Nuclear Science and Engineering Institute, Lafferre Hall, University of Missouri, Columbia, MO, 65211, USA.
Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Pl, St. Louis, MO, 63110, USA.
Med Phys. 2017 Sep;44(9):4415-4425. doi: 10.1002/mp.12278. Epub 2017 Jul 28.
To evaluate the level of risk involved in treatment planning system (TPS) commissioning using a manual test procedure, and to compare the associated process-based risk to that of an automated commissioning process (ACP) by performing an in-depth failure modes and effects analysis (FMEA).
The authors collaborated to determine the potential failure modes of the TPS commissioning process using (a) approaches involving manual data measurement, modeling, and validation tests and (b) an automated process utilizing application programming interface (API) scripting, preloaded, and premodeled standard radiation beam data, digital heterogeneous phantom, and an automated commissioning test suite (ACTS). The severity (S), occurrence (O), and detectability (D) were scored for each failure mode and the risk priority numbers (RPN) were derived based on TG-100 scale. Failure modes were then analyzed and ranked based on RPN. The total number of failure modes, RPN scores and the top 10 failure modes with highest risk were described and cross-compared between the two approaches. RPN reduction analysis is also presented and used as another quantifiable metric to evaluate the proposed approach.
The FMEA of a MTP resulted in 47 failure modes with an RPN of 161 and S of 6.7. The highest risk process of "Measurement Equipment Selection" resulted in an RPN of 640. The FMEA of an ACP resulted in 36 failure modes with an RPN of 73 and S of 6.7. The highest risk process of "EPID Calibration" resulted in an RPN of 576.
An FMEA of treatment planning commissioning tests using automation and standardization via API scripting, preloaded, and pre-modeled standard beam data, and digital phantoms suggests that errors and risks may be reduced through the use of an ACP.
通过执行深入的失效模式与影响分析(FMEA),评估使用手动测试程序进行治疗计划系统(TPS)调试的风险水平,并将相关基于过程的风险与自动化调试过程(ACP)进行比较。
作者合作使用(a)涉及手动数据测量、建模和验证测试的方法和(b)利用应用程序编程接口(API)脚本、预加载和预建模标准辐射束数据、数字异种体模和自动化调试测试套件(ACTS)的自动化过程,确定 TPS 调试过程的潜在失效模式。为每个失效模式评分严重度(S)、发生度(O)和可检测度(D),并根据 TG-100 量表得出风险优先数(RPN)。然后根据 RPN 分析和对失效模式进行排名。描述并比较两种方法之间的失效模式总数、RPN 得分和风险最高的前 10 个失效模式。还提出了 RPN 降低分析,并将其用作另一个可量化的指标来评估所提出的方法。
MTP 的 FMEA 产生了 47 个失效模式,RPN 为 161,S 为 6.7。“测量设备选择”的最高风险过程导致 RPN 为 640。ACP 的 FMEA 产生了 36 个失效模式,RPN 为 73,S 为 6.7。“EPID 校准”的最高风险过程导致 RPN 为 576。
通过使用 API 脚本、预加载和预建模标准光束数据以及数字体模进行自动化和标准化,对治疗计划调试测试进行 FMEA 表明,通过使用 ACP,错误和风险可能会降低。