Artificial Intelligence-Assisted Colonoscopy in Colorectal Cancer Screening in a General Hospital (Delta-AI)

January 20, 2025 updated by: Erik Francois, Chirec

Real-World Experience of Artificial Intelligence-Assisted Colonoscopy in Colorectal Cancer Screening in a General Hospital: a Single-Center Cohort Phase IV Study

Cancer can develop in the colon, or large bowel. Examination of the colon with a tube fitted with a camera is called a colonoscopy.

Colonoscopy allows detection of small growths in the colon, called "polyps". Polyps can often be removed during colonoscopy. Some of these polyps are called adenomas and can become cancer after several years.

A good colonoscopy aims to find and take out as many of these polyps as possible.

A quality indication of colonoscopy is the "adenoma detection rate" (ADR). It should be high, meaning many polyps are detected and taken out.

New artificial intelligence devices to assist colonoscopy seem to increase the ADR, and maybe help prevent cancer even better than normal colonoscopy.

The goal of this clinical trial is to compare the ADR when using standard colonoscopy to the ADR with artificial intelligence (AI)-assisted colonoscopy.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

The colon is a part of the bowel where colon cancer can develop.

It is possible to prevent colon cancer by doing a screening test called a colonoscopy.

The colonoscopy procedure allows detection of "polyps" which can often be removed during the procedure. Some of these polyps are called adenomas and can become cancer after several years.

A good colonoscopy aims to find and take out as many of these polyps as possible.

A quality indication of colonoscopy is the "adenoma detection rate" (ADR). It should be high, meaning many polyps are detected and taken out.

New artificial intelligence devices to assist colonoscopy seem to increase the ADR, and maybe help prevent cancer even better than normal colonoscopy.

The goal of this clinical trial is to compare the ADR when using standard colonoscopy to the ADR with artificial intelligence (AI)-assisted colonoscopy.

Patients who are scheduled to have screening colonoscopy and who agree to participate, and are aged 45 years or more, will be randomly assigned to receive either standard colonoscopy or AI-assisted colonoscopy.

The main objective of this study is the difference in the ADR between a conventional colonoscopy procedure and an AI-assisted colonoscopy procedure.

Secondary objectives will compare the 2 groups (conventional colonoscopy and AI-assisted colonoscopy) regarding polyp size, polyp quantity, polyp histology (laboratory analysis of the polyp that was taken out), polyp dysplasia grade (how close the polyp is to cancer), polyp location in the colon, endoscopist experience (older or younger doctor), time of day and colonoscopy preparation quality (how clean the bowel is).

With these results we can show that AI-assisted colonoscopy is useful or not to help better prevent colon cancer.

Study Type

Interventional

Enrollment (Estimated)

765

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Belgium
    • Brussels
      • Auderghem, Brussels, Belgium, 1160
        • Hopital Delta Chirec
        • Contact:
        • Contact:
          • Erik Francois, M.D.
        • Contact:
          • Philippe Langlet, M.D.

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion criteria:

  • Patient (woman or man) candidate for a screening colonoscopy - Age: 45 to 74 years included
  • Absence of inflammatory bowel disease
  • Absence of significant digestive symptoms indicating colonoscopy (i.e. screening is the only indication for the examination)
  • Patient able to understand the concept of the study and agreeing to participate

Exclusion criteria:

  • Patient outside the inclusion age
  • All exclusion criteria for a colonoscopy.
  • The indication for colonoscopy is not simple screening; for example, assessment of anemia, rectal bleeding, weight loss or abdominal pain.
  • Patient's refusal to participate, or patient's inability to understand the study concept
  • Any patient with major psychological or psychiatric disorders.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: CCP: conventional colonoscopy procedure
The conventional colonoscopy arm subjects will undergo a screening colonoscopy without assistance from artificial intelligence.
Other: conventional colonoscopy procedure
Study subjects in this interventional arm will undergo conventional colonoscopy.
Active Comparator: ACP: artificial intelligence-assisted colonoscopy procedure
The artificial intelligence-assisted colonoscopy arm subjects will undergo a screening colonoscopy with assistance from an artificial intelligence module.
Other: artificial intelligence-assisted colonoscopy procedure
Study subjects in this interventional arm will undergo colonoscopy done with a commercially-available module that uses artificial intelligence to highlight suspected polyps on the screen during colonoscopy. This module also attempts to characterize the detected polyp as adenomatous or not. The detection and characterization of polyps is in real time, during the procedure.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adenoma Detection Rate in Conventional versus Artificial Intelligence-Assisted Colonoscopy
Time Frame: 1 day
The main objective of this study is the difference in the detection rate of colorectal adenomas in individuals over 45 years old during colonoscopies for colon cancer screening between a conventional colonoscopy procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The difference in the detection rate of colorectal adenomas according to size by group (5 mm/6-9 mm/>10 mm) between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Time Frame: 1 day
Detection rate of diminutive, small, and large polyps will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas according to the number per group (n=1-2/n= 3-10/n >10) between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Time Frame: 1 day
The number of adenomas detected during the procedure will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas based on histology by group (hyperplastic/conventional adenomas/serrated adenomas/adenocarcinoma) between a conventional colonoscopic procedure (PCC) and a colonoscopy procedure with AI.
Time Frame: 1 month
Adenomas have different histologic types. After obtaining histology, the detection rate of the various histologic types will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 month
The difference in detection rate of colorectal adenomas based on dysplastic grade by group
Time Frame: 1 day

The difference in detection rate of colorectal adenomas based on dysplastic grade

by group (conventional or serrated adenomas/low-grade dysplasia/high-grade dysplasia/adenocarcinoma) or Narrow Band Imaging International Colorectal Endoscopic (NICE) (stages 1, 2 or 3) classification or Japan Narrow Band Imaging Expert Team (JNET) classification (stages 1, 2A and 2B, or 3) between a conventional colonoscopy procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas depending on the location by group (rectum/left colon/transverse colon/right colon) between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Time Frame: 1 day
Location of adenomas will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas according to experience by group of colonoscopists
Time Frame: 1 day
The difference in the detection rate of colorectal adenomas according to experience by group (Colonoscopists aged 45-55 years/56-65 years/>66 years) between a conventional colonoscopic procedure (CCP) and a conventional colonoscopic procedure (CCP) colonoscopy with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas depending on the time of day .
Time Frame: 1 day
The difference in the detection rate of colorectal adenomas depending on the time of day (before 11:00/between 11:00 and 15:00/after 15:00) and the number of colonoscopies (Colonoscopy from 1 to 6 per half-day) per group (hyperplastic/conventional adenomas/scalloped adenomas/adenocarcinoma) between a conventional colonoscopic procedure (PCC) and a colonoscopy procedure with AI (ACP).
1 day
The difference in the detection rate of colorectal adenomas according to colonic preparation by group (Boston Score 9/6-8/<6) between a conventional colonoscopic procedure (PCC) and a colonoscopy procedure with AI (ACP).
Time Frame: 1 day
The difference in the adenoma detection rate according to the quality of colonic preparation will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
1 day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chirec

Investigators

  • Study Chair: Denis Franchimont, M.D., PhD, CHIREC

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

February 1, 2025

Primary Completion (Estimated)

December 31, 2026

Study Completion (Estimated)

June 1, 2027

Study Registration Dates

First Submitted

January 12, 2025

First Submitted That Met QC Criteria

January 20, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

January 20, 2025

Last Verified

January 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2024 Chirec Delta Colo-AI

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Individual Participant Data will include anonymized demographic information, clinical outcomes, laboratory results, and recorded adverse events.

Access to the data will be available to qualified researchers, with requests submitted by contacting one of the investigators.

The investigators will employ strict data protection measures, ensuring all shared data is de-identified and in compliance with applicable data protection laws. Access to the individual participant data will be contingent on the signing of a data sharing agreement that outlines the intended use of the data and adherence to ethical guidelines.

IPD Sharing Time Frame

The investigators anticipate that data will be available within six months after the completion of the trial and publication of the primary findings, and for a period of one year thereafter.

IPD Sharing Access Criteria

Access to the data will be available to qualified researchers, with requests submitted by contacting one of the investigators.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ICF
  • CSR

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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