An observational study in Intestinal Metaplasia of Gastric Mucosa, Artificial Intelligence and Endoscopy, sponsored by Qilu Hospital of Shandong University. Recruiting at 3 sites in China. Open to participants aged 40 Years to 75 Years. Per ClinicalTrials.gov, last updated 2025-12-02.
Sponsored by Qilu Hospital of Shandong University · Observational
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).
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.
Qilu Hospital of Shandong University is the lead sponsor of 299 studies on the registry; 181 are open to participants now.
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Consecutive patients who receive the gastrointestinal endoscopy examination and screened that fulfill the eligibility criteria will be enrolled into the study.
Exclusion Criteria:
Eligible patients will undergo independent EGGIM score assessment by both endoscopists and the AI system.
Performance of AI system to diagnose the grade of intestinal metaplasia by calculating the EGGIM score
The performance of the AI system will be evaluated in diagnosing the grade of gastric intestinal metaplasia (IM) based on the Endoscopic Grading of Gastric Intestinal Metaplasia (EGGIM) system. EGGIM is a validated scoring method ranging from 0 to 10, reflecting the extent of IM across five gastric regions: two in the antrum, two in the corpus, and one at the incisura. Each region is scored as 0 (no IM), 1 (focal IM, ≤30% of the area), or 2 (extensive IM, \>30% of the area), with a total possible score of 10. Higher EGGIM scores correspond to more severe IM and greater gastric cancer risk. The AI-derived scores will be compared with expert' EGGIM scores, which serve as the gold standard, to assess diagnostic accuracy.
Time frame: 1 year
Eligibility is decided by the study team. Share this record with your doctor or contact the team directly.
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Qilu Hospital of Shandong University