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

NCT04586556 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 372

Last updated 2022-11-25

No results posted yet for this study

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).

Conditions

  • Adenomatous Polyps

Interventions

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

Sponsors & Collaborators

  • Centre hospitalier de l'Université de Montréal (CHUM)

    lead OTHER

Principal Investigators

  • Daniel von Renteln · Centre hospitalier de l'Université de Montréal (CHUM)

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
45 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-12-18
Primary Completion
2022-03-31
Completion
2022-05-11

Countries

  • Canada
  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04586556 on ClinicalTrials.gov