NCT07257796

Artificial Intelligence in Assessing Gastric Intestinal Metaplasia Via the EGGIM Score

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 3,000 (estimated)
• Sponsor: Qilu Hospital of Shandong University · Academic / Other
• Sex: All
• Age: 40 Years – 75 Years
• Healthy volunteers: —

Summary

The endoscopic grading system (EGGIM) has been widely used to assess the extent of gastric intestinal metaplasia during endoscopy. Investigators developed an artificial intelligence (AI) system to automatically evaluate the extent of gastric intestinal metaplasia (GIM) and calculate the EGGIM scores in endoscopy examination. This study is a prospective, multi-center study aimed at exploring the performance and reliability of AI-EGGIM scoring. This is a prospective study designed to validate the AI-EGGIM system in a larger cohort. The study protocol was developed based on preliminary experience from a prior investigation (NCT05464108).

Detailed description

Gastric intestinal metaplasia (GIM) is an important precancerous stage in the gastric carcinogenesis cascade. The endoscopic grading system (EGGIM) has been proposed as a practical method to evaluate the extent of GIM during endoscopy. Investigators developed an artificial intelligence (AI) system to automatically assess the extent of GIM and calculate EGGIM scores from endoscopic examinations. This study is a prospective, multi-center study aimed at evaluating the accuracy, performance, and reliability of AI-assisted EGGIM scoring.

Conditions

• Intestinal Metaplasia of Gastric Mucosa
• Artificial Intelligence
• Endoscopy

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	The diagnostic performance of AI system and endoscopists	Eligible patients will undergo independent EGGIM score assessment by both endoscopists and the AI system.

Timeline

• Start date: 2025-11-01
• Primary completion: 2027-05-31
• Completion: 2027-12-31
• First posted: 2025-12-02
• Last updated: 2025-12-02

Locations

3 sites across 1 country: China