评估机器日志文件/基于 MC 的治疗计划和交付 QA 与 ArcCHECK QA 相比。
Evaluation of machine log files/MC-based treatment planning and delivery QA as compared to ArcCHECK QA.
机构信息
Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, MI, 48073, USA.
Department of Medical Physics, Wayne State University, Detroit, MI, 48202, USA.
出版信息
Med Phys. 2018 Jul;45(7):2864-2874. doi: 10.1002/mp.12926. Epub 2018 May 11.
PURPOSE
A treatment planning/delivery QA tool using linac log files (LF) and Monte Carlo (MC) dose calculation is investigated as a standalone alternative to phantom-based patient-specific QA (ArcCHECK (AC)).
METHODS
Delivering a variety of fields onto MapCHECK2 and ArcCHECK, diode sensitivity dependence on dose rate (in-field) and energy (primarily out-of-field) was quantified. AC and LF QAs were analyzed with respect to delivery complexity by delivering 12 × 12 cm static fields/arcs comprised of varying numbers of abutting sub-fields onto ArcCHECK. About 11 clinical dual-arc VMAT patients planned using Pinnacle's convolution-superposition (CS) were delivered on ArcCHECK and log file dose (LF-CS and LF-MC) calculated. To minimize calculation time, reduced LF-CS sampling (1/2/3/4° control point spacing) was investigated. Planned ("Plan") and LF-reconstructed CS and MC doses were compared with each other and AC measurement via statistical [mean ± StdDev(σ)] and gamma analyses to isolate dosimetric uncertainties and quantify the relative accuracies of AC QA and MC-based LF QA.
RESULTS
Calculation and ArcCHECK measurement differed by up to 1.5% in-field due to variation in dose rate and up to 5% out-of-field. For the experimental segment-varying plans, despite CS calculation deviating by as much as 13% from measurement, Plan-MC and LF-MC doses generally matched AC measurement within 3%. Utilizing 1° control point spacing, 2%/2 mm LF-CS vs AC pass rates (97%) were slightly lower than Plan-CS vs AC pass rates (97.5%). Utilizing all log file samples, 2%/2 mm LF-MC vs AC pass rates (97.3%) were higher than Plan-MC vs AC (96.5%). Phantom-dependent, calculation algorithm-dependent (MC vs CS), and delivery error-dependent dose uncertainties were 0.8 ± 1.2%, 0.2 ± 1.1%, and 0.1 ± 0.9% respectively.
CONCLUSION
Reconstructing every log file sample with no increase in computational cost, MC-based LF QA is faster and more accurate than CS-based LF QA. Offering similar dosimetric accuracy compared to AC measurement, MC-based log files can be used for treatment planning QA.
目的
研究一种使用直线加速器日志文件（LF）和蒙特卡罗（MC）剂量计算的治疗计划/交付 QA 工具，作为基于体模的患者特定 QA（ArcCHECK（AC））的独立替代方案。
方法
在 MapCHECK2 和 ArcCHECK 上测量各种射野，量化二极管剂量率（场内）和能量（主要是场外）依赖性。通过在 ArcCHECK 上交付由不同数量相邻子野组成的 12×12cm 静态射野/弧形，分析 AC 和 LF QA 相对于交付复杂性。使用 Pinnacle 的卷积叠加（CS）为大约 11 个临床双弧 VMAT 患者进行计划，并在 ArcCHECK 上进行交付，并计算日志文件剂量（LF-CS 和 LF-MC）。为了最小化计算时间，研究了 LF-CS 的减少采样（1/2/3/4°控制点间距）。通过统计[平均值±标准差（σ）]和伽马分析将计划（“Plan”）和 LF 重建的 CS 和 MC 剂量与 AC 测量进行比较，以隔离剂量不确定性并量化 AC QA 和基于 MC 的 LF QA 的相对准确性。
结果
由于剂量率的变化，场内计算和 ArcCHECK 测量的差异最大可达 1.5%，场外最大可达 5%。对于实验分段变化的计划，尽管 CS 计算与测量的差异最大可达 13%，但 Plan-MC 和 LF-MC 剂量通常与 AC 测量相差在 3%以内。使用 1°控制点间距，LF-CS 与 AC 的 2%/2mm 通过率（97%）略低于 Plan-CS 与 AC 的通过率（97.5%）。使用所有日志文件样本，LF-MC 与 AC 的 2%/2mm 通过率（97.3%）高于 Plan-MC 与 AC 的通过率（96.5%）。与体模相关、与计算算法相关（MC 与 CS）以及与交付误差相关的剂量不确定性分别为 0.8±1.2%、0.2±1.1%和 0.1±0.9%。
结论
在不增加计算成本的情况下重建每个日志文件样本，基于 MC 的 LF QA 比基于 CS 的 LF QA 更快、更准确。与 AC 测量相比，提供类似的剂量准确性，基于 MC 的日志文件可用于治疗计划 QA。
Zotero 插件