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一种用于步进式IMRT放疗中强度图分割的差异矩阵元启发式算法。

A difference-matrix metaheuristic for intensity map segmentation in step-and-shoot IMRT delivery.

作者信息

Gunawardena Athula D A, D'Souza Warren D, Goadrich Laura D, Meyer Robert R, Sorensen Kelly J, Naqvi Shahid A, Shi Leyuan

机构信息

Department of Mathematics and Computer Sciences, University of Wisconsin-Whitewater, 800 West Main Street, Whitewater, WI, USA.

出版信息

Phys Med Biol. 2006 May 21;51(10):2517-36. doi: 10.1088/0031-9155/51/10/011. Epub 2006 Apr 26.

Abstract

At an intermediate stage of radiation treatment planning for IMRT, most commercial treatment planning systems for IMRT generate intensity maps that describe the grid of beamlet intensities for each beam angle. Intensity map segmentation of the matrix of individual beamlet intensities into a set of MLC apertures and corresponding intensities is then required in order to produce an actual radiation delivery plan for clinical use. Mathematically, this is a very difficult combinatorial optimization problem, especially when mechanical limitations of the MLC lead to many constraints on aperture shape, and setup times for apertures make the number of apertures an important factor in overall treatment time. We have developed, implemented and tested on clinical cases a metaheuristic (that is, a method that provides a framework to guide the repeated application of another heuristic) that efficiently generates very high-quality (low aperture number) segmentations. Our computational results demonstrate that the number of beam apertures and monitor units in the treatment plans resulting from our approach is significantly smaller than the corresponding values for treatment plans generated by the heuristics embedded in a widely use commercial system. We also contrast the excellent results of our fast and robust metaheuristic with results from an 'exact' method, branch-and-cut, which attempts to construct optimal solutions, but, within clinically acceptable time limits, generally fails to produce good solutions, especially for intensity maps with more than five intensity levels. Finally, we show that in no instance is there a clinically significant change of quality associated with our more efficient plans.

摘要

在调强放射治疗(IMRT)计划的中间阶段,大多数用于IMRT的商业治疗计划系统会生成强度图,该强度图描述了每个射束角度的子野强度网格。为了生成可用于临床的实际放射治疗计划,需要将各个子野强度矩阵进行强度图分割,形成一组多叶准直器(MLC)孔径及相应的强度。从数学角度来看,这是一个非常困难的组合优化问题,尤其是当MLC的机械限制导致孔径形状存在诸多约束,且孔径的设置时间使得孔径数量成为总治疗时间的一个重要因素时。我们已经开发、实现并在临床病例上测试了一种元启发式算法(即一种为指导另一种启发式算法的重复应用提供框架的方法),该算法能够高效地生成高质量(低孔径数量)的分割结果。我们的计算结果表明,采用我们的方法生成的治疗计划中的射束孔径数量和监测单位数量,显著小于广泛使用的商业系统中嵌入的启发式算法所生成的治疗计划的相应数值。我们还将我们快速且稳健的元启发式算法的出色结果与“精确”方法——分支定界法的结果进行了对比,分支定界法试图构建最优解,但在临床可接受的时间限制内,通常无法产生良好的解决方案,尤其是对于具有超过五个强度级别的强度图。最后,我们表明,对于我们更高效的计划,在任何情况下都不存在与质量相关的临床显著变化。

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