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模型优化可提高委托三维二次剂量计算系统时的置信水平和临床一致性。

Model refinement increases confidence levels and clinical agreement when commissioning a three-dimensional secondary dose calculation system.

机构信息

Henry Ford Health System, Detroit, Michigan, USA.

出版信息

J Appl Clin Med Phys. 2022 Jun;23(6):e13590. doi: 10.1002/acm2.13590. Epub 2022 Apr 7.

DOI:10.1002/acm2.13590
PMID:35389554
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9194992/
Abstract

PURPOSE

Evaluate custom beam models for a second check dose calculation system using statistically verifiable passing criteria for film analysis, DVH, and 3D gamma metrics.

METHODS

Custom beam models for nine linear accelerators for the Sun Nuclear Dose Calculator algorithm (SDC, Sun Nuclear) were evaluated using the AAPM-TG119 test suite (5 Intensity Modulated Radiation Therapy (IMRT) and 5 Volumetric Modulated Arc Therapy (VMAT) plans) and a set of clinical plans. Where deemed necessary, adjustments to Multileaf Collimator (MLC) parameters were made to improve results. Comparisons to the Analytic Anisotropic Algorithm (AAA), and gafchromic film measurements were performed. Confidence intervals were set to 95% per TG-119. Film gamma criteria were 3%/3 mm (conventional beams) or 3%/1 mm (Stereotactic Radiosurgery [SRS] beams). Dose distributions in solid water phantom were evaluated based on DVH metrics (e.g., D95, V20) and 3D gamma criteria (3%/3 mm or 3%/1 mm). Film passing rates, 3D gamma passing rates, and DVH metrics were reported for HD MLC machines and Millennium MLC Machines.

RESULTS

For HD MLC machines, SDC gamma film agreement was 98.76% ± 2.30% (5.74% CL) for 6FFF/6srs (3%/1 mm), and 99.80% ± 0.32% (0.83% CL) for 6x (3%/3 mm). For Millennium MLC machines, film passing rates were 98.20% ± 3.14% (7.96% CL), 99.52% ± 1.14% (2.71% CL), and 99.69% ± 0.82% (1.91% CL) for 6FFF, 6x, and 10x, respectively. For SDC to AAA comparisons: HD MLC Linear Accelerators (LINACs); DVH point agreement was 0.97% ± 1.64% (4.18% CL) and 1.05% ± 2.12% (5.20% CL); 3D gamma agreement was 99.97% ± 0.14% (0.30% CL) and 100.00% ± 0.02% (0.05% CL), for 6FFF/6srs and 6x, respectively; Millennium MLC LINACs: DVH point agreement was 0.77% ± 2.40% (5.47% CL), 0.80% ± 3.40% (7.47% CL), and 0.07% ± 2.15% (4.30% CL); 3D gamma agreement was 99.97% ± 0.13% (0.29% CL), 99.97% ± 0.17% (0.36% CL), and 99.99% ± 0.06% (0.12% CL) for 6FFF, 6x, and 10x, respectively.

CONCLUSION

SDC shows agreement well within TG119 CLs for film and redundant dose calculation comparisons with AAA. In some models (SRS), this was achieved using stricter criteria. TG119 plans can be used to help guide model adjustments and to establish clinical baselines for DVH and 3D gamma criteria.

摘要

目的

使用经统计学验证的胶片分析、剂量体积直方图 (DVH) 和 3D 伽马指标通过标准,评估用于第二个检查剂量计算系统的定制射束模型。

方法

使用 AAPM-TG119 测试套件(5 个强度调制放射治疗 (IMRT) 和 5 个容积调制弧形治疗 (VMAT) 计划)和一组临床计划,评估了 Sun 核剂量计算器算法 (SDC,Sun 核) 的九种直线加速器的定制射束模型。在认为必要的情况下,对多叶准直器 (MLC) 参数进行调整以改善结果。对分析各向异性算法 (AAA) 和 Gafchromic 胶片测量结果进行了比较。置信区间设定为 TG-119 的 95%。胶片伽马标准为 3%/3mm(常规射束)或 3%/1mm(立体定向放射外科 [SRS] 射束)。基于剂量体积直方图指标(如 D95、V20)和 3D 伽马标准(3%/3mm 或 3%/1mm),在固体水模体中评估剂量分布。报告了 HD MLC 机器和千禧 MLC 机器的 HD 胶片通过率、3D 伽马通过率和剂量体积直方图指标。

结果

对于 HD MLC 机器,SDC 伽马胶片的一致性对于 6FFF/6srs(3%/1mm)为 98.76%±2.30%(5.74%CL),对于 6x(3%/3mm)为 99.80%±0.32%(0.83%CL)。对于千禧 MLC 机器,胶片通过率分别为 98.20%±3.14%(7.96%CL)、99.52%±1.14%(2.71%CL)和 99.69%±0.82%(1.91%CL),对于 6FFF、6x 和 10x。对于 SDC 与 AAA 的比较:HD MLC 直线加速器(LINACs);剂量体积直方图点的一致性为 0.97%±1.64%(4.18%CL)和 1.05%±2.12%(5.20%CL);3D 伽马一致性为 99.97%±0.14%(0.30%CL)和 100.00%±0.02%(0.05%CL),分别用于 6FFF/6srs 和 6x;千禧 MLC LINACs:剂量体积直方图点的一致性为 0.77%±2.40%(5.47%CL)、0.80%±3.40%(7.47%CL)和 0.07%±2.15%(4.30%CL);3D 伽马一致性为 99.97%±0.13%(0.29%CL)、99.97%±0.17%(0.36%CL)和 99.99%±0.06%(0.12%CL),分别用于 6FFF、6x 和 10x。

结论

SDC 在与 AAA 的胶片和冗余剂量计算比较中,符合 TG119 的 CLs。在某些模型(SRS)中,通过使用更严格的标准来实现这一点。TG119 计划可用于帮助指导模型调整,并为剂量体积直方图和 3D 伽马标准建立临床基准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/a68f6f5b1fcc/ACM2-23-e13590-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/663f426317b3/ACM2-23-e13590-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/f47f36d5aa5a/ACM2-23-e13590-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/f682700b8add/ACM2-23-e13590-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/57501e39ae71/ACM2-23-e13590-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/808a148386d7/ACM2-23-e13590-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/1961a0968e47/ACM2-23-e13590-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/67020f443877/ACM2-23-e13590-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/4635aead49f8/ACM2-23-e13590-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/a68f6f5b1fcc/ACM2-23-e13590-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/663f426317b3/ACM2-23-e13590-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/f47f36d5aa5a/ACM2-23-e13590-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/f682700b8add/ACM2-23-e13590-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/57501e39ae71/ACM2-23-e13590-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/808a148386d7/ACM2-23-e13590-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/1961a0968e47/ACM2-23-e13590-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/67020f443877/ACM2-23-e13590-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/4635aead49f8/ACM2-23-e13590-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/740a/9194992/a68f6f5b1fcc/ACM2-23-e13590-g001.jpg

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