Hendrickson, Chloe

Introduction: Dysfunction of pelvic floor muscles (PFMs) can limit physical activity and health. Current screening methods are invasive or expensive, although transabdominal ultrasound (TAUS) is gaining popularity. PFM contraction causes bladder base displacement (BBD) and magnitude reflects PFM function; however, manual image analysis is labor-intensive. Artificial intelligence (AI)–assisted TAUS may offer more efficient and feasible solutions. This study compared standard analysis of BBD to measurement with AI-assisted TAUS to assess reliability and validity. Methods: A total of 20 healthy female participants (26.4 ± 8.5 years) performed 6 repeated Kegel contractions after following a bladder-filling protocol. A curvilinear transducer was placed between the anterior superior iliac spines with the probe placed transversely and then angled inferiorly toward the bladder. The Clarius Bladder AI tool automatically measured distance from bladder apex to base. Images were also saved without an AI overlay and measured manually using ImageJ. Results: Average BBD values were equivalent (manual 0.7 ± 0.5 cm; AI-assisted 0.7 ± 0.6 cm, 90% confidence interval: −0.09 to 0.04 [ P < .05]). Measures were highly related ( r = 0.97, intraclass correlation coefficients [ICC 3,k ] = 0.98) and showed good agreement (95% limits of agreement: −0.33 to 0.28 cm). Test–retest reliability was excellent for both manual (ICC 3,k = 0.94, standard error of measurement [SEM]: 0.12 cm) and AI-assisted measures (ICC 3,k = 0.94, SEM = 0.14 cm). Discussion: No systematic differences were shown between methods, which were highly related. The Clarius AI-assisted bladder tool provided valid, reliable BBD measures consistent with traditional methods. The small SEM supports clinical application for PFM assessment. Conclusion: AI-assisted TAUS appears to be an efficient noninvasive method for assessing PFM function and may be applied easily in various clinical and research settings.