This project will study the incorporation of individual patient related geometric uncertainties in the calculation, compilation and treatment of optimized radiotherapy dose distributions. Even advanced treatment planning techniques nearly always rely on population-based rules to ensure that the majority of patients receive adequate dose in the face of positioning errors and organ motion. This """"""""one size fits all"""""""" approach potentially penalizes patients who exhibit exceptionally large variation in position or motion, requiring more intensive measures to ensure adequate target volume coverage. However, it also penalizes a substantial proportion of patients with less uncertainty in their target position, who through the use of smaller margins would be at lesser risk for treatment related toxicity or eligible for higher tumor dose. We believe that a new combined approach involving a) dose computation strategies that already include the effects of geometric uncertainties, b) rigorous in-room methodologies for rapidly assessing target and patient configuration and c) accounting for delivered dose and its influence on subsequent treatment delivery optimization will yield improvements in efficient and accurate dose delivery, optimally tailored for each patient. Thus, the project's specific aims are to 1) implement general clinical frameworks for inclusion of patient related setup uncertainties and organ motion into the computation of dose distributions, 2) assess improvements in accuracy achieved through inroom, on-treatment measurement and action, 3) investigate human anatomic changes over short and long time periods and how to accumulate dose to date using this information, and 4) determine the best ways to react to differences between what is seen at treatment and what had been planned. In addition to better tailoring overall treatments, these investigations will help determine how much complexity (in modeling, measurement and intervention) is actually beneficial for a given patient, thus helping to establish the most efficient use of advanced in-room imaging resources within the radiotherapy community.
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