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

• Sponsor: Shandong University (Other)
• Overall Status: Unknown status
• CT.gov ID: NCT04131530
• Collaborator: (none)
• Enrollment: 60
• Location: 1
• Anticipated Duration (Months): 2
• Patients Per Site Per Month: 29.9

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Ulcerative Colitis; Artificial Intelligence; Confocal Laser Endomicroscopy	Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist

Study Design

• Study Type: Observational
• Anticipated Enrollment: 60 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Official Title: Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
• Anticipated Study Start Date: Oct 1, 2019
• Anticipated Primary Completion Date: Dec 1, 2019
• Anticipated Study Completion Date: Dec 1, 2019

Arms and Interventions

Arm	Intervention/Treatment
Colon mucosa observed by pCLE pCLE is used to evaluate the inflammation activity in different parts of the colon mucosa	Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist; When the colon mucosa 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

Primary Outcome Measures

1. The diagnosis efficiency of Artificial Intelligence [3 months]

   The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for evaluation of inflammation activity of UC on pCLE examination.

Secondary Outcome Measures

1. Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists [3 months]

   The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV ) between Artificial Intelligence and endoscopists.

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years to 80 Years
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Department of Gastroenterology, Qilu Hospital, Shandong University	Jinan	Shandong	China	250012

Sponsors and Collaborators

• Shandong University

Investigators

• Principal Investigator: Yanqing Li, Qilu Hospital, Shandong University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Yanqing Li, Vice president of QiLu Hospital, Shandong University
• ClinicalTrials.gov Identifier: NCT04131530
• Other Study ID Numbers: 2019SDU-QILU-10
• First Posted: Oct 18, 2019
• Last Update Posted: Oct 18, 2019
• Last Verified: Oct 1, 2019

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Additional relevant MeSH terms: Colitis; Colitis, Ulcerative; Inflammation; Ulcer

Study Results

No Results Posted as of Oct 18, 2019