WE-G-BRA-08: Failure Modes and Effects Analysis (FMEA) for Gamma Knife Radiosurgery

Purpose: To perform a failure modes and effects analysis (FMEA) study for Gamma Knife (GK) radiosurgery processes at our institution based on our experience with the treatment of more than 13,000 patients. Methods: A team consisting of medical physicists, nurses, radiation oncologists, neurosurgeons at the University of Pittsburgh Medical Center and an external physicist expert was formed for the FMEA study. A process tree and a failure mode table were created for the GK procedures using the Leksell GK Perfexion and 4C units. Three scores for the probability of occurrence (O), the severity (S), and the probability of no detection (D) for failure modes were assigned to each failure mode by each professional on a scale from 1 to 10. The risk priority number (RPN) for each failure mode was then calculated (RPN = OxSxD) as the average scores from all data sets collected. Results: The established process tree for GK radiosurgery consists of 10 sub-processes and 53 steps, including a sub-process for frame placement and 11 steps that are directly related to the frame-based nature of the GK radiosurgery. Out of the 86 failure modes identified, 40 failure modes are GK specific, caused by the potential for inappropriate use of the radiosurgery head frame, the imaging fiducial boxes, the GK helmets and plugs, and the GammaPlan treatment planning system. The other 46 failure modes are associated with the registration, imaging, image transfer, contouring processes that are common for all radiation therapy techniques. The failure modes with the highest hazard scores are related to imperfect frame adaptor attachment, bad fiducial box assembly, overlooked target areas, inaccurate previous treatment information and excessive patient movement during MRI scan. Conclusion: The implementation of the FMEA approach for Gamma Knife radiosurgery enabled deeper understanding of the overall process among all professionals involved in the care of the patient and helped identify potential weaknesses in the overall process.