SU-F-T-592: A Delivery QA-Free Approach for Adaptive Therapy of Prostate Cancer with Static Intensity Modulated Radiotherapy.

PURPOSE: Clinical implementations of adaptive radiotherapy (ART) are limited mainly by the requirement of delivery QA (DQA) prior to the treatment. Small segment size and small segment MU are two dominant factors causing failures of DQA. The aim of this project is to explore the feasibility of ART treatment without DQA by using a partial optimization approach.

METHODS: A retrospective simulation study was performed on two prostate cancer patients treated with SMLC-IMRT. The prescription was 180cGx25 fractions with daily CT-on-rail imaging for target alignment. For each patient, seven daily CTs were selected randomly across treatment course. The contours were deformablely transferred from the simulation CT onto the daily CTs and modified appropriately. For each selected treatment, dose distributions from original beams were calculated on the daily treatment CTs (DCT plan). An ART plan was also created by optimizing the segmental MU only, while the segment shapes were preserved and the minimum MU constraint was respected. The overlaps, between PTV and the rectum, between PTV and the bladder, were normalized by the PTV volume. This ratio was used to characterize the difficulty of organs-at-risk (OAR) sparing.

RESULTS: Comparing to the original plan, PTV coverage was compromised significantly in DCT plans (82% ± 7%) while all ART plans preserved PTV coverage. ART plans showed similar OAR sparing as the original plan, such as V40Gy=11.2cc (ART) vs 11.4cc (original) for the rectum and D10cc=4580cGy vs 4605cGy for the bladder. The sparing of the rectum/bladder depends on overlap ratios. The sparing in ART was either similar or improved when overlap ratios in treatment CTs were smaller than those in original plan.

CONCLUSION: A partial optimization method is developed that may make the real-time ART feasible on selected patients. Future research is warranted to quantify the applicability of the proposed method.