Clinical validation of AI‐assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance

AI-assisted contouring in prostate radiotherapy reduced intra- and inter-observer variability and improved contouring consistency. However, C<sub>AI, adj</sub> did not consistently surpass C<sub>man</sub>, especially for the CTV and rectum, where automation bias or selective clinical acceptance may have influenced edits. Fixed-plan recalculations revealed dose differences from minor geometric deviations. These findings underscore the importance of structured quality assurance (QA) and human oversight to mitigate automation bias while leveraging AI's efficiency. The single-institution design with two oncologists and one AI software limits generalizability, underscoring the need for multi-observer validation.

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Publication Details

Journal
Journal of Applied Clinical Medical Physics
Published
2025-12-19
DOI
https://doi.org/10.1002/acm2.70425
Citations
1
Primary Topic
Advanced Radiotherapy Techniques
Type
article
Field-Weighted Citation Impact
1.88
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article

Clinical validation of AI‐assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance

Ahmadreza Sebzari, Saeid Rezaei, Najmeh Arjmandi, Fatemeh Molaei et al.
1 citations
Journal of Applied Clinical Medical Physics
Advanced Radiotherapy Techniques
1.88
article

Clinical validation of AI‐assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance

Ahmadreza Sebzari, Saeid Rezaei, Najmeh Arjmandi, Fatemeh Molaei, Maryam Rezaie-Yazdi, Malihe Rezaie-Yazdi
article en
1 citations

Abstract

AI-assisted contouring in prostate radiotherapy reduced intra- and inter-observer variability and improved contouring consistency. However, C<sub>AI, adj</sub> did not consistently surpass C<sub>man</sub>, especially for the CTV and rectum, where automation bias or selective clinical acceptance may have influenced edits. Fixed-plan recalculations revealed dose differences from minor geometric deviations. These findings underscore the importance of structured quality assurance (QA) and human oversight to mitigate automation bias while leveraging AI's efficiency. The single-institution design with two oncologists and one AI software limits generalizability, underscoring the need for multi-observer validation.

Journal of Applied Clinical Medical PhysicsVol. 27(1)
Gerash University of Medical Sciences (IR), Tehran University of Medical Sciences (IR), Birjand University of Medical Sciences (IR)
Openalex Percentile: Top 11%
Advanced Radiotherapy Techniques
1.88
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