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美国医学物理师协会第105任务组报告:基于蒙特卡罗方法的光子和电子外照射治疗计划临床实施相关问题

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning.

作者信息

Chetty Indrin J, Curran Bruce, Cygler Joanna E, DeMarco John J, Ezzell Gary, Faddegon Bruce A, Kawrakow Iwan, Keall Paul J, Liu Helen, Ma C M Charlie, Rogers D W O, Seuntjens Jan, Sheikh-Bagheri Daryoush, Siebers Jeffrey V

机构信息

University of Michigan, Ann Arbor, Michigan 48109, USA.

出版信息

Med Phys. 2007 Dec;34(12):4818-53. doi: 10.1118/1.2795842.

Abstract

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

摘要

许多研究表明,蒙特卡罗(MC)方法可用于计算临床放射治疗的精确剂量分布,特别是在非均匀的患者组织中,传统的确定性剂量算法无法准确处理电子传输的影响。尽管MC方法已被证明具有准确性,且改进的剂量分布有可能影响治疗结果,但以前与MC模拟相关的计算时间过长,使得该方法在常规临床治疗计划中不切实际。然而,针对放射治疗计算进行优化的更快代码的开发以及计算机处理器技术的改进,已大幅减少了计算时间,在某些情况下,单处理器上的计算时间可缩短至几分钟以内。这些进展促使几家主要的治疗计划系统供应商走上了MC技术的道路。几家商业供应商已经发布或正在发布用于光子和/或电子束治疗计划的MC算法。因此,MC治疗计划算法的可及性和应用很可能在放射治疗界广泛普及。使用MC模拟时,剂量是根据第一原理随机计算的;因此,该方法与传统剂量算法有很大不同。统计不确定性、方差减少技术的使用、在加速器治疗头模拟中考虑几何细节的能力以及其他特征等问题,都是MC治疗计划算法的独特组成部分。临床物理学家成功实施这样一个系统需要了解MC技术的基本原理。本报告的目的是在对放射治疗计划中使用MC模拟进行教育和回顾的同时,为用户和开发者阐述与MC剂量算法的临床实施和实验验证相关的突出问题。由于MC方法是一项新兴技术,本报告并非规定性的。相反,它旨在作为一份初步报告来回顾MC方法的原则,并提供一个框架,在此基础上构建一个用于基于MC的治疗计划系统调试和常规质量保证的综合程序。

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