Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence

Shandong University

Status: Unknown

Conditions: Artificial Intelligence; Confocal Laser Endomicroscopy; Ulcerative Colitis

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

Study type: Observational

Funder types: Other

Identifiers

NCT04131530

2019SDU-QILU-10

Details and patient eligibility

About

Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables to evaluate the inflammation activity of ulcerative colitis with excellent correlation with histopathology. 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: 60 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• aged between 18 and 80; diagnosed as UC

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

60 participants in 1 patient group

Colon mucosa observed by pCLE

Description:

pCLE is used to evaluate the inflammation activity in different parts of the colon mucosa

Treatment:

Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist