Automatic Classification of Colorectal Polyps Using Probe-based Endomicroscopy With Artificial Intelligence

Shandong University

Status: Unknown

Conditions: Artificial Intelligence; Colorectal Polyps; Probe-based Confocal Laser Endomicroscopy

Treatments: Other: AI presentation

Study type: Interventional

Funder types: Other

Identifiers

NCT03787784

2018SDU-QILU-8

Details and patient eligibility

About

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.

Enrollment: 200 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: Accepts 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

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

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200 participants in 2 patient groups

AI visible group

Experimental group

Treatment:

Other: AI presentation

AI invisible group

No Intervention group