Automated Recognition and Measurement for Levator Hiatus in 3D Ultrasound: A Clinical Study in Postpartum Women.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Published Date: Nov 25, 2025

Abstract

OBJECTIVES: To evaluate the performance of a CNN-based (convolutional neural networks-based) AI software for automatic recognition and measurement of minimal levator hiatus in transperineal ultrasound volumes from postpartum women, and to assess its agreement with manual measurements in different functional states. METHODS: We conducted a retrospective analysis of 100 transperineal ultrasound volumes measured independently by two sonographers (one junior, one senior) using a SonoScape S60 ultrasound system. Manual measurements included anteroposterior diameter (AP), left-to-right diameter (LR), levator hiatus area (HA), which were assessed at rest, during maximum pelvic floor contraction maneuver, and during maximum Valsalva maneuver. The levator-urethra gap (LUG) was additionally measured during contraction. The same volumes were identified and measured using automated CNN-based software (Auto PF software, SonoScape). When automatic identification failed, manual slice adjustment was permitted before reattempting automated measurement. The automatic recognition rate was recorded in different functional states. Inter-rater reliability between manual and automated measurements was evaluated using intraclass correlation coefficient (ICC) and Bland-Altman analysis. RESULTS: The overall automatic recognition rate was 86.69%, varying by functional state: 94% at rest, 86.17% during contraction, 79.80% during Valsalva. Automated measurements showed good agreement with manual measurements for HA, AP and LR (ICC > 0.75), excellent agreement with the senior sonographer's measurement for HA, AP (ICC > 0.90). The senior sonographer's measurements demonstrated higher concordance with automated results. Furthermore, the agreement was poorest for LUG measurements. CONCLUSIONS: Automated software is feasible for the recognition and measurement of LH in postpartum women, which can reduce the inter-observer variability, standardize pelvic floor assessment and improve workflow efficiency. Our study supports the clinical utility of CNN-based AI ultrasound software, but optimization is needed for LUG measurements to enhance clinical applicability.

Authors

  • Fanhua Xu
    a College of Information Engineering , Xiangtan University , Xiangtan , China.
  • Qi Lin
    Shandong University, School of Mechanical, Electrical and Information Engineering, Weihai, 264209, China. Electronic address: [email protected].
  • Wei Zeng
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
  • Jinfeng Xu
    Department of Ultrasound, The Second Clinical Medical College，Jinan University, Guangdong, China.
  • Yujuan Zhang
    Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China.

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