Demarco J J, Chetty I J, Solberg T D
UCLA Department of Radiation Oncology, University of California Los Angeles, 90095-6951, USA.
Med Dosim. 2002 Spring;27(1):43-50. doi: 10.1016/s0958-3947(02)00087-0.
Monte Carlo-based treatment planning algorithms are advancing rapidly and will certainly be implemented as part of conventional treatment planning systems in the near future. This paper was designed as a basic tutorial for using the Monte Carlo method as applied to radiotherapy treatment planning. The tutorial addresses the basic transport differences between photon and electron transport as well as the sampling distributions. The implementation of a virtual linac source model and the conversion from the Monte Carlo source modeling reference plane into the treatment reference plane is discussed. The implementation of a thresholding algorithm for converting CT electron density to patient specific materials is also presented. A 6-field prostate boost treatment is used to compare a conventional treatment planning algorithm (pencil beam model) with a Monte Carlo simulation algorithm. The agreement between the 2 calculation methods is good based upon the qualitative comparison of the isodose distribution and the dose-volume histograms for the prostate and the rectum. The effects of statistical uncertainty on the Monte Carlo calculation are also presented.
基于蒙特卡洛的治疗计划算法正在迅速发展，并且在不久的将来肯定会作为传统治疗计划系统的一部分得到应用。本文旨在作为将蒙特卡洛方法应用于放射治疗计划的基础教程。该教程阐述了光子和电子输运之间的基本输运差异以及抽样分布。讨论了虚拟直线加速器源模型的实现以及从蒙特卡洛源建模参考平面到治疗参考平面的转换。还介绍了用于将CT电子密度转换为患者特定材料的阈值算法的实现。采用六野前列腺强化治疗来比较传统治疗计划算法（笔形束模型）和蒙特卡洛模拟算法。基于前列腺和直肠的等剂量分布以及剂量体积直方图的定性比较，两种计算方法之间的一致性良好。还介绍了统计不确定性对蒙特卡洛计算的影响。
