Deep learning–assisted two-dimensional transperineal ultrasound for analyzing bladder neck motion in women with stress urinary incontinence

No universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensive assessment of stress urinary incontinence. Although bladder neck motion plays a major role in stress urinary incontinence, objective and visual methods to evaluate its impact on stress urinary incontinence remain lacking. To use a deep learning–based system to evaluate bladder neck motion using 2-dimensional transperineal ultrasound videos, exploring motion parameters for diagnosing and evaluating stress urinary incontinence. We hypothesized that bladder neck motion parameters are associated with stress urinary incontinence and are useful for stress urinary incontinence diagnosis and evaluation. This retrospective study including 217 women involved the following parameters: maximum and average speeds of bladder neck descent, β angle, urethral rotation angle, and duration of the Valsalva maneuver. The fitted curves were derived to visualize bladder neck motion trajectories. Comparative analyses were conducted to assess these parameters between stress urinary incontinence and control groups. Logistic regression and receiver operating characteristic curve analyses were employed to evaluate the diagnostic performance of each motion parameter and their combinations for stress urinary incontinence. Overall, 173 women were enrolled in this study (82, stress urinary incontinence group; 91, control group). No significant differences were observed in the maximum and average speeds of bladder neck descent and in the speed variance of bladder neck descent. The maximum and average speed of the β and urethral rotation angles were faster in the stress urinary incontinence group than in the control group (151.2 vs 109.0 mm/s, P=.001; 6.0 vs 3.1 mm/s, P