Real-time AI assistance improves adherence to standardized biliopancreatic EUS examination: a real-world comparative study.
Authors
Affiliations (5)
Affiliations (5)
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P. R. China.
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, Hubei 430060, P. R. China.
- Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, Hubei 430060, P. R. China.
Abstract
Biliopancreatic endoscopic ultrasound (EUS) is highly operator-dependent, and adherence to standardized examination pathways may vary in routine practice. Evidence on whether real-time artificial intelligence (AI) assistance improves adherence to standardized biliopancreatic EUS examination in real-world settings remains limited. We conducted a retrospective comparative cohort study at a tertiary referral center to evaluate the real-world implementation of a real-time AI assistance system during biliopancreatic EUS. Examinations from the pre-AI period were compared with those from the post-AI period after a washout interval. Propensity score matching and interrupted time-series analysis were used to reduce baseline imbalance and assess temporal changes. The primary outcome was adherence to the standardized examination protocol, operationalized as total documentation completeness across eight predefined anatomical stations. Secondary outcomes included station-level adherence and lesion detection, with prespecified evaluation of pancreatic masses smaller than 2 cm. Among 1,465 eligible examinations, 854 matched examinations (427 per group) were analyzed. Adherence to the standardized eight-station examination was higher in the post-AI group, reflected by greater total documentation completeness (89.93% vs 81.29%, adjusted absolute difference 8.65%, 95% confidence interval [CI] 6.58-10.71, <i>P </i>< 0.001). Detection of pancreatic masses smaller than 2 cm was also higher after AI implementation (11.48% vs 6.56%, adjusted odds ratio 1.82, 95% CI 1.13-3.01, <i>P </i>= 0.016). In this real-world comparative study, real-time AI assistance was associated with greater adherence to a standardized biliopancreatic EUS examination protocol and a higher observed detection rate of pancreatic masses smaller than 2 cm. These findings suggest that real-time AI assistance may facilitate more standardized biliopancreatic EUS examination in routine practice.