Stanford University, Stanford, California 94394, USA.
Med Phys. 2010 Dec;37(12):6466-79. doi: 10.1118/1.3517837.
To develop and implement a failure mode and effect analysis (FMEA)-based commissioning and quality assurance framework for dynamic multileaf collimator (DMLC) tumor tracking systems.
A systematic failure mode and effect analysis was performed for a prototype real-time tumor tracking system that uses implanted electromagnetic transponders for tumor position monitoring and a DMLC for real-time beam adaptation. A detailed process tree of DMLC tracking delivery was created and potential tracking-specific failure modes were identified. For each failure mode, a risk probability number (RPN) was calculated from the product of the probability of occurrence, the severity of effect, and the detectibility of the failure. Based on the insights obtained from the FMEA, commissioning and QA procedures were developed to check (i) the accuracy of coordinate system transformation, (ii) system latency, (iii) spatial and dosimetric delivery accuracy, (iv) delivery efficiency, and (v) accuracy and consistency of system response to error conditions. The frequency of testing for each failure mode was determined from the RPN value.
Failures modes with RPN > or = 125 were recommended to be tested monthly. Failure modes with RPN < 125 were assigned to be tested during comprehensive evaluations, e.g., during commissioning, annual quality assurance, and after major software/hardware upgrades. System latency was determined to be approximately 193 ms. The system showed consistent and accurate response to erroneous conditions. Tracking accuracy was within 3%-3 mm gamma (100% pass rate) for sinusoidal as well as a wide variety of patient-derived respiratory motions. The total time taken for monthly QA was approximately 35 min, while that taken for comprehensive testing was approximately 3.5 h.
FMEA proved to be a powerful and flexible tool to develop and implement a quality management (QM) framework for DMLC tracking. The authors conclude that the use of FMEA-based QM ensures efficient allocation of clinical resources because the most critical failure modes receive the most attention. It is expected that the set of guidelines proposed here will serve as a living document that is updated with the accumulation of progressively more intrainstitutional and interinstitutional experience with DMLC tracking.
开发并实施一种基于失效模式与影响分析（FMEA）的调试验证和质量保证框架，用于动态多叶准直器（DMLC）肿瘤跟踪系统。
对使用植入式电磁传感器进行肿瘤位置监测和使用 DMLC 进行实时光束适形的实时肿瘤跟踪系统原型进行了系统性失效模式与影响分析。创建了 DMLC 跟踪输送的详细过程树，并确定了潜在的跟踪特定失效模式。对于每种失效模式，通过发生概率、影响严重程度和失效可探测性的乘积计算风险概率数（RPN）。基于 FMEA 的分析结果，制定了调试验证和质量保证程序，以检查（i）坐标系转换的准确性、（ii）系统时滞、（iii）空间和剂量传递精度、（iv）输送效率，以及（v）系统对误差条件的响应准确性和一致性。根据 RPN 值确定了每种失效模式的测试频率。
推荐将 RPN≥125 的失效模式每月进行测试。RPN＜125 的失效模式分配在综合评估期间进行测试，例如调试验证、年度质量保证和重大软件/硬件升级后。系统时滞约为 193ms。系统对错误条件有一致和准确的响应。跟踪精度在正弦和各种源自患者的呼吸运动下均达到 3%-3mmγ（通过率 100%）。每月 QA 所需的总时间约为 35 分钟，而全面测试所需的总时间约为 3.5 小时。
FMEA 被证明是开发和实施 DMLC 跟踪质量管理（QM）框架的强大且灵活的工具。作者得出结论，基于 FMEA 的 QM 的使用确保了临床资源的有效分配，因为最关键的失效模式得到了最多的关注。预计本文提出的准则集将作为一份活文档，随着越来越多的机构内和机构间的 DMLC 跟踪经验的积累而不断更新。
