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Development and Performance Validation of Artificial Intelligence-Assisted Image Analysis Software for the Diagnosis of Gastric Intestinal Metaplasia

Development and Performance Validation of Artificial Intelligence-Assisted Image Analysis Software for the Diagnosis of Gastric Intestinal Metaplasia - Development and Validation of an AI System for Diagnosing Gastric Intestinal Metaplasia

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
JPRN
Registry ID
JPRN-UMIN000059857
Enrollment
400
Registered
2025-12-01
Start date
2025-12-01
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

gastric intestinal metaplasia

Interventions

Two biopsies of the gastric mucosa for histopathological confirmation of intestinal metaplasia.

Sponsors

International University of Health and Welfare
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients aged 18 years or older. 2. Patients who meet either of the following conditions (i) or (ii): (i) Patients diagnosed with atrophic gastritis (AG) or intestinal metaplasia (IM) in previous endoscopic examinations. (ii) Patients currently infected with Helicobacter pylori or who have undergone eradication therapy in the past. 3. Patients from whom written informed consent for participation in this study has been obtained.

Exclusion criteria

Exclusion criteria: 1. Patients who are unable to discontinue antithrombotic medication. 2. Pregnant women or women who may be pregnant. 3. Others.

Design outcomes

Primary

MeasureTime frame
Diagnostic sensitivity of the developed AI for gastric intestinal metaplasia

Secondary

MeasureTime frame
1. Diagnostic specificity of gastric intestinal metaplasia (IM) by the developed AI 2. Diagnostic sensitivity and specificity of IM based on physicians' endoscopic diagnosis 3. Concordance rate of OLGA/OLGIM grading between the developed AI and histopathology 4. Concordance rate of OLGA/OLGIM grading between physicians' endoscopic diagnosis and histopathology 5. Diagnostic sensitivity and specificity of IM using the virtual chromoendoscopy program 6. Diagnostic accuracy of IM stratified by physicians' level of experience 7. Diagnostic accuracy of IM stratified by patient characteristics

Countries

Japan

Contacts

Public ContactSho Suzuki

International University of Health and Welfare, Ichikawa General Hospital Gastroenterology

s.sho.salubriter.mail@gmail.com047-322-0151

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026