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开发一种无滤过板多源模型,用作临床试验的独立蒙特卡罗剂量计算质量保证工具。

Development of a flattening filter free multiple source model for use as an independent, Monte Carlo, dose calculation, quality assurance tool for clinical trials.

机构信息

Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, 77030, USA.

出版信息

Med Phys. 2017 Sep;44(9):4952-4960. doi: 10.1002/mp.12433. Epub 2017 Aug 1.

Abstract

PURPOSE

The Imaging and Radiation Oncology Core-Houston (IROC-H) Quality Assurance Center (formerly the Radiological Physics Center) has reported varying levels of compliance from their anthropomorphic phantom auditing program. IROC-H studies have suggested that one source of disagreement between institution submitted calculated doses and measurement is the accuracy of the institution's treatment planning system dose calculations and heterogeneity corrections used. In order to audit this step of the radiation therapy treatment process, an independent dose calculation tool is needed.

METHODS

Monte Carlo multiple source models for Varian flattening filter free (FFF) 6 MV and FFF 10 MV therapeutic x-ray beams were commissioned based on central axis depth dose data from a 10 × 10 cm field size and dose profiles for a 40 × 40 cm field size. The models were validated against open-field measurements in a water tank for field sizes ranging from 3 × 3 cm to 40 × 40 cm . The models were then benchmarked against IROC-H's anthropomorphic head and neck phantom and lung phantom measurements.

RESULTS

Validation results, assessed with a ±2%/2 mm gamma criterion, showed average agreement of 99.9% and 99.0% for central axis depth dose data for FFF 6 MV and FFF 10 MV models, respectively. Dose profile agreement using the same evaluation technique averaged 97.8% and 97.9% for the respective models. Phantom benchmarking comparisons were evaluated with a ±3%/2 mm gamma criterion, and agreement averaged 90.1% and 90.8% for the respective models.

CONCLUSIONS

Multiple source models for Varian FFF 6 MV and FFF 10 MV beams have been developed, validated, and benchmarked for inclusion in an independent dose calculation quality assurance tool for use in clinical trial audits.

摘要

目的

成像和放射肿瘤学核心-休斯顿(IROC-H)质量保证中心(前身为放射物理学中心)报告了他们的人体模体审核计划的不同程度的合规性。IROC-H 的研究表明,机构提交的计算剂量与测量值之间存在差异的一个原因是机构的治疗计划系统剂量计算和使用的不均匀性校正的准确性。为了审核放射治疗治疗过程的这一步骤,需要使用独立的剂量计算工具。

方法

基于 10×10cm 射野大小的中心轴深度剂量数据和 40×40cm 射野大小的剂量分布,为瓦里安无均整过滤器(FFF)6MV 和 FFF 10MV 治疗 X 射线束开发了多源蒙特卡罗模型。模型在水箱中的开阔场测量中进行了验证,射野大小范围从 3×3cm 到 40×40cm。然后,将模型与 IROC-H 的人体头颈部模体和肺部模体测量值进行了基准测试。

结果

使用 ±2%/2mm 伽马标准评估验证结果,分别为 FFF 6MV 和 FFF 10MV 模型的中心轴深度剂量数据的平均一致性为 99.9%和 99.0%。使用相同的评估技术,剂量分布的一致性分别为各自模型的 97.8%和 97.9%。使用 ±3%/2mm 伽马标准评估模体基准测试比较,分别为各自模型的平均一致性为 90.1%和 90.8%。

结论

已经为瓦里安 FFF 6MV 和 FFF 10MV 束开发、验证和基准测试了多源模型,以将其纳入用于临床试验审核的独立剂量计算质量保证工具中。

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本文引用的文献

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Flattening filter-free accelerators: a report from the AAPM Therapy Emerging Technology Assessment Work Group.
J Appl Clin Med Phys. 2015 May 8;16(3):5219. doi: 10.1120/jacmp.v16i3.5219.
4
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