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基于遗传算法和模拟动力学的混合方法对调强放射治疗的射束方向进行优化。

Beam orientation optimization for IMRT by a hybrid method of the genetic algorithm and the simulated dynamics.

作者信息

Hou Qing, Wang Jun, Chen Yan, Galvin James M

机构信息

Key Lab for Radiation Physics and Technology, Institute of Nuclear Science and Technology, Sichuan University, Chengdu 610064, China.

出版信息

Med Phys. 2003 Sep;30(9):2360-7. doi: 10.1118/1.1601911.

Abstract

We have developed a new method for beam orientation optimization in intensity-modulated radiation therapy (IMRT). The problem of beam orientation optimization in IMRT is solved by a decoupled two-step iterative process: (1) optimization of the intensity profiles for given beam configurations; (2) selection of optimal beam configurations based on the ranking by an objective function score for the results of the intensity profile optimization. The simulated dynamics algorithm is used for the intensity profile optimization. This algorithm enforces both the hard constraints and dose-volume constraints. A genetic algorithm is used to select beam orientation configurations. The method has been tested for both a simulated and clinical case, and the results show that beam orientation optimization significantly improved IMRT plans within a time period that is clinically acceptable. The results also show the dependence of the optimal orientation configurations on the prescribed constraints. In addition, beam orientation optimization by the method described here can provide multiple plans with similar dose distributions. This degeneracy characteristic can be exploited to our advantage in introducing additional planning objectives, e.g., the smoothness of intensity profiles, for the selection of the optimal plan among the degenerate configurations for treatment delivery.

摘要

我们已经开发出一种用于调强放射治疗(IMRT)中射束方向优化的新方法。IMRT中的射束方向优化问题通过一种解耦的两步迭代过程来解决:(1)针对给定的射束配置优化强度分布;(2)基于强度分布优化结果的目标函数得分排名来选择最优射束配置。模拟动力学算法用于强度分布优化。该算法同时强制执行硬约束和剂量体积约束。遗传算法用于选择射束方向配置。该方法已在模拟病例和临床病例中进行了测试,结果表明射束方向优化在临床可接受的时间段内显著改善了IMRT计划。结果还显示了最优方向配置对规定约束的依赖性。此外,通过此处所述方法进行的射束方向优化可以提供具有相似剂量分布的多个计划。这种简并特性可在引入额外的计划目标(例如强度分布的平滑度)时加以利用,以便在简并配置中选择用于治疗的最优计划。

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