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在 Monaco 治疗计划系统中建模灵活性 MLC。

Modeling the Agility MLC in the Monaco treatment planning system.

机构信息

Wayne State University School of Medicine; Karmanos Cancer Institute.

出版信息

J Appl Clin Med Phys. 2016 May 8;17(3):190-202. doi: 10.1120/jacmp.v17i3.6044.

Abstract

We investigate the relationship between the various parameters in the Monaco MLC model and dose calculation accuracy for an Elekta Agility MLC. The vendor-provided MLC modeling procedure - completed first with external vendor participation and then exclusively in-house - was used in combination with our own procedures to investigate several sets of MLC modeling parameters to determine their effect on dose distributions and point-dose measurements. Simple plans provided in the vendor procedure were used to elucidate specific mechanical characteristics of the MLC, while ten complex treatment plans - five IMRT and five VMAT - created using TG-119-based structure sets were used to test clinical dosimetric effects of particular parameter choices. EDR2 film was used for the vendor fields to give high spatial resolution, while a combination of MapCHECK and ion chambers were used for the in-house TG-119-based proced-ures. The vendor-determined parameter set provided a reasonable starting point for the MLC model and largely delivered acceptable gamma pass rates for clinical plans - including a passing external evaluation using the IROC H&N phantom. However, the vendor model did not provide point-dose accuracy consistent with that seen in other treatment systems at our center. Through further internal testing it was found that there existed many sets of MLC parameters, often at opposite ends of their allowable ranges, that provided similar dosimetric characteristics and good agreement with planar and point-dose measurements. In particular, the leaf offset and tip leakage parameters compensated for one another if adjusted in opposite directions, which provided a level curve of acceptable parameter sets across all plans. Interestingly, gamma pass rates of the plans were less dependent upon parameter choices than point-dose measurements, suggesting that MLC modeling using only gamma evaluation may be generally an insufficient approach. It was also found that exploring all parameters of the very robust MLC model to find the best match to the vendor-provided QA fields can reduce the pass rates of the TG-119-based clinical distributions as compared to simpler models. A wide variety of parameter sets produced MLC models capable of meeting RPC passing criteria for their H&N IMRT phantom. The most accurate models were achievable using a combination of vendor-provided and in-house procedures. The potential existed for an over-modeling of the Agility MLC in an effort to obtain the fine structure of certain quality assurance fields, which led to a reduction in agreement between calculation and measurement of more typical clinical dose distributions.

摘要

我们研究了 Monaco MLC 模型中的各种参数与 Elekta Agility MLC 剂量计算准确性之间的关系。我们使用供应商提供的 MLC 建模过程(最初由外部供应商参与,然后完全内部完成),结合我们自己的程序,研究了几组 MLC 建模参数,以确定它们对剂量分布和点剂量测量的影响。供应商程序中提供的简单计划用于阐明 MLC 的特定机械特性,而使用基于 TG-119 的结构集创建的十个复杂治疗计划(五个 IMRT 和五个 VMAT)用于测试特定参数选择的临床剂量学效果。EDR2 胶片用于供应商场,以提供高空间分辨率,而 MapCHECK 和离子室的组合用于基于内部 TG-119 的程序。供应商确定的参数集为 MLC 模型提供了一个合理的起点,并为临床计划提供了可接受的伽马通过率 - 包括使用 IROC H&N 体模进行的外部评估。然而,供应商模型并没有提供与我们中心其他治疗系统一致的点剂量准确性。通过进一步的内部测试发现,存在许多组 MLC 参数,它们通常处于其允许范围的两端,这些参数提供了相似的剂量学特性,并与平面和点剂量测量很好地吻合。特别是,如果以相反的方向调整叶偏移和尖端泄漏参数,它们会相互补偿,从而在所有计划中提供可接受的参数集的水平曲线。有趣的是,计划的伽马通过率比点剂量测量更不依赖于参数选择,这表明仅使用伽马评估的 MLC 建模可能通常是不够的。还发现,探索非常强大的 MLC 模型的所有参数,以找到与供应商提供的 QA 场的最佳匹配,可以降低基于 TG-119 的临床分布的通过率,与更简单的模型相比。各种各样的参数集产生了能够满足其 H&N IMRT 体模 RPC 通过标准的 MLC 模型。最准确的模型可以通过结合供应商提供的和内部的程序来实现。在努力获得某些质量保证字段的精细结构的过程中,存在对 Agility MLC 进行过度建模的可能性,这导致计算和测量之间的一致性降低更典型的临床剂量分布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca07/5690908/cae36c762834/ACM2-17-190-g001.jpg

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