Effect of a Computer-Aided Device for Detecting Gastric Neoplasms: A Multicenter, Randomized Controlled Trial

Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lacking. We aimed to explore whether AI can enhance gastric neoplasm detection.

Participants from 24 hospitals in China from December 21, 2021, to November 11, 2023, were randomized to AI-assisted or nonassisted esophagogastroduodenoscopy. Primary outcome was detection rate of gastric neoplasms after pathologic review. Secondary outcomes included detection rate of gastric neoplasms before review, relative early gastric cancer detection ratio, detection rate of intestinal metaplasia and/or gastric atrophy before or after review, biopsy rate, number of blind spots, and procedure/inspection time. We did intention-to-treat (ITT), per-protocol, and exploratory subgroup analysis.

In the ITT cohort, 29,514 patients were enrolled. AI did not improve detection rate of gastric neoplasm after pathological review (RR, 1.13; 0.92-1.38; 1.42 vs 1.25%; P = .25). However, based on original pathology, an improvement with AI was observed (RR, 1.14; 1.0-1.28; 4.06 vs 3.57%; P = .03). AI reduced blind spots number from 2.52 to 1.07 (P < .001) and prolonged procedure and inspection time. No significant differences were observed for relative early gastric cancer detection ratio or detection rate of intestinal metaplasia and/or gastric atrophy before/after pathologic review in ITT cohort. Subgroup analysis suggested potential benefit among less experienced endoscopists and during fatigue periods. In the experimental group, AI diagnosed 100%, 91.9%, and 57.1% of pathologically confirmed gastric adenocarcinoma, high-grade, and low-grade intraepithelial neoplasia, respectively.

AI did not improve the detection rate of gastric neoplasms. Further real-world studies are needed to fully address the adaptability of AI. (Chinese Clinical Trial Registry, ChiCTR2100054449.).