ArticleJournal of applied clinical medical physics2026
Clinical validation of AI-assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance.
Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Artificial intelligence in radiation treatment planning: a narrative review from automation to clinical decision support.Translational cancer research · 2026Review
- Inter-observer variability in radiotherapy contouring with the use of autocontouring software: A systematic review.Clinical and translational radiation oncology · 2026Review
- AI-driven precision diagnosis and treatment of prostate cancer: a narrative review.Frontiers in oncology · 2026Review
- Clinical validation of AI-assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance.Journal of applied clinical medical physics · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study evaluated the impact of a commercial AI-assisted contouring tool on intra- and inter-observer variability in prostate radiation therapy and assessed the dosimetric consequences of geometric contour differences.
methodsTwo experienced radiation oncologists independently delineated clinical target volume (CTV) and organs at risk (OARs) for prostate cancer patients. Manual contours (C
resultsAI-assisted contouring significantly improved both intra- and inter-observer agreement. Inter-observer analysis revealed that the Dice similarity coefficient (DSCs) for CTV increased from 0.78 (± 0.11) for C
conclusionAI-assisted contouring in prostate radiotherapy reduced intra- and inter-observer variability and improved contouring consistency. However, C
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.