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

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  • Lim, Gino J.
  • Cao, Wenhua
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    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.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 217 (2012)
    Issue (Month): 3 ()
    Pages: 609-618

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    Handle: RePEc:eee:ejores:v:217:y:2012:i:3:p:609-618

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    Web page: http://www.elsevier.com/locate/eor

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    Keywords: IMRT; Beam angle optimization; Fluence map optimization; Radiation treatment; Local neighborhood search;

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    Cited by:
    1. H. Rocha & J. Dias & B. Ferreira & M. Lopes, 2013. "Selection of intensity modulated radiation therapy treatment beam directions using radial basis functions within a pattern search methods framework," Journal of Global Optimization, Springer, vol. 57(4), pages 1065-1089, December.
    2. Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.

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