TREATMENT INDIVIDUALIZATION AMID GEOMETRIC UNCERTAINTY

University Of Michigan At Ann Arbor, Ann Arbor MI

Investigators

Linked publications & trials

Abstract

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