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使用 TOPAS 蒙特卡罗系统从治疗计划中进行场内和场外患者特定继发性癌症风险估计的框架。

A framework for in-field and out-of-field patient specific secondary cancer risk estimates from treatment plans using the TOPAS Monte Carlo system.

机构信息

Department of Radiation Oncology, Massachusetts General Hospital, Boston, United States of America.

Department of Radiation Oncology, Harvard Medical School, Boston, United States of America.

出版信息

Phys Med Biol. 2024 Aug 6;69(16). doi: 10.1088/1361-6560/ad64b6.

DOI:10.1088/1361-6560/ad64b6
PMID:39019051
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11345907/
Abstract

. To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework.. Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection's Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets.. The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk.. This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options.

摘要

. 为了在全面且用户友好的蒙特卡罗 (MC) 框架中估算放射治疗计划的继发癌症风险。.. 使用国际辐射防护委员会出版物 145 计算网格体模和骨骼匹配,将患者计划 CT 扫描向上和向下扩展。使用 TOPAS MC 系统的新型网格功能和数字成像和通信在医学放射治疗扩展接口中计算剂量分布。最后,使用肉瘤和癌风险模型以及两种替代参数集计算场内和场外癌症风险。.. TOPAS MC 框架得到扩展,以促进关于放射性癌症风险的流行病学研究。该框架效率高,允许对大型数据集进行自动分析。与场内剂量相比,场外器官剂量较小,但风险估计表明其对总放射性诱导癌症风险有不可忽视的贡献。.. 这项工作为 TOPAS MC 系统配备了解剖扩展、网格几何和癌症风险模型功能,使最先进的场外剂量计算和风险估计能够为大量用户所使用。此外,这些功能将有助于进一步完善风险模型和对患者特定治疗方案的敏感性分析。

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本文引用的文献

1
The Pediatric Proton and Photon Therapy Comparison Cohort: Study Design for a Multicenter Retrospective Cohort to Investigate Subsequent Cancers After Pediatric Radiation Therapy.儿童质子与光子治疗比较队列研究:一项多中心回顾性队列研究的设计,旨在调查儿童放射治疗后的后续癌症情况。
Adv Radiat Oncol. 2023 May 21;8(6):101273. doi: 10.1016/j.adro.2023.101273. eCollection 2023 Nov-Dec.
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Complete patient exposure during paediatric brain cancer treatment for photon and proton therapy techniques including imaging procedures.在小儿脑癌治疗中,包括成像程序在内的光子和质子治疗技术的完整患者暴露情况。
Front Oncol. 2023 Sep 19;13:1222800. doi: 10.3389/fonc.2023.1222800. eCollection 2023.
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Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table for proton therapy.基于 CT 的质子治疗用 Hounsfield 查找表预测阻止本领比的共识指南。
Radiother Oncol. 2023 Jul;184:109675. doi: 10.1016/j.radonc.2023.109675. Epub 2023 Apr 19.
4
Comparison of out-of-field normal tissue dose estimates for pencil beam scanning proton therapy: MCNP6, PHITS, and TOPAS.笔形束扫描质子治疗的野外正常组织剂量估算比较:MCNP6、PHITS 和 TOPAS。
Biomed Phys Eng Express. 2022 Dec 23;9(1). doi: 10.1088/2057-1976/acaab1.
5
Simulation and experimental verification of ambient neutron doses in a pencil beam scanning proton therapy room as a function of treatment plan parameters.笔形束扫描质子治疗室中环境中子剂量随治疗计划参数变化的模拟与实验验证。
Front Oncol. 2022 Sep 8;12:903537. doi: 10.3389/fonc.2022.903537. eCollection 2022.
6
Applications of a patient-specific whole-body CT-mesh hybrid computational phantom in second cancer risk prediction.一种基于个体化全身 CT 网格混合计算体模在二次癌症风险预测中的应用。
Phys Med Biol. 2022 Sep 12;67(18). doi: 10.1088/1361-6560/ac8851.
7
MOQUI: an open-source GPU-based Monte Carlo code for proton dose calculation with efficient data structure.MOQUI:一款基于 GPU 的开源蒙特卡罗质子剂量计算代码,具有高效的数据结构。
Phys Med Biol. 2022 Aug 30;67(17). doi: 10.1088/1361-6560/ac8716.
8
Validation of a Monte Carlo Framework for Out-of-Field Dose Calculations in Proton Therapy.用于质子治疗中射野外剂量计算的蒙特卡罗框架的验证
Front Oncol. 2022 Jun 8;12:882489. doi: 10.3389/fonc.2022.882489. eCollection 2022.
9
Determining Out-of-Field Doses and Second Cancer Risk From Proton Therapy in Young Patients-An Overview.确定年轻患者质子治疗的野外剂量和二次癌症风险——概述
Front Oncol. 2022 May 31;12:892078. doi: 10.3389/fonc.2022.892078. eCollection 2022.
10
Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning.在对头颈部容积调强弧形治疗计划切换到蒙特卡罗剂量引擎时保持剂量学质量。
J Appl Clin Med Phys. 2022 May;23(5):e13572. doi: 10.1002/acm2.13572. Epub 2022 Feb 25.