Jiang H, Paganetti H
Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts 02114, USA.
Med Phys. 2004 Oct;31(10):2811-8. doi: 10.1118/1.1796952.
The GEANT4 Monte Carlo code provides many powerful functions for conducting particle transport simulations with great reliability and flexibility. However, as a general purpose Monte Carlo code, not all the functions were specifically designed and fully optimized for applications in radiation therapy. One of the primary issues is the computational efficiency, which is especially critical when patient CT data have to be imported into the simulation model. In this paper we summarize the relevant aspects of the GEANT4 tracking and geometry algorithms and introduce our work on using the code to conduct dose calculations based on CT data. The emphasis is focused on modifications of the GEANT4 source code to meet the requirements for fast dose calculations. The major features include a quick voxel search algorithm, fast volume optimization, and the dynamic assignment of material density. These features are ready to be used for tracking the primary types of particles employed in radiation therapy such as photons, electrons, and heavy charged particles. Recalculation of a proton therapy treatment plan generated by a commercial treatment planning program for a paranasal sinus case is presented as an example.
GEANT4蒙特卡罗代码提供了许多强大的功能，能够以极高的可靠性和灵活性进行粒子输运模拟。然而，作为一个通用的蒙特卡罗代码，并非所有功能都是专门为放射治疗应用而设计和充分优化的。其中一个主要问题是计算效率，当需要将患者CT数据导入模拟模型时，这一点尤为关键。在本文中，我们总结了GEANT4跟踪和几何算法的相关方面，并介绍了我们使用该代码基于CT数据进行剂量计算的工作。重点在于对GEANT4源代码的修改，以满足快速剂量计算的要求。主要特性包括快速体素搜索算法、快速体积优化以及材料密度的动态分配。这些特性可用于跟踪放射治疗中使用的主要粒子类型，如光子、电子和重带电粒子。作为示例，给出了由商业治疗计划程序为一例鼻窦病例生成的质子治疗计划的重新计算结果。
