title: Local beam angle optimization with linear programming and gradient search.
abstract: The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed.
authors: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. dcraft@partners.org
authors: David
authors: D
authors: Craft
mesh_terms: D000465:Algorithms; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D010190:Pancreatic Neoplasms / Q000532:radiotherapy; D019047:Phantoms, Imaging; D011382:Programming, Linear; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000295:instrumentation* / Q000379:methods*; D012542:Scattering, Radiation; D012984:Software