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Validation the Artificial Intelligence System for Automatic Evaluation of the Extent of Intestinal Metaplasia

NCT ID: NCT05464108

Last Updated: 2024-12-03

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

COMPLETED

Total Enrollment

1080 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-07-01

Study Completion Date

2023-12-30

Brief Summary

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The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. But its clinical application is limited for at least biopsy samples. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. The investigators designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.

Detailed Description

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Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. An EGGIM score of 5 was the best cut off value for identifying OLGIM stage III/IV patients. The investigators have designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.

Conditions

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Intestinal Metaplasia of Gastric Mucosa Artificial Intelligence Endoscopy

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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Gastric intestinal metaplasia observed by IEE

Get pictures from gastric antrum body and angle by image-enhanced endoscopy in order to calculate the EGGIM score.

The diagnosis of Artificial Intelligence and endosopists

Intervention Type DIAGNOSTIC_TEST

Endosopists and AI will assess the EGGIM score independently when the patients is eligible. In addition, they can not see the OLGIM score of the patients.

Interventions

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The diagnosis of Artificial Intelligence and endosopists

Endosopists and AI will assess the EGGIM score independently when the patients is eligible. In addition, they can not see the OLGIM score of the patients.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* patients aged 40-75 years who undergo the IEE examination

Exclusion Criteria

* patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric
* disorders who cannot participate in gastroscopy
* patients with previous surgical procedures on the stomach
* patients with contraindications to biopsy
* patients who refuse to sign the informed consent form
Minimum Eligible Age

40 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Shandong University

OTHER

Sponsor Role lead

Responsible Party

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Yanqing Li

Vice President of Qilu Hospital

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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yanqing Li, MD, PHD

Role: STUDY_CHAIR

Qilu Hospital, Shandong University

Locations

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Department of Gastrology, QiLu Hospital, Shandong University

Jinan, Shandong, China

Site Status

Countries

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China

Other Identifiers

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2022SDU-QILU-111

Identifier Type: -

Identifier Source: org_study_id