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A two-phase method for selecting IMRT treatment beam angles: Branch-and-Prune and local neighborhood search

Gino Lim (ginolim***at***uh.edu)
Wenhua Cao (wcao***at***uh.edu)

Abstract: This paper presents a new two-phase solution approach to the beam angle and fluence map optimization problem in Intensity Modulated Radiation Therapy (IMRT) planning. We introduce Branch-and-Prune (B&P) to generate a robust feasible solution in the first phase. A local neighborhood search algorithm is developed to find a local optimal solution from the Phase I starting point in the second phase. The goal of the first phase is to generate a clinically acceptable feasible solution in a fast manner based on a Branch-and-Bound tree. In this approach, a substantially reduced search tree is iteratively constructed. In each iteration, a merit score based branching rule is used to select a pool of promising child nodes. Then pruning rules are applied to select one child node as the branching node for the next iteration. The algorithm terminates when we obtain a desired number of angles in the current node. Although Phase I generates quality feasible solutions, it does not guarantee optimality. Therefore, the second phase is designed to converge Phase I starting solutions to local optimality. Our methods are tested on two sets of real patient data. Results show that not only can B&P alone generate clinically acceptable solutions, but the two-phase method consistently generates local optimal solutions, some of which are shown to be globally optimal.

Keywords: IMRT, Beam Angle Optimization, Fluence Map Optimization, Radiation Treatment, Local Neighborhood Search

Category 1: Applications -- Science and Engineering (Biomedical Applications )

Citation: Accepted for publication, EJOR

Download: [PDF]

Entry Submitted: 09/08/2011
Entry Accepted: 09/08/2011
Entry Last Modified: 09/08/2011

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