External beam radiation therapy is a common treatment for many types of cancer. During such treatment, radiation is delivered with a gantry, equipped with a radiation source, that is pointed at the patient from various angles. Optimization models are commonly used in individualized treatment planning, and formulation and solution methods for such models have been an area of active research and collaborations. VMAT is a particular technique for delivering radiation, in which the gantry continuously rotates around the patient while the leaves of a multi-leaf collimator (MLC) move in and out of the radiation field to "shape" it. Proposed over a decade ago, this technique has the potential to produce treatments of high quality similar to, e.g., Intensity Modulated Radiation Therapy (IMRT), but requiring less time for treatment delivery. Recently, treatment systems capable of delivering VMAT treatments became commercially available, necessitating the development of relevant treatment planning methods. We propose one such method, which uses optimization models and column generation-based heuristics to produce high-quality VMAT treatment plans that allow for (i) dynamically adjustable gantry speed; (ii) dynamically adjustable dose rate; and (iii) MLC leaf speed constraints. This talk is based on joint work with Fei Peng and H. Edwin Romeijn at the University of Michigan and Xun Jia, Xuejun Gu and Steve B. Jiang at the University of California San Diego.
Group for Research in Decision Analysis