AI-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis

Study Overview
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Brief Summary
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Grading endoscopic atrophy according to the Kimura-Takemoto classification can assess the risk of gastric neoplasia development. However, the false negative rate of chronic atrophic gastritis is high due to the varying diagnostic standardization and diagnostic experience and levels of endoscopists. Therefore, this study aims to develop an AI model to identify the Kimura-Takemoto classification.

Detailed Description
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Grading endoscopic atrophy according to the Kimura-Takemoto classification can assess the risk of gastric neoplasia development. The higher the score, the more severe the degree of atrophic gastritis. However, the false negative rate of chronic atrophic gastritis is high due to the varying diagnostic standardization and diagnostic experience and levels of endoscopists. Therefore, this study aims to develop an AI model to identify the Kimura-Takemoto classification of atrophic gastritis to achieve gastric cancer risk assessment.

Official Title
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Artificial Intelligence-assisted White Light Endoscopy to Identify the Kimura-Takemoto Classification of Atrophic Gastritis to Achieve Gastric Cancer Risk Assessment

Conditions
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Atrophic Gastritis, Artificial Intelligence, Endoscopy

Intervention / Treatment
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* Diagnostic Test: Diagnostic Test: The diagnosis of Artificial Intelligence and endosopists


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients aged 18-80 years who undergo the white light endoscope examination Informed consent form provided by the patient. Exclusion Criteria: patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric; disorders who cannot participate in gastroscopy; Patients with progressive gastric cancer; low quality pictures; patients with previous surgical procedures on the stomach or esophageal; patients who refuse to sign the informed consent form;

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Chronic atrophic gastritis observed by white light endoscope<br>Get pictures from gastric antrum,gastric angle,lesser curvature of gastric body, cardia, gastric fundus, greater curvature of gastric body by white light endoscope | Diagnostic Test: Diagnostic Test: The diagnosis of Artificial Intelligence and endosopists<br>* Endosopists and AI will assess the Kimura-Takemoto classification independently when the patients is eligible.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy of AI model to diagnose the Kimura-Takemoto classification | Accuracy of AI model to diagnose the Kimura-Takemoto classification | 2 years | 
| Sensitivity of AI model to diagnose the Kimura-Takemoto classification | Sensitivity of AI model to diagnose the Kimura-Takemoto classification | 2 years | 
| Specificity of AI model to diagnose the Kimura-Takemoto classification | Specificity of AI model to diagnose the Kimura-Takemoto classification | 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The MIOU value of AI model in semantic segmentation of endoscopic atrophy picture | The MIOU value of AI model in semantic segmentation of endoscopic atrophy picture | 2 years |