AI in GIM Diagnosis

Artificial Intellegence Clinical Trial

Official title:

Usefulness of Artificial Intelligence (AI) for Gastric Intestinal Metaplasia Diagnosis

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04358198
• Other study ID #: RP018
• Status: Recruiting
• Phase: N/A
• Start date: May 1, 2020
• Est. completion date: February 28, 2024

Study information

• Verified date: March 2022
• Source: King Chulalongkorn Memorial Hospital
• Contact: Rapat Pittayanon, MD
• Phone: 66804224999
• Email: rapat125[@]gmail.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This study will use artificial intelligence (AI) for diagnosing gastric intestinal metaplasia.

Description:

The patients with previously diagnose gastric intestinal metaplasia (GIM) and have the surveillance gastroscopy will be enrolled. The routine surveillance program will be performed additional to taking photo at both GIM and normal mucosa at least 5 pictures in each. Biopsy will be done to confirm the diagnosis of GIM and normal mucosa. All pictures will be inserted to AI algorithm based on the convolutional neural network (CNN). Then, the AI program will be validated in daily endoscopy compared with pathology. Accuracy, sensitivity and specificity can be calculated by 2x2 table.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 120
• Est. completion date: February 28, 2024
• Est. primary completion date: November 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• More than 18 years of age

• Able to sign a consent form

Exclusion Criteria:

• History of gastric surgery

• Coagulopathy

• Pregnancy/Breast feeding

Related Conditions & MeSH terms

• Artificial Intellegence
• GIM Diagnosis

Intervention

Diagnostic Test:
• Artificial intelligence
The AI algorithm based on the convolutional neural network (CNN) will be used for analysis the pictures of gastric intestinal metaplasia and normal mucosa. Then AI will be used as a diagnostic tool for GIM during routine endoscopy by using pathology as a gold standard.

Locations

Country	Name	City	State
Thailand	Rapat Pittayanon	Pathum Wan	Bangkok

Sponsors (1)

Lead Sponsor	Collaborator
King Chulalongkorn Memorial Hospital

Country where clinical trial is conducted

Thailand, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of AI for GIM diagnosis	Accuracy, sensitivity, specificity can be calculated by 2x2 table (pathology is a gold standard)	1 year