Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Failure modes and effects analysis for clinical implementation of online adaptive radiotherapy: A systematic review.

Created on 25 Aug 2026

Authors

Deepikaa Balaji, Sonja Wegener, Sebastian Klüter, Sara L Hackett

Published in

Journal of applied clinical medical physics. Volume 27. Issue 9. Pages e70749.

Abstract

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.
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.
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).
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.
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.

PMID:
42638337
Bibliographic data and abstract were imported from PubMed on 25 Aug 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 15
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement