Journal of applied clinical medical physics · 2026
Failure modes and effects analysis for clinical implementation of online adaptive radiotherapy: A systematic review.
СтатьяСистематический обзорНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Balaji Deepikaa, Wegener Sonja, Klüter Sebastian, Hackett Sara L
Аннотация
BACKGROUND: The accuracy of radiotherapy is limited by anatomical variations occurring over time scales ranging from sub-seconds to days. Online Adaptive Radiotherapy (OART) addresses this by enabling daily plan adaptation based on real-time imaging. While OART offers improved dose conformity, its dynamic, time-constrained workflow introduces novel failure modes that challenge traditional quality assurance protocols.
PURPOSE: This study aims to synthesize the existing literature on Failure Modes and Effects Analysis (FMEA) for OART to systematically catalog risks and identify mitigation strategies.
METHODS: A systematic literature search was conducted to identify studies applying FMEA to OART workflows. Eleven studies were included, covering MR-guided (ViewRay MRIdian, Elekta Unity), CBCT-guided (Varian Ethos), and MR-enhanced C-arm linac systems. To address heterogeneity in risk scoring methodologies (e.g., TG-100 10-point scales vs. 5-point rankings), extracted failure modes were harmonized into a standardized three-tier risk classification system (Class I: Low, Class II: Intermediate, Class III: High).
RESULTS: A total of 300 unique failure modes were identified, with 49.6 percent classified as high-risk (Class III). Analysis revealed that the majority of high-risk failures were concentrated in the online treatment delivery phase, specifically within human-computer interactions and anatomical contouring steps.
CONCLUSIONS: This study supports the development of tailored, robust QA frameworks that prioritize human factors and process consistency to guide safe implementation in diverse clinical settings.
PURPOSE: This study aims to synthesize the existing literature on Failure Modes and Effects Analysis (FMEA) for OART to systematically catalog risks and identify mitigation strategies.
METHODS: A systematic literature search was conducted to identify studies applying FMEA to OART workflows. Eleven studies were included, covering MR-guided (ViewRay MRIdian, Elekta Unity), CBCT-guided (Varian Ethos), and MR-enhanced C-arm linac systems. To address heterogeneity in risk scoring methodologies (e.g., TG-100 10-point scales vs. 5-point rankings), extracted failure modes were harmonized into a standardized three-tier risk classification system (Class I: Low, Class II: Intermediate, Class III: High).
RESULTS: A total of 300 unique failure modes were identified, with 49.6 percent classified as high-risk (Class III). Analysis revealed that the majority of high-risk failures were concentrated in the online treatment delivery phase, specifically within human-computer interactions and anatomical contouring steps.
CONCLUSIONS: This study supports the development of tailored, robust QA frameworks that prioritize human factors and process consistency to guide safe implementation in diverse clinical settings.