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Retrospective Dosimetric Analysis of Large Cohorts of Patients, the Tool and First Results

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P Yepes

P Yepes1*, A Adair2 , A Liu3 , D Mirkovic4 , U Titt5 , Q Wang6 , R Mohan7 , (1) Rice University/The University of Texas M. D. Anderson Cancer, Houston, TX, (2) Rice University, Houston, TX, (3) MD Anderson Cancer Ctr, Houston, texas, (4) U.T M.D. Anderson Cancer Center, Houston, TX, (5) MD Anderson Cancer Center, Houston, TX, (6) ,,,(7) UT MD Anderson Cancer Center, Houston, TX


TU-C3-GePD-J(A)-3 (Tuesday, August 1, 2017) 10:30 AM - 11:00 AM Room: Joint Imaging-Therapy ePoster Lounge - A

Purpose: To develop an analysis tool to evaluate and characterize dosimetric information for large cohorts of patients treated with proton therapy. Moreover, the inclusion of RBE weighted dose (RWD), and the comparison with various clinical outcomes should allow to discriminate among the various biological models used to calculate RWD.

Methods: The core of the GUI-controlled system is a relational database, where patient and each treatment plan information are stored. The system allows for the recalculations of the dose with fixed and variable RBE, utilizing the Fast Dose Calculator, a Monte Carlo (MC) GEANT4-based track-repeating algorithm. The Wilkens and McNamara models have been utilized to calculate RWD. Search tools were developed to identify structures, where the MC dose predictions are significantly different from those of the Treatment Planning System (TPS). Dose constraints, used to optimize plans, can be also utilized to identify plans for which the MC recalculated dose distributions violate such constraints. By ranking the level of violation, the likelihood of toxicity according to those models can be evaluated.

Results: Around 450 patients treated at University of Texas MD Anderson Cancer with Intensity Modulated Proton Therapy have been processed through the system. Monte Carlo dose with 1.1 RBE shows a systematic decrease of a few percent in delivered dose for the target volumes. The effect is largest for thoracic patients, and least pronounced for brain patients. RWD often predicts significantly larger dose values for organs at risk. The correlation of those predictions with clinical outcomes can be utilize to discriminate among various biological models, or to constrain their parameters.

Conclusion: A system that allows for the retrospective analysis of proton treatment plans of large cohorts of patients has been developed.

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