Try the modernized ClinicalTrials.gov beta website. Learn more about the modernization effort.
Working…
ClinicalTrials.gov
ClinicalTrials.gov Menu

Automatic Real-time Diagnosis of Gastric Mucosal Disease Using pCLE With Artificial Intelligence

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT03784209
Recruitment Status : Recruiting
First Posted : December 21, 2018
Last Update Posted : July 20, 2021
Sponsor:
Information provided by (Responsible Party):
Yanqing Li, Shandong University

Study Description
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information
Brief Summary:
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastric mucosal disease during ongoing endoscopy examination. However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.

Condition or disease Intervention/treatment
Gastric Diseases Artificial Intelligence Confocal Laser Endomicroscopy Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist

Study Design
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information

Layout table for study information
Study Type : Observational
Estimated Enrollment : 928 participants
Observational Model: Other
Time Perspective: Prospective
Official Title: Automatic Real-time Diagnosis of Gastric Mucosal Disease Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
Actual Study Start Date : July 1, 2018
Estimated Primary Completion Date : August 2021
Estimated Study Completion Date : August 2021
Groups and Cohorts
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information

Group/Cohort Intervention/treatment
lesions observed by pCLE
pCLE is used to distinguish the suspected lesions detected by white light endoscopy.
 Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist
When suspected lesion is observed using pCLE, endoscopist and AI will make a diagnosis independently. In addition, the endoscopist can not see the diagnosis of AI.


Outcome Measures
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information

Primary Outcome Measures :
  1. The diagnosis efficiency of Artificial Intelligence [ Time Frame: 20 months ]
    The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing gastric mucosal disease on real-time pCLE examination.


Secondary Outcome Measures :
  1. Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists [ Time Frame: 20 months ]
    The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing gastric mucosal disease on real-time pCLE examination) between Artificial Intelligence and endoscopists.


Biospecimen Retention:   Samples With DNA
When a gastric mucosal lesion is found using white light endoscopy , endoscopist will observe this lesion using pCLE and then take biopsy for histology examination.

Eligibility Criteria
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


Layout table for eligibility information
Ages Eligible for Study:   18 Years to 80 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Consecutive patients who receive the upper gastrointestinal tract pCLE examination and screened that fulfill the eligibility criteria at Qilu Hospital, Shandong University will be enrolled into the study
Criteria

Inclusion Criteria:

  • aged between 18 and 80;
  • agree to give written informed consent.

Exclusion Criteria:

  • Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium;
  • Inability to provide informed consent
Contacts and Locations
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03784209


Contacts
Layout table for location contacts
Contact: Yanqing Li 053182169385 liyanqing@sdu.edu.cn

Locations
Layout table for location information
China, Shandong
Endoscopic unit of Qilu Hospital Shandong University Recruiting
Jinan, Shandong, China, 250001
Contact: Yanqing Li, PhD,MD    053182169385    liyanqing@sdu.edu.cn   
Sponsors and Collaborators
Shandong University
Investigators
Layout table for investigator information
Principal Investigator: Yanqing Li Qilu Hospital, Shandong University
More Information
Go to 
Top of Page Study Description Study Design Groups and Cohorts Outcome Measures Eligibility Criteria Contacts and Locations More Information
Layout table for additonal information
Responsible Party: Yanqing Li, Vice president of QiLu Hospital, Shandong University
ClinicalTrials.gov Identifier: NCT03784209    
Other Study ID Numbers: 2018SDU-QILU-12
First Posted: December 21, 2018    Key Record Dates
Last Update Posted: July 20, 2021
Last Verified: July 2021

Layout table for additional information
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Additional relevant MeSH terms:
Layout table for MeSH terms
Stomach Diseases
Gastrointestinal Diseases
Digestive System Diseases