ArticleRadiological physics and technology2026
Clinical edge-case stress testing of two Asia-developed AI auto-contouring systems using prostate radiotherapy planning CT images.
Article in Radiological physics and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Clinical evaluation of novel deep learning-based auto-segmentation software: Utility and potential pitfalls.Journal of applied clinical medical physics · 2026Article
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7 authors.
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Abstract
To compare the geometric accuracy of two Asia‑developed AI auto‑contouring systems (RatoGuide and OncoStudio) for prostate radiotherapy planning CT, including performance in clinical edge cases. Planning CT data from 45 patients were stratified into four groups (Normal, Spacer, Seed/Spacer, GM/Spacer). Manual contours of prostate, rectum, bladder, seminal vesicles, and femoral heads served as reference. Segmentation accuracy was assessed using DSC and 95% Hausdorff distance; Wilcoxon signed‑rank and Mann-Whitney U tests were applied, with edge‑case analyses treated as exploratory. Median DSC exceeded 0.7 for all structures. RatoGuide performed better for the rectum, whereas OncoStudio performed better for the bladder, seminal vesicles, and femoral heads. Outliers were concentrated in combined implant/spacer groups. Both tools showed generally favorable geometric agreement, with structure‑dependent advantages and edge‑case outliers that warrant workflow‑aware quality assurance and future dosimetric validation.
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