Science, Irving K. Barber Faculty of (Okanagan)
Computer Science, Mathematics, Physics and Statistics, Department of (Okanagan)
DSpace
UBCO
Kunkyab, Tenzin
Doctor of Philosophy - PhD
University of British Columbia
Radiation therapy is used to treat various types of cancers. The technologies in radiation delivery continue to advance rapidly. Currently, we are able to accurately target a radiation beam to a tumour volume by conforming the shape of the beam to the complex tumour shape. However, with that, there is a need for radiation dose detection tools that accurately capture the complex dose distribution in 3D space in order to verify the accuracy and precision of a treatment delivery. The purpose of this work is to implement a promising solution to this clinical challenge that utilizes a 3D NIPAM polymer gel dosimetry system with CBCT readout to verify the dosimetric and spatial accuracy of stereotactic radiosurgery (SRS) and spatially fractionated radiotherapy (SFRT) technique. Three main objectives of this work are 1) to evaluate the reproducibility of a NIPAM gel dosimetry workflow between two institutions, by implementing three identical verification plans in order to demonstrate its wide scale applicability in commissioning advanced radiotherapy techniques. In the study, two separate gel analysis pipelines were utilized based on the individual institution’s preference. 2) to commission two SRS techniques; HyperArc® (Varian Medical Systems, Palo Alto CA) to treat brain metastases and a virtual cone technique to treat trigeminal neuralgia. In the virtual cone study, an end-to-end spatial accuracy test of the treatment delivery was performed using a 3D printed anthropomorphic phantom. The dosimetric accuracy of the gel dosimetry system was benchmarked against a gold standard, film dosimeter. 3) utilizing a traditional dosimeter solely to verify the treatment delivery accuracy of SFRT is incredibly challenging and inefficient due to the heterogenous dose distribution generated in three-dimensional space. Therefore, goal of the final study is to demonstrate the application of the gel dosimetry system to commission SFRT technique. A semi-automated SFRT planning approach was utilized to generate a verification plan on a gel dosimeter for analysis. This work presents novel applications of a gel dosimetry workflow in two advanced radiotherapy deliveries (SRS and SFRT). The dosimetric and spatial accuracy with this type of gel dosimetry analysis is invaluable for the clinical commissioning process.
CLINICAL APPLICATIONS OF 3D POLYMER GEL DOSIMETRY WITH CONE-BEAM COMPUTED TOMOGRAPHY READOUT IN DOSIMETRIC AND SPATIAL ACCURACY VERFICATION by Tenzin Kunkyab MSc., The University of British Columbia, 2020 BSc., Maastricht University, 2017 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE COLLEGE OF GRADUATE STUDIES (MEDICAL PHYSICS) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) July 2024 © Tenzin Kunkyab, 2024 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, the dissertation entitled: CLINICAL APPLICATIONS OF 3D POLYMER GEL DOSIMETRY WITH CONE-BEAM COMPUTED TOMOGRAPHY READOUT IN DOSIMETRIC AND SPATIAL ACCURACY VERFICATION submitted by Tenzin Kunkyab in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Medical Physics Examining Committee: Dr. Andrew Jirasek, I. K. Barber School of Arts & Sciences Supervisor Dr. Derek Hyde, I.K. Barber School of Arts & Sciences Supervisory Committee Member Dr. Jeff Andrews, I. K. Barber School of Arts & Sciences Supervisory Committee Member Dr. Nathan Becker, I. K. Barber School of Arts & Sciences Supervisory Committee Member Dr. Zheng Liu, School of Engineering University Examiner Dr. Chris Thomas, Department of Radiation Oncology, Dalhousie University External Examiner iii Abstract Radiation therapy is used to treat various types of cancers. The technologies in radiation delivery continue to advance rapidly. Currently, we are able to accurately target a radiation beam to a tumour volume by conforming the shape of the beam to the complex tumour shape. However, with that, there is a need for radiation dose detection tools that accurately capture the complex dose distribution in 3D space in order to verify the accuracy and precision of a treatment delivery. The purpose of this work is to implement a promising solution to this clinical challenge that utilizes a 3D NIPAM polymer gel dosimetry system with CBCT readout to verify the dosimetric and spatial accuracy of stereotactic radiosurgery (SRS) and spatially fractionated radiotherapy (SFRT) technique. Three main objectives of this work are 1) to evaluate the reproducibility of a NIPAM gel dosimetry workflow between two institutions, by implementing three identical verification plans in order to demonstrate its wide scale applicability in commissioning advanced radiotherapy techniques. In the study, two separate gel analysis pipelines were utilized based on the individual institution’s preference. 2) to commission two SRS techniques; HyperArc® (Varian Medical Systems, Palo Alto CA) to treat brain metastases and a virtual cone technique to treat trigeminal neuralgia. In the virtual cone study, an end-to-end spatial accuracy test of the treatment delivery was performed using a 3D printed anthropomorphic phantom. The dosimetric accuracy of the gel dosimetry system was benchmarked against a gold standard, film dosimeter. 3) utilizing a traditional dosimeter solely to verify the treatment delivery accuracy of SFRT is incredibly challenging and inefficient due to the heterogenous dose distribution generated in three-dimensional space. iv Therefore, goal of the final study is to demonstrate the application of the gel dosimetry system to commission SFRT technique. A semi-automated SFRT planning approach was utilized to generate a verification plan on a gel dosimeter for analysis. This work presents novel applications of a gel dosimetry workflow in two advanced radiotherapy deliveries (SRS and SFRT). The dosimetric and spatial accuracy with this type of gel dosimetry analysis is invaluable for the clinical commissioning process. v Lay Summary Over the last four decades, radiation therapy technologies in treatment delivery and treatment planning improved rapidly. Currently, the shape of the radiation beam can be matched to the shape of the targeted tumour volume in treatment planning and delivery, such that radiation to the surrounding normal tissue is minimized as much as possible. In cancer clinics, it is routine but also essential to verify the treatment delivery utilizing radiation dose detection equipment (dosimeters) prior to the actual patient treatment. Traditional point dose and planar dose measurements are inefficient to capture the entirety and complexity of the dose information in three-dimensional space. Therefore, the purpose of this work is to utilize a 3D polymer gel dosimeter to capture the complex 3D dose distribution, ultimately to verify the accuracy of the radiotherapy delivery. vi Preface The work presented in this PhD dissertation was performed under the direct co-supervision of Dr. Derek Hyde and Dr. Andrew Jirasek. The supervisory committee members include Dr. Nathan Becker and Dr. Jeff Andrews, whose guidance were invaluable. The funding for this work was provided by the Moss Rock Park and BC Cancer Foundation. No generative artificial intelligence (AI) was used in this work. Chapter 4 of the dissertation presented a dual-institutional collaborative study with Duke University. It is published in the Physics in Medicine and Biology, Volume 69, page 15. The submitted work is titled “Clinical applicability of Linac-integrated CBCT based NIPAM 3D dosimetry: a dual-institutional investigation” co-authored by Tenzin Kunkyab, Kawtar Lakrad, Dr. Andrew Jirasek, Dr. Mark Oldham, Benjamin Quinn, Dr. Derek Hyde, and Dr. Justus Adamson. Kawtar and I were responsible for the gel fabrication, radiation delivery, analysis at the individual institution, and manuscript writing. Dr. Hyde and Dr. Adamson generated the verification plans at the individual institutions and supervised all the gel experiments. Dr. Jirasek and Dr. Oldham supervised the entire work with their gel expertise. Benjamin supervised the Duke University collaborators regarding the VisaAce gel dosimetry analysis tool. All authors contributed to manuscript revision. Chapter 5 of the dissertation was published in the Journal of Physics: Conference series, titled “Spatial and Dosimetric accuracy of 3D polymer gel with CBCT readout-Varian HyperArc® SRS implementation”. I was responsible for the gel fabrication, experiment, analysis, and interpretation. vii Dr. Hyde created the SRS verification plan, supervised the gel experiment, assisted in the interpretation of the results. Dr. Hyde, Dr. Jirasek and Dr. Hilts supervised the first author. All authors contributed to manuscript revision. Chapter 6 of the dissertation is currently under review in the Journal of Applied Clinical Medical Physics. The submission is titled “Dosimetric verification and Spatial accuracy of a virtual cone technique for trigeminal neuralgia radiosurgery using Acuros (XB Version 18.0) and polymer gel dosimetry”. The research was conducted by the following co-authors: Tenzin Kunkyab, Dr. Michael Lamey, Dr. Andrew Jirasek, Dr. Nathan Becker, Dr. Michael Kudla, Dr. Benjamin Mou, and Dr. Derek Hyde. I was responsible for the gel fabrication, experiment (gel and film), analysis (gel and film), and manuscript writing. Dr. Hyde supervised all the gel and film experiments and interpretation of the result. Dr. Lamey created the C# code using Eclipse scripting API for the virtual cone treatment. Dr. Jirasek provided guidance for the gel experiment, analysis, and interpretation. Dr. Becker and Dr. Mou provided guidance to the authors with their clinical expertise. Dr. Michael Kudla assisted in the entire 3D printing process. All authors contributed to the manuscript revision. Chapter 7 of the dissertation is accepted and will be available in the Journal of Applied Clinical Medical Physics. The title of the accepted work is “Semi-automated vertex placement for lattice radiotherapy and dosimetric verification using 3D polymer gel dosimetry”. The work presented the application of a semi-automated vertices placement tool to improve efficiency of spatially fractionated radiotherapy (SFRT) planning workflow. I led the entire project, assisted in SFRT radiotherapy planning, fabricated the gel, conducted the experiments, and performed the study viii specific gel analysis. Dr. Hyde assisted in creating the verification plan and supervised the gel experiment. Dr. Jirasek and Dr. Mou supervised the authors in gel and clinical expertise respectively. Anthony Magliari and Pierre Lansonneur (both from Varian) assisted the author in getting started with the SFRT tool. All authors contributed to the manuscript revision. ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ......................................................................................................................... ix List of Tables .............................................................................................................................. xiv List of Figures ...............................................................................................................................xv List of Abbreviations ................................................................................................................. xix Acknowledgements .................................................................................................................... xxi Dedication ................................................................................................................................. xxiii Chapter 1: Introduction: Radiation Therapy .............................................................................1 1.1 Brief Overview of Radiation Therapy and its clinical workflow ................................... 1 1.2 Radiotherapy in the modern era ...................................................................................... 4 1.3 Stereotactic Radiosurgery (SRS) .................................................................................... 7 1.3.1 SRS clinical workflow ............................................................................................ 7 1.3.2 SRS for intracranial metastases .............................................................................. 9 1.3.3 SRS in Trigeminal Neuralgia ................................................................................ 10 1.4 Spatially Fractionated Radiotherapy (SFRT)................................................................ 12 1.5 Dosimetric verification and geometric precision of a treatment delivery..................... 15 1.6 Thesis Scope ................................................................................................................. 15 Chapter 2: Radiation Dosimetry ................................................................................................17 2.1 Brief Overview of Radiation Dosimetry ....................................................................... 17 x 2.2 Radiation Dosimeters .................................................................................................... 18 2.2.1 Point Dose Measurement ...................................................................................... 18 2.2.2 Planar Dose Measurement .................................................................................... 20 2.2.2.1 EBT-XD Film Dosimeters ................................................................................ 20 2.2.3 3D Volume Dose Measurement ............................................................................ 22 2.2.3.1 NIPAM Polymer Gel Dosimeter Overview ...................................................... 24 2.2.3.2 NIPAM Polymer Gel Dosimetry with X-Ray CT Readout .............................. 26 2.2.3.3 NIPAM Polymer Gel Dosimetry with CBCT Readout..................................... 30 Chapter 3: Material and Methods: Brief Overview of 3D Polymer Gel Dosimetry Pipeline........................................................................................................................................................35 3.1 Polymer Gel Dosimeter fabrication .............................................................................. 35 3.2 Polymer Gel Dosimeter irradiation and CBCT readout ................................................ 37 3.3 Polymer Gel Dosimetry analysis .................................................................................. 38 Chapter 4: Dual-institutional reproducibility study .................................................................40 4.1 Introduction ................................................................................................................... 41 4.2 Material and Methods ................................................................................................... 44 4.2.1 Treatment planning ............................................................................................... 44 4.2.2 Gel fabrication ...................................................................................................... 45 4.2.3 Gel Irradiation ....................................................................................................... 46 4.2.4 Gel readout with Linac Integrated-CBCT............................................................. 46 4.3 Results ........................................................................................................................... 50 4.3.1 3 Field ................................................................................................................... 50 4.3.2 C-shape spine plan ................................................................................................ 52 xi 4.3.3 4-targets Stereotactic Radiosurgery ...................................................................... 54 4.3.4 Signal-to-noise ratio comparison and image averages.......................................... 57 4.4 Discussion ..................................................................................................................... 58 4.5 Conclusion .................................................................................................................... 65 Chapter 5: HyperArc® commissioning with 3D Polymer Gel Dosimetry ..............................66 5.1 Introduction ................................................................................................................... 66 5.2 Methods......................................................................................................................... 67 5.2.1 Gel fabrication ...................................................................................................... 67 5.2.2 Treatment planning ............................................................................................... 68 5.2.3 Irradiation .............................................................................................................. 68 5.2.4 Image processing .................................................................................................. 70 5.2.5 Dose analysis ........................................................................................................ 70 5.2.6 Spatial accuracy analysis ...................................................................................... 71 5.3 Results ........................................................................................................................... 71 5.3.1 3D gamma analysis ............................................................................................... 71 5.3.2 Spatial accuracy analysis ...................................................................................... 72 5.4 Discussion ..................................................................................................................... 72 5.5 Conclusion .................................................................................................................... 73 Chapter 6: SRS Virtual cone commissioning with 3D Polymer Gel Dosimetry ....................74 6.1 Introduction ................................................................................................................... 75 6.2 Material and Methods ................................................................................................... 78 6.2.1 Implementation of the virtual cone technique ...................................................... 78 6.2.2 Treatment planning and delivery .......................................................................... 79 xii 6.2.3 EBT-XD film analysis .......................................................................................... 80 6.2.4 Gel Dosimetry workflow ...................................................................................... 81 6.2.4.1 Gel Fabrication.................................................................................................. 81 6.2.4.2 Gel readout and analysis ................................................................................... 82 6.2.4.3 3D printed anthropomorphic skull phantom ..................................................... 85 6.3 Results ........................................................................................................................... 86 6.3.1 EBT-XD film analysis .......................................................................................... 86 6.3.2 3D Gel dosimetry analysis .................................................................................... 88 6.3.3 End-to-End Spatial accuracy test with 3D anthropomorphic phantom and IGRT setup ............................................................................................................................... 90 6.4 Discussion ..................................................................................................................... 92 6.5 Conclusion .................................................................................................................... 96 Chapter 7: Semi-automated Vertex placement for SFRT and dosimetric verification using 3D Polymer Gel Dosimetry .........................................................................................................98 7.1 Introduction ................................................................................................................... 99 7.2 Material and Methods ................................................................................................. 101 7.2.1 Automated vertices placement ............................................................................ 101 7.2.2 SFRT planning .................................................................................................... 101 7.2.3 Gel dosimeter fabrication .................................................................................... 102 7.2.4 Gel irradiation, readout and analysis .................................................................. 103 7.3 Results ......................................................................................................................... 104 7.4 Discussion ................................................................................................................... 111 7.5 Conclusion .................................................................................................................. 113 xiii Chapter 8: Conclusion and Future Work ................................................................................115 8.1 Research Conclusions ................................................................................................. 115 8.2 Future Work ................................................................................................................ 118 Bibliography ...............................................................................................................................119 Appendices ..................................................................................................................................146 Appendix A ............................................................................................................................. 146 Appendix B : Details of dosimeter calibration ....................................................................... 147 Appendix C ............................................................................................................................ 151 Appendix D ............................................................................................................................. 153 Appendix E VistaAce Software Gamma Index Plots for both institutions ............................. 155 Appendix F ............................................................................................................................. 160 Appendix G ............................................................................................................................. 161 xiv List of Tables Table 1. Typical NIPAM gel dosimeter formulation.123 ............................................................... 28 Table 2. Image acquisition parameter and its relationship with CT image noise (σN) in PAGAT gel dosimeter.121 ............................................................................................................................ 29 Table 3. Selected Dosimeter Characteristics. ............................................................................... 33 Table 4. The 10 Gy isodose width of profile along sagittal plane (anterior-posterior and superior-inferior), coronal plane (left-right and sup-inf) using EBT-XD film dosimeter. .......................... 88 Table 5. Presents the 50% isodose width of the profile across Axial plane (anterior-posterior), Axial plane (left-right), and coronal plane (superior-inferior) using the 3D gel dosimetric analysis. ......................................................................................................................................... 90 Table 6. Equivalent diameter of the 10 Gy isodose region in the 3D printed anthropomorphic gel experiment in mm ......................................................................................................................... 91 Table 7. Presents the equivalent diameter of the isodose volume of the prescription dose (20 Gy) in Eclipse plan and Gel image volume. The Center of Mass distance between the planned vertex and measured is also shown. The percent error was calculated based on the normalized difference between the Eclipse plan and the gel measurement. .................................................. 110 xv List of Figures Figure 1. a.) A Varian Truebeam Linear Accelerator (Linac) b.) High-Definition Multileaf Collimator (HDMLC) ..................................................................................................................... 3 Figure 2. A standard radiotherapy workflow in cancer clinic. ....................................................... 4 Figure 3. Illustrates the frameless approach to patient immobilization during SRS treatment delivery. .......................................................................................................................................... 8 Figure 4. Illustrates a generic design of an ionization chamber dosimeter. .................................. 19 Figure 5. EBT-XD film design. .................................................................................................... 21 Figure 6. Illustrates the setup for gel fabrication. ......................................................................... 36 Figure 7. Left (1 L gel jar), Right (2 L gel jar). ............................................................................ 37 Figure 8. Illustrates the Linac integrated kV-CBCT in position for gel dosimetry imaging. ....... 38 Figure 9. Illustrates the workflow of the two institutions. The gel fabrication, treatment plan and gel irradiation were kept constant. The analysis of the PGD were different based on the preference of the institution. Box A and B represents the individual workflow since the CBCT image is already inherently registered with the planned dose, while it was performed in Institution A’s workflow because the dose was calculated on CT scan of the dosimeter instead of a CBCT. ........................................................................................................................................ 47 Figure 10. Central axial slices from the TPS (Planned slice), and the post-irradiation CBCT (Measured slice), comparing the 3-field irradiation isodose lines from both institutions. ........... 51 Figure 11. Scatter plot of 3D gamma pass percent set to 2 mm DTA and 10% dose threshold, and gamma maps of the 2%2mm criteria for both institutions. ........................................................... 52 xvi Figure 12. Illustrates: 1) a central axial slice of the AAPM TG-119 C-shape treatment plan and the isodose line to be delivered from Eclipse TPS (Top-Bottom left) 2) the isodose lines of the measured data from both institutions (Top-Bottom right). ........................................................... 53 Figure 13. Scatter plot of 3D gamma pass percent set to 2 mm DTA and 10% dose threshold, and gamma maps of the 2%2mm criteria for both institutions. ........................................................... 54 Figure 14. Illustrates: 1) a central coronal slice of the SRS treatment plan to be delivered from Eclipse TPS (Top left), 2) a central coronal slice of the post-irradiation CBCT of the dosimeter (Bottom left), 3) the scatter plot of the 3D gamma pass percent, and 4) Central coronal slices representing the isodose lines of the measured data from both institutions (Top-Bottom right). 55 Figure 15. Line profiles comparison: 4 targets SRS treatment plan (Institution A) .................... 57 Figure 16. SNR vs image averages plot with and without image processing in both institution A and B in C-shape treatment plan ................................................................................................... 58 Figure 17. Illustrates the experimental set-up for the PGD irradiation and imaging. ................... 69 Figure 18. a.) Illustrates the dose profile along x = 120, y = 130, and diagonal direction through the 2 out of the three targets. 2.b.) The dose profile on the image slice containing the third target (1 cm), along x = 62, y = 91 horizontal and vertical profile. The color bar represents the dose in Gy. ................................................................................................................................................. 71 Figure 19. All panels illustrate the gel experiment set-up for the dosimetric analysis containing a verification plan with virtual cone and calibration region is shown from different views. .......... 82 Figure 20. a.) Shows the 3D printed anthropomorphic skull phantom setup. b.) The virtual cone plan generated on the planning CT of the skull phantom is shown. ............................................. 84 xvii Figure 21. Illustrates the dose profile along the a.) sagittal plane (anterior-posterior), b.) coronal plane (left-right), c.) coronal plane (superior-inferior), and d) sagittal plane (superior-inferior) with EBT-XD film and the v18.0 verification plan. ..................................................................... 87 Figure 22. Individual Gel. Illustrates the dose profile along the a.) Axial plane (anterior-posterior), b.) Axial plane (left-right), c.) coronal plane (superior-inferior) using the 3D gel dosimetric analysis. ....................................................................................................................... 89 Figure 23. Gel within Anthropomorphic phantom with CBCT setup Illustrates the line profile across the maximum dose of the eclipse verification plan: a.) Axial plane (anterior-posterior) b.) Axial plane (left-right) c.) coronal plane (superior-inferior). ....................................................... 90 Figure 24. a.) Gel image after averaging and background subtraction. b.) Filtered image with image processing. c.) The final calibrated image. The colormap indicates dose in Gy. ............... 92 Figure 25. a.) Presents the 2 L gel phantom set up, 1b.) dosimetric calibration curve obtained from a central slice. ..................................................................................................................... 104 Figure 26. a.) Illustrates the 3D visualization of Eclipse plan and b.) Gel. The color bar represents the dose in Gy. ........................................................................................................... 105 Figure 27. a.) Demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in transverse plane (anterior-posterior). ............................... 106 Figure 28. a.) demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in transverse plane (left-right). ............................................. 107 Figure 29. a.) demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in coronal plane (superior-inferior). ..................................... 108 Figure 30. a.) demonstrates a diagonal profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile in transverse plane .......................................................................... 108 xviii Figure 31. a.) illustrates the 2D isodose map of a central slice of the Eclipse plan and b.) Gel. 109 Figure 32. Presents the scatter plot of the 3D global gamma pass percent as a function of distance to agreement in mm. ................................................................................................................... 111 xix List of Abbreviations SRS-Stereotactic Radiosurgery SFRT-Spatially Fractionated Radiotherapy LRT-Lattice Radiotherapy SABR-Stereotactic Ablative Radiotherapy VMAT-Volumetric Modulated Arc Therapy IMRT-Intensity Modulated Radiation Therapy MBRT-Minibeam Radiotherapy MRT-Microbeam Radiation Therapy CT-Computed Tomography CBCT-Cone Beam Computed Tomography MRI-Magnetic Resonance Imaging OCT-Optical Computed Tomography LINAC-Linear Accelerator PGD-Polymer Gel Dosimeter NIPAM-N-isopropylacrylamide BIS or MBA-N-N’methylenebisacrylamide THPC-Tetrakis Hydroxymethyl Phosphonium Chloride (THPC) PTV-Planning Target Volume NSCLC-Non-Small-Cell Lung Cancer PAG-Polyacrylamide Acid Gelatin DNA-Deoxyribonucleic Acid xx OAR-Organ At Risk MLC-MultiLeaf Collimator DLG-Dosimetric Leaf Gap SNR-Signal-to-noise ratio RAR-Remnant artefact removal TN-Trigeminal Neuralgia MU-Monitor Units COM-Center of Mass HU-Hounsfield Unit E2E-End-to-End FFF-Flattening Filter Free DVH-Dose Volume Histogram ESAPI-Eclipse Scripting Application Programming Interface xxi Acknowledgements First and foremost, I’d like to thank the Medical Physics graduate program at UBCO, BC Cancer Kelowna, and the Dalai Lama foundation (Gaden Phodrang Foundation) for facilitating the last six years of my graduate studies. The supportive network of faculties at UBCO and BC Cancer Kelowna have had tremendous impact throughout my PhD journey. I’d like to give special thanks to the following group of people: the medical physics faculty at UBCO, the Medical Physics students, my PhD and master’s supervisory committee (Dr. Nathan Becker, Dr. Jeff Andrews, and Dr. Christina Haston), BC Cancer clinical staffs and our research collaborators. I would like to thank Jakob Marshall for helping me become acquainted with the gel dosimetry analysis in MATLAB in the early stages of my PhD. My first project, which was a collaboration with Duke University, was only successful because of Kawtar Lakrad, Dr. Mark Oldham, and Dr. Justus Adamson. I am very grateful for their time, patience, and expertise when we faced numerous roadblocks and challenges in performing this dual-institutional study. Their approach to understanding and solving those problems were incredibly inspiring to me. My second work in virtual cone commissioning was only fruitful because of the assistance from Dr. Tony Teke, Dr. Michael Kudla and Mark Robinson. Dr. Teke’s expertise and guidance in film dosimetry was instrumental in successfully commissioning the virtual cone technique. Dr. Kudla and Mark spent countless hours helping me in the 3D printing process of our “Logan 2.0” phantom, a name bestowed by Dr. Derek Hyde. I’d also like to thank Dr. Michael Lamey, Dr. Nathan Becker and Dr. Benjamin Mou for their supervision and guidance in this research. xxii My last work is on an implementation of a spatially fractionated radiotherapy workflow. For this, I’d like to give many thanks to Anthony Magliari and Pierre Lansonneur, both from Varian, who assisted me in getting started with their open-source SFRT tool. We utilized their tool and combined our gel expertise to design the final study for my PhD. I am eternally grateful to my two supervisors, Dr. Derek Hyde, and Dr. Andrew Jirasek. I vividly remember starting my master’s studies in medical physics with an overwhelming feeling of self-doubt in my ability to successfully complete the program. I am not exaggerating if I were to say that I am only here at this last stage of my PhD because of their kind, consistent guidance, and support. I am indebted to both of you, and I’ve thoroughly enjoyed being your graduate student for the last 5 years. Lastly, I extend my deepest gratitude to Dr. Hyde for showing me what it means to be a holistic clinical medical physicist through his daily actions. Our conversations during the gel experiments have extended beyond the boundaries of medical physics, often circling back to topics such as snowboarding and life in general, which I have thoroughly enjoyed. I am truly humbled to be his first master’s and PhD student. xxiii Dedication To my parents, my late father, Nawang Lobsang and my mother, Tsamchoe Dolma, whose unwavering love and support have shaped my life in profound ways. Despite never having received a single English lesson themselves, they have gone above and beyond to ensure that my four sisters and I receive the best modern education available. To my sisters, who have been the pillars for my emotional and financial support, serving as unwavering champion during both joyful and difficult times. I am also grateful to the people whom I have met and became close friends since my departure for boarding school at the age of 11. Quite often they became my second family. I dedicate this work to each one of you. 1 Chapter 1: Introduction: Radiation Therapy The purpose of this research is to implement a polymer gel dosimetry workflow in order to commission two complex radiotherapy techniques in the clinic. A recently proposed polymer gel dosimetry readout method utilizing Linac-integrated cone-beam computed tomography (CBCT) was utilized in this work due to its high spatial accuracy attributes. Commissioning high dose radiotherapy techniques such as stereotactic radiosurgery (SRS) and spatially fractionated radiotherapy (SFRT) with the currently established dosimeters present complex challenges in accurately verifying the dosimetric and spatial accuracy in three-dimensional space. Thus, the intrinsic three-dimensional nature of polymer gel dosimeter combined with the high spatial accuracy attributes of the CBCT readout method, provides a promising solution to the difficult clinical challenges mentioned above. Chapter 1 introduces radiation therapy, two relevant treatment techniques pertaining to the study, and the scope of this thesis. Section 1.1 presents an overview of radiation therapy and its clinical workflow. Section 1.2 describes some of the advancements in radiation therapy treatment planning strategies in the modern era pertaining to the thesis. Section 1.3 and 1.4 presents SRS and SFRT techniques respectively. Section 1.5 introduces dosimetric and spatial accuracy of a radiotherapy workflow, and lastly section 1.6 presents the scope and outline of the thesis. 1.1 Brief Overview of Radiation Therapy and its clinical workflow Surgery, chemotherapy, and radiation therapy are the three most important methods to treat various types of cancers.1 Surgery is the oldest method, involving an invasive procedure where an incision 2 either partially or fully removes the cancer or tumour from the patient’s body.2 Chemotherapy is the use of cytotoxic drugs that interferes with the abnormal cell replication found in cancerous tissue.3 Radiation therapy or radiotherapy utilizes high energy ionizing radiation to target and kill the tumour cells, while sparing the surrounding healthy tissue.4 The ionizing radiation interferes with the tumour replication mechanisms by either directly or indirectly, by forming intermediatory free radicals that break the DNA (Deoxyribonucleic acid) strands, ultimately leading to tumour cell death.5 Essentially, the goal of a radiation therapy is to utilize the preferential effects of radiation in killing the cancer cells, thereby treating the disease and potentially prolonging the patients’ lives.6 Radiotherapy is currently a well-established treatment technique for many types of cancers. It is often regarded as a standalone treatment method or combined with invasive surgical techniques and chemotherapy. Radiotherapy is also effectively delivered with a palliative intent.5 Around 50% of all cancer patients eventually receives a form of radiation therapy during their treatment, either as a standalone treatment or in combination with chemotherapy or surgical methods.7 Owing to the differences in the modes of radiation delivery, radiotherapy is typically divided into two sub-categories: Internal radiation therapy (Brachytherapy) and External beam radiotherapy (EBRT). Brachytherapy is a specialized radiotherapy technique where radioactive sources are precisely placed directly on or next to the tumour target.8 External beam radiotherapy, on the other hand, is typically delivered from outside of a patient using a medical linear accelerator (Linac) or Cobalt-60 (GammaKnife) that precisely directs the radiation beam to the tumour target (Figure 1a). 3 Figure 1. a.) A Varian Truebeam Linear Accelerator (Linac) b.) High-Definition Multileaf Collimator (HDMLC) A standard external beam radiation treatment workflow is briefly summarized in figure 2.9 This workflow typically begins with patient simulation using a computed tomography (CT) imaging. The patient is placed on the CT couch in a position that is identical to the actual treatment on a Linac. High-resolution 3D images are acquired and then subsequently used for treatment planning purposes. The radiation oncologist utilizes the 3D CT image of the patient to design and generate a personalized radiotherapy plan.10 In the treatment planning stage, the radiation oncologist contours the planning target volume (PTV) and the surrounding organs at risk (such as the lung, heart, spinal cord, bladder, and rectum etc.). The PTV contour comprises of the tumour volume and additional margins that accounts for the microscopic spread of the disease, machine and patient positioning uncertainty, as well as tumour motion when applicable.11 A treatment plan is then devised and optimized such that the radiation dose distribution to the PTV is highly conformal and 4 the dose to the surrounding normal tissue is minimized. When the treatment planning is completed, the radiation therapy treatment is delivered using the Linac. A conventional Linac uses high-energy X-ray beams, focused by variety of collimation techniques, including multileaf collimators (MLC) (Figure 1b) that conforms the radiation beam to the tumour. Figure 2. A standard radiotherapy workflow in cancer clinic. 1.2 Radiotherapy in the modern era In the last four decades, the radiotherapy technologies in treatment planning and delivery have evolved substantially. Invention of CT in 1967 led the development of treatment planning on a three dimensional image of the patient anatomy in the mid 1980s.12,13 Introduction of cone-beam CT on Linacs in the early 2000s provided a tool to verify patient position before or during the radiotherapy.14 These advancements in the field led to a widespread utilization of radiotherapy delivery strategies (SRS, SABR, SFRT (emerging technique)) that are extremely precise, demonstrated to be safe, and result in favorable clinical outcomes. 5 In this section, some of the recent developments in modern radiotherapy planning strategies are highlighted: • Volumetric-modulated arc therapy (VMAT): VMAT, developed by Karl Otto in 2008, is an inverse treatment planning optimization method where the treatment planner decides on the desired dose distribution and the planning software generates the group of beam parameters.15 VMAT delivery is continuous while the Linac gantry rotates around the patient in a single 360° arc, thus, it is associated with reduced treatment time due to the continuous radiation delivery and has the capability of generating highly conformal and complex dose distribution.16 VMAT is utilized in multiple treatment sites including lung, breast, colorectal, and brain.17 • Stereotactic Radiosurgery (SRS) and Fractionated Stereotactic Radiotherapy (FSRT): Advancements in radiotherapy technologies (high-resolution 3D imaging, image-guided radiotherapy, patient immobilization etc.)18 and treatment planning workflow (treatment planning software, advanced dose calculation algorithm etc.) led to a widespread utilization of the SRS technique. SRS technique uses a high radiation dose in one fraction to ablate the tumour or lesions found in an intracranial environment, for example, 24, 18, 15 Gy in single fraction for tumour size less than 20, 21-30, 31-40 mm, respectively, as outlined in the Radiation Therapy Oncology Group (RTOG) study.19 A fractionated stereotactic radiotherapy (FSRT), on the other hand, utilizes 2-5 fractions, for example, 27 Gy in 3 fractions for brain metastases measuring 2 to 3 cm diameter.20,21 FSRT takes the advantages of normal tissue repair between the treatment fractions to allow acceptable toxicity in the surrounding tissue.22 Both methods of dose delivery significantly reduces 6 the overall treatment time and alleviates patient comfort. SRS and FSRT technique utilizes small beam sizes to reduce the radiation dose outside of the treatment area, i.e. healthy tissues of the brain.23,24 Generally, SRS is typically used to treat multiple brain metastases, spine metastases, but also for other neurological conditions such as trigeminal neuralgia (TN).25 • Stereotactic Ablative Radiotherapy (SABR): Similar to SRS, SABR utilizes higher dose per fraction, for example, 12 Gy per fraction, total dose 54 to 60 Gy for peripheral lung tumours)18 compared to the conventional radiotherapy, for example, 2-2.75 Gy per fraction, total dose 54 Gy to 74 Gy for peripheral lung tumours) to treat extracranial tumours.18 Consequently, the treatment is completed in fewer fractions (3-5 fractions).18,26 SABR is also associated with high tumour control and improved treatment outcomes, and has become a standard of care for lung,27 liver,28 spine29 and oligometastases.30 • Spatially Fractionated Radiotherapy (SFRT): SFRT is an emerging radiotherapy technique to treat large and bulkier tumours.31 SFRT deviates from the conventional radiotherapy paradigm where an entire tumour volume is treated with uniform radiation dose. In SFRT, a non-uniform dose distribution throughout the tumour volume, with high peak and low valley dose region is generated. Only a few clinical trials that demonstrates the efficacy of SFRT exist,32 however several individual institutions reported significant improved tumour control and outcomes with the SFRT technique.33 7 In the next section, SRS and a type of SFRT technique called the lattice radiotherapy (LRT) is discussed. 1.3 Stereotactic Radiosurgery (SRS) An invasive neurosurgery procedure is considered the standard method to treat various neurological diseases.34 In 1951, Lars Leksall introduced stereotactic radiosurgery as an alternative method to treat various neurological disease, since the invasive nature of neurosurgery technique at the time, was associated with morbidity and mortality.35 With the Gamma Knife SRS technique (Elekta, Stockholm, Sweden), Leksell treated 762 patients throughout 1968 to 1982, of which more than half of the patients suffered from arteriovenous malformations or benign tumours.36 Leksell reported the first clinical application of SRS to treat trigeminal neuralgia in 1971 utilizing the Gamma Knife tool.37 Currently, Gamma Knife, Cyber Knife and the conventional Linac are utilized to perform SRS treatments. The advantage of using a conventional Linac for SRS technique is its wide availability in many radiotherapy centers compared to a Gamma Knife or Cyber Knife tool. 1.3.1 SRS clinical workflow Establishing a SRS program in a cancer clinic requires a dedicated immobilization device (frame-based or frameless patient positioning system), high-resolution 3D imaging, SRS treatment planning and appropriate dose verification tools. For intracranial lesions, a high precision SRS delivery with a submillimeter accuracy is required to achieve high tumour control probability and low radiation-induced toxicity.38 The frame-based approach is considered a standard tool to achieve robust patient immobilization, however it has several disadvantages.38 Fixing the surface 8 of a patient’s skull by four carbon fiber posts causes noticeable pain and discomfort to the patient during the treatment delivery.39 Furthermore, frame-based technique is a potential risk for local infection to the patient,40 requiring additional support from medical and nursing staff. One solution is to replace the positioning system with a frameless device, which uses a thermoplastic material that molds to the specific shape of the patient head, thereby, immobilizing the skull (figure 3). A study comparing the two immobilization systems concluded that these two techniques can be considered equivalent in terms of patient positioning accuracy for SRS treatment (p>0.05), however the frameless approach provides a non-invasive solution over the frame-based approach.38 The other aspect of SRS treatment planning involves acquisition of a high-resolution 3D image of the patient anatomy. Often, this is accomplished by utilizing multiple imaging modalities, most commonly CT and MRI (Magnetic Resonance Imaging).41 The delineation of target volumes (PTV) along with the organ at risk in the 3D images of the patient, is generally done by the Figure 3. Illustrates the frameless approach to patient immobilization during SRS treatment delivery. 9 physician. Since a high dose technique is used in SRS, it is essential to minimize the patient positioning uncertainty to limit the size of the PTV.41 After the target volume delineation, the treatment planner generates the SRS treatment plan such that the dosimetric objectives to the target and organ at risks specified by the radiation oncologist, is successfully met. The two treatment sites utilizing SRS treatment technique are brain and trigeminal neuralgia, which is the primary focus in this thesis.25 1.3.2 SRS for intracranial metastases The occurrence of intracranial metastatic disease or brain metastases is common and poses a significant threat to cancer patients, affecting 30% of all cancer patients.42 These brain metastases frequently originate from primary tumours in lung, breast, and melanoma.43 The intracranial metastases are often associated with high morbidity and mortality.42 The most common local treatments for intracranial metastases are surgical methods, whole brain radiotherapy, and more recently the SRS technique is utilized.42 Whole brain radiotherapy for brain metastases is often negatively associated with normal tissue toxicities such as memory loss, decline in neurocognitive function, pituitary dysfunction, and hearing problems.43,44,45 The clinical outcome of WBRT in the treatment of brain metastases is poor with 100% failure rate at one year follow-up46 and median survival range of only about 3-4 months.47 Intracranial metastases are the most common disease site treated with the SRS technique.25 Owing it to its highly focal radiation delivery to the tumour sites, SRS gained wide interest in radiotherapy centers due to its high precision in targeting the radiation to the tumour. SRS is reported as an 10 effective treatment for 1-4 brain metastases within cerebrum, cerebellum and brain stem, achieving high local control rates.48,49 A meta-analysis reported that a patient group treated with SRS alone had better local control rates compared with a group that underwent surgical resection with radiation treatment at two years timepoint.50 Furthermore, there was no differences in the overall survival between the two arms at either one year or two year time period.50 Another study investigated the efficacy of SRS in a large number of metastases. The study reported an overall survival outcome for patients with 5-10 metastatic diseases was similar to the patients with 2-4 brain metastases.51 Currently, SRS is a standard of care for small number of metastases and an alternative treatment method for four or more brain metastases.52 A radiation-induced side effect known as radiation necrosis is observed in the intracranial metastatic patients treated with SRS technique.42 Radiation necrosis has a significant impact on the quality of life of the patient,42 with commonly observed symptoms such as headaches, seizures, and neurodegeneration.53 Radiation necrosis is a challenging late effect of SRS treatment, which is difficult to detect with conventional imaging. Ultimately a biopsy is required to confirm the presence of radiation necrosis. A recently published review paper (literature searched until September 2020) reported that the incidence of radiation necrosis post-SRS treatment of 5-26% of which 33% to 50% were symptomatic.54 1.3.3 SRS in Trigeminal Neuralgia Trigeminal neuralgia is the most common neuralgia condition that has a low global incidence of only about 4-5 cases per 100,000 population.55 The disease is presented with severe, unilateral, and episodic facial pain that significantly affects the quality of life of a patient. The first line of 11 treatment for trigeminal neuralgia is a drug called carbamazepine.55 The efficacy of the drug degrades over a period, and often patients develop side effects that negatively affects the quality of life. A study included 143 trigeminal neuralgia patients treated with carbamazepine in order to evaluate the long-term effects of the drug. The treatment was initially effective for 99 patients (69%). Thirteen percent of those developed resistance over 2 months-10 years period, requiring an alternative treatment. The drug was effective for 49 patients for 1-4 years and 31 patients for 5-16 years.56 A surgical procedure known as microvascular decompression is also used to treat the disease. However, the complications associated with the invasive procedure can lead to hearing loss and brainstem infarction, brainstem stroke, or even death.55 SRS is an effective treatment for trigeminal neuralgia, providing a minimally invasive treatment within a short treatment duration.42 SRS is effectively delivered with a Gamma Knife, Cyber Knife and conventional Linac. Although Gamma Knife SRS is the gold standard for trigeminal neuralgia,57 Gamma Knife and Cyber Knife are not readily available in many cancer centers. The median targeting length for the radiosurgery target for trigeminal neuralgia was reported as 3.8 mm.58 Therefore, spatial accuracy of the radiosurgery delivery is of paramount importance. A recent review by Tuleasca et al. reported the outcomes of different SRS treatment techniques on trigeminal neuralgia patients from 1951 to December 2015.55 The study found no statistically significant difference in freedom from pain responses with or without medication between the Gamma Knife and conventional Linac treatments (p = 0.4). The time to pain relief measurement was 15-78 days (mean) and 10-90 days (median) for Gamma Knife. For Linac-based treatments the mean and median was 28-81 days and 8.5-60 days respectively. The mean recurrence rates associated with Gamma Knife was 24.6%, whereas Linac based SRS was 32.2%. Gamma Knife techniques have superior maintenance of 12 pain relief outcome at 7 years (in Little et al.59, 32%, Dhople et al.60, 22%, Regis et al.61, 60% of the patient population investigated) and 10 years. Linac based studies rarely reported maintenance of pain relief with only one study reported 60% pain relief at three years. The study concluded that an invasive surgery technique such as microvascular decompression is still the reference technique, however, SRS is a non-invasive and highly effective alternative technique for trigeminal neuralgia. 1.4 Spatially Fractionated Radiotherapy (SFRT) Spatially Fractionated Radiotherapy (SFRT) was initially introduced by Kohler et al. in 1909 to treat deep-seated tumours while sparing skin toxicities (caused by the poorly penetrating orthovoltage X-ray at the time).62 It was observed that treating a smaller volume allowed higher doses to be tolerated by the skin tissue, as high as 20 times more than a conventional dose.63,64 With the advent of megavoltage (MV) radiotherapy, the original SFRT technique using the orthovoltage X-ray subsided. Only a few decades ago, renewed interests emerged to implement the SFRT technique utilizing MV energy radiation beams available in modern Linacs.31 Four main forms of SFRT delivery exist 1.) Grid Therapy 2.) Lattice radiotherapy (LRT) 3.) Minibeam radiation therapy (MBRT) 4.) Microbeam radiation therapy (MRT).65 The major differences between the techniques are the geometry, shape and sizes of the beamlets.65 Grid and LRT are utilized to treat palliative tumour in multiple disease sites, such as lung, head and neck and breast.66,67 MBRT and MRT are at pre-clinical stages in their implementation.65 A type of SFRT technique known as the 3D lattice radiotherapy (LRT) was developed by Wu et al in 2010.68 The treatment planning involves generating multiple high-dose and localized spheres 13 called vertices, separated by a pre-specified distance to achieve a high peak-to-valley dose. This process ultimately results in a heterogenous dose distribution within the irradiated volume, ultimately deviating from the contemporary paradigm of treating an entire tumour with homogenous dose distribution. Part of the treatment planning process involves optimizing the placement of the spheres such that the dose in the periphery of the tumour is lowered, in order to achieve high normal tissue sparing and low radiation-induced toxicities.31 LRT was proven to be clinically useful in patients with large and unresectable tumours, resulting in high local control rates and low-grade toxicity at patient follow-up.69,70 A study by Amendola et al. implemented LRT in a large cohort involving 30 patients, mostly diagnosed with advanced gynecological cancer.69,71 The study reported a high local control rates, excellent clinical and imaging-based follow-up results, even after four years.69 Another study by the same group treated 10 patients with advanced stage non-small-cell lung cancer (NSCLC). LRT exhibited statistically significant tumour shrinkage of 42%, with improved long-term survival rates of 22 months (average) and 16 months (median). The study reported no significant acute or late toxicity, and no mortality related to LRT.72 A more recent phase 1 trial by Duriseti et al. reported that LRT is a safe form of palliative treatment for large tumours, exhibiting significant volume shrinkage and no significant toxicity or deterioration in quality of life.32 The studies discussed in this section are primarily single institution experiences with LRT, however, prospective multi-institutional clinical trials of LRT or SFRT in general, is lacking and required before widescale clinical implementation.65,73 The radiobiological effects surrounding LRT includes bystander-like effect (local) and abscopal effect (distant).31,74,75 The tumour cells present in the low dose region (valley) of the LRT treatment are known as the bystander cells.31 In those cells, significant tumour necrosis factor alpha (TNF-14 𝛼) was observed in an in vivo mice with lung carcinoma treated with LRT.76 Abscopal effect was evidently observed in the same study, where LRT treated lung adenocarcinoma in one tumour led to shrinkage in the other tumour in the same mice.76 After the radiation delivery, both the tumours in the same mice observed a high influx of tumour-infiltrating T cells correlating to the tumour size reduction. In grid therapy, indirect evidences of tumour vasculature damages were observed, indicated by the high levels of sphingomyelinase activity and ceramide levels in patients treated with SFRT.77 A mice study utilizing LRT concluded with the same result, indicating damage to the tumour vasculature, indicated by the enhanced acid sphingomyelinase levels.78 One studies suggest that immune system plays an important role in the regulation of aforementioned abscopal like effects.79 Furthermore, the SFRT review suggests the mounting evidences of the important role of immunomodulation in realizing the radiobiological effects observed in SFRT technique.65 A major challenge associated with LRT is the laborious treatment planning process owing to the manual placements of the vertices by the treatment planner. Furthermore, there are currently no standardized guidelines for the radius of the vertices, the lattice design or the centre-to-centre spacing of the spheres. The treatment verification with LRT is also challenging with high dose multiple spheres spanning across a 3D tumour volume. In the subsequent chapters, some methods to mitigate these clinical challenges hindering a wide adoption of LRT, are discussed. In the subsequent chapters of the thesis, the more widely known acronym “SFRT” is utilized instead of LRT for consistency. Note that SFRT is the umbrella term for several radiotherapy techniques, including LRT. 15 1.5 Dosimetric verification and geometric precision of a treatment delivery Two essential aspects of a successful radiotherapy delivery are dosimetric verification and geometric precision. The objective of the dosimetric verification is to ensure that the radiation dose delivered to a patient during the treatment is same as the intended dose in the treatment plan prescribed by the radiation oncologist. This is particularly important in SRS and SFRT, where a high radiation dose is delivered to a patient in a single or few sessions. On the other hand, the geometric precision is vital to ensure that the intended radiation dose accurately hits the target volume with a high spatial accuracy. A geometric miss to the tumour target has a detrimental effect to the surrounding healthy tissue and could cause severe radiation-induced toxicity and potentially a secondary cancer. Therefore, these two verifications are crucial in order to ensure that the delivered treatment to a patient is safe and effective. An end-to-end verification may also be performed, where a comprehensive evaluation of the entire treatment planning and delivery process is accomplished. 1.6 Thesis Scope Traditional radiation dosimeters present unique challenges in terms of verifying the dosimetric and spatial accuracy in three-dimensional space for complex techniques such as SRS and SFRT. Thus, the main objective of this work is to utilize a polymer gel dosimetry system with Linac-integrated CBCT readout to capture the complex 3D dose distribution of the SRS and SFRT treatment techniques. Four translational research projects utilizing a 3D gel dosimetry system were completed in the thesis. It is hypothesized that the gel dosimetry system is capable of acquiring a complex dose 16 distribution in 3D space in order to commission these highly advanced radiotherapy techniques. The research objectives accomplished by this work are as follows: 1.) To conduct a collaborative study in order to evaluate the reproducibility of the gel dosimetry system in a dual-institutional setting. The gel dosimetry technique has potential for a widescale adoption due to the reliance on the CBCT readout method. 2.) To commission a single isocentric SRS HyperArc® (Varian Medical Systems, Palo Alto CA) technique to treat intracranial brain metastases utilizing the gel dosimeter. 3.) To commission a novel SRS virtual cone technique to treat trigeminal neuralgia using a low-cost 3D printed anthropomorphic phantom and benchmark the dosimetric results from gel dosimetry system against a gold standard dosimeter (GafChromic film). 4.) To introduce an application of a semi-automated, open-source SFRT treatment planning tool and use the gel dosimetry system to commission the technique. In chapter 1, a brief overview of radiation therapy, its standard clinical workflow, two highly advanced radiotherapy techniques, and the thesis scope were introduced. The next chapter presents an introduction to the radiation dose detection tools (point dose, planar dose, 3D volume dose measurement), particularly focusing on the 3D polymer gel dosimetry system. 17 Chapter 2: Radiation Dosimetry Chapter 2 outlines and presents a brief overview of radiation dosimetry. Section 2.2 introduces point dose, planar dose, and 3D volume measurements. Section 2.2.3.1 presents a specific type of polymer gel dosimeter fabricated using a NIPAM monomer. The subsequent subsections focus on the X-ray-based readout techniques widely available in radiotherapy centers to acquire the images of NIPAM gel dosimeter for analysis. 2.1 Brief Overview of Radiation Dosimetry Radiation dosimetry is a medical physics discipline that comprehensively deals with radiation dose measurements and treatment verifications. In radiation therapy, it is important to quantify the dose received by a patient to evaluate the overall treatment accuracy. The dose measurement is also vital to ensure patient safety, to identify and mitigate potential inaccuracies in the treatment delivery, particularly when a novel and complex radiotherapy technique is introduced. Measurement of the delivered radiation dose distribution is achieved with various types of radiation dose detectors. These detectors are broadly classified into three categories based on their dimensionality: point dose, planar dose, and 3D volume dose measurements. The underlying physical process that governs the dose measurement is different from detector to detector. For instance, some radiation dosimeters produce an electrical charge or signal that is measured and related to the dose. Some exhibits a change in colour or optical density upon radiation exposure. Other unconventional 3D dosimeters exist that undergo physical and chemical changes upon radiation interaction that is measured and correlated to the absorbed dose. In the subsequent 18 section, point dose and planar dose measurement techniques, and 3D radiation dosimeters are discussed. 2.2 Radiation Dosimeters 2.2.1 Point Dose Measurement Ionization chambers are one of the simplest forms of gas-filled detectors.80 The underlying process relies on collecting the electrical charges generated when radiation interacts with the gas inside the detector.80 In an ideal case, an electric current recorded by the instrument is directly proportional to the intensity of the radiation field.80 Different designs of ionization chamber detector are available, however there are several common structural components between them. An ion chamber typically has a gas filled cavity that is enclosed by a conductive wall with a central electrode.4 An insulator is placed between the wall and the collecting electrode to reduce the current leakage when a voltage is applied to collect the charge. Generally, a temperature and pressure correction are necessary when performing ion chamber measurements since the mass of the gas inside the cavity may alter based upon these ambient conditions. A typical design of an ion chamber is illustrated in figure 4.4 Note that the point dose dosimeters have volume associated with the measurement technique. 19 Other point dose measurement techniques include Thermoluminescent Dosimeter (TLD), Optically Stimulated Luminescence Dosimeter (OSLD), MOSFET system, and Diamond detector.4 The TLD readout system utilizes a planchet to heat up the TLD and photomultiplier tube (PMT) that detects the released thermoluminescence light signals and convert it to the electrical signal. The electrical signal is linearly proportional to the detected photon fluence.4 Before they are used/re-used, the TLDs must be annealed to remove all the residual signals. OSLD works in a similar fashion compared to TLD, the primary difference between the two is the use of optical light to release the trapped energy as opposed to heat. MOSFET or Metal-Oxide Semiconductor Field Effect Transistor is a type of semi-conductor dosimeter, which has high spatial resolution. Both MOSFET and OSLD are useful in in vivo dosimetry.4 Diamond detectors are another type of point dose detectors that are utilized in high dose gradient applications such as stereotactic radiosurgery. They are tissue equivalent, directionally independent, and has high spatial resolution.4 Figure 4. Illustrates a generic design of an ionization chamber dosimeter. 20 2.2.2 Planar Dose Measurement To measure a planar dose distribution, typically a 2D film dosimeter is utilized in clinics over a point dose measurement. An older generation of 2D dosimeter consists of radiographic film that contains radiosensitive emulsion layer (Silver bromide or AgBr).4 The AgBr grains ionize after interacting with the radiation, resulting in a formation of a latent image. The latent image is processed thereafter to make it visible. For a dose readout, a densitometer is commonly used to measure the planar dose distribution. The conversion process relies on the relationship between optical density (OD) and dose by OD = 𝑙𝑜𝑔10(𝐼0 𝐼⁄ ), where I0 is the incident light, and I is the transmitted light through the film. The optical density (OD) is a function of dose, which is also called sensitometric curve characterized by Hurter and Driffield.4 Although the radiographic film has high spatial resolution, it is limited by the clinically useful dose range, high energy dependence in the lower energy photons, and high sensitivity to visible light.81 Moreover, an image development procedure81 is necessary, and consistently processing them is challenging in clinics.4 2.2.2.1 EBT-XD Film Dosimeters Radiochromic film, on the other hand, is a relatively newer type of film dosimeter.4 Commonly used radiochromic film in radiotherapy is a GafChromic film dosimeter, which is a colorless sheet that turns opaque upon radiation interaction.4 The film has an active layer that contains radiosensitive dye (yellow marker) that polymerizes as a function of dose. Similar to a radiographic film, a light transmission is used to measure the dose distribution using a densitometer or a film digitizer. An advantage of using radiochromic film is that it is self-developing, therefore, it doesn’t require a user to process the image. Radiochromic film (e.g. EBT-XD) also has a high spatial resolution (able to resolve 25 𝜇𝑚 or less as per the vendor product description) and weak energy 21 dependence (range 100 KeV to MV)82. It is almost insensitive to visible light,83 tissue equivalent and dose rate independent that makes it appropriate to measure complex dose distributions where high dose gradient exists.4,81,84 Figure 5. EBT-XD film design. In 2011, International Specialty Products, later acquired by Ashland Inc. (Ashland Inc, NJ, USA) developed a new generation of GafChromic EBT3 film dosimeter.85 In 2015, a newer series of EBT model called EBT-XD was introduced, which was specifically designed to verify high dose radiotherapy techniques such as stereotactic radiosurgery.81 The optimum dose range for the measurement is reported to be 0.4 to 40 Gy. Structurally, the EBT-XD film has three layers: an active layer sandwiched between two base layers. In EBT-XD film, the active layer measures 25 𝜇𝑚 and the base layer (matte-polyester substrate) measures 125 𝜇𝑚. The base layer provides overall structure to the film dosimeter as shown in figure 5.81 A flatbed scanner is typically used to scan the film dosimeter (~ 24 hours later) in order to measure the optical density distribution. The optical density map is converted to dose distribution map for the dosimetric analysis. Two dosimetry studies reported EBT-XD is a suitable dosimeter for high dose radiotherapy techniques such as SRS.86,87 22 More recently, another type of planar dose measurement with Electronic Portal Imaging Device (EPID) was utilized to perform patient specific quality assurance measurements for SRS/SABR cases.88 The advantage of EPID over other planar dosimeters (such as GafChromic film), is the ease of use, doesn’t require alignment of the physical dosimeter setup, and easier to process/analyze compared to EBT-XD film. 2.2.3 3D Volume Dose Measurement The point dose and planar dose measurements, previously described are spatially positioned in 3D space to obtain a pseudo 3D dose measurement.89 A pseudo 3D measurement is inherently and severely limited by its achievable spatial resolution since only a fraction of the entire 3D dose distribution is captured.89 Furthermore, for a point dose measurement, there is an uncertainty in the knowledge of exact positioning of the dosimeter in 3D space, which causes difficulties in interpreting the dose measurement required to commission complex radiotherapy techniques.90 Thus, comparing a planned and measured dose distribution of a pseudo 3D data is complicated and inefficient. A truly 3D dosimetric and spatial measurement is commonly achieved with a gel dosimetry system.89 A gel dosimeter is a continuous medium composed of radiation sensitive materials that undergo chemical or physical change upon irradiation. It is nearly tissue equivalent and can be conformed to the shape of an anthropomorphic phantom. Traditionally two types of gel dosimetry system exist: Fricke gel dosimeter and polymer gel dosimeter. More recently a solid radiochromic dosimeter has also been developed.89 23 • Fricke gel dosimeter: Fricke ferrous sulfate dosimeter is a chemical dosimeter, which upon irradiation, converts the Fe2+ ions dispersed in a matrix (gelatin or agarose) to Fe3+.91 The concentration of resultant Fe3+ ions is measured by a photo-spectrometry technique.89 Moreover, the ferric ion production also leads to a strong change in the magnetic property of the solution, which can be quantified using a magnetic resonance imaging (MRI).91 One limitation of using Fricke dosimeter is its natural ion diffusion that causes an image blurring effect. Moreover, the ion diffusion effect leads to a poor spatial stability and sets a limit to the allowable time between irradiation and measurement.92 To mitigate this issue, a gelling agent (hydrogel, gelatin, agarose etc.) is introduced to reduce the ion diffusion effect.93,94,95 Optical technique can be also used to quantify the 3D dose distribution of a Fricke gel dosimeter.96 • Polymer gel dosimeter: Polymer gel dosimeter is the most widely used 3D gel dosimeter.97 It is composed of water, gelatin, monomer, catalyzer or crosslinker, and oxygen scavenger.98 The radiation induces a water radiolysis which leads to the formation of free radicals that catalyzes the polymerization and crosslinking process.98 The chemical process ultimately leads to the change in the physical and optical density, which is correlated to the absorbed dose. Note that some formulations utilize an oxygen scavenger in order to inhibit oxygen from interfering with the polymerization and crosslinking process. The list of polymer gel dosimeters is extensive; however, two broad categories of polymer gel dosimeter based on the type of monomer used are: Methacryclic Acid Gelatin fabricated at ATmospheric conditions (MAGAT) and Polyacrylamide Acid Gelatin (PAG). Out of the two, the PAG dosimeter is the most studied polymer gel dosimeter.96 Recently, 24 Vandecasteele et al. proposed a radiochromic gel dosimeter that uses different class of monomers (sodium dodecyl sulfate, chloroform, trichloroacetic acid).99 • Solid radiochromic dosimeter: Solid radiochromic dosimeter is a new type of dosimeter that is commercially available. It contains a plastic material that polymerizes after an interaction with radiation. This type of photopolymerization process is further amplified using coloring dye. The underlying chemical components and processes are similar to the EBT film products explained in the previous section. Compared to the other types of gel dosimeters, the production of this dosimeter is relatively easy and straightforward. The primary dose readout method is to measure the optical density.100 In the next section, a specific type of polymer gel dosimeter that uses NIPAM (N-isopropylacrylamide) as a monomer is discussed. In the subsequent sections, the imaging tools available in cancer clinics to quantify the 3D dose distribution are presented. 2.2.3.1 NIPAM Polymer Gel Dosimeter Overview PAG dosimeter, which uses acrylamide monomer is traditionally known to be neurotoxic, carcinogenic and oxygen sensitive.101,96 Furthermore, certain fundamental problems are associated with the gel recipe that cause incorrect dosimetric measurement.102 In a past study, temporal and spatial instability was observed using acrylamide monomer in a gel formulation.101 Temporal stability was observed due to the polymerization process extending for hours and days after irradiation.103 Spatial instability were also observed in the dose gradient regions in which additional polymers were formed.104 These properties made the PAG dosimeter inconvenient to use in a clinical application.101 In 2006, Senden et al. investigated three less toxic monomers: N-25 isopropylacrylamide (NIPAM), diacetone acrylamide (DAAM), and N-vinylformamide (NVF).101 The study concluded that NIPAM is a viable monomer substitute for acrylamide as it maintained the good features such as dose sensitivity and reproducibility. However, the temporal instability was observed to be slightly reduced in NIPAM gel formulation compared to PAGAT dosimeter (Polyacrylamide Acid Gelatin at Atmospheric conditions) which is a normoxic PAG dosimeter.101 The spatial stability, on the other hand, was reported to be excellent for the NIPAM dosimeter imaged between 15-36 h post-irradiation in the referenced gel characterization study.105 This was due to the lower diffusion coefficient property of the larger monomer size of the NIPAM molecule, which consequently reduced the overall edge enhancing effect.101 NIPAM is known to be less volatile, hence less likely to be inhaled by the user and less capable to pass through a human tissue. 101,106,107 In 2011, Chain et al. optimized the NIPAM-based gel dosimeter by mixing different concentrations of the monomer and crosslinker and developed a new formulation that has improved dose sensitivity in X-ray CT readout.107 The recommendation from the Chain et al. contained a formulation of gel that has by weight: 15% NIPAM, 4.5% N-N’methylenebisacrylamide (BIS or MBA), and high concentration of THPC (> 5 mM).107 Standard imaging tools for gel dosimeter readout exist; Magnetic Resonance Imaging (MRI)90,93,101,108–118, X-ray computed tomography (CT)106,107,119–126, and optical-CT.127–139,139–143 A recently studied readout technique, based on Linac-integrated cone-beam CT (CBCT) is also used.144–148 MRI has a high spatial and contrast resolution, but despite these, the potential benefits, a widescale clinical adoption of MRI in gel dosimetry faces numerous challenges. MRI is not 26 readily available in many centers, furthermore, accessing MRI for research purposes is even more difficult during a demanding clinical schedule. Similarly, gel dosimetry readout utilizing optical-CT, which also has a high spatial resolution, requires a specialized scanner at the institution for the 3D dose quantification. X-ray CT is a more viable option, from an accessibility standpoint, as it is available in almost all radiotherapy centers and well-integrated into the clinical workflow. However, utilizing all the above readout techniques introduces inherent spatial accuracy uncertainties since the position of the gel dosimeter during the radiation delivery is different from the gel readout. This challenge is mitigated by performing an image registration for the analysis purposes. However, differences in spatial frame of reference between the radiation delivery and imaging readout may cause complication in dose registration during the analysis. In the next section, the readout method based on X-ray CT and Linac integrated CBCT readout is discussed in detail. 2.2.3.2 NIPAM Polymer Gel Dosimetry with X-Ray CT Readout X-ray CT was first utilized as a 3D dose readout method for PAGAT gel dosimeters.119,124 The study referenced showed that a dose dependent contrast changes in the CT images of the irradiated gel dosimeters can be quantified, and a dose response relationship can be established.119,124 This finding enabled the use of X-ray CT as an alternative dose readout method to MRI.125 Unlike MRI, CT imaging is available in almost every cancer clinic worldwide, well-integrated within a clinical workflow and has a minimal cost of operation.144 It is typically easy and fast to acquire images, relatively insensitive to environmental conditions, and has a spatially stable dose response (shown in a deformable gel dosimetry study).149 A significant limitation of CT-based gel dosimetry is the 27 low dose sensitivity, i.e. changes in CT number (Hounsfield unit) is low compared to the dose delivered (~1 HU/Gy). Furthermore, the act of CT imaging itself will contribute minimal radiation dose to the gel dosimeter.125 NIPAM-gel dosimetry with X-ray CT readout is extensively studied and well understood. In CT-based polymer gel dosimetry workflow, the fundamental process affecting the contrast measurement is the change in mass density of the gel dosimeter after an irradiation.90 This change in physical density is attributed to the underlying polymerization and crosslinking mechanisms. However, since the change in physical density is small, the changes in attenuation coefficient and therefore the CT number (HU) is low. This leads to the low dose resolution issues traditionally found in the gel dosimetry systems involving CT imaging readout methods.144 However, this problem was tackled on multiple fronts in multiple studies: • Optimizing the gel recipe: The interest to replace the toxic acrylamide ingredient with a less toxic monomer substitute led to some early studies that utilized normoxic gel formulation.101,150,151 Furthermore, a normoxic gel dosimeter is an attractive alternative because it is manufactured and irradiated without physically purging the oxygen out of a container using an inert gas like nitrogen.101 Based on a previous acrylamide-based gel formulation, Senden et al. initially evaluated three monomer substitutes, and reported that NIPAM is a suitable substitute due to its superior dose sensitivity compared with the other two monomers investigated. However, the formulation was not optimized in the study.101 Therefore, further investigations by Chain et al. and Jirasek et al. optimized this initial recipe that led to a gel formulation that has increased dose sensitivity (~ 0.88 H/Gy in Chain 28 et al. study) and improved dose resolution (~ 0.052 Gy in Chain et al. study).106,107 Currently the widely adopted formulation for NIPAM gel dosimeter is presented in table 1.123 The dose response of the formulation was reported as 0.8-1 HU/Gy evaluated with 120 kVp.123 Table 1. Typical NIPAM gel dosimeter formulation.123 Chemical Ingredients Concentration (by weight) N-isopropylacrylamide (NIPAM) 15% N, N’methylenebisacrylamide (Bis or MBA) 4.5% Gelatin 5% Water 75.5% Tetrakis hydroxymethyl phosphonium chloride (THPC) 5-10 mM • Image acquisition parameters: The CT imaging parameters, such as tube voltage (kVp), current (mA), slice thickness, acquisition time and reconstruction methods, influence the overall image quality of the irradiated gel dosimeters. Table 2 presents the effect of relevant image acquisition parameter on image noise, reproduced from a study by Hilts et al.121 Note that the study utilized a PAGAT gel formulation. 29 Table 2. Image acquisition parameter and its relationship with CT image noise (𝝈𝑵) in PAGAT gel dosimeter.121 Imaging parameter Effect on image noise (𝜎𝑁 Tube voltage (kV) 𝜎𝑁 ∝ 𝑘𝑉−1.4 Tube current (mA) 𝜎𝑁 ∝ 𝑚𝐴−0.5 Slice scan time (s) 𝜎𝑁 ∝ 𝑠−0.5 Number of image averages (Nave) 𝜎𝑁 ∝ 𝑁𝑎𝑣𝑒−0.5 Pixel dimension (w) 𝜎𝑁 ∝ 𝑤−0.65 Slice thickness (h) 𝜎𝑁 ∝ ℎ−0.5 • Image processing: The use of image averaging, background subtraction, and image filtering improved the signal-to-noise ratio in the inherently low contrast CT system.152–154 Post-irradiation image processing methods include adaptive mean filtering which removes stochastic image noise while maintaining an edge preservation.152 Remnant artefact removal was also introduced to remove the intrinsic inhomogeneities present in the processed CT images.126 Wiener filter is also another alternative filter introduced by Trapp et al.155 A past study by Kakakhel et al. proposed a “zero-scan technique” to improve the overall image quality. The zero-scan technique essentially calculates the image before any CT scan is done. This is achieved by acquiring repeated CT images, which increase the dose over the number of CT scans. Thus, the intercept represents the “zero-scan” image.156,157 Other newer method to improve signal-to-noise ratio includes the use of iterative reconstruction filters, if available in the clinical systems.144 Two companion studies were published by Jirasek and Johnston et al. The first study proposed the use of a 30 remnant artefact removal (RAR) filter to remove the ring and streaking artefacts (structural noise) commonly seen on CT images.126 The study efficiently combined the RAR filter to reduce structural noise and an adaptive mean (AM) filter to remove the stochastic noise in order to improve the overall CT image quality. The other companion study characterized this gel dosimetry workflow by investigating the temporal and spatial stability of the dosimeter, its dose rate dependency, and batch reproducibility.105 Another study by the same group found that the dose response of NIPAM gel dosimeter is affected by machine dose rate (100-600 MU min-1).158 The conclusion of the study was that NIPAM-based gel dosimeter is a promising verification tool for complex radiotherapy techniques. A more recent study by Maynard et al. investigated the use and effectiveness of an inter-batch gel calibration technique.123 The study concluded that a sufficiently high accuracy was achieved when a generic calibration curve was obtained (96.8% with 3% 3 mm criteria) by averaging calibration curves from multiple gel dosimeter, compared to a self-calibration method (98.2%), which represents a highest achievable gamma pass percent or “best-case scenario” for calibration.123 2.2.3.3 NIPAM Polymer Gel Dosimetry with CBCT Readout Linac-integrated cone beam CT (CBCT) is currently a standard tool in modern radiation therapy workflow. Often the term image-guided radiotherapy (IGRT) is used to define this new paradigm of high precision radiotherapy, where CBCT is utilized in routine treatment delivery. CBCT is utilized to acquire an image of the patient's positioning before or during treatment to ensure that the patient's actual treatment position is consistent to the planned CT simulation. 31 Using CBCT imaging to acquire images of the gel dosimeters present unique advantages over the other imaging modalities available in clinics. Firstly, the irradiation and imaging position are identical, therefore a user re-positioning error of gel dosimeter in another imaging space is essentially eliminated.144 Secondly, the ability to acquire almost real-time imaging of the dose distribution can be achieved successfully with CBCT.146 X-ray CT and CBCT are similar in terms of the physics principles in image formation, therefore much of the workflow can be directly translated into the CBCT realm. However, one disadvantage of using CBCT is the reduced image quality due to the inherent scatter present in a cone-beam geometry.144 This issue may be mitigated by optimizing the imaging parameters and using novel iterative reconstruction methods integrated within the on-board CBCT imaging in the modern linear accelerators.144 CBCT was first utilized to acquire images of NIPAM gel dosimeter in 2019 by Adamson et al.145 The proof of principle study demonstrated the application of CBCT imaging in an end-to-end verification of a multifocal radiosurgery technique.145 The total time of the experiment, including pre-irradiation CBCT and final post- irradiation scan was 28 minutes. Overall, the study demonstrated the use of a novel gel dosimetry workflow in characterizing high dose and steep dose gradient treatment techniques such as SRS. A follow-up work utilizing CBCT readout in NIPAM gel dosimetry was performed by Jirasek et al.146 One major finding of the study was that the post-irradiation CBCT images acquired 20-30 minutes after radiation delivery is adequate for a dosimetry study. This was because >90% polymerization yield was achieved within that time span,146 implying that the images may be acquired after 20-30 minutes rather than 24 hours post-irradiation, as had been the traditional practice. The image acquisition protocol of 100 kVp, 1035 mAs, 15 frames per second was used to acquire the images of the gel dosimeter. Guiding principles 32 from the studies done by Hilts and Maynard et al. was used to select those imaging parameters.119,123 For gamma criteria 3% 3mm, 93% gamma pass rate was obtained for three static field verification plans. Another study by Pant et al. demonstrated the application of kV-CBCT in imaging NIPAM gel dosimeter for imaging isocenter verification. The study reported a sub-millimeter accuracy in their comprehensive verification of radiation isocenter coincidence with kV-CBCT imaging.147 To conclude the chapter 2, table 3 summarizes the individual dosimetric characteristics of three selected dosimeters that were utilized for SRS and LRT commissioning in this work.159 Note that, for routine clinical commissioning, often multiple dosimeters are used in combination to verify an overall dosimetric and geometric precision of a treatment delivery. 33 Table 3. Selected Dosimeter Characteristics. CC13 (ion chamber) EBT-XD NIPAM gel dosimeter Dose Range Very high 40 cGy-40 Gy159 0-25 Gy Dose response Linear160 Complex fit Hyperbolic tan function (empirically determined)123 Dose Rate Dependence None between (200-600 MU min-1 )160 Small difference ~ 1.5% difference between 10 MV, 10 FFF, 6 MV and 6 FFF159 Dependent on machine dose rate investigated (100-600 MU min-1 )158,105 Energy Dependence None161 Small difference ~ 1.5% difference in 10 MV, 10 FFF, 6 MV and 6 FFF159 Energy independent (6, 9 , 12 MeV investigated in a study)162 Spatial Resolution Active volume: 0.13 cm3 (as per vendor description) 25 𝜇𝑚 (as per vendor description), limited by the resolution of the scanner Dependent on the readout technique, CBCT resolution (~0.5 x 0.5 x 1 mm) Application Relative dosimetry and output factor measurements SRS, SABR, LRT SRS, SABR, LRT, end-to-end spatial accuracy test 34 Disadvantage Under responsive in extremely small-field dosimetry (virtual cone technique), ambient condition correction required. High cost per film, 2 orientations required for “3D” dosimetric measurement, end-to-end spatial accuracy not achievable. Require gel fabrication and a lab facility to manufacture them, cost ~ 70 USD per gel dosimeter, resolution limited by the imaging modality To summarize, in chapter 2, an overview of radiation dosimetry was presented. The chapter also introduced point dose, planar dose, and 3D volume dose measurement techniques. A NIPAM gel formulation developed by Senden et al.101 and refined by Chain107 and Jirasek et al.106 was discussed. Two X-ray-based readout methods to quantify the 3D dose distribution of a polymer gel dosimeter were also presented. In the next chapter, material and methods of the study is presented. 35 Chapter 3: Material and Methods: Brief Overview of 3D Polymer Gel Dosimetry Pipeline Chapter 3 presents the general material and methods section. Note that the additional details including specific gel analysis for a particular study are given in the respective chapters to minimize duplication. Section 3.1 describes the fabrication method. Section 3.2 presents the radiation delivery and CBCT imaging. Section 3.3. presents the gel image analysis. 3.1 Polymer Gel Dosimeter fabrication The gel fabrication was performed based on the methodology presented by Maynard et al.123 For a 1000 g or 1 L gel dosimeter, 755 g of deionized water was placed in a 2000 mL beaker with a magnetic stirrer. The beaker was put on a hot plate stirrer as shown in figure 6. A temperature probe was used to carefully measure the temperature during the entire mixing procedure. The temperature was controlled using the hot plate stirrer. The first ingredient, 50 g of Gelatin (Sigma-Aldrich, Oakville, On, Canada) was mixed into the deionized water. The mixture was brought to a temperature of 40.0 ± 0.5 °C. Once the gelatin was fully dissolved, the mixture was brought to a temperature of 34.0 ± 0.5 °C. 150 g of NIPAM (TCI, America, Portland, OR, USA) was then added. After it completely dissolved, 45 g of BIS or MBA (Sigma-Aldrich) was added. The mixture was brought to a temperature of 30.0 ± 0.5 °C and then 10 mM of THPC (Sigma-Aldrich) was finally added. THPC was allowed to mix for 1.5 minutes before putting the mixture into the gel jar. 36 Figure 6. Illustrates the setup for gel fabrication. Before the mixing procedures, a gel jar either 1L (Modus Medical Devices Inc., London, ON, Canada) or 2L (Uline, Pleasant Prairie, Wisconsin, United States) in figure 7 was sealed with a polytetrafluoroethylene tape wrapped around the top of the jar (prior to and in preparation for insertion of the gel material) to ensure no air passed through the gap after closing the container. Once the gel was fabricated and placed inside the jar, the container was put into a water bath in a refrigerator for at least 5 hours. The entire fabrication process was performed in the medical physics laboratory facility at the University of British Columbia Okanagan campus. 37 Figure 7. Left (1 L gel jar), Right (2 L gel jar). 3.2 Polymer Gel Dosimeter irradiation and CBCT readout The gel dosimeter was placed into a cooler with several ice packs and brought to BC Cancer Kelowna for irradiation. The gel dosimeter was placed in our in-house gel holder. Positioning the gel on the Linac couch using the patient setup laser took about five minutes before each experiment. Six pre- and six post- irradiation CBCT scans were performed for gel analysis (figure 8). The entire gel experiment (imaging and delivery) took less than 2 hours. 38 Figure 8. Illustrates the Linac integrated kV-CBCT in position for gel dosimetry imaging. 3.3 Polymer Gel Dosimetry analysis The gel dosimetry analysis was performed using an in-house MATLAB script. Six pre- or background CBCT images and 6 post-irradiation images were individually averaged. The averaged background image was then subtracted from the averaged post-irradiation image. An adaptive mean filter (3 by 3 pixels), and remnant artefact removal filter (span = 7, degree = 3, and iterations 2) were used to process the gel images as described in the previous study.126 The calibration of gel images was performed according to the past study by Johnston et al.105, which was subsequently refined by Jirasek and Hilts et al.163 A pixel by pixel calibration from a central slice of the verification plan and the processed gel image was utilized to calibrate the gel images using the following empirically-derived equation123: 39 ∆𝑁𝐶𝑇 = 𝛼 + 𝛽𝑡𝑎𝑛ℎ⁡(𝛾𝐷 − 𝜑) Where ∆𝑁𝐶𝑇 represents the change in CT number, D is the dose from the verification plan, 𝛼, 𝛽, 𝛾,𝜑 are the fitted parameters of the equation. Note that the tanh fitting curve was chosen out of four functions (two sigmoid, two tanh) in the previous study by Jirasek et al. based on precision, relative error and dose difference criteria between the planning system and gel measurement, .163 The fitting process in our work returns the best estimate for these calibration curve parameters with the error associated with each of them (95% confidence interval). Chapter 3 summarized the general material and methods procedure common to all the subsequent research chapters. Gel fabrication was performed according to the previously published protocol.123 Radiation delivery and CBCT imaging was achieved using a robust in-house gel holder. Gel analysis including image processing was performed using an in-house MATLAB script based on the previously established workflow.146 In the next chapter, a dual-institutional study to investigate the reproducibility of the gel dosimetry workflow is presented. 40 Chapter 4: Dual-institutional reproducibility study In chapter 4, the reproducibility of the gel dosimetry system utilizing CBCT readout was evaluated in a dual-institutional setting. This dosimetry system has a potential for wide scale applicability due to the reliance on CBCT readout. The study was accomplished by generating three identical verification plans (3-field, TG119 C-shape spine, 4-target SRS) delivered to a NIPAM gel dosimeter at the individual institutions. Independent gel analysis tools were used based on the individual institution’s preference (Duke University: VistaAce software, UBCO: In-house MATLAB script). 1D line profiles, 2D contour plots, 3D global gamma maps were used to compare the planned and measured dose distributions. Variation between the gamma pass percentages were observed between the two institutions, however, a better consistency was observed within each pipeline (by sharing the data), indicating the need for a standardized analysis workflow. The work presented in this research chapter is currently under review in the Physics in Medicine and Biology journal. Since this is a collaborative study, Kawtar and I were the first co-authors. Dr. Hyde and Dr. Adamson were responsible for the generating the verification plans. Dr. Jirasek and Dr. Oldham provided guidance to the authors with their gel expertise. Benjamin Quinn assisted the Duke University collaborators in their VistaAce gel analysis software. 41 4.1 Introduction Polymer Gel Dosimetry (PGD) is a dose verification tool that is beneficial for highly complex and advanced radiation therapy treatments.109,90 PGD distinguishes itself from other commonly used dosimeters, such as ionization chamber (1D) and film (2D), since it inherently records dose information in three dimensions.102 PGD is particularly advantageous for intensity-modulated radiation therapy (IMRT) with complex dose distributions and stereotactic radiosurgery (SRS) techniques, where geometric precision is paramount and steep dose gradients are often present.109,102 For end-to-end verification, PGD can be incorporated into an anthropomorphic phantom and it is also radiologically equivalent to soft tissue.123,105 A practical disadvantage of using PGD may be the need for a dedicated space to manufacture the gel dosimeter, which is challenging in many clinical environments. However, this can be managed by collaborating with an institution with a chemical laboratory within proximity of the clinic. In the past, low image contrast and chemical toxicity impeded clinical use, however, recent innovations have led to the gel having increased dose sensitivity, and fabrication methods that are easier and less toxic.101,106 Furthermore, the use of impermeable gel containers, even for oxygen, enables the clinical user to handle the dosimeter with almost no health and safety risks once it is transferred into the container. Consequently, PGD has become a valuable tool for commissioning radiotherapy equipment and techniques. Polymer gel dosimeters are composed of radiosensitive chemicals, which upon irradiation undergo polymerization and crosslinking as a function of the absorbed dose.90 The polymerization and crosslinking result in changes in the physical density of the gel dosimeter, which can be recorded with clinically available imaging modalities. The use of N-isopropylacrylamide (NIPAM) as a 42 monomer with a commonly utilized cross-linker such as N,N’-methylenebisacrylamide (BIS or MBA) was initially introduced by Senden et al.101 This composition was further optimized by Chain et al. increasing dose sensitivity and resolution to allow the use of a more widely available imaging readout system, X-ray CT.164,107 PGD workflow requires a gel readout method after an irradiation is completed. Common PGD readout techniques include magnetic resonance imaging (MRI)111, optical computed tomography (optical CT), and X-ray CT (CT)123,105,106,165,. More recently linear accelerator (Linac) integrated cone-beam CT (CBCT) has been investigated.146,166–168 Despite the fact that a better contrast resolution is achieved with an MRI-readout, an accurate and clinically viable MRI dosimetry demands more technical requirements than CT and CBCT-based readout methods,107,169 and MRI is not as widely available thus limiting its general applicability. In contrast, CT or CBCT-based PGD is appealing because of its wide availability and simplified equipment requirements.107,146 Unlike MRI, these imaging modalities are not too sensitive to environmental and temperature fluctuations. However, one of the challenges in implementing CT and CBCT-based PGD is the small density changes of the irradiated gel (in order of 1mg/cm3 per 1Gy of absorbed dose), which limits the change of linear attenuation coefficient.122 This results in low signal-to-noise ratio in the image, reducing image quality and contrast resolution. Nevertheless, this challenge has been efficiently addressed in previous research by acquiring multiple scans of the gel dosimeter for image averaging, as well as applying image processing techniques.105,126,145,146,156,157,170,171 More recently, Linac-integrated CBCT has become an attractive PGD readout method since the set up for gel dosimeter for irradiation is identical to the PGD readout.147,146 Maintaining the same frame of reference eliminates any positioning errors from setting up the gel dosimeter in another imaging 43 system.146,145,147 Therefore, CBCT-based PGD readout eliminates the need to register the gel readout images with the treatment planning system since the CBCT is inherently integrated within the treatment delivery system. Thus, this readout technique is particularly useful in comprehensive verification for spatial accuracy of complex delivered dose distributions. Due to its spatial accuracy, CBCT-based PGD is an excellent tool in commissioning stereotactic radiosurgery (SRS) and stereotactic ablative radiotherapy (SABR) techniques, where there are stringent requirements for the spatial localization. Furthermore, this readout technique is available at any radiotherapy center with CBCT image guidance capability, and has the potential to be adopted widely.145–147,166,172 Although CBCT is now available in most clinics, the use of CBCT readout for PGD is still relatively unknown outside of a few academic institutions. In a previous work, Jirasek et al. investigated the optimal time to acquire CBCT after a gel irradiation (20-30 min), and the overall dosimetric accuracy and precision of a CBCT based PGD technique. A gamma pass rate of (>90%) at 3% 3 mm was obtained in the study using a standard 3-field treatment plan.146 Another study by Adamson et al. presented the potential of PGD based on CBCT by visualizing the 3D dose distribution, with sufficient contrast-to-noise ratio, immediately after delivering an SRS irradiation using the kV CBCT system mounted on board the linear accelerator. In the study, the PTV was overlayed with the dose distribution on the CBCT after the SRS treatment, ensuring an accurate delivery is achieved. Although the dose analysis was qualitative, the study presented a promising application of PGD in SRS application.145 Pant demonstrated the use of CBCT based PGD in comprehensive with sub-mm accuracy, which is also relevant to the SRS applications.147 Since all the previous studies are largely single institution research initiatives, in this study, our goal is to 44 provide a dual-institution validation of the PGD based on Linac integrated CBCT readout.145–147,166,172 In a broader context, few multi-institutional gel studies have been accomplished previously.173,174 However, there are currently no collaborative studies in the context of NIPAM gel dosimetry workflow with Linac integrated CBCT readout technique. Therefore, this dual-institution verification can serve to provide guidance to other clinics in regards to what is achievable using CBCT readout, and is modeled after the TG-119 multi-institutional benchmark that was provided for film dosimetry.175,176 In this work, we investigated the dosimetric reproducibility of a NIPAM-based gel dosimeter between Institution A and Institution B by implementing three identical radiation therapy treatment plans. The PGD workflow of the two institutions includes: identical PGD manufacturing steps, the same CBCT readout technique, and identical radiotherapy treatment plans. After the CBCT images were acquired, a site-specific image processing and analysis pipeline for each individual institution was implemented in this study. In addition to analyzing our own data, we shared the gel readout data between the two institutions and analyzed the images using our site-specific gel analysis pipeline, providing two separate analyses for each treatment plan. 4.2 Material and Methods 4.2.1 Treatment planning The Eclipse treatment planning software (Varian Medical Systems, CA) was used to create three treatment plans common between the two institutions: 1.) a simple 3 field plan as implemented and described in a previous study111, with a prescribed dose of 27 Gy; slightly different beam geometry and beam weighting was used by the two institutions for the 3-field plan. 2.) a 4-target radiosurgery plan with VMAT arcs at 0°, 45°, 90°, 315° couch angles with prescribed dose of 25 45 Gy (with maximum dose up to 30 Gy). 3.) AAPM TG119 IMRT C-Shape treatment plan, where the target is a C-Shape that surrounds a central avoidance structure (Spine), with a prescribed dose of 25 Gy and maximum dose of 30 Gy. Anisotropic Analytical Algorithm (version 15.6) was used to plan the 3-field treatment plan, and Acuros (AXB version 15.6) was used to plan the C-shape and SRS treatment plans. 1 mm dose resolution and PO was utilized for dose calculation. One notable inherent difference between the two institution is the clinical beam model utilized in this study. 4.2.2 Gel fabrication Each gel used in this study was fabricated using a previously established protocol.111 In summary, the gels were manufactured with 15% N-isopropylacrylamide (NIPAM, Sigma Aldrich, Mississauga ON, Canada), 4.5% N,N’-methylenebisacrylamide (Sigma), 5% 300 bloom gelatin (Sigma), 10 mM tetrakis(hydroxymethyl)phosphonium chloride (THPC, Sigma), and 75.5% deionized water. Gels were then transferred to either a 1 L or 2L clear plastic jar (Modus Medical Devices Inc., London, ON, Canada (1L) and Uline, Pleasant Prairie, Wisconsin, United States (2L)), depending on the experiment that was performed in the study. A polytetrafluoroethylene (PTFE) tape was used to seal around the lid of the gel jar to prevent oxygen entering the container, which may inhibit the polymerization and crosslinking process.123 The gels were cooled in a water bath inside a refrigerator at 4° C for at least 5 hours before delivering the respective treatment plans. 46 4.2.3 Gel Irradiation Each gel was allowed to equilibrate at room temperature prior to irradiation.146 The gel was set up using in-house immobilization devices (site specific for institution A and B) to allow reproducible gel positions in regards to the linear accelerator (Linac) isocenter. Institution A used an in-house built Styrofoam platform for gel, institution B used a rigid mechanical set up with gel insert (images of both setups are given in supplemental data, Appendix A). Both institutions used a Varian TrueBeam Linac (Varian Inc, Palo Alto, CA, USA) with 6 MV photon for C-shape treatment plan, while a Varian Truebeam Linac with a High-Definition Multi-leaf collimator (HDMLC) with 6 MV Flattening-filter-free (FFF) was used to deliver a volumetrically modulated arc therapy (VMAT) at up to 1400 MU/min, for the radiosurgery and 3-field plans. After the irradiation, institution A allocated 30-35 minutes post-irradiation wait time, depending on the treatment plan, and institution B waited consistently for 20 minutes for all the 3 experiments. This inconsistency between the wait times occurred due to the Linac availability time in our respective clinics. 4.2.4 Gel readout with Linac Integrated-CBCT A Linac integrated on-board imager was used to obtain 6 pre- and 6 post-irradiation scans of the gel for each experiment. In contrast to the previous gel studies,105,123,126,145,146 the pre-irradiation CBCT scans were used for background subtraction rather than making a separate background gel. Using a separate background gel may introduce positioning errors when inserting and removing the gel from the immobilization device. Although this problem can be efficiently mitigated by overlaying the 3D data with an image registration technique, using one gel for both pre- and post-scan would reduce the amount of chemicals required for manufacturing and increase the efficiency 47 of the PGD workflow. CBCT images were obtained using a scan parameter of tube voltage 125 kVp, tube current of 1620 mAs, 5400 projections and 1 mm reconstructed slice thickness, as determined previously.147 The same CBCT imaging parameters were used by both institutions A and B. The scan time for each CBCT acquisition was around 6 minutes. Image processing and analysis: Figure 9. Illustrates the workflow of the two institutions. The gel fabrication, treatment plan and gel irradiation were kept constant. The analysis of the PGD were different based on the preference of the institution. Box A and B represents the individual workflow since the CBCT image is already inherently registered with the planned dose, while it was performed in Institution A’s workflow because the dose was calculated on CT scan of the dosimeter instead of a CBCT. 48 The PGD workflow for each institution is summarized in figure 9. Institution A used commercial software, VistaAce v0.7 (Modus Medical Devices Inc., IBA Dosimetry)177, which was designed to analyze 3D dosimetry data. Since it was specifically developed for radiochromic 3D gel dosimeters with optical CT readout, it had to be modified in conjunction with the manufacturer to accommodate NIPAM dosimeters with Linac integrated CBCT readout. The 6 pre- and 6 post-irradiation scans were uploaded to the software where they were individually averaged, then the averaged pre-irradiation scan was subtracted from the post irradiation scan to minimize background noise. The fact that both the treatment delivery system and the readout device use the same coordinate system increases the spatial accuracy and reduces the margin for positioning errors. However, a spatial registration, between the dose plan and the measured data, was performed in the VistaAce software as the DICOM registration between the TPS dose and the CBCT is not accounted for in the software at this time. The gel images were self-calibrated against the eclipse planned dose. A best fit calibration was performed by gathering CT number data and corresponding dose for as many points as possible, covering regions of high, medium, and low dose in 3D and using a polynomial fit (equation 1) for the 3-field and the 4 targets SRS cases, and a scaled logistic sigmoid curve (equation 2) for the AAPM TG-119 IMRT C-shape case. Two different functions were required to better fit the calibration curve based on the specific treatment plan in VistaAce software. The parameters for the calibration curves are listed in Appendix B): 𝐷 = 𝑎𝑥2 + 𝑏𝑥 + 𝑐 ⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛 (1) 𝐷 =𝐿(1 + 𝑒−𝑘(𝑥−𝑥0))+ 𝑐⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛⁡(2) 49 where x represents the change in the CT number; D is the dose; a, b and c are parameters of the polynomial fit. For the sigmoid fit L is the curve’s dose scaling (maximum of the curve), k is the growth rate of the curve, x0 is the midpoint of the curve and c is the dose offset of the curve (y-axis offset). The values of the parameters are presented in Appendix B (table B1) for each irradiation plan and each institution. Following the calibration process, adjustments were made to the volumes and the jar walls, lids, and bottom were cropped inward by 1cm. This was done in order to eliminate inaccuracies in the obtained results since gels under respond towards the edges of the dosimeter. After the completion of the calibration process, a comprehensive dosimetric analysis was conducted which involved the utilization of 3D global gamma analysis and gamma map comparison. Institution B used an in-house MATLAB (MathWorks, Natick MA) script for image processing and analysis. The 6 pre- and 6 post-irradiation scans were individually averaged, and the averaged pre-irradiation image was subtracted from the post-irradiation image. On the “background-subtracted image”, an adaptive mean filter of kernel size (3X3 pixels) and remnant artifact removal (window span, 7) were applied to lower the image noise and eliminate artefacts respectively.146,126 After the image processing step, a central slice of the volumetric image was used to acquire a CT number (pixel values) to dose calibration curve using the matching treatment plan slice. Similar to the institution A’s workflow, the gel images were self-calibrated against the eclipse planned dose. Using the calibration curve (equation 3), which was determined empirically in the prior study,163 the entire volume of the gel was self-calibrated. Once the entire gel is calibrated, 3D gamma analysis (global) was performed using the calibrated gel volume against the treatment plan, using 50 several dose criterions with an open-source MATLAB code (https://github.com/mwgeurts/gamma).178 The calibration utilized the equation: Δ𝑁𝐶𝑇 = ⁡𝛼 + 𝛽 tanh(𝛾𝐷 − 𝜑) ⁡⁡𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛⁡(3) where Δ𝑁𝐶𝑇 is the change in CT number; D is the dose; and 𝛼, 𝛽, 𝛾, and 𝜑 are parameters of the calibration curve. The values of parameters obtained are presented in Appendix B (table B2). Figure B3 in Appendix presents the calibration curves obtained using the two-analysis software for the 3 experiments conducted at the two institutions. For 3D global gamma analysis, institution A used the geometric calculation method179, which represents the dose distribution and find the minimum distance between the reference dose point to the evaluated dose surface, which produces the results independent of dose gradients and grid spacing, whereas, institution B utilized an open-source MATLAB script based on the classical interpolation method explained in Low et al.180 4.3 Results 4.3.1 3 Field The planned dose from the 3-field treatment plan was compared with the measured dose from institutions A and B using a site-specific 3D gamma analysis pipeline. The dose criterion used for this treatment plan was from 1% to 7% with distance-to-agreement (DTA) set to 2 mm. Figure 10 presents the planned and acquired dose distribution and isodose maps for the two institutions. Figure 11 presents a scatter plot of 3D gamma pass percent set to 2 mm DTA and 10% minimum 51 dose threshold. Additional gamma pass percent (2%,3mm; 3%, 3mm; and 5%,1 mm) were also presented in Table D1 of Appendix D. For the entire analysis, the minimum dose threshold was set to 10%. As shown in table D1 of Appendix D, the 3D gamma pass percent for the dose criterion were above 90%. Out of all the gamma criteria calculated in Appendix D, the maximum difference in pass rates is 5.1% between the two institutions for the 2% 2mm dose criterion with the MATLAB analysis. The average 3D gamma passing percentage obtained with VistaAce software is noticeably higher than MATLAB analysis. The difference in 3D gamma pass percentage between the two analysis pipelines (VistaAce and MATLAB) is addressed in the discussion section. A better consistency was observed in the data analyzed with VistaAce software. Figure 10. Central axial slices from the TPS (Planned slice), and the post-irradiation CBCT (Measured slice), comparing the 3-field irradiation isodose lines from both institutions. 52 Figure 11. Scatter plot of 3D gamma pass percent set to 2 mm DTA and 10% dose threshold, and gamma maps of the 2%2mm criteria for both institutions. 4.3.2 C-shape spine plan Figures 12 and 13 present the C-shape plan and acquired dose distribution, 3D gamma pass percent (for DTA 2mm, 1-7% dose difference), and isodose maps for comparison. Table D2 (Appendix D) presents remaining 3D gamma pass percent rates of the C-shape spine treatment plan (2, 3, 5% dose difference, 1, 2, 3 mm DTA). For the gamma criteria presented in Table D2 of Appendix D, the maximum difference is 6.4% with dose criterion at 5% 1 mm with VistaAce analysis. The gamma failure region in this case is presented in red in Figure E1 of Appendix E. Note that the Figure E1 represents a 2D gamma map evaluation whereas Table D2 shows the 3D gamma computation. For institution B, the gamma failures were mostly associated with regions inside the 53 C-shape target, whereas for institution A, failures were seen outside the target volume. A reconstructed 3D gel and treatment plan are presented in Appendix C. In the tighter dose-difference criteria, the MATLAB analysis is more consistent between the two data compared to VistaAce. Figure 12. Illustrates: 1) a central axial slice of the AAPM TG-119 C-shape treatment plan and the isodose line to be delivered from Eclipse TPS (Top-Bottom left) 2) the isodose lines of the measured data from both institutions (Top-Bottom right). 54 Figure 13. Scatter plot of 3D gamma pass percent set to 2 mm DTA and 10% dose threshold, and gamma maps of the 2%2mm criteria for both institutions. 4.3.3 4-targets Stereotactic Radiosurgery For 4-targets SRS treatment plan, a tighter gamma criterion of 1mm DTA with 1-7% were used due to the requirement for high spatial accuracy. Figure 14 presents the plan and dose distribution, scatter plot of the 3D gamma results, and isodose maps for comparison. All other dose criterion for 3D gamma analysis, implemented in the previous sections, was performed for the 4-targets SRS treatment plan. The dose threshold was set to 10%. Table D3 (Appendix D) presents all the remaining 3D gamma pass percent rates from institution A and B using the two analysis pipelines. For the dose criteria presented in Table D3 of Appendix D, the maximum difference in 3D gamma pass rate is in dose criterion 2% 2mm, with about a difference of 7.9% using MATLAB analysis. 55 For VistaAce analysis, the maximum difference in pass rate at 5% 1mm dose criterion is difference of 7.4%. Figure C2 in appendix C presents the 3D visualization of the 4 targets in the original treatment plan, final reconstructed 3D gel images from institution A and B. Appendix E presents the gamma failure region of the gel data acquired from the two institutions. For both the institutions, the gamma failure region is associated outside the respective targets except 5%, 1 mm and 2%, 2 mm in institution B and A, respectively (figure E2, Appendix E). A similar trend in consistency was observed in the SRS treatment plan: better consistency was observed between the MATLAB analyses in tighter dose-difference region. Figure 14. Illustrates: 1) a central coronal slice of the SRS treatment plan to be delivered from Eclipse TPS (Top left), 2) a central coronal slice of the post-irradiation CBCT of the dosimeter (Bottom left), 3) the scatter plot of the 3D gamma pass percent, and 4) Central coronal slices representing the isodose lines of the measured data from both institutions (Top-Bottom right). 56 Figure 15 shows a diagonal line profile crossing the three SRS targets in the MATLAB, VistaAce processed images and the Eclipse plan. As shown in figure 15, line profiles have been acquired in a region of interest including a range of dose levels to investigate the response of the gel dosimeter to irradiation and evaluate its accuracy. Due to the high dose gradient that may be delivered to target volumes, this is highly significant in clinical applications, such as single isocenter multi-target SRS. A strong correlation was seen between the planned and measured results. The observed fluctuations in the plots may be attributed to imaging artifacts and noise arising from the analysis process. A higher fluctuation was observed in institution A’s dose profile due to the lack of image filtering process in their workflow. Background subtraction removes structural noise arising from the CBCT acquisition, however, a past study has shown that there are residual structural noise that are present, which can be removed with other image filtering processes such as Remnant Artefact Removal.126 57 Figure 15. Line profiles comparison: 4 targets SRS treatment plan (Institution A) 4.3.4 Signal-to-noise ratio comparison and image averages The institution B performed MATLAB analysis with adaptive mean filtering for noise, and remnant artefact removal for artefacts, whereas institution A performed the entire analysis in VistaAce without the artefact removal or adaptive mean filtering, therefore, we performed a signal-to-noise ratio comparison between the final images, with and without the noise reduction, in all the three-treatment plans. As shown in figure 16, the signal-to-noise ratio, as expected, is higher in the gel images with image processing implemented in the PGD workflow. A scatter plot of SNR against number of image averages used in the study is presented in figure 16 using the C-shape treatment plan based on a 10 by 10 mm square region of interest. A plot of SNR vs number of image averages may be useful to present if the gain in SNR is justifiable to perform multiple CBCT, especially when an efficient PGD workflow is desirable for implementation in wider 58 clinics. Note that the Figure 16 only shows the C-shape treatment plan since the trend in the increase in SNR for the other two treatment plan is expected to be similar. Figure 16. SNR vs image averages plot with and without image processing in both institution A and B in C-shape treatment plan 4.4 Discussion In this study, we present a dual-institutional evaluation of the reproducibility of a NIPAM-based polymer gel dosimetry workflow with Linac integrated CBCT readout, using a site-specific gel analysis technique. The three-treatment plans, gel dosimeter preparation, image readout techniques were all consistent across both institutions. Furthermore, we shared the CBCT images of the gel dosimeter between the two institutions and analyzed each other’s data with our respective software. Based on the results presented in the study, the 3D gamma pass percent is consistent to within an average difference of about 2.5% across the two institutions within each analysis software, based on various gamma criteria (Appendix D). 59 Although the general workflow of PGD technique in this current work was kept consistent, there are several key differences in the analysis based on the individual preference of the institutions. First, two different workflows were employed: Institution A used the VistaAce software, while B used an in-house MATLAB script. Second, in regard to the calibration technique, institution A used data points across the entire gel, whereas institution B used one central slice comprising of the entire dose distribution to calibrate the entire gel volume. Furthermore, a unique equation defining the calibration curve were used within the analysis software for each institution. Institution A used data points across the entire gel and a best fit curve was obtained by comparing the CT number to the calculated dose distribution. Institution B used a previously established technique to obtain the calibration curve by Johnston et al.,105 which then was refined by Jirasek and Hilts.163 A pixel-by-pixel comparison between the dose and calculated dose distribution was performed by an empirical model described by equation 2. Note that in institution B’s workflow, the calibration curve was only obtained after the image processing step (figure 9). In institution A's workflow, the calibration step was performed after image averaging and background subtraction, without any image processing (adaptive mean filtering and remnant artefact removal). The parameters of the calibration curves of the both institutions were presented in table B1 and B2 of Appendix B. Third, even though the treatment plan was the same, institution B used the dose matrix plan calculated on a CBCT image for the all the analysis, whereas institution A used the CT image from the treatment plan for analysis. The re-planning on the CBCT image consist of overriding the density of the gel dosimeter as “water” with +17 HU and physical density of 1.025 g/cm3,181 therefore, the CBCT values were not utilized to perform the dose calculation. This was implemented in institution B’s pipeline to eliminate the need for image registration during the 60 analysis. Note that the beam model utilized in the two institutions were not the same causing an inherent difference between the two experiments. Last, an image processing step (remnant artefact removal and adaptive mean filtering) was incorporated in institution B’s MATLAB analysis based on previous research.11 The use of image filtering may have influenced the spatial resolution of the gel images, and consequently could affect the gamma results. However, the parameters for adaptive mean filtering and remnant artefact removal utilized in this study was carefully chosen based prior studies and guidelines.126,152 These factors may have contributed towards the divergence in our 3D gamma pass percent results between the two analyses. However, within the context of the study, the current work showed better reproducibility in the gamma passing percentages within each analysis pipeline as opposed to in comparison to each other. Two gamma calculation approaches were utilized in this study. VistaAce utilized a geometric interpretation to the gamma formalism, whereas MATLAB analysis used the traditional interpolation approach.163,180 The geometric method has a couple of advantages over the traditional interpolation method. In general, the gamma calculated by the traditional interpolation approach have artefacts in the steep dose gradients causing an overestimation of the gamma values. This difference may explain the notable differences between the results, for example, a better consistency was observed in the VistaAce analysis method. Secondly the geometric method allows for a faster calculation since the search can be limited based on the distance-to-agreement criteria. Therefore, the appreciable differences between the two methods further warrants the need for a standardized analysis pipeline required for gel dosimetry studies. 61 This study highlights the importance of the image processing techniques in the overall gel analysis workflow. The institution B’s PGD analysis pipeline included a remnant artefact removal and adaptive mean filtering method, which improved the signal to noise ratio in all of the treatment plan with maximum gain in SNR about factor of 6. Although the SNR has increased, the 3D gamma passing rate is lower in MATLAB based analysis over VistaAce. This may be due to a number of potential differences discussed in previous studies182,183,179, such as the different computational approaches referring to whether or not to interpolate the evaluated dose distribution and whether to search the entire evaluated distribution or limit the search. While using similar dosimeters and Linacs, in this study, the method of calibration and the type of gamma analysis used by each institution are the most important differences between the two software. Furthermore, the gel images analyzed in MATLAB were smoothed by the image processing pipeline, which may also have affected the gamma results. One of the other inconsistencies between the two institutions were the wait time allocated prior to the post-irradiation CBCT scans. Due to the variability in our clinical schedules for the Linac availability, our wait times were slightly different, which may have contributed to the difference in our 3D gamma pass percentages. However, within each analysis, it is promising to observe the consistency in our 3D gamma pass percent rates, analyzed by sharing the data across the two institutions. These findings validate a prior study's182 conclusion that it is crucial for each institution to rigorously establish their own gamma analysis protocol by determining the specific type of gamma index analysis to be employed. In summary, an essential criterion for widespread applicability of Linac-Integrated Polymer Gel Dosimetry is the availability of standardized and thoroughly vetted analysis software in order to achieve comparable results across different institutions. 62 Other image processing tools to improve the image quality of the gel dosimeter have been used in the past. One such study by Kakakhel et al. used a “zero-scan” technique to improve the overall image quality of a polymer gel scanned with X-ray CT. The study generated large number of CT scans of the gel dosimeter, due to the fact that the absorbed dose also increases gradually over time, a function was fitted for the small increase in Houndsfield Unit over the scans. The intercept value enabled a formation of a new image “zero-scan” which represents the irradiated gel image prior to CT scan readout.157 In another study, the zero-scan technique was coupled with adaptive mean filtering to improve the SNR of the X-ray CT images.156Image processing can also use an averaging filter or a median filter as alternatives to the adaptive mean filter.170 In another early work by Jirasek et al. a 2D two-point maximum entropy regularization method (TPMEM) was used as an image filter to enhance the X-ray CT image quality. The results showed that the image processing tools not only were able to improve the SNR of an image, it was able to accomplish the task without minimally distorting the original image details.171 Another study by Adamson et al. using a 2D Gaussian filter was investigated.145 Another way to improve image quality is by using iterative reconstruction for CBCT images. In our study, we only used regular CBCT since some centers potentially may not have the iCBCT capability on their Linac system. The C-shape results obtained in this study can be compared to previously published TG-119 multi-institution benchmarking based on film results. Mynampati et al. reported a 3% 3 mm gamma pass percent of 96.8% based on film analysis.175 Our C-shape analysis obtained 3D gamma pass percent of 98.2% (institution A data), 96.7% (institution B data) based on VistaAce software analysis and 96.4% (institution A data), 95.4% (institution B data) based on MATLAB analysis. The results from our 3% 3 mm gamma analysis are consistent with the film analysis from the previously 63 published result.175 Another study by Saeb et al. Acquired 3%3mm and 2% 2mm gamma pass percent rate of 97.7% and 93.4% respectively, with EDR2 film measurements.176 Our 3D gamma pass percent (3% 3mm) is comparable, although the 2% 2mm dose criterion is lower (average 85.78% with our analyses). However, the advantage of using a gel dosimeter over a film, is it provides a 3D gamma measurement as opposed to a 2D measurement. One relatively novel approach implemented in this study is the use of same gel dosimeter in acquiring a pre- (background) and post- irradiation CBCT images. A previous study performed both the background and post-irradiation image readout using a single gel dosimeter.184 This workflow provides a unique advantage in positional accuracy over setting up a separate background gel and using another gel for irradiation. This is especially advantageous in commissioning stereotactic radiosurgery, where spatial accuracy of the dose delivery system is of utmost importance. The use of a single gel not only improves the efficiency of PGD workflow, but it also reduces the manufacturing cost of the dosimeters and reduces the error introduced by fabricating two gel dosimeters for each experiment. Our study has presented that the use of single gel for background and irradiation is not only efficient, but able to deliver high 3D gamma passing rates because of its accurate spatial positioning, and limiting errors introduced by setting up another gel. The use of single gel further adds extra superiority and presents the unique advantage of using CBCT over other gel readout methods when it comes to treatment verification in high dose radiation delivery technique since it provides unmatched spatial accuracy over CT, MRI, and other imaging modalities. This is achieved by removing the user setup error associated with setting up the background gel and post-irradiation gel separately and eliminating the need for the registration between the two. Although we implemented the workflow using a single gel, an image 64 registration between the background and irradiation images can be manually applied to avoid misalignment, however, a single gel for both background and irradiation workflow is more efficient both in terms of gel manufacturing and the precision and accuracy of the setup. One limitation of our current workflow is the implementation of a self-calibration technique to obtain the calibration curve that converts CT number to dose. For institution A, a number of different points across the gels were used to obtain a calibration curve. For institution B, we chose one central slice, which contained the information of an entire dose distribution, which is used to calibrate the rest of the slices. This type of self-calibration method indicates a baseline for achievable accuracy of the PGD workflow, removing errors due to dissimilarities caused by variation in manufacturing process, irradiation and read-out. Variation can also be caused by storage, handling, PGD set up and radiation delivery, which would be addressed by experimenting with multiple gel dosimeters as previously done by Maynard et al.123 However, in this study, the self-calibration technique is deemed sufficient enough to address our ultimate goal, which is to investigate the reproducibility of a gel dosimeter across two different institutions and present the achievable accuracy with this CBCT-based readout technique. An important advantage of performing a self-calibration technique is its practical workflow implications; fabricating a single gel for both calibration and testing enables a use of less chemical components and significant reduction of manufacturing time. For a wide-scale applicability of gel dosimetry systems, it is crucial to have a workflow that is efficient and practical for the clinical users. The other limitation of our PGD workflow is the total “Linac” time it took for each gel experiments. The entire CBCT scanning took about 72 minutes (with 6 pre- and 6 post-CBCT scans), and the irradiation along with the polymerization took around 40 minutes. However, for commissioning purposes, our PGD 65 workflow is deemed accomplishable and recommended in clinics. For regular and periodic system validation, our PGD workflow is limited by the long CBCT scan time, and therefore, is an unfavorable aspect of our PGD system. 4.5 Conclusion In this work we have highlighted the applications of PGD with a relatively new Linac integrated CBCT readout technique in validating complex radiotherapy dose delivery techniques, implemented by two separate institutions. The ultimate goals of our research were to examine the dual-institutional reproducibility of PGD workflow. Our analysis showed that PGD workflow has better reproducibility across the institutions when the same gel analysis tool was used. However, across the two analysis pipelines, we observe a variation in gamma results that indicates that a standardized and vetted analysis software is an essential element of a robust and widespread Linac-Integrated CBCT NIPAM 3D dosimetry program. We also highlighted the use of our novel approaches in PGD, such as Linac-integrated CBCT in acquiring high resolution gel images with slow CBCT modes. Furthermore, we implemented a PGD workflow without the need to manufacture an additional gel dosimeter for a background scan, thereby increasing the efficiency and reducing manufacturing cost. In summary, we demonstrated that utilizing PGD in commissioning various tasks is not only feasible, but recommended in a clinical setting. 66 Chapter 5: HyperArc® commissioning with 3D Polymer Gel Dosimetry In chapter 5, the gel dosimetry system was utilized to verify the 3D dosimetric and spatial accuracy of a HyperArc® SRS technique to treat intracranial brain metastases. In this project, three targets (3 cm, 2 cm, 1 cm) were defined in the verification plan, prescribed with a maximum dose of 25 Gy. Gamma pass rates of > 95% were observed for dosimetric result and a submillimeter delivery accuracy was observed for the geometric precision analysis. The work presented in this chapter was published as a conference paper in the Journal of Physics : Conference Series.185 I was responsible for the gel fabrication, treatment delivery and analysis. Dr. Hyde assisted in generating the HyperArc® treatment plan. Dr. Andrew Jirasek and Dr. Michelle Hilts provided guidance in the gel experiments and manuscript revision. 5.1 Introduction HyperArc® (Varian Medical Systems, Palo Alto, CA) SRS technique is utilized to deliver high-dose radiation to multiple lesions in the brain using a single isocenter treatment.186 HypeArc® is associated with a short treatment duration, thus improves patient comfort during the course of the SRS treatment. Dosimetric and spatial accuracy analysis of the SRS technique is essential, since missing the target may lead to radiation induced necrosis in the surrounding healthy brain tissue. The purpose of this work is to utilize a 3D polymer gel dosimetry system to investigate the delivery accuracy of the HyperArc® SRS technique. 67 3D polymer gel dosimeters (PGD) are a promising tool for treatment verification of complex radiotherapy techniques such as SRS.187 The inherent three-dimensional nature of PGD’s have the advantages of providing both 3D dosimetric and spatial information. Generally, gel dosimeters require a read-out method to extract dose information after the irradiation. This can be achieved with magnetic resonance imaging (MRI), optical computed tomography (OCT) and x-ray computed tomography (CT),109 however, more recently, Linac integrated cone-beam CT (CBCT) has become a promising alternative.146,145 The advantage of CBCT read-out is that it eliminates any positioning inaccuracies introduced when setting up the irradiated dosimeter for imaging off-line (for example with MRI or CT). Jirasek et al. have shown that acquiring CBCT images of the gel dosimeter 20-30 min after irradiation provides excellent polymerization yield (> 90%).146 Due to this short wait-time after the irradiation, we can achieve a close to “real-time” image acquisition after the dose delivery with CBCT modality. In this study, we use a polymer gel dosimeter imaged with CBCT to evaluate the dosimetric and spatial accuracy of a non-coplanar SRS technique, using a HyperArc® treatment plan (Varian Medical Systems, Palo Alto CA). 5.2 Methods 5.2.1 Gel fabrication The gels for this study were produced using the established manufacturing protocol outlined by Maynard et al.123 To summarize, the gel composition was 15% N-isopropylacrylamide (NIPAM, Sigma Aldrich, St. Louis, MO), 5% gelatin (Sigma), 5% N-N’-methylenebisacrylamide (Sigma), 10 mM tetrakis hydroxymethylphosphonium chloride (THPC, Sigma) and 75% deionized water. 68 Following mixing under precisely controlled temperatures, the final mixture was transferred into a 1 L gel jar (Modus Medical, London, ON), and then allowed to cool in a water bath in the refrigerator for a minimum of 5 hours. 5.2.2 Treatment planning The Eclipse treatment planning software (Varian Medical Systems, CA) was used to create a HyperArc® plan with 3 spherical targets (diameters 3 cm, 2 cm, and 1 cm), prescribed to a dose of 20 Gy (and maximum dose up to 25 Gy), mimicking an SRS treatment for multiple brain metastases. The Acuros XB V15.6 (PO) dose calculation algorithm was used with a 1 mm dose grid. The “HyperArc®” treatment plan comprised of 3 arcs (2 non-coplanar): couch rotation of 0° with the co-planar arc, 315° and 45° with the non-coplanar arcs. 5.2.3 Irradiation The gel dosimeter was allowed to equilibrate at room temperature prior to each irradiation. Similar to Johnston et al.105, the gel was positioned in a custom-made gel holder affixed securely to the treatment couch to maintain alignment during each couch rotation of the treatment. The set-up is shown in figure 17. 69 Figure 17. Illustrates the experimental set-up for the PGD irradiation and imaging. A Varian Truebeam Linac with a High-Density Multi-leaf collimator (HDMLC), with 6MV Flattening-filter-free (FFF) was used to deliver a volumetrically modulated arc therapy (VMAT) at up to 1400 MU/min. Couch rotations were manually set-up to the next position during the treatment since automated couch movement can only be enabled when delivering a true HyperArc® treatment technique with encompass immobilization. We did not use an encompass mask since only the gel dosimeter without the skull phantom was utilized in this experiment. The overall irradiation time took < 7 minutes. For both pre- and post-irradiation scans, a slow scan mode with 1620 mAs, 125 kVp, 5400 projections, 0.5112 pixel spacing, and 0.99 mm slice thickness was used to acquire the images of the gel. 70 5.2.4 Image processing All image processing and analyses were completed using an in-house MATLAB (MathWorks, Natick MA) program. Five pre- and five post-irradiation CBCT images were separately averaged and the averaged pre-irradiation images were subtracted from the averaged post-irradiation image. An Adaptive mean filter (3×3 kernel) and remnant artefact removal (RAR) (window span, 7) were used to reduce image noise and artefacts.146,126 Using the DICOM coordinate system of the CBCT image, the treatment plan was aligned to enable dose comparison. 5.2.5 Dose analysis A central slice containing the two largest targets was used to obtain a calibration curve to convert the CT number (pixel values) to dose using the corresponding treatment plan slice. The entire volume of gel was “self-calibrated” using the calibration curve obtained from the central slice. The calibration method utilized a pixel-by-pixel calibration, which covers the entire dose distribution. 3D Gamma analysis (https://github.com/mwgeurts/gamma) was performed with dose criterion of 5% 1mm, 3% 1mm and 2% 1 mm with 30% threshold throughout all the slices that contained 3 targets (~ 49 slices). The gamma analysis method utilized the traditional interpolation method of gamma computation described by Low et al.180 30% of 25 Gy yields 7.5 Gy, which is well below 12 Gy and that is the dose threshold for the occurrence of radiation necrosis. However, typically, in our clinic, a dose threshold of 10% is utilized. 71 5.2.6 Spatial accuracy analysis A 3D center of mass calculation was performed on the 3 targets, both in the plan and measured image. The distance between the two center of mass coordinates was calculated on the same targets, which was then converted to mm in terms of spatial distance between the two. 5.3 Results 5.3.1 3D gamma analysis The gamma pass percentages achieved with thresholding the dose to 30% of the maximum dose (25 Gy) was 99.9%, 98.5%, 96.6% for 5% 1mm, 3% 1mm and 2% 1mm respectively. All gamma pass percent rates were above 95%. Figure 18. a.) Illustrates the dose profile along x = 120, y = 130, and diagonal direction through the 2 out of the three targets. 2.b.) The dose profile on the image slice containing the third target (1 cm), along x = 62, y = 91 horizontal and vertical profile. The color bar represents the dose in Gy. 72 A dose profile along three directions (horizontal: x = 120, vertical: y = 130, and diagonal) of an example slice from the measured and planned dose images are shown in figure 18 a.). The diagonal profile was plotted to evaluate the profile across both the targets. Figure 18 b.) shows the dose profile along the image slice containing the third target (1 cm). 5.3.2 Spatial accuracy analysis The spatial accuracy analysis shows that delivered target center of mass agrees with planned position within 0.7mm for all targets. The spatial accuracy of the 3 cm, 2 cm, and 1 cm targets were achieved within 0.58 mm, 0.62 mm, and 0.60 mm respectively. 5.4 Discussion In the current study, we evaluated the dosimetric and spatial accuracy of a “HyperArc®” treatment plan comprising of three targets, using a novel CBCT polymer gel dosimetry technique. Both 3D spatial and dosimetric conditions were in satisfactory agreement between the treatment plan and the measurement, with gamma criterion of 5% 1mm, 3% 1mm and 2% 1mm all > 95%. Dose threshold set to 30% is used to evaluate for target coverage and conformality. 30% of maximum dose (25 Gy) delivered in this study is 7.5 Gy, which is well below the 12 Gy dose threshold for the occurrence of radiation necrosis. Furthermore, Acuros XB algorithm utilizes an adaptive mesh refinement, such that any doses below 15% would be calculated at a lower spatial resolution. For dosimetric comparison purposes, threshold is set above the 15% level. This study forms an essential step towards fully commissioning the clinical workflow of the HyperArc® technique in our clinic. The results from the current study may also provide incentive 73 for other institutions to utilize polymer gel dosimetry in their clinics to verify treatment such as SRS where spatial localization of the dose delivery is of utmost important. Geometric miss in an actual patient treatment delivery may cause a loss of target coverage, thereby, underdosing the PTV. Our study has shown that a sub-millimeter accuracy can be achieved with SRS treatment delivery using the 3D spatial information extracted from the polymer gel dosimeter. Our study also highlighted the advantages of implementing CBCT for the read-out of the polymer gel dosimeter to minimize positioning inaccuracies and essentially providing a “real-time” dose read-out. 3D reproducibility of the PGDs with multiple irradiations will be analysed in our future work. 5.5 Conclusion The current study showed that CBCT polymer gel dosimetry can be a valuable clinical tool to commission highly complex radiation delivery techniques such as SRS. A 3D gamma analysis showed that all dose criterions were met, and a sub-millimeter accuracy of the dose delivery was achieved. 74 Chapter 6: SRS Virtual cone commissioning with 3D Polymer Gel Dosimetry In chapter 6, the gel dosimetry system was utilized to evaluate the dosimetric and geometric precision of a novel virtual cone technique for the treatment of trigeminal neuralgia planned with the latest Eclipse version 18.0. The dosimetric results were benchmarked against a GafChromic film dosimeter, which is currently the gold standard for SRS treatment verification. A 3D printed anthropomorphic phantom was utilized to evaluate the end-to-end spatial accuracy. This type of end-to-end analysis is only achievable with gel dosimetry system with CBCT readout. The work presented in this chapter is currently under review in the Journal of Applied Clinical Medical Physics. I was the primary author of this work and my contribution to the project encompasses gel fabrication/measurement/analysis, film measurements/analysis, interpretation, 3D modelling and 3D printing the anthropomorphic phantom. Dr. Michael Lamey created the C# code for virtual cone planning. Dr. Derek Hyde generated the v18.0 verification plans, performed planning for our initial commissioning work, and provided guidance in all the gel and film experiments. Dr. Andrew Jirsek provided support and guidance in terms of the interpretation of the gel dosimetry results. Dr. Nathan Becker and Dr. Benjamin Mou advised the authors with their clinical expertise. Dr. Becker also performed output verification and second-checked the SRS treatment plans. Dr. Tony Teke assisted in film analysis. Dr. Michael Kudla and Mark Robinson assisted in the 3D printing process of the anthropomorphic skull phantom. 75 6.1 Introduction Trigeminal Neuralgia (TN) is a rare neurological condition that affects 4 to 13 people in 100,000 annually.188 Although the incidence of TN is uncommon, it is among one of the most common facial pain syndromes.188–190 TN is characterized by severe, unilateral, and episodic pain that has significant implications on the patient’s quality of life.191,192 Treatments for TN include medications, surgical procedures, and non-invasive radiotherapy utilizing stereotactic radiosurgery (SRS).189 Traditionally, trigeminal neuralgia was treated with stereotactic radiosurgery (SRS) utilizing a Gamma Knife unit, a Cyberknife or C-arm Linac with a physical stereotactic cone.189,193–197 A Gamma Knife or Cyberknife unit is not readily accessible in many radiotherapy centers. A C-arm Linac with a physical stereotactic cone has its own limitations, including the requirement for additional machine quality assurance, a cone-specific dose calculation algorithm, and patient-specific quality assurance, which significantly increases the clinical workload.198,199 To mitigate these challenges, researchers at the University of Alabama at Birmingham (UAB) developed a virtual cone technique utilizing a Varian High-Definition Multi-Leaf Collimator (HDMLC) to deliver a small spherical dose distribution with 70-90 Gy at the isocenter.197 The isocenter is typically placed such that the 50% isodose volume (40 Gy) is close to the brainstem, which is a critical structure inside the brain.200 The dose limit for the brainstem for an SRS radiotherapy is 15 Gy, based on the 2010 AAPM Task Group 101 report.201 Thus, an evaluation of the dosimetric and geometric accuracy of the virtual cone delivery is of high importance to overcome serious complications, for instance, brainstem necrosis that can result in death or disabling neuropathy.202 This virtual cone method produces a spherical dose distribution that approximates that of a 5 mm 76 physical stereotactic cone. A static field is defined by the two central collimator leaf pairs and collimator angles of 45 and 315 degrees are used to deliver an X pattern with two arcs at each couch angle. A 10-MV Flattening Filter Free (FFF) beam is used to deliver 10 arcs and the monitor units (MU) delivered per degree is varied by the sine function of the gantry angle in order to produce the spherical dose distribution. The use of the 10-MV FFF beam with a maximum dose rate of 2400MU/min enables the treatment time to be significantly reduced from a 6-MV FFF beam with a maximum dose rate of 1400MU/min.203 Accurate dosimetry of the virtual cone technique is challenging due to the well-known small field conditions in SRS radiotherapy204 : the lack of lateral charged particle equilibrium in beam axis, partial blockage of the primary photon source, and detector size larger than the photon beam dimensions.205 A detector size with sub-millimeter dimension underestimates the dose due to its low mass density whereas over responsive characteristics are observed in other detectors made with high mass density material.206 Gafchromic films (EBT3/EBT-XD) are typically the gold standard for SRS radiotherapy technique due to its high spatial and dosimetric resolution, however, the film scanning and subsequent processing inherently removes the capability to measure a true end-to-end spatial accuracy. A dosimeter that can measure both the dosimetric and geometric precision accurately and simultaneously for the virtual cone SRS technique is invaluable to the clinical workflow. 3D Polymer gel dosimeters are fabricated using radiation sensitive chemicals that undergo polymerization and crosslinking when exposed to ionizing radiation. Gel dosimeters offer distinct advantages over traditional 1D and 2D dosimetry for treatment verification of advanced radiation 77 therapy procedures, especially when steep dose gradients exist.109 The intrinsic 3D characteristics of the gel dosimeter enables a dose distribution to be mapped for the entire 3-dimensional space. Gel dosimetry eliminates the need to utilize multiple point dosimeters (e.g., TLDs) or to measure the dose in multiple planes (e.g., film) if 3D verification is required. Gels are tissue equivalent, have high spatial resolution, low energy dependence,207,162 and can be incorporated into an anthropomorphic phantom.208 As such, polymer gel dosimetry is invaluable for end-to-end testing of complex radiotherapy techniques.90 End-to-End testing refers to evaluation or testing of an entire clinical workflow from CT simulation to radiotherapy delivery. Despite these potential benefits, clinical adoption of gel dosimeters is still relatively uncommon and has potential for further development. Polymer gel dosimetry relies on an imaging tool to read out the 3D dosimetric data. The imaging tool may be Magnetic Resonance Imaging (MRI), X-ray Computed Tomography (CT), optical CT, or Linac-integrated kV cone beam CT (CBCT).109,143,146,165,209 MRI offers excellent spatial and contrast resolution, however, MRI is not readily accessible for many radiotherapy centers. X-ray CT and optical CT are generally more feasible from an accessibility standpoint, however moving the dosimeter to another system for the readout introduces an inherent spatial inaccuracy (also holds true for MRI imaging). Furthermore, the differences in the spatial frame of reference between the Linac and the CT can complicate the dose registration.166 For treatment verification of complex radiotherapy techniques such as SRS, a readout method based on Linac-integrated CBCT is appealing for multiple reasons. It provides unmatched spatial accuracy over the other imaging modalities since the setup for treatment position is identical to the readout position. Therefore, there is no user setup error associated with the dose delivery and measurement.146,166 Secondly, 78 after the radiation is delivered to a gel dosimeter the readout can be acquired in the same session, as a wait time of 20 minutes, for polymerization and crosslinking, is adequate (> 90% polymerization yield).146 A previous study by Pant et al. has used gel dosimetry with CBCT imaging to verify the treatment isocenter of the Linac, and quantify the spatial uncertainty associated with it.147 Moreover, Adamson et al. performed a proof-of-principle study to visualize the 3D dose distribution on the gel dosimeter immediately after irradiation, using CBCT imaging.145 However, the clinical applications of Linac-integrated CBCT in gel readout is still not as routine as other imaging modalities, such as MRI and X-ray CT. In this work, a polymer gel dosimetry workflow with CBCT readout was utilized to verify the spatial and dosimetric accuracy of the virtual cone technique.197 The dosimetric results from the gel are benchmarked against a film dosimeter, which is the gold standard measurement tool in many clinics. Furthermore, we performed a dedicated and complete end-to-end spatial accuracy analysis using a low-cost 3D printed anthropomorphic skull phantom. 6.2 Material and Methods 6.2.1 Implementation of the virtual cone technique We developed an in-house eclipse executable script in C# to generate a virtual cone treatment plan, based on the original work by the UAB.197 As in their work, our eclipse script generated ten arcs for five couch positions: 2 arcs per each unique couch angle. The five couch angles were 0°, 36°, 72°, 288°, 324° degrees with the collimator set to 45° and 315° for each couch position. For 0° couch angle, a 360° arc was used, whereas the remaining couch angles had 180° partial arcs.197 The original UAB study recommended the formula: 2.1 mm + 0.36 mm-Dosimetric Leaf Gap 79 (DLG ) to obtain the MLC leaf separation to account for the institutional differences in DLG settings.197 As such, our institutional DLG of 1 mm, resulted in 1.4 mm leaf separation for the virtual cone technique. Using the 1.4 mm leaf separation, our institution has treated several TN patients with the virtual cone method using treatment planning system version 15.6 (Varian Medical Systems, Palo Alto CA). We decided not to implement a separate beam model, knowing that we would be upgrading our treatment planning system in the near future. We are currently in the process of transitioning to Eclipse version 18.0 (Varian Medical Systems, Palo Alto CA), which no longer includes a dosimetric leaf gap (DLG) offset and essentially models the MLC leaves. In this work, we used the same 1.4 mm leaf separation for all the virtual cone verification plans generated with v18.0. 6.2.2 Treatment planning and delivery As per the UAB technique, the MU per degree varied proportionally to the sine of the gantry angle.197 The dose calculation algorithm used was Acuros XB v15.6 with PO (Varian Medical Systems, Palo Alto CA) and all the treatment plans were delivered with a Varian Truebeam (Varian Medical Systems, Palo Alto CA) with all the Edge capabilities (HDMLC, 6DOF couch, Identify SGRT). The 10 MV FFF beam with 2400 MU/min dose rate was used for all the experiments. The clinical treatment plan originally with a prescription dose of 80 Gy at isocentre (using Eclipse v15.6) were recalculated on the respective QA phantom with a maximum dose of 20 Gy to prevent film/gel saturation. These were then recalculated with v18.0 using the same MU for comparison. 80 Three phantom experiments were conducted: 1.) a cylindrical phantom with EBT-XD film insert 2.) 3D Gel with an additional calibration region 3.) Gel inserted into a 3D printed anthropomorphic phantom. The goal of our first gel experiment was to characterize the relative dosimetric properties of the gel dosimeter. Therefore, for the dosimetric analysis, we used the gel only experiment with the verification plan that contains a virtual cone and a calibration region on the same gel. The calibration plan involved a (- 4 cm) longitudinal couch shift and was delivered on the same gel with 2 co-planar arcs. The calibration dose was slightly higher than 20 Gy to ensure that entire dose distribution of virtual cone is comfortably covered within the calibration region (Appendix A1). A single gel was used for the calibration process to avoid any potential differences due to the chemical batches and intra-user manufacturing variability. The setup for this irradiation is shown in figure 19. The verification plan generated for the 3D printed anthropomorphic skull phantom was used for a dedicated end-to-end spatial accuracy verification. The skull phantom was setup using CBCT and treated like an actual TN patient with the virtual cone technique. The setup for this radiation delivery is shown in figure 20. 6.2.3 EBT-XD film analysis The FilmQApro software (Ashland Advanced Materials, Bridgewater, New Jersey) was used to analyze all the film measurements. Measurements were conducted in two film orientations (sagittal and coronal plane). The measured film data were scanned digitally, 24 hours post-irradiation with 81 an Epson Expression 12000XL flatbed scanner (Nagano Japan). The measured film data was placed at the center of the scanner and scanned at a resolution of 50 dpi. The red channel was used for all film analysis. A profile along the sagittal plane (anterior-posterior), coronal plane (left-right), coronal plane (superior-inferior), sagittal plane (superior-inferior) was exported for the virtual cone experiment. The 10 Gy isodose width was measured. Our standard EBT-XD film protocol uses a cylindrical polystyrene phantom (radius = 10 cm, height = 30 cm). Prior to delivering the virtual cone plan, we delivered calibration doses to 4 strips of the EBT-XD film obtained from a single manufacturing batch. The respective film strips were exposed to known radiation dose with 10x10 cm field size, under the reference condition in a polystyrene slab phantom at 95 cm SSD. The film strip was centered on the 10 x 10 cm2 field and placed at 5 cm depth of the phantom. The calibration experiment was performed on the same day as the virtual cone experiment, to ensure that the Linac output and ambient conditions are all kept identical between the calibration and the virtual cone treatment delivery. 6.2.4 Gel Dosimetry workflow 6.2.4.1 Gel Fabrication A NIPAM gel dosimeter was fabricated based on a previously published protocol.123 In summary, the dosimeter composed of 15% N-isopropylacrylamide (NIPAM, Sigma Aldrich, Mississauga ON, Canada), 4.5% N,N’-methylenebisacrylamide (BIS or MBA, Sigma), 5% 300 bloom gelatin (Sigma), 10 mM tetrakis(hydroxymethyl)phosphonium chloride (THPC, Sigma), and 75.5% deionized water. After carefully following the mixing procedure, the dosimeter was cooled in a 1 L jar (Modus Medical, London ON, Canada) in a water bath inside a refrigerator for at least 5 82 hours. Prior to the irradiation, the gel dosimeters were allowed to stabilize at the room temperature for at least 5 minutes. Figure 19. All panels illustrate the gel experiment set-up for the dosimetric analysis containing a verification plan with virtual cone and calibration region is shown from different views. 6.2.4.2 Gel readout and analysis Six pre-irradiation CBCT and six post-irradiation CBCT images were acquired in order to reduce image noise and provide background subtraction. For both the gel experiments, the 6 pre-irradiation and 6 post-irradiation CBCT images were individually averaged, and then background subtracted from one another. An adaptive mean filtering (3 x 3 kernel) and remnant artefact removal (window span = 7) was applied to the background subtracted image slices to reduce the image noise and artefacts respectively. For 3D gel dosimetric study, the imaging parameters used for both the pre- and post-scans was a slow CBCT scan mode with 1620 mAs, 125 kVp, 5400 projections, 0.5112 pixel spacing and 0.99 mm slice thickness. The calibration region, delivered with two co-planar arcs, was used to acquire 83 a calibration curve relating the dose to the CT number. The calibration curve (appendix F; figure F1) obtained was used to calibrate the irradiated gel region containing the virtual cone dose distribution. To enable pixel by pixel calibration without an interpolation step, we recalculated the delivered verification plan on one of the acquired CBCT images. We measured the 10 Gy isodose width (50% isodose width) in sagittal and coronal planes of the verification plan and the gel data. For the end-to-end spatial accuracy analysis with the anthropomorphic skull phantom, an iterative CBCT scan mode with 2160 mAs, 125 kVp, 5400 projections, 0.5112 pixel spacing, and 0.99 mm slice thickness resolution was used. We increased the mAs and used the iterative reconstruction method since the gel was imaged within the anthropomorphic phantom. This was done to maintain the geometric position and eliminate any user-set up error from the removal of the skull phantom. Using a higher mAs and iterative reconstruction reduce the image noise caused by the heterogenous materials in the skull phantom, while not contributing significantly to the image distortion. Moreover, the role of image processing in our gel workflow was necessary to recover the underlying signal of the dose distribution in the noisy image of the anthropomorphic phantom. A self-calibration technique was performed by selecting the central slice of the virtual cone verification plan and calibrated the entire gel data with the corresponding iterative CBCT slice (Figure 24). To enable pixel-by-pixel calibration in the phantom study, the original planning CT was interpolated to the dimensions of the CBCT in order to obtain the calibration curve parameters. The 3D center of mass (COM) of the 10 Gy isodose region was calculated for the Eclipse verification plan and the gel, and then the Euclidean distance between them was then calculated. 84 The experimental set-up and v18.0 verification plan involving 3D anthropomorphic phantom is shown in figure 20. Figure 20. a.) Shows the 3D printed anthropomorphic skull phantom setup. b.) The virtual cone plan generated on the planning CT of the skull phantom is shown. The entire gel analysis was completed using our in-house MATLAB script (MathWorks, Natick, USA). For the center of mass calculation, regionprops3, a built-in function in MATLAB was used.210,211 Moreover, the equivalent diameter of the spherical 50% isodose region in mm was also measured for the 3D anthropomorphic skull phantom study resembling an actual virtual cone treatment delivery. The empirical calibration curve model is as follows: 𝛥𝑁𝐶𝑇 = ⁡𝛼 + 𝛽 𝑡𝑎𝑛ℎ(𝛾𝐷 − 𝜑)⁡ 85 Where ∆𝑁𝐶𝑇 is the change in CT number of the gel, D represents dose, 𝛼, 𝛽, 𝛾,𝜑⁡represents the parameters of the calibration equation. The parameters defining the calibration equations, acquired from the two gel experiments with 95% confidence interval are provided in Appendix F (table F1). 6.2.4.3 3D printed anthropomorphic skull phantom A 3D printed anthropomorphic skull model was devised such that it accommodates the gel dosimeter jar inside the skull phantom. The gel dosimeter jar fits in through the “neck” of the skull phantom and covers a significant portion of “brain” space. An STL model was acquired from a patient CT image from the TCIA image database.212,213 The skull was segmented using an HU threshold setting (500 (lower)-1200 (higher)) and the file was exported in an STL format using the 3D slicer software.214 The 3D printing software, Meshmixer (Autodesk, San Francisco, USA), was used to clean and re-model the skull phantom, such that the gel jar can be inserted into the anthropomorphic phantom. The outer skull structure was 3D printed with a CaCO3 PLA (Protopasta, Vancouver, Washington, USA).215 The CT number of the skull structure (CaCO3) was 636 Hounsfield unit (HU) and had a physical density of 1.45 g/cm3. We selected the CaCO3 PLA material as a representation of bone over other high-density PLA used in a previous study, such as iron, copper and bronze,216 to reduce artifacts in our background and post-irradiation CBCT images. Image distortion and artefact (streaking) is commonly observed in images of the previously used high-density materials and would be detrimental to the gel image analysis.216 The ‘brain’ was represented with VytaFlex-50, a urethane rubber casting material (Smooth-On Inc, Macungie, Pennsylvania, USA), with a CT number 30 HU and a physical density of 1.04 g/cm3. The Acuros XB calculation with dose-to-medium was used, both the CaCO3 and VytaFlex-50 86 materials were assigned as water with their appropriate mass densities overridden for dose calculation. Our 3D printed anthropomorphic phantom is a low-cost SRS phantom (raw material cost < 900 USD), which could be manufactured at any center with 3D printing capabilities (figure 20). 6.3 Results The eclipse v18.0 (Acuros XB) verification plans for both the gel and film dosimeter resulted in a lower peak dose compared to the original plan (v15.6) with max dose of 20 Gy. The treatment plan was previously delivered to a trigeminal neuralgia patient with the clinical v15.6. However, the scope of the current thesis chapter is the evaluation of the accuracy using the pre-clinical v18.0 system. In all the subsequent figures, the calculated peak dose is lower than 20 Gy, however, the full width half maximum of the measured film profile was consistent with the v18.0 verification plan. The dose profiles within Eclipse v15.6 were slightly larger than our patient-specific QA measurements using Gafchromic film (EBT-XD, Ashland Specialty Ingredients, Bridgewater, NJ, USA), which were closer to 5mm at 10 Gy. 6.3.1 EBT-XD film analysis The EBT-XD film analysis was completed in two orientations: coronal and sagittal plane. Figure 21 presents the profile along the sagittal plane (anterior-posterior), coronal plane (left-right), coronal plane (superior-inferior) and sagittal plane (superior-inferior). We measured a 50% 87 isodose width of 4.70 ±⁡0.08 mm, 5.34 ±⁡0.25 mm, 4.87 ±⁡0.15 mm, 4.70 ±⁡0.07 mm in the sagittal plane (anterior-posterior), coronal plane (left-right), coronal plane (superior-inferior) and sagittal plane (superior-inferior) respectively. The dose profile along sagittal plane (superior-inferior) represents an alternative measurement to the coronal plane (superior-inferior). The measurements are presented in table 4. We observe a lower peak in the Eclipse v18.0 plan relative to the gel measurement, however, with our clinical v15.6 treatment plan, the maximum dose is more consistent with the film measurement. However, the 50% isodose width measurement of the v15.6 treatment plan was wider than the v18.0. The Eclipse v15.6 results are not incorporated in this thesis and is out of the scope of the current work. Figure 21. Illustrates the dose profile along the a.) sagittal plane (anterior-posterior), b.) coronal plane (left-right), c.) coronal plane (superior-inferior), and d) sagittal plane (superior-inferior) with EBT-XD film and the v18.0 verification plan. 88 Table 4. The 10 Gy isodose width of profile along sagittal plane (anterior-posterior and superior-inferior), coronal plane (left-right and sup-inf) using EBT-XD film dosimeter. Sagittal plane (Ant-Post), (mm) Coronal plane (Left-Right), (mm) Coronal plane (Sup-Inf), (mm) Sagittal plane (Sup-Inf), (mm) (Mean) ± SD (mm) Calculation (Eclipse v18.0) 5.50 mm 5.41 mm 5.50 mm 5.50 mm 5.47 ± 0.05 mm Measurement (EBT-XD film) 4.70 ±⁡0.08 mm 5.34 ± 0.25 mm 4.87 ± 0.15 mm 4.70 ± 0.07 mm 4.90 ± 0.30 mm 6.3.2 3D Gel dosimetry analysis Figure 22 presents the dose profile along the sagittal plane (anterior-posterior), coronal plane (left-right) and coronal plane (superior-inferior) through the pixel containing the maximum dose of the eclipse verification plan and the corresponding pixel position in the gel image. The maximum peak dose through the sagittal plane (anterior-posterior) and coronal plane (left-right) profile is observed to be smaller than the verification plan. In the case of coronal plane (superior-inferior), we observe a large spike in the dose profile, furthermore the profile along this direction appears to be truncated. We calculated the Euclidean distance between the two centers of masses (3D) of the 10 Gy isodose region of the verification plan and the gel, resulting in measured distance of 0.66 mm between the two centers of masses. However, this does not represent a complete end-to-end spatial accuracy test since the verification plan was re-calculated on one of the acquired CBCT image prior to the analysis to match the plan image and CBCT image dimensions for analysis purposes. In the re-calculation process, a density override was performed to assign the gel dosimeter as “water” material with an accurate HU value of +17 and the physical density of 1.0256g/cm3.181 89 Table 5 presents the 10 Gy isodose width of the profiles across Axial plane (anterior-posterior), Axial plane (left-right) and coronal plane (superior -inferior). The largest deviation between the eclipse verification plan and gel was in the coronal plane (superior-inferior) of about 1.35 mm. In figure 22 (c), we observed a partial volume effect due to the CBCT resolution in the slice thickness direction. In Axial plane (left-right and anterior-posterior), a maximum deviation of 0.37 mm is observed by measuring the 50% isodose width between the verification plan and gel, presented in table 5. The error in the measurements of the 50% isodose profile were obtained in a two-step process. Firstly, the width of the profile one pixel above and below the central pixel at 10 Gy was measured. Secondly, the difference between each of the two measured values and width through the central pixel was calculated and averaged to get the final uncertainty. Alternatively, an uncertainty estimation for each system may be incorporated as performed in the prior study if they are known.203 Note that this was done also in the film measurement in the previous section. Figure 22. Individual Gel. Illustrates the dose profile along the a.) Axial plane (anterior-posterior), b.) Axial plane (left-right), c.) coronal plane (superior-inferior) using the 3D gel dosimetric analysis. 90 Table 5. Presents the 50% isodose width of the profile across Axial plane (anterior-posterior), Axial plane (left-right), and coronal plane (superior-inferior) using the 3D gel dosimetric analysis. Axial plane (Ant-Post), (mm) Axial plane (Left-Right), (mm) Coronal plane (Sup-Inf), (mm) Mean (mm) Calculation (Eclipse v18.0) 5.48 mm 5.46 mm 5.27 mm 5.40 Measurement (Gel) 5.11 ± 0.08 mm 5.20 ± 0.08 mm 3.92 ± 0.05 mm 4.74 6.3.3 End-to-End Spatial accuracy test with 3D anthropomorphic phantom and IGRT setup Figure 23. Gel within Anthropomorphic phantom with CBCT setup Illustrates the line profile across the maximum dose of the eclipse verification plan: a.) Axial plane (anterior-posterior) b.) Axial plane (left-right) c.) coronal plane (superior-inferior). Figure 23 illustrates the dose profiles along the pixel with the maximum dose of the eclipse verification plan, and the corresponding profiles along the same pixel position acquired from the gel insert in the 3D anthropomorphic skull phantom. A relatively better agreement in 50% isodose widths is seen in the Axial plane (anterior-posterior), whereas in the coronal plane (left-right), the maximum peak dose in the profile is shifted approximately about a 1 pixel (~ 0.5 mm). Due to the limited slice thickness resolution in the coronal plane (superior-inferior), we observe a truncated 91 profile similar to the prior gel study. Furthermore, the gel profile appears to be shifted by approximately 1 mm along the slice thickness direction (figure 23 c). We calculated the Euclidean distance between the two 3D centers of masses of the eclipse verification plan and gel. The distance between the two centers of masses measures 0.95 mm using the 50% isodose region. This investigation represents a complete end-to-end spatial accuracy testing of our virtual cone radiotherapy workflow using a low-cost 3D printed anthropomorphic phantom. We present the equivalent diameter of the 10 Gy isodose region in millimeters in Table 6. Note that the equivalent diameter of eclipse v18.0 plan for the end-to-end spatial accuracy analysis is calculated using the interpolated CT image to match the CBCT image dimensions for calibration purposes. Table 6. Equivalent diameter of the 10 Gy isodose region in the 3D printed anthropomorphic gel experiment in mm Eclipse v18.0 (Equivalent diameter of 10 Gy isodose volume in mm) Gel (Equivalent diameter of 10 Gy isodose volume in mm) End-to-end spatial accuracy 5.53 mm 5.03 ±⁡0.02 mm Figure 24 a.) shows a central slice of the image acquired with iterative CBCT, b.) gel with image processing, c.) and the final calibrated gel slice. We analyzed the dose contribution of CBCT imaging to the gel dosimeter in both of our experiments. In our analysis, for each CBCT scan, a dose of about 0.032 Gy (for 12 scans ~ 0.38 Gy) was measured. For our iterative CBCT scan, each 92 scan contributed a dose of 0.043 Gy (for 12 scans ~ 0.52 Gy). The dose in the latter experiment is higher since a higher mAs was utilized to image the skull phantom with the gel dosimeter jar. A total dose percentage of 1.9% and 2.6% were contributed to the gel in dosimetric analysis and end-to-end spatial accuracy experiment, respectively. The dose contribution of CBCT readout is significantly lower than the dose delivered, moreover, the use of background subtraction reduces the dose contribution of the CBCT scans during the analysis. Figure 24. a.) Gel image after averaging and background subtraction. b.) Filtered image with image processing. c.) The final calibrated image. The colormap indicates dose in Gy. 6.4 Discussion The publication by UAB utilized a stereotactic end-to-end verification anthropomorphic skull phantom (Computerized Imaging Reference Systems, Norfolk, VA) with the EBT-XD GafChromic film dosimeter insert (Ashland Chemical, Covington, KY). An output constancy check was performed with a 2 cm parallel plate ion chamber (Exradin A11, Standard Imaging, Madison. WI). Their treatment plan was normalized to deliver 20 Gy at the isocenter. In their work, the 50% isodose width of a 2.1 mm dosimetric leaf gap (DLG) corresponded to the width of a 4 mm physical stereotactic cone.197 More recently, a study by Brown et al. at the Tri-cities Cancer 93 Center (TCCC) reproduced this SRS technique in collaboration with UAB, and their commissioning data was benchmarked against the previous UAB study.203 In their work, EBT3 film (Ashland Advanced Materials, Bridgewater, NJ, USA) and Exradin W2 scintillation detector (Standard Imaging, Middleton, WI, USA) were used to commission this SRS technique with the multi-leaf collimator leaf gap measuring 2.1 mm. The original UAB study performed the treatment with 10 MV FFF (Anisotropic Analytical Algorithm (AAA), Eclipse version 13.6), whereas the TCCC study used 6 MV FFF beam (Eclipse version 15.6). More recently Neupane et al. implemented a fixed MLC field setting (0.5 by 0.5 cm) using this SRS technique in their center.217 This group used SRS MapCHECK (Sun Nuclear Corporation, FL) to measure the 50% isodose width of the dose distribution and reported that the results are comparable to a physical stereotactic cone.217 Their study corroborated the previous findings and concluded that a virtual cone technique is indeed a viable method for an SRS treatment for trigeminal neuralgia. Another recent study by Eric Lobb et al. adapted this virtual cone technique to a standard MLC with 5 mm leaf width and concluded that it is feasible to efficiently generate a spherical dose distribution for small brain metastasis. Although, physical stereotactic cones were able to achieve superior peak dose gradients as opposed to the adapted virtual cone technique, the current novel SRS technique could be useful as an alternative method to decrease the cost, complexity and improve technology consolidation in an SRS program. In our work, we commissioned the virtual cone technique planned with the recently released eclipse v18.0 (Acuros XB) using a film and gel dosimetry technique. Reproducing the virtual cone method for the eclipse v18.0 did not require the use of a specifically tuned DLG offset for this delivery, and moreover, utilizing Acuros XB for dose calculation algorithm potentially achieves 94 greater dose calculation speed.218,219 For the dosimetric analysis, we benchmarked our gel dosimetry results to film, which is the current standard in our clinic. The 10 Gy isodose width profiles showed relatively good agreement between the gel and the EBT-XD film dosimeter. The largest deviation of 0.86 mm, between the film and gel is observed in coronal plane (superior-inferior). This may be caused by the partial volume effect evidently observed as a result of the poor resolution of CBCT in slice thickness (0.99 mm) direction compared to the axial resolution (0.5112 mm). Despite this shortcoming, the important advantage of using a gel dosimetry system is the availability of the 3D dosimetric information without the need to perform additional set up or experimentation. In addition to the 3D dosimetric data, we were able to obtain complete 3D spatial information using the gel dosimeter. Our results indicated that the virtual cone treatment delivery in the current study was accurate to within 0.95 mm in the end-to-end spatial accuracy verification using the anthropomorphic head phantom. The 3D center of mass distance observed in the gel dosimetric analysis was calculated as 0.66 mm and our MV-KV imager offset was found to be approximately 0.29 mm (Daily Machine Performance Check). The 0.66 mm distance observed in the gel only study, inherently represents the limitation of the CBCT slice thickness resolution. Therefore, the end-to-end spatial accuracy result is consistent within the two studies and our expectation. This type of end-to-end spatial accuracy analysis is currently only achievable with gel dosimetry with CBCT readout. It should be noted that the 0.95 mm end-to-end spatial accuracy of the virtual cone reported in our study is a significant fraction of the 5 mm target placed on the trigeminal nerve. However, the diameter of the trigeminal nerve has been reported as approximately 2.5 mm,220 and the mean targeting length of 3.8 mm has been reported in a prior study.58 As such, the end-to-end spatial 95 accuracy uncertainty reported in our study would still encapsulate the radiosurgery target, as per the virtual cone technique.197 Although the gel dosimeter inherently exhibits a high spatial resolution, the resolution of the image readout technique is can be a limiting factor in our current gel dosimetry workflow. Our highest attainable spatial resolution with the CBCT modality is achieved by 0.5112 mm by 0.5112 mm by 0.99 mm in axial and slice thickness direction, respectively. Therefore, when measuring a small dose region of 5 mm, our workflow is limited by the voxel spacing, particularly by the partial volume artifacts in the slice thickness direction. This is evident in figure 22 c.) and 23 c.), where we observe a truncated profile in gel due to the partial volume effect in the coronal (superior-inferior). The low resolution in slice thickness direction which resulted in the partial volume effect, also may have influenced our entire end-to-end spatial accuracy analysis. Furthermore, the profiles in all three directions appear shifted, which may be due to number of non-experimental related reasons: interpolation of CT data to match the CBCT resolution, poor SNR of the averaged and background subtracted gel images acquired with the skull phantom, and the calculation algorithm of the center of mass value from the inbuilt MATLAB function (regionprops3). In our 3D gel dosimetric experiment, we observe that the maximum peak dose measured with gel to be significantly lower than the EBT-XD measurement. However, the 50% isodose width between the EBT-XD film measurement and gel agrees within 0.86 mm in coronal plane (superior-inferior), 0.39 mm in sagittal (anterior-posterior) and 0.28 mm in coronal (left-right). An alternative film measurement in the sagittal plane (superior-inferior) agrees with gel coronal plane (superior-inferior) within 0.69 mm. In two planes, the gel analysis agrees with the film dosimeter 96 within 0.5 mm. Our clinical prescription for treating trigeminal neuralgia is based on the 10 Gy profile width through the isocenter Therefore, the dosimetric accuracy based on the 50% isodose width measurements from the gel is concluded to be adequate in comparison to the EBT-XD film measurement. For a comprehensive virtual cone commissioning with Eclipse V18.0, absolute dose measurements such as, with ion chamber dosimeter, and an independent dosimetry check with film dosimeter is essential. Although not reported in our paper, we performed absolute dose measurements with the cc13 ionization chamber (IBA Dosimetry Group, Herndon, Virginia, USA) and microDiamond detector (PTW, Freiburg, Germany) with our clinical Eclipse V15.6 beam model. The cc13 ion chamber and microdiamond detector measurements reported an under response and over response in our dose measurements, corroborating with its respective correction factors (cc13 with 1.15 and mciroDiamond with 0.96 at 4 mm respectively).221 A complete clinical transition to the Eclipse V18.0 system necessitates rigorous absolute dose measurements and independent dose check with GafChromic film (Ashland Advanced Materials, Bridgewater, New Jersey, USA) dosimeters. Furthermore, a comprehensive comparison between the gel results against the ion chamber/GafChromic film measurements is valuable to demonstrate the dosimetric accuracy of our gel workflow. 6.5 Conclusion Commissioning an extremely small-field SRS radiotherapy technique such as virtual cone method presents some unique and complex challenges both in terms of dosimetry and spatial accuracy uncertainties. Additionally, the treatment isocenter is typically placed such that 50% isodose 97 surface is close to the critical structure (brainstem), which necessitates a very high geometric precision (sub-millimeter) in the treatment delivery process. In this work, we utilized an EBT-XD film dosimeter, which is the currently the gold standard in our clinic, and a gel dosimetry tool to verify a virtual cone delivery method using the recently released eclipse v18.0 (Acuros XB). The 50% isodose width of the film in two orientations were all slightly less than 5 mm, except in coronal (left-right) direction which measured 5.34 mm. The 50% isodose width of the gel measured 5.09 mm, 5.06 mm, 4.01 mm in sagittal (anterior-posterior), coronal (left-right), coronal (superior-inferior) plane, respectively The end-to-end spatial accuracy analysis, with 3D anthropomorphic phantom, showed that we were able to achieve a 0.95 mm accuracy in the virtual treatment delivery, based on the Euclidean distance between the two centers of masses of the 50% isodose region. The analysis included a CBCT setup error with kV-MV isocenter uncertainty of 0.29 mm. This type of end-to-end spatial accuracy test is achievable only with a gel dosimetry with CBCT readout, and the spatial information obtained from this type of SRS technique is invaluable to our clinic. 98 Chapter 7: Semi-automated Vertex placement for SFRT and dosimetric verification using 3D Polymer Gel Dosimetry The purpose of the final work is to introduce a semi-automated vertex placement approach to improve the efficiency of a SFRT planning workflow and demonstrate the application of the 3D polymer gel dosimetry in commissioning this emerging technique. A publicly available vertex placement tool was utilized to place the spheres in a PTV contoured on a 2 L gel phantom CT image. A VMAT optimization was performed utilizing the vertices generated by the user to create a SFRT plan. 1D dose profile, 2D isodose map, 3D visualization and 3D global gamma analysis were used to evaluate the dosimetric accuracy of this emerging technique. The work presented in this chapter is currently accepted at the Journal of Applied Clinical Medical Physics. I was the primary author and project lead of this work responsible for gel fabrication, irradiation and analysis. I also fostered a new collaboration with the Varian developers, who were concurrently working on the SFRT tool. I assisted Dr. Derek Hyde in generating the SFRT verification plan. Dr. Hyde created the SFRT plan and provided guidance to me in both the gel experiment and interpretation. Dr. Andrew Jirasek and Dr. Benjamin Mou provided their expertise in gel dosimetry and clinical workflow respectively. Anthony Magliari and Pierre Lansonneur (both from Varian ) provided their guidance on running their semi-automated vertex placement tool in the initial stages of this research. 99 7.1 Introduction Chapter 1 of the thesis discussed the clinical application of an emerging technique known as SFRT. Despite the potential applications of SFRT in combating refractory tumours, a widescale clinical adoption of SFRT must overcome two key challenges: SFRT planning and dosimetric verification. SFRT is associated with a long and inherently laborious treatment planning process, owing to the manual placement of the vertices.222 Furthermore, bulkier tumour volumes require a large number of localized vertices, which adds even more workload to the treatment planner. Secondly, there are dosimetry challenges associated with the heterogenous dose distribution delivered utilizing the SFRT technique. The complex spatial arrangement of the vertices, in 3D space, is difficult to verify with the traditional point dose and planar dose measurement techniques commonly used in many radiotherapy centers. Therefore, an accurate dosimetric and geometric measurement of the high and low dose region inside the tumour volume is vital. For widescale clinical implementation of SFRT, overcoming the challenges associated with SFRT planning and dosimetric verification are essential. 3D polymer gel dosimeters contain radiosensitive chemicals. Upon irradiation, the gel dosimeter changes its physical density attributing to the underlying process of polymerization and crosslinking. The change in Hounsfield Unit (HU) due to these chemical processes is measured by an imaging modality and correlated to the dose delivered. Gel dosimeters are particularly beneficial in verifying dosimetric and spatial accuracy of the radiotherapy techniques in which steep dose gradients exist.109 Furthermore, to verify geometric precision of a radiotherapy technique with complex spatial arrangement of multiple radiation beam targets, such as SFRT, 3D dosimeters can provide definite advantages compared to the established dosimeters used in routine 100 clinical workflow. Therefore, utilizing 3D gel dosimeters for SFRT dosimetric verification purposes is a promising solution for a clinical commissioning process. The advantage of using CBCT as a readout method over the other imaging tools is its superior geometric and spatial accuracy characteristics. Reliance on CBCT for PGD readout method avoids the need to setup the gel dosimeter in a different imaging coordinate (i.e. MRI and X-ray CT etc.), therefore, the inherent user setup error for readout is theoretically minimized. Furthermore, an image registration necessary for the gel dosimetry system in the traditional imaging modalities may not necessary if a CBCT is used. An automatic spatial registration could be implemented based on the identical DICOM coordinates of the treatment planning system and CBCT imaging. The gel dosimetry workflow with CBCT can provide “actual” geometric accuracy and 3D spatial information which is highly beneficial in complex radiotherapy techniques such as stereotactic radiosurgery (SRS), stereotactic ablative radiotherapy (SABR), and SFRT. Therefore, combining the 3D attributes of the gel dosimeter with the high spatial accuracy of the CBCT is a promising solution to verify the treatment delivery accuracy. The work in this research is summarized into two main objectives: 1) To implement an open-source, reproducible and semi-automated vertices placement tool available on GitHub in order to improve the efficiency of an SFRT workflow in the clinic. 2.) To generate and evaluate a verification plan utilizing the SFRT software on a 2 L polymer gel dosimeter and perform a dosimetric verification of the SFRT delivery using the dosimetry system with CBCT readout. Ultimately the goal is to demonstrate the promising application of this type of dosimetry system in commissioning complex radiotherapy techniques such as SFRT. 101 7.2 Material and Methods 7.2.1 Automated vertices placement In this work, an open-source, reproducible, and semi-automated software tool (MAAS-SFRT helper) publicly available on GitHub repository (https://github.com/Varian-MedicalAffairsAppliedSolutions/MAAS-SFRThelper) was utilized. The software allows the user to create either a regular shaped (spheres) or irregular shaped (angles and rods) patterns for the SFRT planning. In terms of the lattice structural design, either a hexagonal or rectangular pattern is available. The user specifies the center-to-center spacing and diameter of the vertices (spheres) to generate the overall lattice design. The repository was downloaded into the clinical system and the C# code solution was built using the Visual Studio software (Microsoft, Redmond, Washington, USA). 7.2.2 SFRT planning The current study generated the SFRT verification plan based on a planning approach recommended by Grams et al.223 Utilizing the MAAS-SFRThelper software, a hexagonal lattice design with each sphere measuring 1.5 cm in diameter, and a center-to-center spacing of 3 cm between the vertices, was generated.223 Note that the Grams et al. study recommended a spacing of at least 3 cm between the vertices. Since the software tool places the vertices inside a planning target volume (PTV), the body contour of the gel phantom was symmetrically contracted by 2 cm to obtain the PTV (volume: 575.7 cm3). This was also done to reduce the PTV volume in order to decrease the processing time and to ensure that all the vertices are all built around the center of the gel dosimeter. The software generated a total of 19 spheres on a 2 L gel phantom. 102 The VMAT (volumetric arc therapy) plan consisted of 4 gantry arcs, due to the vertices (Grams et al. recommendation: 3-4 arcs for 10 to 25 spheres).223 The collimator angles used were 15°, 345°, 75°, 105° for each gantry arc. The 2 L gel dosimeter phantom was prescribed a dose of 20 Gy, with maximum point dose of 24.1 Gy. The VMAT optimization was implemented such that 50% of the lattice volume receive a 100% prescription dose.223 A co-planar plan was created with 6 MV Flattening Filter Free (FFF), as opposed to 10 MV FFF, in order to minimize the valley dose (to <40% of the maximum peak dose). The optimization was completed once 50% of the volume of each vertex lay within ± 50 cGy of the prescription dose on the dose volume histogram (DVH). The Eclipse version 15.6 with Acuros XB (Varian Medical Systems, Palo Alto CA) dose calculation algorithm was used to generate the SFRT plan. The dose calculation was performed at 1 mm dose resolution with PO was utilized in this study. 7.2.3 Gel dosimeter fabrication A 3D NIPAM polymer gel dosimeter recipe in this study. The gel dosimeter was carefully fabricated based on a previously published protocol.123 The dosimeter recipe comprised of by weight: 15% N-isopropylacrylamide (NIPAM, Sigma Aldrich, Mississauga ON, Canada), 4.5% N,N’-methylenebisacrylamide (BIS or MBA, Sigma), 5% 300 bloom gelatin (Sigma), 10 mM tetrakis(hydroxymethyl)phosphonium chloride (THPC, Sigma), and 75.5% deionized water. The temperature-controlled mixing procedure was carefully followed according to the previous protocol.123 Once the gel was fabricated, the mixture was transferred into a 2 L jar (Uline, Pleasant Prairie, Wisconsin, United States) and cooled in a water bath in the refrigerator for at least 5 hours. 103 7.2.4 Gel irradiation, readout and analysis A Varian Truebeam Linac (Varian Medical Systems, Palo Alto CA) with High Definition Multi-Leaf Collimator (HDMLC) was utilized to deliver the verification plan on the gel dosimeter. The gel dosimeter setup for the experiment is shown in figure 25a. Six pre-irradiation (background) and 6 post-irradiation CBCT scans were acquired for the gel dosimetry analysis. The image acquisition parameter of 1836 mAs, 125 kVp, 5400 projections, 0.5112 pixel spacing, and 1 mm slice thickness was used to acquire all twelve CBCT scans. The background and post-irradiation images were individually averaged and subtracted from one another to generate the background subtracted image. An adaptive mean filtering (3 x 3 pixel) and remnant artefact removal (window span = 7) was utilized to reduce image noise and CBCT artefacts on the background subtracted images.123,126,156 A central slice from the verification plan that contains an entire range of dose values (0 to 24.1 Gy) and the corresponding gel image slice, was used self-calibrate the image by a pixel-by-pixel calibration technique. The dose response curve (figure 25b) was then used to calibrate the entire gel image volume (Appendix G). After the gel calibration, 3D gamma analysis between the Eclipse verification plan and the gel volume was performed. The entire analysis was done in our in-house MATLAB script. 104 Figure 25. a.) Presents the 2 L gel phantom set up, 1b.) dosimetric calibration curve obtained from a central slice. 7.3 Results Figure 26 illustrates a 3D visualization of the 19 spheres in the image volume of a.) Eclipse plan b.) gel dosimeter, displayed on the same colormap. The figure presents the spatial localization of the 19 spheres in the same axis. Qualitatively, the spatial positions of the vertices in the measured gel appear similar to the Eclipse plan. 105 Figure 26. a.) Illustrates the 3D visualization of Eclipse plan and b.) Gel. The color bar represents the dose in Gy. Figure 27 shows a.) line profile through X = 126 in a gel slice and b.) the corresponding the dose profile obtained through a transverse plane (anterior-posterior) of both Eclipse plan and gel dosimeter. The overall dose profile (location of the peak and valley dose) appeared consistent between the plan and measured dose distribution. The peak dose at the center of the two vertices were about 10% higher in the measured gel compared to the Eclipse plan. The width of the dose profile at the 20 gy, which represents the prescription dose showed a good consistency between the plan and measurement. A valley dose of 29.3% was observed in this slice (both in Eclipse plan and the measured gel). 106 Figure 27. a.) Demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in transverse plane (anterior-posterior). In figure 28, a similar analysis was shown. Figure 28.a) shows the line profile along Y = 127 in the gel slice, and figure 28.b) presents the corresponding dose profile in Eclipse plan and gel dosimeter. The maximum peak dose in the Eclipse plan and gel dosimeter appeared more consistent in this case compared to the Figure 27. The width of the profile across the 20 Gy dose line appeared similar between the Eclipse plan and the gel dosimeter. A valley dose of 39.9% was measured in this slice, and a slightly lower valley dose was observed in the gel compared to Eclipse plan (42%) in certain areas of the dose profile. 107 Figure 28. a.) demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in transverse plane (left-right). Figure 29.a.) illustrates the dose profile at Y = 40, along a sagittal view of the gel slice plotted through the superior-inferior direction. Figure 29.b.) shows the corresponding dose profile of the Eclipse plan and the gel dosimeter. Both the peak and valley dose of the gel match well with the Eclipse plan. A valley dose of slightly more than 40% was observed in this slice in both the images, however the valley dose in measured gel (40.2%) appeared lower than the Eclipse plan dose. 108 Figure 29. a.) demonstrates a line profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile along the line in coronal plane (superior-inferior). Figure 30.a.) presents a diagonal through the 3 targets and its corresponding dose profile in b.) for both Eclipse plan and gel dosimeter. The width of the profile along the 20 Gy prescription mark was similar in the two periphery targets and slightly less so in the central target. The low valley dose measured 39.9%. Figure 30. a.) demonstrates a diagonal profile through a 2D slice, the color bar represents the dose in Gy. b.) dose profile in transverse plane 109 Figure 31 presents an image of the of 50% to 100% isodose lines with 10% increment in both the Eclipse plan (31.a) and gel slice (31.b). The 100% isodose line represents the prescription dose of 20 Gy since both the images were normalized to the prescription dose. Qualitatively, the 100% isodose line appeared consistent between the plan and the measured gel. A low valley dose (dark spots) between the high dose spheres, at the center of the image in the figure 31.a) was apparent, at least in the planning images and less visible in the gel images. Figure 31. a.) illustrates the 2D isodose map of a central slice of the Eclipse plan and b.) Gel. The equivalent diameter of 20 Gy isodose volume for each of the vertices were calculated. Table 7 presents the equivalent diameter of the 80% isodose volume (refer figure 31 for qualitative comparison) of both the Eclipse plan and the gel dosimeter. The average diameter resulted in 12.6 mm for Eclipse plan and 13.3±0.2 mm for the measured gel volume⁡± standard error for the 19 110 spheres. The percent difference for each measurement was calculated by obtaining the difference between the Eclipse plan and gel measurement, normalized to the measured plan diameter value. Table 7. Presents the equivalent diameter of the isodose volume of the prescription dose (20 Gy) in Eclipse plan and Gel image volume. The Center of Mass distance between the planned vertex and measured is also shown. The percent error was calculated based on the normalized difference between the Eclipse plan and the gel measurement. Eclipse plan (Equivalent diameter in mm) Gel (Equivalent diameter in mm) Center of Mass Distance (mm) Percent difference between the gel and plan (%) Sphere 1 13.0 14.3 0.53 10 Sphere 2 12.6 13.8 0.74 10 Sphere 3 12.9 14.0 0.73 8.0 Sphere 4 13.0 13.9 0.42 10 Sphere 5 12.8 14.4 0.88 13 Sphere 6 12.9 13.6 0.70 5.0 Sphere 7 12.4 12.9 0.74 4.0 Sphere 8 12.3 12.7 0.75 3.0 Sphere 9 12.4 12.9 0.51 4.0 Sphere 10 12.6 12.4 0.84 1.0 Sphere 11 12.3 13.0 0.92 6.0 Sphere 12 12.6 12.9 0.63 2.0 Sphere 13 12.5 11.1 0.50 11 Sphere 14 12.9 13.5 0.71 5.0 Sphere 15 12.4 13.2 0.65 6.0 Sphere 16 12.3 13.1 0.73 7.0 Sphere 17 12.6 13.4 0.82 6.0 Sphere 18 12.9 13.7 0.59 6.0 Sphere 19 12.3 13.4 0.90 9.0 111 Figure 32 and Table G2 (Appendix G) reports the 3D global gamma analysis utilizing 12 commonly used gamma criteria with 10% threshold: the 3D gamma pass percent are all above 95% except the 2% 1mm and 1% 1 mm criteria. Figure 32 presents the gamma pass percent plotted for each dose difference criteria (5%, 3%, 2% and 1%) as a function of distance to agreement in mm. Figure 32. Presents the scatter plot of the 3D global gamma pass percent as a function of distance to agreement in mm. 7.4 Discussion The current study demonstrated the efficacy of a publicly available semi-automated SFRT planning process, which comprised of an open-source, reproducible and automated vertices placement tool. This code was built within the Eclipse Scripting Applications Programming Interface (ESAPI) and was easily integrated into the Eclipse treatment planning workflow. Moreover, polymer gel dosimetry system was utilized to verify the dosimetric accuracy of the 112 planned SFRT delivery. This novel application of 3D gel dosimetry utilizing CBCT to verify a SFRT technique has not been published to this date. A systematic review concluded that a strict guideline in the lattice array design, including optimal number of vertices, spatial location and its dimensions are lacking to date.70 Some studies reported an arbitrary lattice design based on the radiation oncologist and medical physicist’s recommendation, founded on the size and proximity of the location of the tumour to organ at risks (OARs).69,213-215 Another SFRT efficacy case study utilized an in-house script to optimize the number of vertices in a tumour volume.227 Despite the lack of consensus in SFRT planning approach, removal of vertices closer than 1.5 cm to the OARs is consistently observed.70 The study demonstrated a novel application of 3D gel dosimetry in verifying the SFRT delivery. A qualitative comparison between the Eclipse planned dose and measured gel dose were consistent in the 1D dose profiles and 2D isodose map (figure 27-30). Utilizing a gel dosimetry system in this case provided an advantage over the traditional dosimeter since an entire 3D dose information was efficiently acquired within a single experiment. The 1D dose profile appears consistent between the Eclipse plan and the measured gel in valley dose region, however, in the high dose area, the gel indicates an over responsive characteristic. This may be due to the dosimetric calibration curve parameter affecting the high dose region. The equivalent diameter of the 20 Gy isodose volume in both Eclipse plan and measure gel was also measured. The mean diameters were 12.6±0.3 mm and 13.3±0.2 mm for Eclipse plan and gel, respectively. The VMAT optimization protocol by the Mayo clinic study concluded that the original 15 mm diameter vertex should contract to an approximate a size of 1 cm,223 although, the study has not provided a stringent 113 quantitative measurement of the value. The optimization process was purposefully designed to undercover the 1.5 cm spherical volume until 50% of the volume reach the prescription dose, therefore the 15 mm diameter vertex “shrinks” to a size of 1 cm volume. Figure 26 shows a 3D visualization achievable with the gel dosimetry system. The placement of the vertex in the Eclipse plan and measured gel appeared consistent in terms of a qualitative analysis, however the gel image volume appeared to have a slightly higher maximum dose in the entire dose distribution. The 3D global gamma pass rates were more than 95% for all gamma criteria were obtained, except the 1%, 1 mm and 2%, 1 mm criteria. Thus, with all the analysis combined, the study demonstrated that utilizing a gel dosimeter in verifying SFRT delivery provided a comprehensive evaluation of the treatment delivery process within a single gel irradiation 7.5 Conclusion To achieve a widescale clinical adoption of the emerging SFRT technique, two key challenges must be addressed: SFRT treatment planning and dosimetric verification. In this work, a semi-automated vertex placement approach for SFRT in order to increase the efficiency of the planning process was implemented. The optimized VMAT verification plan generated was concluded to be adequate according to a prior clinical guideline by Grams et al. at Mayo clinic.223 Their VMAT treatment planning guideline comprised of diameter and center to center spacing of the vertices, the choice of number of treatment arcs, couch and collimator angles, beam energy and optimization workflow. This work has demonstrated the promising application of a 3D polymer gel dosimetry system in dosimetric verification of the complex dose distribution achieved with the SFRT technique. An accurate dosimetric verification utilizing the routine point dose and planar dose measurement tools available in radiotherapy centers, may not be as effective in acquiring the entire 114 heterogenous dose distribution dispersed in 3D space. Thus, incorporating an unconventional dose measurement tool such as 3D polymer gel dosimeter in the clinical workflow is invaluable and recommended in commissioning sophisticated radiotherapy techniques such as SFRT. 115 Chapter 8: Conclusion and Future Work Rapid advancements in the field of radiotherapy has led to the planning and delivery of highly conformal dose distributions that matches a complex tumour shape. However, this also necessitates the development and use of radiation dosimeters that accurately verify the dosimetric and spatial accuracy of the complete radiotherapy processes. Traditional dosimeters (point dose and planar dose measurements) have their own limitations, particularly in accurately and efficiently quantifying the entire 3D dose distribution. Therefore, the purpose of this work is to utilize a 3D polymer gel dosimetry system with CBCT readout in order to commission two highly sophisticated radiotherapy techniques (SRS and SFRT). A gel dosimetry readout based on CBCT is a relatively novel workflow and a promising solution to the proposed clinical challenge because of its high spatial accuracy attributes. The gel dosimetry system incorporating CBCT also has a potential for wide scale adoption due to its accessibility across almost all radiotherapy centers. 8.1 Research Conclusions In chapter 4, a dual-institutional investigation was performed in order to evaluate the reproducibility of the entire gel dosimetry workflow, using three identical radiotherapy plans. The study concluded that a higher reproducibility was observed when the same gel analysis pipeline was utilized. This was true especially for the 3D gamma analysis. However, a qualitative comparison of the 1D dose profile and 2D contour plots showed relatively good similarity between the two institution’s data. There were specific differences in the gel analysis process between the two institutions. The in-house MATLAB script (UBCO gel analysis pipeline) employed an image processing step before calibrating the entire gel volume. This was done in order to remove 116 stochastic and structural image noise. The calibration process also differed, the VistaAce (Duke University) analysis utilized data points across the entire gel volume, whereas the MATLAB script only used a central slice to obtain the calibration curve that converts the HU to dose. Therefore, the study indicated the need for a standardized and vetted gel analysis pipeline to achieve wide scale adoption and clinical implementation of the proposed dosimetry system. In chapter 5, the spatial and dosimetric accuracy of a HyperArc® (Varian Medical Systems, Palo Alto CA) SRS technique was investigated. The SRS HyperArc® technique is utilized to treat intracranial brain metastases. In this work, a verification plan was generated with three targets of different sizes (1, 2, 3 cm). A 3D center of mass vector between the verification plan and the gel dosimeter was calculated for spatial accuracy test, which showed a sub-millimeter accuracy in the dose delivery. All 3D global gamma criteria were above 95% with dose threshold set to 30%. The 30% of maximum dose 25 Gy yields a 7.5 Gy, which is well below the 12.5 Gy, which is a radiation dose predictor for the occurrence of radiation necrosis. Therefore a 30% dose threshold was chosen for this specific experiment. In chapter 6, the spatial and dosimetric accuracy of a SRS virtual cone technique to treat trigeminal neuralgia, was performed. For the dosimetric accuracy, the measurements from a 3D polymer gel dosimetry system were benchmarked to the gold standard, EBT-XD film dosimeter. To quantify the geometric precision, an end-to-end spatial accuracy test was performed utilizing a 3D printed anthropomorphic phantom. The dosimetric analysis showed that the 50% isodose width measurements from gel dosimeter was consistent to the film dosimeter within 0.86 mm. The end-to-end spatial accuracy analysis showed a sub-millimeter accuracy (0.95 mm), including the CBCT 117 setup error with kV-MV isocenter uncertainty (0.29 mm). This type of end-to-end spatial accuracy analysis is only achievable with 3D gel dosimetry with CBCT readout technique. In chapter 7, a dosimetric verification of an emerging radiotherapy technique, known as SFRT, was investigated. The study utilized an open-source and publicly available software tool that automatically places the vertices inside a tumour volume based on the structural design specified by the user. A VMAT optimization was carefully performed based on a guideline recommended by Grams et al.223 The planning objectives were achieved based on the prior clinical guidelines.223 In regards to the dosimetric analysis, all 3D global gamma pass percentages were more than 95%, except 1%, 1 mm and 2%, 1 mm. The dose profiles plotted across the same pixels from the Eclipse plan and measured gel showed excellent similarity, particularly the profile width at the prescription dose (20 Gy) mark. In terms of the qualitative analysis, the 2D isodose map and 3D visualization showed good similarity between the plan and measurement. The current work demonstrated the clinical applications of 3D gel dosimetry in two specialized radiotherapy techniques. One particular application in SRS virtual cone technique was a verification of an extremely small, measured dose distribution where the diameter of the dose distribution was only about 5 mm. The second application was in SFRT, where a large number of spherical dose distributions, called vertices, spanned across the three-dimensional tumour volume. In both cases, this work concluded that utilizing a 3D polymer gel dosimetry system with CBCT to verify the dosimetric and end-to-end spatial accuracy analysis, was indeed invaluable in commissioning a clinical workflow. 118 8.2 Future Work There are several avenues in this PhD research that may be improved. In chapter 1, it was shown that the two 3D gamma computational software achieved different 3D gamma pass percentages. To achieve a widescale implementation of polymer gel dosimetry in clinics, it is important to have a vetted and standardized software across different institutions. A multi-centric approach to establishing a standardized gel dosimetry analysis pipeline is essential for wide scale adoption of the technique. In the SRS virtual cone commissioning work (chapter 6), the slice thickness resolution of the CBCT imaging was a limiting factor in both the dosimetric and spatial accuracy analysis. One approach to mitigate this limitation experimentally, is by acquiring CBCT image by shifting the couch position by 0.5 mm and combining the two images into one to obtain a higher resolution. However, this process was not implemented in the current work. In chapter 7, the vertices placement was not optimized in the SFRT tool. Therefore, before the clinical implementation of the SFRT technique, the positions of the vertices must be optimized to achieve high normal tissue sparing. Since this is only a dosimetry study on a 2 L gel phantom, the optimization of the vertex’s placement was not performed. The current PhD work was successful translational research that implemented the 3D polymer gel dosimetry system into two sophisticated clinical applications, where routinely used radiation dosimeters are limited. 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Treatment Plans a b c 3-Field Institution A 0.01 0.92 5.29 Institution B 0 0.25 10.82 SRS-4 Targets Institution A −0.01 1.17 8.21 Institution B 0 1.07 8.51 Treatment Plans L k x0 AAPM TG 119 C-Shape Institution A 55.27 0.12 19.84 Institution B 44.47 0.13 9.73 Table B 2. presents the parameters of the calibration curve obtained with MATLAB analysis. The parameters below relate to equation 3. Fitting parameters with a 95% confidence interval were shown below. Treatment plans Alpha Beta Gamma Phi 3-field Institution A 14.53 (14.34, 14.71) 15.5 (15.07, 15.93) 0.079 (0.076, 0.082) 0.86 (0.82, 0.91) Institution B 13.44 (13.24, 13.65) 11.68 (11.22, 12.15) 0.080 (0.076, 0.084) 1.38 (1.32, 1.43) C-shape Institution A 2.98 (-0.01, 5.98) 28.2 (25.0, 31.4) 0.052 (0.049, 0.055) 0.06 (-0.04, 0.16) Institution B 13.41 (13.28, 13.55) 12.05 (11.77, 12.32) 0.075 (0.072, 0.077) 1.16 (1.12, 1.21) 148 SRS Institution A 15.33 (15.24, 15.43) 14.5 (14.12, 14.88) 0.083 (0.079, 0.086) 1.19 (1.14, 1.24) Institution B 13.72 (13.59, 13.86) 14.62 (14.07, 15.17) 0.083 (0.078, 0.088) 1.14 (1.07, 1.21) 149 150 Figure B 1.) presents the calibration curve obtained with MATLAB Analysis. a.) 3-field plan with Institution A’s data, b.) 3-field plan with institution B’s data, c.) SRS plan with institution A’s data, d.) SRS plan with institution B’s data, e.) C-shape plan with institution A’s data, f.) C-shape plan with institution B’s data. Figure B 2.) presents the calibration curve obtained with Vista Ace analysis software. a.) 3-field plan with Institution A’s data, b.) 3-field plan with institution B’s data, c.) C-shape plan with institution A’s data, d.) C-151 shape plan with institution B’s d data, e.) SRS plan with institution A’s data, f.) SRS plan with institution B’s data. Appendix C Figure C 1.) 3D visualization of C-shape treatment plan with measured gel images, a.) Institution A, b.) Institution B, c.) treatment plan. The color bar represents the dose in Gy. 152 Figure C 2.) 3D visualization of the dose distribution of the 4-targets in SRS treatment plan and measured gel in a.) institution A and b.) Institution B, c.) treatment plan. The color bar represents the dose in Gy. 153 Appendix D Table D 1.) 3D gamma pass percent results with 3-field treatment plan in institution A and B using both the VistaAce and MATLAB analysis pipeline. Criteria Institution A (VistaAce analysis) Institution B (VistaAce analysis) Institution A (MATLAB analysis) Institution B (MATLAB analysis) 2% 2mm 98.4 99.8 90.9 95.8 2% 3mm 99.9 99.9 95.4 97.2 3% 3mm 99.9 99.9 97.7 98.9 3% 2mm 98.9 99.8 95.2 98.1 5% 3mm 99.9 99.9 99.3 99.9 5% 2mm 99.5 99.9 98.4 99.9 5% 1mm 94.2 99.9 94.4 97.2 Table D 2.) 3D gamma for C-shape plan using VistaAce and MATLAB analysis for both institutions. Criteria Institution A (VistaAce analysis) Institution B (VistaAce analysis) Institution A (MATLAB analysis) Institution B (MATLAB analysis) 2% 2mm 99.4 89.7 83.7 82.9 2% 3mm 99.9 95 93.3 89.6 3% 3mm 99.9 96.6 96.4 95.4 3% 2mm 99.5 92.3 91.3 87.5 154 5% 3mm 99.9 98.9 99.4 97.7 5% 2mm 99.7 96.7 97.9 96.2 5% 1mm 93.4 87 94.2 88.3 Table D 3.) 3D gamma with 4-target SRS plan for both institutions using VistaAce and MATLAB analysis. Criteria Institution A (VistaAce analysis) Institution B (VistaAce analysis) Institution A (MATLAB analysis) Institution B (MATLAB analysis) 2% 2mm 93.7 98.8 96.6 88.7 2% 3mm 98.8 99.8 99.4 94.3 3% 3mm 99.3 99.9 99.7 97.4 3% 2mm 96.1 99.2 98.5 94.2 5% 3mm 99.9 99.9 99.9 99.7 5% 2mm 98.9 99.8 99.8 99.0 5% 1mm 89.8 97.2 97.4 95.4 155 Appendix E VistaAce Software Gamma Index Plots for both institutions Institution A Institution B 5%1mm 2%2mm 2%3mm 73.454% 90.148% 97.866% 95% 89.7% 87% 156 3%2mm 3%3mm 5%2mm 92.3% 96.75% 96.64% 91.165% 93.336% 98.19% 157 5%3mm Figure E 1.) Central axial slice through 3D Gamma maps of TG119 C-Shape with various dose criterion. Institution A Institution B 5%1mm 2%2mm 98.9% 98.829% 85.42% 97.18% 86.25% 98.84% 158 2%3mm 3%2mm 3%3mm 90.87% 99.78% 99.26% 88.38% 99.89% 92.7% 159 5%2mm 5%3mm Figure E 2.) Central axial slice through 3D Gamma maps of 4-target SRS with various dose criteria. 99.801% 92.83% 99.99% 96.25% 160 Appendix F Table F 1.) Presents the calibration parameters for the two gel experiments with 95% confidence interval 𝛼 𝛽 𝛾 𝜑 3D gel dosimetric analysis 11.57 (11.36,11.8) 11.31 (10.9,11.72) 0.13 (0.12,0.13) 0.81 (0.76,0.86) End-to-end analysis 10.22 (9.76,10.69) 10.85 (9.49,12.21) 0.10 (0.08,0.11) 0.65 (0.51,0.78) Figure F 1.) Illustrates the calibration curve and its parameters of the 3D gel dosimetric analysis (Left) and 3D anthropomorphic gel (Right) experiment. 161 Appendix G Table G 1.) Calibration parameters for the SFRT verification plan. 𝜶 𝜷 𝜸 𝝋 Calibration curve parameters 14.5 (14.4,14.6) 14.2 (13.9,14.4) 0.08 (0.07,0.08) 0.94 (0.92,0.98) Table G 2.) 3D global gamma pass percentages with 10% threshold. Criteria 3D Gamma Pass Percent (%) 1% 1 mm 87.5 1% 2 mm 89.5 1% 3 mm 96.6 2% 1 mm 89.6 2% 2 mm 97.4 2% 3 mm 98.3 3% 1 mm 95.7 3% 2 mm 98.4 3% 3 mm 98.8 5% 1 mm 98.9 5% 2 mm 99.7 5% 3 mm 99.8
Thesis/Dissertation
eng
Medical Physics
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Jirasek, Andrew
Clinical applications of 3D polymer gel dosimetry with cone-beam computed tomography readout in dosimetric and spatial accuracy verification
Text