(Tuesday, 7/31/2018) 4:30 PM - 5:30 PM
Room: Exhibit Hall | Forum 3
Purpose: Constraint based radiotherapy plan evaluation using dose-volume data is currently limited to meeting binary dose tolerance points (DTP). Upon meeting DTP, a planner is coerced to use subjective analysis on dose volume histograms to decide whether a plan can be improved to spare normal tissues further or improve target dose coverage. We have formulated and initiated testing of a quantitative evaluation algorithm which utilizes DICOM files and literature-based constraint points to compute a quantitative performance metric that can mitigate some subjectivity when evaluating normal tissue sparing in addition to dose coverage.
Methods: The algorithm works by reconstructing dose-volume histograms (DVH) and identifying structures that have literature-based constraints (ex: Quantec, Emami, RTOG). Polygons are computed between an evaluation ray and the DVH to compute how much sparing was achieved between the DVH and DTP. Similarly, the planning target volume DVH is evaluated to compute performance of coverage and excessive dose. By applying this evaluation method retrospectively to patient plans in the past, we can produce a clinical scoring scale based on the historical performance of treatment plans at our clinic.
Results: Run-time of the evaluation algorithm which includes scanning DICOM files, reconstructing DVH, and identifying structures with DTP is less than 5 seconds for both plans. Scoring scales for rectum, bladder, penile bulb, and PTV final were constructed using historical data.
Conclusion: The work in the present study highlights testing of an innovative approach to produce an objective metric to be used in radiotherapy plan performance.
Funding Support, Disclosures, and Conflict of Interest: This research is supported by the Cancer Prevention & Research Institute of Texas Research Training Award to Ara Alexandrian (RP170345).
Keywords
Computer Software, Treatment Planning, Performance Tests
Taxonomy
TH- External beam- photons: treatment planning/virtual clinical studies
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