应用程序编程接口指导的 QA 计划生成和分析自动化。
Application programming interface guided QA plan generation and analysis automation.
机构信息
Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.
Department of Physics, University of Massachusetts Lowell, Lowell, MA, USA.
出版信息
J Appl Clin Med Phys. 2021 Jun;22(6):26-34. doi: 10.1002/acm2.13288. Epub 2021 May 26.
PURPOSE
Linear accelerator quality assurance (QA) in radiation therapy is a time consuming but fundamental part of ensuring the performance characteristics of radiation delivering machines. The goal of this work is to develop an automated and standardized QA plan generation and analysis system in the Oncology Information System (OIS) to streamline the QA process.
METHODS
Automating the QA process includes two software components: the AutoQA Builder to generate daily, monthly, quarterly, and miscellaneous periodic linear accelerator QA plans within the Treatment Planning System (TPS) and the AutoQA Analysis to analyze images collected on the Electronic Portal Imaging Device (EPID) allowing for a rapid analysis of the acquired QA images. To verify the results of the automated QA analysis, results were compared to the current standard for QA assessment for the jaw junction, light-radiation coincidence, picket fence, and volumetric modulated arc therapy (VMAT) QA plans across three linacs and over a 6-month period.
RESULTS
The AutoQA Builder application has been utilized clinically 322 times to create QA patients, construct phantom images, and deploy common periodic QA tests across multiple institutions, linear accelerators, and physicists. Comparing the AutoQA Analysis results with our current institutional QA standard the mean difference of the ratio of intensity values within the field-matched junction and ball-bearing position detection was 0.012 ± 0.053 (P = 0.159) and is 0.011 ± 0.224 mm (P = 0.355), respectively. Analysis of VMAT QA plans resulted in a maximum percentage difference of 0.3%.
CONCLUSION
The automated creation and analysis of quality assurance plans using multiple APIs can be of immediate benefit to linear accelerator quality assurance efficiency and standardization. QA plan creation can be done without following tedious procedures through API assistance, and analysis can be performed inside of the clinical OIS in an automated fashion.
目的
放射治疗中的直线加速器质量保证（QA）是确保放射治疗机器性能的重要且耗时的部分。本工作的目的是在肿瘤信息系统（OIS）中开发自动化和标准化的 QA 计划生成和分析系统，以简化 QA 流程。
方法
自动化 QA 过程包括两个软件组件：AutoQA Builder，用于在治疗计划系统（TPS）中生成日常、每月、每季度和杂项周期性直线加速器 QA 计划；AutoQA Analysis，用于分析电子射野影像装置（EPID）上采集的图像，以便快速分析获取的 QA 图像。为了验证自动化 QA 分析的结果，将结果与当前的 jaw junction、light-radiation coincidence、picket fence 和 volumetric modulated arc therapy（VMAT）QA 计划的质量评估标准进行比较，该标准跨越了三台直线加速器和 6 个月的时间。
结果
AutoQA Builder 应用程序已在临床中使用 322 次，用于创建 QA 患者、构建体模图像以及在多个机构、直线加速器和物理学家之间部署常见的周期性 QA 测试。将 AutoQA Analysis 结果与我们当前的机构 QA 标准进行比较，场匹配结和滚珠轴承位置检测的强度值比值的平均差异为 0.012 ± 0.053（P = 0.159）和 0.011 ± 0.224（P = 0.355），分别。VMAT QA 计划的分析导致最大百分比差异为 0.3%。
结论
使用多个 API 自动创建和分析质量保证计划可以立即提高直线加速器质量保证的效率和标准化。通过 API 协助，可以避免繁琐的步骤来完成 QA 计划的创建，并且可以在临床 OIS 中以自动化的方式进行分析。
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