NCT04586556

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 372 (actual)
• Sponsor: Centre hospitalier de l'Université de Montréal (CHUM) · Academic / Other
• Sex: All
• Age: 45 Years – 80 Years
• Healthy volunteers: Not accepted

Summary

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).

Detailed description

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);

Conditions

• Adenomatous Polyps

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Polyps detection by Artificial Intelligence	The AI system will capture the live video of the procedure and the AI feedback (polyp detection, tracking, and pathology prediction) will be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp or the information to predict pathology

Timeline

• Start date: 2020-12-18
• Primary completion: 2022-03-31
• Completion: 2022-05-11
• First posted: 2020-10-14
• Last updated: 2022-11-25

Locations

3 sites across 2 countries: Canada, France