Nomogram Analysis Based on Clinical and Sonographic Characteristics for the Assessment of Postpartum Stress Urinary Incontinence.

OBJECTIVES: We aimed to develop and validate a nomogram integrating clinical and sonographic characteristics for the individualized SUI risk evaluation in the early postpartum stage. METHODS: This was a prospective cross-sectional study. From June 2020 to September 2022, singleton primiparas who underwent TPUS examination at 6-8 weeks postpartum were recruited. They were divided into the training and validation cohorts at a ratio of 8:2 according to the temporal split. All subjects were interviewed before TPUS examination. Univariate and multivariate logistic analyses were performed to develop three models: the clinical, sonographic, and combined models. The ROC curve was plotted to evaluate model discrimination ability. Finally, the combined model was selected to establish the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were evaluated in the training and validation cohorts. RESULTS: The performance of the combined model was better than that of the clinical and sonographic models. Six predictors (BMI, delivery mode, lateral episiotomy, SUI during pregnancy, cystocele, and bladder neck funneling) remained in the combined model. The nomogram based on the combined model had good discrimination with AUCs of 0.848 (95% CI: 0.796-0.900) and 0.872 (95% CI: 0.789-0.955) in the training and validation cohorts, respectively, and the calibration curve showed good efficiency in assessing postpartum SUI. Decision curve analysis showed that the nomogram was clinically useful. CONCLUSIONS: The nomogram based on clinical and sonographic characteristics showed good efficiency in assessing postpartum SUI risk and can be a convenient and reliable tool for individual SUI risk assessment.

Locating Multiple Standard Planes in First-Trimester Ultrasound Videos via the Detection and Scoring of Key Anatomical Structures.

OBJECTIVE: This study was aimed at developing a first-trimester standard plane detection (FTSPD) system that can automatically locate nine standard planes in ultrasound videos and investigating its utility in clinical practice. METHODS: The FTSPD system, based on the YOLOv3 network, was developed to detect structures and evaluate the quality of plane images by using a pre-defined scoring system. A total of 220 videos from two different ultrasound scanners were collected to compare detection performance between our FTSPD system and sonographers with different levels of experience. The quality of the detected standard planes was quantitatively rated by an expert according to a scoring protocol. Kolmogorov-Smirnov analysis was used to compare the distributions of scores across all nine standard planes. RESULTS: The expert-rated scores indicated that the quality of the standard planes detected by the FTSPD system was on par with that of the planes detected by senior sonographers. There were no significant differences in the distributions of the scores across all nine standard planes. The FTSPD system performed significantly better than junior sonographers in five standard plane types. CONCLUSION: The results of this study suggest that our FTSPD system has significant potential for detecting standard planes in first-trimester ultrasound screening, which may help to improve the accuracy of fetal ultrasound screening and facilitate early diagnosis of abnormalities. The quality of the standard planes selected by junior sonographers can be significantly improved with the assistance of our FTSPD system.