Cai Bin, Altman Michael B, Reynoso Francisco, Garcia-Ramirez Jose, He Angell, Edward Sharbacha S, Zoberi Imran, Thomas Maria A, Gay Hiram, Mutic Sasa, Zoberi Jacqueline E
Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, MO.
Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, MO.
Brachytherapy. 2019 Jan-Feb;18(1):108-114.e1. doi: 10.1016/j.brachy.2018.09.004. Epub 2018 Oct 29.
To standardize and automate the high-dose-rate (HDR) brachytherapy planning quality assurance (QA) process utilizing scripting with application programming interface (API) in a commercially available treatment planning system (TPS).
Site- and applicator-dependent plan quality (PQ) evaluation criteria and plan integrity (PI) checklists were established based on published guidelines, clinical protocols, and institutional experience. User designed C# programs ("scripts") were created and executed through the API to access planning information in TPS. A set of standardized quality control reports, focusing on PQ evaluations and PI checks, were automatically generated. Information derived from the TPS was compared against predetermined QA metrics with color-coded pass/fail indicators to aid and enhance the efficiency of plan evaluation. Five independent, blinded observers reviewed mock plans with simulated errors to validate the scripts and to quantify the improvement of plan review efficiency.
Scripts were developed for HDR prostate and breast. Forty-one parameters were reported/checked in the PI report; the PQ report returned dose-volume indices and an independent check of dwell time. All simulated errors were detected by the PI scripts with appropriate warning messages displayed, and any values failing to meet the planning constraints were red-flagged successfully in the PQ report. An average time reduction of 16 min for plan review was observed when using the scripts.
API scripting-based automated planning QA for HDR brachytherapy including PI checks and PQ evaluations was designed and implemented. The simulated error study showed promising results in terms of error catching and efficiency improvement.
在商用治疗计划系统（TPS）中利用应用程序编程接口（API）脚本对高剂量率（HDR）近距离放射治疗计划质量保证（QA）流程进行标准化和自动化。
基于已发表的指南、临床方案和机构经验，建立了与部位和施源器相关的计划质量（PQ）评估标准和计划完整性（PI）检查表。通过API创建并执行用户设计的C#程序（“脚本”），以访问TPS中的计划信息。自动生成了一组侧重于PQ评估和PI检查标准的质量控制报告。将从TPS获取的信息与预先确定的QA指标进行比较，并带有颜色编码的通过/失败指标，以帮助提高计划评估的效率。五名独立的、不知情的观察者审查了带有模拟错误的模拟计划，以验证脚本并量化计划审查效率的提高。
针对HDR前列腺癌和乳腺癌开发了脚本。PI报告中报告/检查了41个参数；PQ报告返回剂量体积指数并独立检查驻留时间。PI脚本检测到所有模拟错误，并显示适当的警告消息，任何未满足计划约束的值在PQ报告中都被成功标记为红色。使用脚本时，观察到计划审查平均时间减少了16分钟。
设计并实施了基于API脚本的HDR近距离放射治疗自动化计划QA，包括PI检查和PQ评估。模拟错误研究在错误捕捉和效率提高方面显示出了有前景的结果。
