A technology‐specific risk analysis of surface guided radiation therapy

Abstract Background Surface Guided Radiation Therapy (SGRT) has become an increasingly important tool that complements x‐ray imaging to improve patient safety for setup, respiratory tracking, and motion monitoring. As SGRT is integrated into clinical workflows, its complexity can introduce potential risk of process‐related errors. These risks may depend on workflow design, system integration, equipment configuration, and technology specific features. As SGRT continues to expand across a wider range of treatment sites and clinical applications, comprehensive evaluation of institutional workflows is recommended to support safe and effective implementation. Purpose This study aimed to identify and evaluate safety risks associated with the clinical use of SGRT using Failure Mode and Effects Analysis (FMEA). Emphasis was placed on workflow processes, system integration, and equipment‐specific characteristics within a clinical environment to inform risk mitigation strategies and support safe implementation. Methods A multidisciplinary team performed an FMEA of SGRT related procedures and workflows. A process map was developed to define the scope of clinical applications, including tattoo free setup, free‐breathing and deep‐inspiration breath‐hold (DIBH) breast treatments, prone patient positioning and real‐time motion monitoring for stereotactic body radiation therapy (SBRT) patients across body sites. For each process step, team members identified potential failure modes associated with the clinical workflow and environment, including the integration of a C‐RAD SGRT system with Elekta linear accelerators. Scoring was performed according to AAPM TG‐100 guidelines, using severity (S), occurrence (O), and detectability (D) to calculate the Risk Priority Number (RPN). Failure modes were then ranked by RPN, and those with scores greater than or equal to 100 were selected for further analysis and development of mitigation strategies. Results Thirty‐eight failure modes were identified, with nine having RPN scores greater than or equal to 100 ( S = 5–8, O = 2–5, and D = 5–9). High risk failure modes were most associated with the DIBH workflow, particularly respiratory trace acquisition, respiratory trace configuration, and x‐ray image verification. Additional high risk failure modes were identified in treatment preparation and system quality assurance processes, including manual data import, template selection, calibration, and daily QA procedures. These risks were primarily associated with workflow‐dependent processes involving user interaction and coordination between integrated clinical systems. Conclusions This FMEA identified workflow, system integration and equipment related vulnerabilities associated with SGRT implementation. The findings emphasize the importance of risk assessments tailored to specific clinical workflows and treatment environments and support the development of targeted mitigation strategies for safe clinical use.