The fundamental goal of this work is to improve our ability to optimize the overall plan for each patient'streatment course ('comprehensive' treatment course optimization). Current planning methods make use ofonly a static single instance of the patient's anatomy (typically a treatment planning CT scan), and create anoptimized treatment plan based on the clinical therapy prescription, using interactive or inverse planningoptimization techniques (for Intensity Modulated Radiation Therapy (IMRT)). However, our knowledge ofthe patient and treatment goals is not static, but dynamic. Throughout the patient's course of treatment, weobtain new information on geometrical localization, inter- and intra-fraction motion, clinical response, andthe precision to which we can predict uncertainties in the data used for planning. To better account for andutiltize this knowledge, the proposed research will develop and evaluate new paradigms for comprehensiveoptimization of the entire treatment course, evaluating potential improvements over the single-instanceplanning/optimization techniques which are widely used throughout the radiotherapy community. Theproject will develop a planning/optimization framework for individualized optimization which incorporatesgeometric, dosimetric, clinical and biological information as it becomes available (Aim 1), studyimprovements in single-stage optimization procedures for the multi-criteria problems encountered intherapy planning (Aim 2), and explicitly investigate multi-stage optimization methods for planning anddelivery of the entire treatment course (Aim 3). This project will show that development of plan optimizationstrategies which 1) explicitly account for setup uncertainty and/or organ motion, 2) make use of updatedclinical, biological, dosimetric and geometric information to refine the plan, and 3) model and optimizemulti-stage adaptive therapy for the entire treatment course will better tailor the overall treatment plan toeach individual patient and predict improvements over the current static inverse plan generated once foreach patient.
Showing the most recent 10 out of 289 publications
