SU‐E‐T‐851: An Inter‐Institutional Comparison of Knowledge‐Based IMRT Treatment Planning for Prostate Cancer

Purpose: To evaluate the feasibility of using a site‐specific database of prior plans to generate new prostate IMRT plans for cases drawn from an outside institution. Methods: The assembled database consists of 250 retrospective prostate IMRT treatment plans collected over a three‐year period at our institution. A case‐similarity algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases from an outside institution were each matched against our site‐specific database of prior clinically approved plans. Treatment parameters including fluences and optimization weights from the best‐matched case were adapted to generate new IMRT treatment plans. We conducted a comparison of the differences in plan quality between the new semi‐automated plans and the original, manually generated plans. A simple plan quality (PQ) metric based on the area under the curve (AUC) of each structure of the DVH plot was used to quantitatively score the dose‐volume coverage for the PTV, rectum, and bladder. Results: For ten cases, the mean percentage difference in AUC between the new plan and the original plan was 0.4% for the PTV, indicating very comparable PTV coverage. The mean percentage difference in AUC was −3.6% for the rectum, and −9.3% for the bladder, indicating greater dose sparing for these two critical structures. This indicates that our new semi‐automated plans are very comparable in plan quality to the original, manually‐generated plans Conclusions: It is feasible to utilize a site‐specific knowledge base of prior plans to generate new, clinically acceptable treatment plans for cases drawn from an outside institution. This semi‐automated approach has the potential to improve the efficiency of the treatment planning process while ensuring that the extent of dose‐sparing is consistent and clinically acceptable. © 2011, American Association of Physicists in Medicine. All rights reserved.

Duke Scholars

Author Joseph Yuan-Chieh Lo Radiology

Author Shiva Kumar Das Radiation Oncology