Abstract
We design and implement an intensity-modulated radiation therapy plan generation technology that effectively and efficiently optimizes beam geometry as well as beam intensities. Our approach is based on an existing linear programming-based fluence map optimization model that approximates dose-volume requirements using conditional value-at-risk (C-VaR) constraints. We show how the parameters of the C-VaR constraints can be used to control various metrics of treatment plan quality. Next, we develop an automated search strategy for parameter tuning. Finally, beam angle selection is integrated with fluence map optimization. The beam angle selection scheme employs a bicriteria scoring of beam angle geometries and a selection mechanism to choose from among the set of nondominated geometries. The overall technology is automated and generates several high-quality treatment plans satisfying dose prescription requirements in a single invocation and without human guidance. The technology has been tested on various real-patient cases with uniform success.
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