A genetic algorithm approach to full beam configuration inverse planning in coplanar radiotherapy

Vitoantonio Bevilacqua, G. Mastronardi, G. Piscopo
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引用次数: 1

Abstract

A unified evolutionary approach to coplanar radiotherapy inverse planning is proposed. It consists of a genetic algorithm-based framework that solves with little modification treatment planning for three different kinds of radiation therapy: conformal, so-called aperture-based and intensity modulated. Thanks to evolutionary optimisation techniques we have been able to search for full beam configurations, that is, beam intensity, beam shape and especially beam orientation. Unlike some previous works found in literature, our proposed solution automatically determines exact beam angles not relaying solely on a geometrical basis but involving beam intensity profiles, thus considering the effective delivered dose. Our dose distribution model has been validated through comparison with commercial system: fixed the same beam configuration, both calculated beam shapes and the DVH have been compared. Then we have tested the optimisation algorithm with real clinical cases: these involved both simple (convex target, far OARs) and complex (concave target, close OARs) ones. As stated by physician and by simulation with the same commercial system, our tools found good solutions in both cases using corresponding correct therapy.
基于遗传算法的共面放射治疗全光束构型逆规划
提出了一种统一进化的共面放疗逆规划方法。它由一个基于遗传算法的框架组成,可以解决三种不同的放射治疗方案:适形、所谓的基于孔径和强度调制。由于进化优化技术,我们已经能够搜索完整的光束配置,即光束强度,光束形状,特别是光束方向。与文献中发现的一些先前的工作不同,我们提出的解决方案自动确定精确的光束角度,而不是仅仅根据几何基础,而是涉及光束强度分布,从而考虑有效递送剂量。通过与商业系统的对比验证了我们的剂量分布模型:固定相同的光束配置,计算出的光束形状和DVH都进行了比较。然后,我们用实际的临床病例测试了优化算法:这些病例涉及简单(凸目标,远桨)和复杂(凹目标,近桨)。正如医生所述,通过模拟相同的商业系统,我们的工具在两种情况下都找到了良好的解决方案,使用相应的正确治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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