AI in GIM Diagnosis

• Sponsor: King Chulalongkorn Memorial Hospital (Other)
• Overall Status: Recruiting
• CT.gov ID: NCT04358198
• Collaborator: (none)
• Enrollment: 120
• Location: 1
• Arm: 1
• Anticipated Duration (Months): 45.9
• Patients Per Site Per Month: 2.6

Study Details

Study Description

Brief Summary

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

Condition or Disease	Intervention/Treatment	Phase
GIM Diagnosis; Artificial Intellegence	Diagnostic Test: Artificial intelligence	N/A

Detailed 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.

Study Design

• Study Type: Interventional
• Anticipated Enrollment: 120 participants
• Allocation: N/A
• Intervention Model: Single Group Assignment
• Intervention Model Description: The surveillance EGD in patients with GIM will be done as scheduled and then pictures at GIM lesions and normal mucosa was done and sending to AI for learning. Then AI will be used for diagnosing GIM by using pathology as a gold standardThe surveillance EGD in patients with GIM will be done as scheduled and then pictures at GIM lesions and normal mucosa was done and sending to AI for learning. Then AI will be used for diagnosing GIM by using pathology as a gold standard
• Masking: None (Open Label)
• Primary Purpose: Diagnostic
• Official Title: Usefulness of Artificial Intelligence (AI) for Gastric Intestinal Metaplasia Diagnosis
• Actual Study Start Date: May 1, 2020
• Anticipated Primary Completion Date: Nov 30, 2023
• Anticipated Study Completion Date: Feb 28, 2024

Arms and Interventions

Arm	Intervention/Treatment
Experimental: GIM patient The patients with GIM will be assessed at both GIM and normal mucosa during endoscopy.	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.

Outcome Measures

Primary Outcome Measures

1. Accuracy of AI for GIM diagnosis [1 year]

   Accuracy, sensitivity, specificity can be calculated by 2x2 table (pathology is a gold standard)

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years and Older
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Inclusion Criteria:

• More than 18 years of age

• Able to sign a consent form

Exclusion Criteria:

• History of gastric surgery

• Coagulopathy

• Pregnancy/Breast feeding

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Rapat Pittayanon	Pathum Wan	Bangkok	Thailand	10330

Sponsors and Collaborators

• King Chulalongkorn Memorial Hospital

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Rapat Pittayanon, Principle investigator, King Chulalongkorn Memorial Hospital
• ClinicalTrials.gov Identifier: NCT04358198
• Other Study ID Numbers: RP018
• First Posted: Apr 24, 2020
• Last Update Posted: Mar 31, 2022
• Last Verified: Mar 1, 2022

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Additional relevant MeSH terms: Disease

Study Results

No Results Posted as of Mar 31, 2022