Quality assurance for deep learning-based proton therapy planning in routine clinical use for oropharyngeal cancer
- Journal
- Physics and imaging in radiation oncology (Q1)
- Published
- 20 August 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Ilse G van Bruggen, Minke J Brinkman-Akker, Ilse D Jonkhof, Johannes A Langendijk, Stefan Both, Erik W Korevaar
- PMID
- 42733879
- DOI
- 10.1016/j.phro.2026.101067
Why clinicians should know about it
- Picked for Medical Physics (paper of the day, 15 September 2026).
Abstract
Quality assurance is required to ensure safe and reliable use of deep learning (DL)-based intensity modulated proton therapy (IMPT) planning for oropharyngeal cancer patients. This study presents a range of quality assurance measures applied during routine clinical use and include manual adjustments to DL-based plans, independent organ-of-interest dose guidance and multidisciplinary plan review. DL-based plans were clinically acceptable for all 78 patients and achieved 1.1 Gy (RBE) lower parotid dose than manual plans. The implemented quality assurance measures enabled safe routine clinical use of DL-based IMPT planning over 28-months.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.