کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
481460 | 1446084 | 2012 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A two-phase method for selecting IMRT treatment beam angles: Branch-and-Prune and local neighborhood search A two-phase method for selecting IMRT treatment beam angles: Branch-and-Prune and local neighborhood search](/preview/png/481460.png)
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.
► A two-phase approach for optimizing beam angles and fluence maps in IMRT.
► Introduce Branch-and-Prune for clinically acceptable robust solutions.
► A local neighborhood search algorithm is developed to find a local optimal solution.
► Numerical results on two clinical cancer cases show robustness of our approach.
► The two-phase method often converged to global optimal.
Journal: European Journal of Operational Research - Volume 217, Issue 3, 16 March 2012, Pages 609–618