Automated Ultrasound-Based Analysis of Urethral Kinematics in Stress Urinary Incontinence: A Pilot Study

Stress urinary incontinence (SUI) has been linked to excessive urethral mobility, yet clinical evaluation has been largely limited to assessing maximal excursion rather than capturing the full dynamics of visible urethral movement. In this study, we hypothesize that an automated, ultrasound-based method can objectively differentiate urethral mobility patterns between women with SUI and continent controls.

We used a previously validated optical flow-based algorithm to automatically track urethral motion from transperineal ultrasound images during cough, Valsalva maneuver, and pelvic muscle contraction (PMC) in 11 women with SUI and 10 continent controls. Urethral motion was assessed by defining three regions of interest along the urethra (proximal, mid, and distal). Segmental urethral kinematics were computed and statistically compared between groups.

Substantial variability and overlap between groups were observed, with coefficient of variation ranging 25%-90%. On average, women with SUI demonstrated significantly larger urethral displacement compared to controls, particularly at the proximal segment during Valsalva (10.6 ± 1.2 mm vs. 6.0 ± 0.6 mm, p < 0.01), with pronounced inferior-posterior motion. Additionally, displacement between the upper and lower urethra was significantly larger in the SUI group (0.47 ± 0.10 mm/mm vs. 0.13 ± 0.03 mm/mm, p < 0.05), indicating localized hypermobility particularly near the proximal urethra. Maneuver-specific differences were also noted within the SUI group, with Valsalva producing significantly larger and less uniform urethral movements compared to cough (10.6 ± 1.2 mm vs. 6.6 ± 0.5 mm, p < 0.05).

Our results demonstrate that the automated method is capable of capturing urethral mobility characteristics associated with SUI. Significant inter-individual variability in both continent and SUI groups indicates that urethral kinematics are heterogeneous. The detailed kinematic data have the potential to identify distinct sub-types of urethral mobility, facilitating systematic comparisons with underlying structural and neuromuscular defects. This approach can move clinical evaluation from simple group comparisons toward personalized SUI diagnosis and targeted treatment selection. Future studies with larger sample sizes and inclusion of additional pelvic floor conditions will be needed to validate these findings and advance their translation into clinical practice.