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评估 4-Hz 日志文件和二次蒙特卡罗剂量计算在 VMAT 前列腺计划中的患者特异性质量保证中的应用。

Evaluation of 4-Hz log files and secondary Monte Carlo dose calculation as patient-specific quality assurance for VMAT prostate plans.

机构信息

Institute of Medical Physics, Academic Teaching Hospital Feldkirch, Feldkirch, Austria.

Private University in the Principality of Liechtenstein, Triesen, Liechtenstein.

出版信息

J Appl Clin Med Phys. 2021 Jul;22(7):235-244. doi: 10.1002/acm2.13315. Epub 2021 Jun 20.

DOI:10.1002/acm2.13315
PMID:34151502
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8292700/
Abstract

PURPOSE

In this study, 4-Hz log files were evaluated with an independent secondary Monte Carlo dose calculation algorithm to reduce the workload for patient-specific quality assurance (QA) in clinical routine.

MATERIALS AND METHODS

A total of 30 randomly selected clinical prostate VMAT plans were included. The used treatment planning system (TPS) was Monaco (Elekta, Crawley), and the secondary dose calculation software was SciMoCa (Scientific-RT, Munich). Monaco and SciMoCa work with a Monte Carlo algorithm. A plausibility check of Monaco and SciMoCa was performed using an ionization chamber in the BodyPhantom (BP). First, the original Monaco RT plans were verified with SciMoCa (pretreatment QA). Second, the corresponding 4-Hz log files were converted into RT log file plans and sent to SciMoCa as on-treatment QA. MLC shift errors were introduced for one prostate plan to determine the sensitivity of on-treatment QA. For pretreatment and on-treatment QA, a gamma analysis (2%/1mm/20%) was performed and dosimetric values of PTV and OARs were ascertained in SciMoCa.

RESULTS

Plausibility check of TPS Monaco vs. BP measurement and SciMoCa vs. BP measurement showed valid accuracy for clinical VMAT QA. Using SciMoCa, there was no significant difference in PTV Dmean between RT plan and RT log file plan. Between pretreatment and on-treatment QA, PTV metrics, femur right and left showed no significant dosimetric differences as opposed to OARs rectum and bladder. The overall gamma passing rate (GPR) ranged from 96.10% to 100% in pretreatment QA and from 93.50% to 99.80% in on-treatment QA. MLC shift errors were identified for deviations larger than -0.50 mm and +0.75 mm using overall gamma criterion and PTV Dmean.

CONCLUSION

SciMoCa calculations of Monaco RT plans and RT log file plans are in excellent agreement to each other. Therefore, 4-Hz log files and SciMoCa can replace labor-intensive phantom-based measurements as patient-specific QA.

摘要

目的

本研究使用独立的二次蒙特卡罗剂量计算算法评估 4-Hz 日志文件,以减少临床常规中患者特异性质量保证(QA)的工作量。

材料和方法

共纳入 30 例随机选择的临床前列腺 VMAT 计划。使用的治疗计划系统(TPS)是 Monaco(Elekta,Crawley),二次剂量计算软件是 SciMoCa(Scientific-RT,慕尼黑)。Monaco 和 SciMoCa 使用蒙特卡罗算法。使用 BodyPhantom(BP)中的电离室对 Monaco 和 SciMoCa 进行了合理性检查。首先,使用 SciMoCa 验证原始 Monaco RT 计划(预处理 QA)。其次,将相应的 4-Hz 日志文件转换为 RT 日志文件计划,并将其作为治疗中 QA 发送到 SciMoCa。为了确定治疗中 QA 的灵敏度,对一个前列腺计划引入了 MLC 移位误差。对于预处理和治疗中 QA,进行了伽马分析(2%/1mm/20%),并在 SciMoCa 中确定了 PTV 和 OAR 的剂量学值。

结果

TPS Monaco 与 BP 测量和 SciMoCa 与 BP 测量的合理性检查表明,临床 VMAT QA 的准确性是有效的。使用 SciMoCa,RT 计划和 RT 日志文件计划之间的 PTV Dmean 没有显著差异。与 OAR 直肠和膀胱相比,在预处理和治疗中 QA 之间,PTV 指标、右侧和左侧股骨没有明显的剂量学差异。整体伽马通过率(GPR)在预处理 QA 中范围为 96.10%至 100%,在治疗中 QA 中范围为 93.50%至 99.80%。使用整体伽马标准和 PTV Dmean,对于大于-0.50mm 和+0.75mm 的 MLC 移位误差进行了识别。

结论

Monaco RT 计划和 RT 日志文件计划的 SciMoCa 计算结果彼此非常吻合。因此,4-Hz 日志文件和 SciMoCa 可以替代劳动密集型基于体模的测量,作为患者特异性 QA。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/9e822858cddd/ACM2-22-235-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/338a60e5eee0/ACM2-22-235-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/8eb0a54e1579/ACM2-22-235-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/6516ec7c4bc3/ACM2-22-235-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/a13aa35f114f/ACM2-22-235-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/ab9e6b7a78b0/ACM2-22-235-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/07b13ad82fc9/ACM2-22-235-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/9e822858cddd/ACM2-22-235-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/338a60e5eee0/ACM2-22-235-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/8eb0a54e1579/ACM2-22-235-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/6516ec7c4bc3/ACM2-22-235-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/a13aa35f114f/ACM2-22-235-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/ab9e6b7a78b0/ACM2-22-235-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/07b13ad82fc9/ACM2-22-235-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7953/8292700/9e822858cddd/ACM2-22-235-g003.jpg

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