, Derrick M, Meng F, Li L, Ji X, Trommer B, Beardsley DJ, Luo NL, Back SA, Tan S (2005) Developmental changes in diffusion anisotropy coincide with immature oligodendrocyte progression and maturation of compound action potential. J Neurosci 25:59885997. Glass HC, Bonifacio SL, Chau V, Glidden D, Poskitt K, Barkovich AJ, Ferriero DM, Miller SP (2008) Recurrent postnatal infections are associated with progressive white matter injury in premature infants. Pediatrics 122:299-305. Glenn OA, Ludeman NA, Berman JI, Wu YW, Lu Y, Bartha AI, Vigneron DB, Chung SW, Ferriero DM, Barkovich AJ, Henry RG (2007) Diffusion tensor MR imaging tractography of the pyramidal tracts correlates with clinical motor function in children with congenital hemiparesis. AJNR Am J Neuroradiol 28:1796-1802. Graham EM, Holcroft CJ, Rai KK, Donohue PK, Allen MC (2004) Neonatal cerebral white matter injury in preterm infants is associated with culture positive infections and only rarely with metabolic acidosis. Am J Obstet Gynecol 191:1305-1310. Huppi PS, Maier SE, Peled S, Zientara GP, Barnes PD, Jolesz FA, Volpe JJ (1998) Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr Res 44:584-590.  57  Huppi PS, Murphy B, Maier SE, Zientara GP, Inder TE, Barnes PD, Kikinis R, Jolesz FA, Volpe JJ (2001) Microstructural brain development after perinatal cerebral white matter injury assessed by diffusion tensor magnetic resonance imaging. Pediatrics 107:455-460. Khwaja O, Volpe JJ (2008) Pathogenesis of cerebral white matter injury of prematurity. Arch Dis Child Fetal Neonatal Ed 93:F153-161. Miller SP, Vigneron DB, Henry RG, Bohland MA, Ceppi-Cozzio C, Hoffman C, Newton N, Partridge JC, Ferriero DM, Barkovich AJ (2002) Serial quantitative diffusion tensor MRI of the premature brain: development in newborns with and without injury. J Magn Reson Imaging 16:621-632. Miller SP, Ferriero DM, Leonard C, Piecuch R, Glidden DV, Partridge JC, Perez M, Mukherjee P, Vigneron DB, Barkovich AJ (2005) Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr 147:609-616. Murphy BP, Inder TE, Huppi PS, Warfield S, Zientara GP, Kikinis R, Jolesz FA, Volpe JJ (2001) Impaired cerebral cortical gray matter growth after treatment with dexamethasone for neonatal chronic lung disease. Pediatrics 107:217-221. Murphy DJ, Hope PL, Johnson A (1997) Neonatal risk factors for cerebral palsy in very preterm babies: case-control study. Bmj 314:404-408. Pang Y, Cai Z, Rhodes PG (2003) Disturbance of oligodendrocyte development, hypomyelination and white matter injury in the neonatal rat brain after intracerebral injection of lipopolysaccharide. Brain Res Dev Brain Res 140:205214. Partridge SC, Mukherjee P, Berman JI, Henry RG, Miller SP, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2005) Tractography-based quantitation of diffusion tensor imaging parameters in white matter tracts of preterm newborns. J Magn Reson Imaging 22:467-474. Partridge SC, Vigneron DB, Charlton NN, Berman JI, Henry RG, Mukherjee P, McQuillen PS, Karl TR, Barkovich AJ, Miller SP (2006) Pyramidal tract maturation after brain injury in newborns with heart disease. Ann Neurol 59:640651. Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2004) Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. Neuroimage 22:1302-1314. Segovia KN, McClure M, Moravec M, Luo NL, Wan Y, Gong X, Riddle A, Craig A, Struve J, Sherman LS, Back SA (2008) Arrested oligodendrocyte lineage maturation in chronic perinatal white matter injury. Ann Neurol 63:520-530. Shah DK, Doyle LW, Anderson PJ, Bear M, Daley AJ, Hunt RW, Inder TE (2008) Adverse neurodevelopment in preterm infants with postnatal sepsis or necrotizing enterocolitis is mediated by white matter abnormalities on magnetic resonance imaging at term. J Pediatr 153:170-175, 175 e171. 58  Stoll BJ, Hansen NI, Adams-Chapman I, Fanaroff AA, Hintz SR, Vohr B, Higgins RD (2004) Neurodevelopmental and growth impairment among extremely low-birthweight infants with neonatal infection. Jama 292:2357-2365. Toussaint N, Souplet J, Fillard P (2007) MedINRIA: DT-MRI processing and visualization software. In: Proc. of MCCCAI'07 Workshop on Interaction in Medical Image Analysis and Visualization. Brisbane, Australia. Volpe J (2001) Neurology of the Newborn, 4th Edition. Philadelphia: W.B. Saunders. Volpe JJ (2009) Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol 8:110-124. Woodward LJ, Anderson PJ, Austin NC, Howard K, Inder TE (2006) Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. N Engl J Med 355:685694. Yeh TF, Lin YJ, Lin HC, Huang CC, Hsieh WS, Lin CH, Tsai CH (2004) Outcomes at school age after postnatal dexamethasone therapy for lung disease of prematurity. N Engl J Med 350:1304-1313.  59  Appendix I: Comparison of FA and D av trajectories from first to second scan in neonates with and without moderate to severe MRI abnormalities On the first scan, 12 neonates with normal MRIs had FA values below the mean; FA remained below average in 9 neonates and returned above the mean in 3 on the second scan. The proportion of neonates with FA values remaining below the mean on the second scan did not significantly differ in neonates with abnormal-MRI: FA on the second scan remained below the mean in 6 of 10 neonates and returned to higher levels in 4 of them (interaction term P=0.7). Dav values higher than the mean were found in 15 neonates with normal MRIs on the first scan; Dav on the second scan remained higher than the mean in 7 neonates and were lower in 9. The proportion of neonates with Dav values remaining above the mean on the second scan This did not differ in neonates with abnormal-MRI (interaction term P=0.4); 6 of 9 neonates with high Dav on the first scan remained high in the second, and decreased to below average Dav levels in 3 neonates.  60  Appendix II: University of British Columbia Research Ethics Board Certificate of Approval  61  Page 1 of 2  The University of British Columbia Office of Research Services Clinical Research Ethics Board – Room 210, 828 West 10th Avenue, Vancouver, BC V5Z 1L8  ETHICS CERTIFICATE OF EXPEDITED APPROVAL: RENEWAL WITH AMENDMENTS TO THE STUDY PRINCIPAL INVESTIGATOR:  DEPARTMENT:  UBC CREB NUMBER: H05-70579  Steven Paul Miller  INSTITUTION(S) WHERE RESEARCH WILL BE CARRIED OUT: Institution  Site  Children's and Women's Health Centre of BC (incl. Sunny Hill)  Children's and Women's Health Centre of BC (incl. Sunny Hill)  Other locations where the research will be conducted:  N/A  CO-INVESTIGATOR(S): Alan Hill Anne Synnes Ruth E. Grunau Vesna Popovska Kenneth J. Poskitt Norbert Froese  SPONSORING AGENCIES: - Canadian Institutes of Health Research (CIHR) - "Abnormal Brain Development in Premature Newborns" - Canadian Institutes of Health Research (CIHR) - "Abnormal Brain Development in Premature Newborns: Risk Factors and Neurodevelopmental Outcome"  PROJECT TITLE: Abnormal Brain Development in Premature Newborns: Risk Factors and Neurodevelopmental Outcome The current UBC CREB approval for this study expires: December 8, 2009 AMENDMENT(S): Document Name  Version  Date  N/A  November 28, 2008  AMENDMENT APPROVAL DATE: December 8, 2008  Consent Forms: Premie study consent form  CERTIFICATION: In respect of clinical trials: 1. The membership of this Research Ethics Board complies with the membership requirements for Research Ethics Boards defined in Division 5 of the Food and Drug Regulations. 2. The Research Ethics Board carries out its functions in a manner consistent with Good Clinical Practices. 3. This Research Ethics Board has reviewed and approved the clinical trial protocol and informed consent form for the trial which is to be conducted by the qualified investigator named above at the specified clinical trial site. This approval and the views of this Research Ethics Board have been documented in writing. The Chair of the UBC Clinical Research Ethics Board has reviewed the documentation for the above named project. The research study, as presented in the documentation, was found to be acceptable on ethical grounds for research involving human subjects and was approved for renewal by the UBC Clinical Research Ethics Board.  Approval of the Clinical Research Ethics Board by :  62 https://rise.ubc.ca/rise/Doc/0/TKGPAGHQ99G4T7IENN804VRU68/fromString.html  12/8/2008  

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