Browsing by Author "Quon, Harvey C."

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    Artificial Intelligence to Advance Adaptive Radiation Therapy
    (2020-09-03) Weppler, Sarah Joanne; Smith, Wendy Lani; Schinkel, Colleen; Davidsen, Jörn; Quon, Harvey C.
    The precision of head and neck cancer radiotherapy may be adversely affected by changes in patient and tumor anatomy occurring over the 6-7 weeks of daily treatment. Adaptive radiation therapy (ART) is used to correct precision losses by replanning treatment in response to anatomical changes. However, the resource costs associated with routine ART may be prohibitive. This thesis considers various open questions in head and neck ART including: protocol performance; workflow streamlining and patient selection criteria; and the potential clinical implications of plan adaptation. We first proposed a framework to compare physician dose-monitoring priorities against protocol capabilities and assessed a common ART protocol monitoring changes in patient external contour. We found this protocol’s performance is comparable to randomly selecting patients for ART. Artificial intelligence techniques allowed us to more effectively model interactions between anatomical and dosimetric changes, and propose new patient selection practices. A novel heuristic converted models into simple criteria for clinical use. Various ART correction goals were considered with promising performance on an external validation dataset, including: parotid gland sparing (sensitivity=0.82, specificity=0.70), and pharyngeal constrictor sparing (sensitivity=0.84, specificity=0.68). Selection criteria relied only on pre-treatment patient data, allowing ART consults to be scheduled in advance. Deformable image registration (DIR) is a workflow tool capable of further streamlining ART. However, not all DIR implementations produce equivalent results. We proposed a data clustering method to identify representative examples of DIR differences that most affect ART output. In addition, we provided a general framework to derive workflow-specific DIR performance requirements that ensures ART workflow equivalence. To estimate the potential clinical benefit of ART, we compared patient-reported outcomes with planned and delivered radiotherapy doses. Results indicated that ART may be most beneficial in reducing patient-reported dysphagia, conferring a ≥5% decrease in absolute dysphagia risk in 1.2% of patients with dose increases, with a ≥5% decrease in relative risk in 23.3% of patients. This suggests a novel goal for ART, given that the literature primarily focusses on xerostomia reduction. The results from these studies have prepared our centre to be among the first to lead a randomized clinical trial in ART.
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    Investigation of Volumetric Modulated Arc Therapy Dosimetry: from Planning to Delivery
    (2018-09-10) Sun, Lingyue; Smith, Wendy Lani; Kirkby, Charles; Quon, Harvey C.; Schinkel, Colleen
    Volumetric modulated arc therapy (VMAT) for cancer treatment uses high-energy radiation to kill malignant cells. The general goal is to deliver a high and conformal dose to the target while minimizing dose to organs-at-risk. This thesis focuses on two areas in VMAT: developing high quality treatment plans and assessing the dosimetric impact of delivering pre-designed plans to patients whose anatomy and position change during treatment. Firstly, a quantitative assessment was made by comparing prostate plans optimized with and without a planning target volume upper dose constraint. It was found that removing the target dose uniformity requirement resulted in better rectum sparing and improved tumor control probability. Secondly, the impact of body contour changes on dose distributions for prostate and head and neck VMAT plans was examined. Rules of thumb for dose percentage change and isodose line shift were developed and body contour changes unlikely to require further investigations were addressed.