This grant supports the development of new integrated models and algorithms for intensity modulated radiation therapy (IMRT) treatment planning. IMRT is considered to be the most effective radiation therapy for many forms of cancer. Current approaches decompose the treatment planning problem into several stages and the corresponding subproblems are solved sequentially. Although this may lead to inferior treatment plans, the lack of suitable model formulations that allow for efficient solution methods has so far prevented the integration of the subproblems. In particular, the subproblem that has received the most attention is the central problem of determining an intensity profile or fluence map for each of the beams used in irradiating a cancer patient. However, issues pertaining to treatment-delivery efficiency and quality are known to have a significant impact on IMRT treatments. Models that fully take into account both potential and limitations of the treatment equipment as well as changes in the patient anatomy over the course of the treatment will be developed along with algorithms to solve the resulting integrated problems. All of the developed models and algorithms will be tested on actual clinical patient data.
Every year, hundreds of thousands of patients receive cancer treatment by radiation therapy. This project will provide highly effective and robust integrated models for IMRT treatment-planning problems that integrate clinical considerations that are currently not yet addressed satisfactorily. The development of efficient approaches to solve the resulting integrated optimization problems in realistic computational times will provide real-time decision support to physicians and clinicians and will help them to find treatment plans that do not require a choice between a good chance for a cure or control of disease and the potential quality of life.
