Clinical trial NCT06792292: Artificial Intelligence-Assisted Colonoscopy in Colorectal Cancer Screening in a General Hospital
Official title: Real-World Experience of Artificial Intelligence-Assisted Colonoscopy in Colorectal Cancer Screening in a General Hospital: A Single-Center Cohort Phase IV Study
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Artificial Intelligence
Colonic Adenoma
Colonic Neoplasms
Colonic Polyp
Colonoscopy
Keywords: colo-rectal cancer screening
artificial intelligence assisted colonoscopy
Lead sponsor: Chirec
Sponsor class: OTHER
First posted: 2025-01-24
Enrollment: 765
Sex: ALL
Minimum age (years): 45
Maximum age (years): 74
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Arm 1- Conventional colonoscopy Arm 2- Colonoscopy assisted by artificial intelligence system
Primary purpose: DIAGNOSTIC

Brief summary: 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.

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Adenoma Detection Rate in Conventional versus Artificial Intelligence-Assisted Colonoscopy
timeFrame: 1 day
Secondary outcomes:
measure: 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).
timeFrame: 1 day
measure: 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).
timeFrame: 1 day
measure: 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.
timeFrame: 1 month
measure: The difference in detection rate of colorectal adenomas based on dysplastic grade by group
timeFrame: 1 day
measure: 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).
timeFrame: 1 day
measure: The difference in the detection rate of colorectal adenomas according to experience by group of colonoscopists
timeFrame: 1 day
measure: The difference in the detection rate of colorectal adenomas depending on the time of day .
timeFrame: 1 day
measure: 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).
timeFrame: 1 day
Other outcomes:
Locations:
city: Auderghem
country: Belgium
facility: Hopital Delta Chirec
state: Brussels
Study officials:
affiliation: Chirec
name: Denis Franchimont, M.D., PhD
role: STUDY_CHAIR
References:
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