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Clinical Trial Summary

The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. But its clinical application is limited for at least biopsy samples. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. The investigators designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.


Clinical Trial Description

Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. An EGGIM score of 5 was the best cut off value for identifying OLGIM stage III/IV patients. The investigators have designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05464108
Study type Observational
Source Shandong University
Contact yanqing Li, MD, PHD
Phone 0531182169385
Email liyanqing@sdu.edu.cn
Status Recruiting
Phase
Start date July 1, 2022
Completion date December 30, 2023

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