Generally, the inverse planning of radiation therapy consists mainly of the fluence optimization. The beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) consists of selecting appropriate radiation incidence directions and may influence the quality of the IMRT plans, both to enhance better organ sparing and to improve tumor coverage. However, in clinical practice, most of the time, beam directions continue to be manually selected by the treatment planner without objective and rigorous criteria. The goal of this paper is to introduce a novel approach that uses beam's-eye-view dose ray tracing metrics within a pattern search method framework in the optimization of the highly non-convex BAO problem. Pattern search methods are derivative-free optimization methods that require a few function evaluations to progress and converge and have the ability to better avoid local entrapment. The pattern search method framework is composed of a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and ensures the convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Beam's-eye-view dose metrics assign a score to each radiation beam direction and can be used within the pattern search framework furnishing a priori knowledge of the problem so that directions with larger dosimetric scores are tested first. A set of clinical cases of head-and-neck tumors treated at the Portuguese Institute of Oncology of Coimbra is used to discuss the potential of this approach in the optimization of the BAO problem.
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