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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05459610
Other study ID # 2022SDU-QILU-109
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date July 1, 2022
Est. completion date December 30, 2023

Study information

Verified date July 2022
Source Shandong University
Contact yanqing Li, MD, PHD
Phone 0531182169385
Email liyanqing@sdu.edu.cn
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, the high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.


Description:

Globally, gastric cancer is the fifth most prevalent malignancy and the third leading cause of cancer mortality. Gastric intestinal metaplasia (GIM) is an intermediate precancerous gastric lesion in the gastric cancer cascade. Studies have shown that the 5-year cumulative incidence of gastric cancer in IM patients ranges from 5.3% to 9.8% . With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, The high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.


Recruitment information / eligibility

Status Recruiting
Enrollment 600
Est. completion date December 30, 2023
Est. primary completion date December 30, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years to 80 Years
Eligibility Inclusion Criteria: - patients aged 18-80 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 who refuse to sign the informed consent form

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
China Department of Gastrology, QiLu Hospital, Shandong University Jinan Shandong

Sponsors (1)

Lead Sponsor Collaborator
Shandong University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary The specificity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture The specificity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture 2 years
Primary The accuracy of AI model to assess the degree of intestinal metaplasia in an endoscopic picture The accuracy of AI model to assess the degree of intestinal metaplasia in an endoscopic picture 2 years
Primary The sensitivity of AI model to assess the degree of intestinal metaplasia in an endoscopic picture The sensitivity of AI model to assess the degree of intestinal metaplasia in an 2 years
Secondary Accuracy of the experienced endoscopists to assess the degree of intestinal metaplasia Accuracy of the experienced endoscopists to assess the degree of intestinal metaplasia in an endoscopic picture 2 years
Secondary Accuracy of the inexperienced endoscopists to assess the degree of intestinal metaplasia Accuracy of the inexperienced endoscopists to assess the degree of intestinal metaplasia in an endoscopic picture 2 years
Secondary Inter-observer agreement among experienced endoscopists in identifying the degree of intestinal metaplasia Inter-observer agreement among experienced endoscopists in identifying the degree of intestinal metaplasia in an endoscopic picture 2 years
Secondary Inter-observer agreement among inexperienced endoscopists in identifying degree of intestinal metaplasia Inter-observer agreement among inexperienced endoscopists in identifying degree of intestinal metaplasia in an endoscopic picture 2 years
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