Author: Haleem Azmy, Robbie Beckert, Farnoush Forghani, Dean Hobbis, Dan Hong, Hyun Kim, Eric Laugeman, Silpa Raju-Salicki, Domenic Sievert 👨🔬
Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine in St. Louis, Washington University School of Medicine, Wash U Medicine, Washington University in St. Louis 🌍
Purpose: A novel radiation therapy (RT) workflow has recently emerged with the advent of online adaptive RT systems, direct-to-unit (DTU). DTU utilizes online adaptive platforms (MR and CT based) to obviate the need for a traditional CT-simulation prior to treatment. Prior studies have demonstrated feasibility in using DTU in palliative RT settings. Further advances in on-board imaging (OBI) capabilities have allowed for HU fidelity imaging to be performed with CBCT, making curative intent DTU treatments possible. However, DTU is a significant deviation in clinical practice, requiring this new workflow to be evaluated. We assessed DTU for curative intent RT using TG-100 failure mode and effects analysis (FMEA).
Methods: A process map was created based on a generalized online adaptive platform. Failure modes (FM) for each process step were identified and listed with their associated steps and consequences. Eight participants consisting of MDs, medical physicists, and radiation therapists evaluated the FM individually, scoring each based on occurrence frequency, detectability, and severity of the outcome. These scores were used to calculate the risk priority number (RPN) of each FM and averaged.
Results: 45 DTU failure modes were identified. The highest RPN FM was target contouring, likely due to the lack of high-quality diagnostic imaging fused to the daily image, human error, and time pressure to contour during DTU. The top ten RPN scores can be grouped as follows: contouring errors(four at the machine, one in preplanning), patient setup issues (two FM), and electron density errors for dose calculation (one HU inaccuracy, two manual electron density assignment errors).
Conclusion: Using the prospective risk assessment method of FMEA, we identified the process steps that are most at-risk for errors in the DTU workflow. Further development of improved processes and QA checks are on-going to reduce the risk of failure in the DTU workflow.