Implementing failure mode and effect analysis to improve the safety of volumetric modulated arc therapy for total body irradiation

Abstract

AbstractPurposeVolumetric‐modulated arc therapy for total body irradiation (VMAT‐TBI) is a novel radiotherapy technique that has been implemented at our institution. The purpose of this work is to investigate possible failure modes (FMs) in the treatment process and to develop a quality control (QC) program for VMAT‐TBI following TG‐100 guidelines.MethodsWe formed a multidisciplinary team to map out the complete treatment process of VMAT‐TBI following the AAPM TG‐100 guidelines. This process map gives a visual representation of the VMAT‐TBI workflow from the CT simulation, image processing, contouring, treatment planning, to treatment delivery. From the process map, potential FMs were identified. The occurrence (O), detectability (D), and severity of impact (S) of each FM were assigned according to scoring criteria (1–10) by the multidisciplinary team. A risk priority number (RPN) was calculated from average O, S, and D of each FM (RPN = O x S x D). High risk FMs were identified as 20% of the FMs having the highest RPN scores. After the FMEA analysis, fault‐tree analysis (FTA) was performed for each major step of the treatment process to determine the effects of potential failures to the treatment outcome. Effective QC methods were identified to prevent the high risk failures and to improve the safety of the VMAT‐TBI program.ResultsWe identified a total of 55 sub‐processes and 128 FMs from the VMAT‐TBI workflow. The top five high‐risk FMs were: (1) Prescription and/or OAR constraints changed during planning and not communicated to the planner, (2) Patient moves or breathes too heavily during the upper body CT scan (3) Patient moves during the lower body CT scan, (4) Treatment planning system not calculating total body DVH metrics correctly for TBI, (5) Improper optimization criteria used or not sufficient optimization, resulting in suboptimal dose coverage, OAR sparing or excessive hotspots during treatment planning. Two FMs have average severity scores ≥8: Incorrect PTV subdivision/isocenter placement and Prescription and/or OAR constraints changed during planning and not communicated to the planner. Quality assurance and QC interventions including staff training, standard operating procedures, and quality checklists were implemented based on the FMEA and FTA.ConclusionFM and effect analysis was performed to identify high‐risk FMs of our VMAT‐TBI program. FMEA and FTA were effective in identifying potential FMs and determining the best quality management (QM) measures to implement in the VMAT‐TBI program.