Artificial intelligence as a surrogate for inspection time to assess completeness in Esophagogastroduodenoscopy: a prospective, randomized, non-inferiority study.

Abstract

Introduction: The completeness of esophagogastroduodenoscopy (EGD) is a prerequisite for detecting lesions. This study aims to explore whether the quality of complete examinations assisted by artificial intelligence (AI) would be comparable to those conducted within the guideline-recommended inspection time.

Methods: Patients referred for diagnostic, screening, or surveillance EGD were enrolled at Renmin Hospital of Wuhan University. Patients were randomly assigned to two groups in a 1:1 ratio. In the AI-assisted group, endoscopists completed observation of the entire upper gastrointestinal (UGI) tract with AI assistance. In the control group, endoscopists were instructed to spend no less than 7 minutes (min) on each procedure. The primary outcome was the detection rate of neoplastic lesions. Non-inferiority was confirmed when the lower bound of the 95% confidence interval (CI) was greater than the margin of -1.5%.

Results: 1,723 patients were prospectively enrolled between July 3, 2023, and April 7, 2024. 796 and 763 patients in the AI-assisted and control groups were included in the final analysis, respectively. The detection rates of neoplastic lesions in the AI-assisted and control group were 3.14% and 2.36%, respectively, resulting in an absolute proportion difference of 0.78% (95%CI, -0.58%-2.14%; OR 1.342 [95%CI, 0.726-2.480]). The median inspection time was reduced by 1.5 min in the AI-assisted group (6.18[2.87] vs 7.70[1.90], P < 0.001).

Conclusions: Inspection time of complete EGD can be significantly shortened by AI without compromising its quality. These findings provide crucial evidence to support that AI-assisted procedural completeness serves as an objective and effective quality indicator for EGD.