A dual-layer quality assurance approach leveraging dose prediction for efficient review of automated contours of organs at risk in the brain in radiotherapy
Our dual-layer QA approach effectively identifies critical OAR segmentations with high sensitivity and acceptable specificity, potentially reducing manual review requirements significantly. By focusing on clinically relevant dose/volume metric endpoints, this method assures the quality of brain AS results in clinical radiotherapy practice.
Authors
- Elias Rüfenacht (ORCID: https://orcid.org/0000-0001-6983-1695)
- Amith Kamath (ORCID: https://orcid.org/0000-0002-7243-8883)
- Robert Poel (ORCID: https://orcid.org/0000-0002-9817-4935)
- Peter Manser (ORCID: https://orcid.org/0000-0003-3225-8025)
- Nicolaus Andratschke (ORCID: https://orcid.org/0000-0003-3647-5916)
- Mauricio Reyes (ORCID: https://orcid.org/0000-0002-2434-9990)
- Jonas Willmann (ORCID: https://orcid.org/0000-0002-2531-3551)
- Ekin Ermiş (ORCID: https://orcid.org/0000-0002-6974-6762)
- Daniel M. Aebersold (ORCID: https://orcid.org/0000-0002-9493-3834)
Institutions
- University of Bern (CH)
- Memorial Sloan Kettering Cancer Center (US)
- University of Zurich (CH)
- University Hospital of Bern (CH)
- University Hospital of Zurich (CH)
Publication Details
- Journal
- Physics and Imaging in Radiation Oncology
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1016/j.phro.2025.100888
- Citations
- 1
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- Innosuisse - Schweizerische Agentur für Innovationsförderung
- Swiss Cancer Research Foundation