AI in GIM Diagnosis | NCT04358198

Studies
AI in GIM Diagnosis

NCT04358198

Sponsor

King Chulalongkorn Memorial Hospital

Status

Unknown status

Last Update Posted

Mar 31, 2022Actual

Enrollment

120Estimated

Phase

Not Applicable

Conditions

GIM Diagnosis
Artificial Intellegence

Interventions

Artificial intelligence

Countries

Thailand

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Mar 2022

Overall Recruitment Status or Expanded Access Status

Unknown status

Last Known Status

Recruiting

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

May 1, 2020Actual

Primary Completion Date

Nov 30, 2023Estimated

Completion Date

Feb 28, 2024Estimated

First Submitted Date

Apr 12, 2020

First Submission Date that Met QC Criteria

Apr 21, 2020

First Posted Date

Apr 24, 2020Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Mar 28, 2022

Last Update Posted Date

Mar 31, 2022Actual

Sponsor/Collaborators Module

Responsible Party, by Official Title

Rapat Pittayanon, Principle investigator, King Chulalongkorn Memorial HospitalPrincipal Investigator

Lead Sponsor

King Chulalongkorn Memorial HospitalOTHER

Collaborators

Not provided

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

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

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.

Design Module

Study Type

Interventional

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Not provided

Target Follow-Up Duration

Not provided

Phases

Not Applicable

Interventional Study Design

Allocation

Biospecimen

No data available

No data is available for this block.

Enrollment

120Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
GIM patient	Experimental	The patients with GIM will be assessed at both GIM and normal mucosa during endoscopy.	Diagnostic Test: Artificial intelligence

Interventions

Name	Type	Description	Arm Group Labels	Other Names
Artificial intelligence	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.

Outcomes Module

Primary Outcomes

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

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

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

Exclusion Criteria:

History of gastric surgery
Coagulopathy
Pregnancy/Breast feeding

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

Not provided

Sampling Method

Not provided

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Rapat Pittayanon, MD	Contact	66804224999		rapat125@gmail.com

Overall Officials

Not provided

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Rapat Pittayanon	Recruiting	Pathum Wan	Bangkok	10330	Thailand

Intervention Browse Module

MeSH Terms

ID	Term
D001185	Artificial Intelligence

Ancestor Terms

ID	Term
D000465	Algorithms
D055641	Mathematical Concepts

Browse Leaves

Not provided

Browse Branches

Not provided

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 standard