Automatic Classification of Colorectal Polyps Using Probe-based Endomicroscopy With Artificial Intelligence
Trial Snapshot
- Phase
- Not Applicable
- Sponsor
- Enrollment
- 200
- Locations
- 1
- Primary Endpoint
- The accuracy of classifying colorectal Polyps using Probe-based endomicroscopy with deep neural networks
Study Overview
Brief Summary
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastrointestinal mucosa during ongoing endoscopy examination. It can predict the classification of Colorectal Polyps accurately. However this requires much experience, which limits the application of pCLE. The investigators designed a computer program using deep neural networks to differentiate hyperplastic from neoplastic polyps automatically in pCLE examination.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Diagnostic
- Masking
- Triple (Participant, Investigator, Outcomes Assessor)
Eligibility Criteria
- Ages
- 18 Years to 80 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
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
Arms & Interventions
AI visible group
Intervention: AI presentation (Other)
AI invisible group
Outcomes
Primary Outcomes
The accuracy of classifying colorectal Polyps using Probe-based endomicroscopy with deep neural networks
Time Frame: 4 months
The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing Colorectal Polyps on real-time pCLE examination.
Secondary Outcomes
- Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists(3 month)
Investigators
Yanqing Li
Vice president of QiLu Hospital
Shandong University