AI in GIM Diagnosis

NCT ID: NCT04358198

Last Updated: 2022-03-31

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

UNKNOWN

Clinical Phase

NA

Total Enrollment

120 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-05-01

Study Completion Date

2024-02-28

Brief Summary

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

Detailed Description

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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.

Conditions

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GIM Diagnosis Artificial Intellegence

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

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 standard
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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GIM patient

The patients with GIM will be assessed at both GIM and normal mucosa during endoscopy.

Group Type EXPERIMENTAL

Artificial intelligence

Intervention Type DIAGNOSTIC_TEST

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.

Interventions

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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.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* More than 18 years of age
* Able to sign a consent form

Exclusion Criteria

* History of gastric surgery
* Coagulopathy
* Pregnancy/Breast feeding
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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King Chulalongkorn Memorial Hospital

OTHER

Sponsor Role lead

Responsible Party

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Rapat Pittayanon

Principle investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Rapat Pittayanon

Pathum Wan, Bangkok, Thailand

Site Status RECRUITING

Countries

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Thailand

Central Contacts

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Rapat Pittayanon, MD

Role: CONTACT

66804224999

Facility Contacts

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Rapat Pittayanon

Role: primary

Other Identifiers

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RP018

Identifier Type: -

Identifier Source: org_study_id

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