Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps

Artificial Intelligence for Real-time Detection and Monitoring of Colorectal Polyps

The investigators hypothesize that the clinical implementation of a deep learning AI system is an optimal tool to monitor, audit and improve the detection and classification of polyps and other anatomical landmarks during colonoscopy. The objectives of this study are to generate preliminary data to evaluate the effectiveness of AI-assisted colonoscopy on: a) the rate of detection of adenomas; b) the automatic detection of the anatomical landmarks (i.e., ileocecal valve and appendiceal orifice).

In this trial, the investigators aim to evaluate the followings:

1. the accuracy of automatic detection of important anatomical landmarks (i.e., ileocecal valve, appendiceal orifice);
2. the accuracy of automatic detection of polyps/adenomas (PDR/ADR);

Inclusion Criteria :

• Signed informed consent
• Age 45-80 years
• Indication to undergo a lower GI endoscopy.

Exclusion Criteria :

• Coagulopathy
• Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
• Emergency colonoscopies
• Hospitalized patients
• Known inflammatory bowel disease (IBD)
• Patients currently in the emergency room