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一种用于碳疗法的基于数据驱动的碎片化模型:GPU加速的蒙特卡罗剂量重新计算

A Data-Driven Fragmentation Model for Carbon Therapy GPU-Accelerated Monte-Carlo Dose Recalculation.

作者信息

De Simoni Micol, Battistoni Giuseppe, De Gregorio Angelica, De Maria Patrizia, Fischetti Marta, Franciosini Gaia, Marafini Michela, Patera Vincenzo, Sarti Alessio, Toppi Marco, Traini Giacomo, Trigilio Antonio, Schiavi Angelo

机构信息

Department of Physics, University of Rome "Sapienza", Rome, Italy.

INFN (Istituto Nazionale di Fisica Nucleare) section of Roma 1, Rome, Italy.

出版信息

Front Oncol. 2022 Mar 25;12:780784. doi: 10.3389/fonc.2022.780784. eCollection 2022.

DOI:10.3389/fonc.2022.780784
PMID:35402249
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8990885/
Abstract

The advent of Graphics Processing Units (GPU) has prompted the development of Monte Carlo (MC) algorithms that can significantly reduce the simulation time with respect to standard MC algorithms based on Central Processing Unit (CPU) hardware. The possibility to evaluate a complete treatment plan within minutes, instead of hours, paves the way for many clinical applications where the time-factor is important. FRED (Fast paRticle thErapy Dose evaluator) is a software that exploits the GPU power to recalculate and optimise ion beam treatment plans. The main goal when developing the FRED physics model was to balance accuracy, calculation time and GPU execution guidelines. Nowadays, FRED is already used as a quality assurance tool in Maastricht and Krakow proton clinical centers and as a research tool in several clinical and research centers across Europe. Lately the core software has been updated including a model of carbon ions interactions with matter. The implementation is phenomenological and based on carbon fragmentation data currently available. The model has been tested against the MC FLUKA software, commonly used in particle therapy, and a good agreement was found. In this paper, the new FRED data-driven model for carbon ion fragmentation will be presented together with the validation tests against the FLUKA MC software. The results will be discussed in the context of FRED clinical applications to C ions treatment planning.

摘要

图形处理单元(GPU)的出现推动了蒙特卡罗(MC)算法的发展,相较于基于中央处理器(CPU)硬件的标准MC算法,该算法能显著缩短模拟时间。在几分钟而非数小时内评估完整治疗计划的可能性,为许多时间因素至关重要的临床应用铺平了道路。FRED(快速粒子疗法剂量评估器)是一款利用GPU能力重新计算和优化离子束治疗计划的软件。开发FRED物理模型的主要目标是平衡准确性、计算时间和GPU执行准则。如今,FRED已在马斯特里赫特和克拉科夫质子临床中心用作质量保证工具,并在欧洲多个临床和研究中心用作研究工具。最近,核心软件已更新,包括碳离子与物质相互作用的模型。该模型是唯象的,基于目前可用的碳碎裂数据。该模型已针对粒子治疗中常用的MC FLUKA软件进行了测试,结果显示二者吻合度良好。本文将介绍用于碳离子碎裂的新FRED数据驱动模型,以及针对FLUKA MC软件的验证测试。将在FRED临床应用于碳离子治疗计划的背景下讨论这些结果。

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本文引用的文献

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Fred: a GPU-accelerated fast-Monte Carlo code for rapid treatment plan recalculation in ion beam therapy.弗雷德:一种用于离子束治疗中快速治疗计划重新计算的GPU加速快速蒙特卡罗代码。
Phys Med Biol. 2017 Sep 5;62(18):7482-7504. doi: 10.1088/1361-6560/aa8134.
2
Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy.goCMC的初步开发:一种面向GPU的用于碳离子治疗的快速跨平台蒙特卡罗引擎。
Phys Med Biol. 2017 May 7;62(9):3682-3699. doi: 10.1088/1361-6560/aa5d43. Epub 2017 Jan 31.
3
Clinically Applicable Monte Carlo-based Biological Dose Optimization for the Treatment of Head and Neck Cancers With Spot-Scanning Proton Therapy.
基于蒙特卡洛方法的临床适用生物剂量优化在头颈部癌调强适形质子治疗中的应用
Int J Radiat Oncol Biol Phys. 2016 Aug 1;95(5):1535-1543. doi: 10.1016/j.ijrobp.2016.03.041. Epub 2016 Apr 6.
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A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of nonelastic interactions.基于快速GPU的质子输运蒙特卡罗模拟以及非弹性相互作用的详细建模。
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5
Validation of a GPU-based Monte Carlo code (gPMC) for proton radiation therapy: clinical cases study.基于图形处理器(GPU)的质子放射治疗蒙特卡罗代码(gPMC)的验证:临床病例研究
Phys Med Biol. 2015 Mar 21;60(6):2257-69. doi: 10.1088/0031-9155/60/6/2257. Epub 2015 Feb 26.
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A simplified methodology to produce Monte Carlo dose distributions in proton therapy.一种用于质子治疗中生成蒙特卡洛剂量分布的简化方法。
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