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FMEA of MR-Only Treatment Planning in the Pelvis.
Advances in Radiation Oncology 2019 January
Purpose: To evaluate the implementation of a magnetic resonance (MR)-only workflow (ie, implementing MR simulation as the primary planning modality) using failure mode and effects analysis (FMEA) in comparison with a conventional multimodality (MR simulation in conjunction with computed tomography simulation) workflow for pelvis external beam planning.
Methods and Materials: To perform the FMEA, a multidisciplinary 9-member team was assembled and developed process maps, identified potential failure modes (FMs), and assigned numerical values to the severity (S), frequency of occurrence (O), and detectability (D) of those FMs. Risk priority numbers (RPNs) were calculated via the product of S, O, and D as a metric for evaluating relative patient risk. An alternative 3-digit composite number (SOD) was computed to emphasize high-severity FMs. Fault tree analysis identified the causality chain leading to the highest-severity FM.
Results: Seven processes were identified, 3 of which were shared between workflows. Image fusion and target delineation subprocesses using the conventional workflow added 9 and 10 FMs, respectively, with 6 RPNs >100. By contrast, synthetic computed tomography generation introduced 3 major subprocesses and propagated 46 unique FMs, 15 with RPNs >100. For the conventional workflow, the largest RPN scores were introduced by image fusion (RPN range, 120-192). For the MR-only workflow, the highest RPN scores were from inaccuracies in target delineation resulting from misinterpretation of MR images (RPN = 240) and insufficient management of patient- and system-level distortions (RPN = 210 and 168, respectively). Underestimation (RPN = 140) or overestimation (RPN = 192) of bone volume produced higher RPN scores. The highest SODs for both workflows were related to changes in target location because of internal anatomy changes (conventional = 961, MR-only = 822).
Conclusions: FMEA identified areas for mitigating risk in MR-only pelvis RTP, and SODs identified high-severity process modes. Efforts to develop a quality management program to mitigate high FMs are underway.
Methods and Materials: To perform the FMEA, a multidisciplinary 9-member team was assembled and developed process maps, identified potential failure modes (FMs), and assigned numerical values to the severity (S), frequency of occurrence (O), and detectability (D) of those FMs. Risk priority numbers (RPNs) were calculated via the product of S, O, and D as a metric for evaluating relative patient risk. An alternative 3-digit composite number (SOD) was computed to emphasize high-severity FMs. Fault tree analysis identified the causality chain leading to the highest-severity FM.
Results: Seven processes were identified, 3 of which were shared between workflows. Image fusion and target delineation subprocesses using the conventional workflow added 9 and 10 FMs, respectively, with 6 RPNs >100. By contrast, synthetic computed tomography generation introduced 3 major subprocesses and propagated 46 unique FMs, 15 with RPNs >100. For the conventional workflow, the largest RPN scores were introduced by image fusion (RPN range, 120-192). For the MR-only workflow, the highest RPN scores were from inaccuracies in target delineation resulting from misinterpretation of MR images (RPN = 240) and insufficient management of patient- and system-level distortions (RPN = 210 and 168, respectively). Underestimation (RPN = 140) or overestimation (RPN = 192) of bone volume produced higher RPN scores. The highest SODs for both workflows were related to changes in target location because of internal anatomy changes (conventional = 961, MR-only = 822).
Conclusions: FMEA identified areas for mitigating risk in MR-only pelvis RTP, and SODs identified high-severity process modes. Efforts to develop a quality management program to mitigate high FMs are underway.
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