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

Adenomatous Polyps Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04586556
• Other study ID #: 20.198
• Status: Completed
• Phase: N/A
• Start date: December 18, 2020
• Est. completion date: May 11, 2022

Study information

• Verified date: November 2022
• Source: Centre hospitalier de l'Université de Montréal (CHUM)
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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).

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);

Recruitment information / eligibility

• Status: Completed
• Enrollment: 372
• Est. completion date: May 11, 2022
• Est. primary completion date: March 31, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 45 Years to 80 Years

Eligibility

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

Related Conditions & MeSH terms

• Adenomatous Polyps
• Polyps

Intervention

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

Locations

Country	Name	City	State
Canada	Centre Hospitalier Universitaire de Montréal	Montréal	Quebec
Canada	Université de Montréal	Montréal	Quebec
France	IHU Strasbourg	Strasbourg

Sponsors (1)

Lead Sponsor	Collaborator
Centre hospitalier de l'Université de Montréal (CHUM)

Countries where clinical trial is conducted

Canada,  France, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Number of polyps detected	Efficacy of AI assisted colonoscopy to detect the proportion of patients with at least 1 polyp. Polyp detection rate with an AI.	Day 1
Primary	Evaluation of the automatic report of the colonoscopy quality indicators	Compare of the automatic detection of the ileocecal valve, appendiceal orifice, and the automatic calculation of the withdrawal time with manual detection	Day 1