Efficacy of an AI System in Training Endoscopists to Assess Gastric Intestinal Metaplasia Via the EGGIM Score

Condition(s) studied

Investigational drug(s) / intervention(s)

AI-assisted EGGIM scoring: Endoscopists will evaluate the videos with the assistance of the AI system via EGGIM score.

Conventional EGGIM scoring: Endoscopists will evaluate the videos without the assistance of the AI system via EGGIM score.

Study summary

This prospective randomized controlled trial with a crossover design incorporated image-enhanced endoscopy (IEE) videos demonstrating complete standardized examinations of five standard gastric areas (antrum greater curvature, antrum lesser curvature, incisura, corpus lesser curvature, and corpus greater curvature). Endoscopists were stratified by experience level and randomly assigned to either the AI-assisted scoring first group, which performed EGGIM scoring with AI assistance in the initial phase followed by conventional scoring after a washout period, or the conventional scoring first group, which completed the assessments in reverse order. The study primarily evaluated the training efficacy of the EGGIM-AI system for improving endoscopists' EGGIM scoring performance by comparing diagnostic accuracy metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity between groups at different study phases.

Eligibility

Primary outcome measure(s)

• Efficacy of the EGGIM-AI system for improving endoscopists' EGGIM scoring performance — Through study completion, an average of 3 months
  Diagnostic accuracy metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity between groups at different study phases.

Trial sites (1)

More Qilu Hospital of Shandong University trials in China

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