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An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Hongjie Zhu·Xin Geng·Huayuan Zhou·Wei Guo·Yin Dai·Hao Zhang·Meng Dong·Hong Li·Xinlu Wang
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Abstract

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n = 688) and an independent prospective test cohort (n = 193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' κ of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7 s to 9.9 s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

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HumansDecision Support Systems, ClinicalUltrasonographyCystoceleFemaleProspective StudiesRetrospective StudiesArtificial IntelligenceMaleAdultMiddle AgedArtificial intelligenceClinical decision support systemDynamic transperineal ultrasoundGreen classificationReader studyJournal Article

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Hongjie Zhu, Xin Geng, Huayuan Zhou, Wei Guo, Yin Dai, Hao Zhang, Meng Dong, Hong Li, Xinlu Wang. 2026-09-01. An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.. https://doi.org/10.1007/s10916-026-02453-7

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