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

Shandong University

Status: Completed

Conditions: Artificial Intelligence; Confocal Laser Endomicroscopy; Gastric Diseases

Treatments: Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist

Study type: Observational

Funder types: Other

Identifiers

NCT03784209

2018SDU-QILU-12

Details and patient eligibility

About

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.

Enrollment: 951 patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

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

Trial design

951 participants in 1 patient group

lesions observed by pCLE

Description:

pCLE is used to distinguish the suspected lesions detected by white light endoscopy.

Treatment:

Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist