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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

1500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-06-01

Study Completion Date

2024-12-31

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.

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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.

Conditions

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Atrophic Gastritis Artificial Intelligence Endoscopy

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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Chronic atrophic gastritis observed by white light endoscope

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: The diagnosis of Artificial Intelligence and endosopists

Intervention Type DIAGNOSTIC_TEST

Endosopists and AI will assess the Kimura-Takemoto classification independently when the patients is eligible.

Interventions

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Diagnostic Test: The diagnosis of Artificial Intelligence and endosopists

Endosopists and AI will assess the Kimura-Takemoto classification independently when the patients is eligible.

Intervention Type DIAGNOSTIC_TEST

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

1. patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric;
2. disorders who cannot participate in gastroscopy;
3. Patients with progressive gastric cancer;
4. low quality pictures;
5. patients with previous surgical procedures on the stomach or esophageal;
6. patients who refuse to sign the informed consent form;

Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No