Artificial IntelligenceDelta-AINCT06792292
Artificial Intelligence-Assisted Colonoscopy in Colorectal Cancer Screening in a General Hospital
A study testing conventional colonoscopy procedure and artificial intelligence-assisted colonoscopy procedure in people with Artificial Intelligence and Colonic Adenoma, run by Chirec at 1 site in Belgium.
Trial 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. Read more about this study
- Who is it for?
- Ages 45 to 74 yearsHealthy volunteers can take part
- Conditions the study is for
- Artificial Intelligence, Colonic Adenoma, Colonic Neoplasms
- What is being tested?
- conventional colonoscopy procedure and artificial intelligence-assisted colonoscopy procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 765 participants
- Where
- 1 siteBelgium
- Study dates
- 1 Feb 2025to 1 Jun 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 45 to 74 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Belgium1 site
Hopital Delta Chirec
Auderghem, Brussels Capital, 1160
Erik Francois, M.D., drfrancois.chirec@gmail.com
Erik Francois, M.D.
About this study
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
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.
Read more
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.
Read the 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.
- Being tested
- conventional colonoscopy procedure, artificial intelligence-assisted colonoscopy procedure
- Keywords
- colo-rectal cancer screening, artificial intelligence assisted colonoscopy
- Medical subject headings
- Colonic Neoplasms, Colonic Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
conventional colonoscopy procedureOther
Study subjects in this interventional arm will undergo conventional colonoscopy.
artificial intelligence-assisted colonoscopy procedureOther
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.
| Study group | Role | What they receive |
|---|---|---|
| CCP: conventional colonoscopy procedure | Active comparator | The conventional colonoscopy arm subjects will undergo a screening colonoscopy without assistance from artificial intelligence. Receives: Other: conventional colonoscopy procedure |
| ACP: artificial intelligence-assisted colonoscopy procedure | Active comparator | The artificial intelligence-assisted colonoscopy arm subjects will undergo a screening colonoscopy with assistance from an artificial intelligence module. Receives: Other: artificial intelligence-assisted colonoscopy procedure |
What is being measured
The primary outcome is the main question the study is designed to answer.
Adenoma Detection Rate in Conventional versus Artificial Intelligence-Assisted Colonoscopy
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).
Measured: 1 day
Secondary outcomes (8)
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).
Detection rate of diminutive, small, and large polyps will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Measured: 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).
The number of adenomas detected during the procedure will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Measured: 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.
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).
Measured: 1 month
The difference in detection rate of colorectal adenomas based on dysplastic grade by group
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).
Measured: 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).
Location of adenomas will be compared between a conventional colonoscopic procedure (CCP) and a colonoscopy procedure with AI (ACP).
Measured: 1 day
The difference in the detection rate of colorectal adenomas according to experience by group of colonoscopists
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).
Measured: 1 day
The difference in the detection rate of colorectal adenomas depending on the time of 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).
Measured: 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).
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).
Measured: 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Jan 2025
- Study start1 Feb 2025 (estimated)
- Primary completion31 Dec 2026 (estimated)
- Study completion1 Jun 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (8)Papers the sponsor has linked to this study.
- Other trials for Artificial IntelligenceStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Arm 1- Conventional colonoscopy Arm 2- Colonoscopy assisted by artificial intelligence system
- Masking
- None (open label)
- Enrolment
- 765 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chirec
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Erik Francois, Chirec
- Investigators
- Denis Franchimont, M.D., PhD, Study chair, Chirec
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06792292
- Sponsor's protocol ID
- 2024 Chirec Delta Colo-AI
- Acronym
- Delta-AI
- Status last verified
- Jan 2025
- First submitted
- 12 Jan 2025
- Last updated
- 24 Jan 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: 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.
Publications
Spadaccini M, Marco A, Franchellucci G, Sharma P, Hassan C, Repici A. Discovering the first US FDA-approved computer-aided polyp detection system. Future Oncol. 2022 Apr;18(11):1405-1412. doi: 10.2217/fon-2021-1135. Epub 2022 Jan 27.
PubMed 35081745Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1.
PubMed 32371116Gupta S, Lieberman D, Anderson JC, Burke CA, Dominitz JA, Kaltenbach T, Robertson DJ, Shaukat A, Syngal S, Rex DK. Recommendations for Follow-Up After Colonoscopy and Polypectomy: A Consensus Update by the US Multi-Society Task Force on Colorectal Cancer. Gastrointest Endosc. 2020 Mar;91(3):463-485.e5. doi: 10.1016/j.gie.2020.01.014. Epub 2020 Feb 7. No abstract available.
PubMed 32044106Kaminski MF, Thomas-Gibson S, Bugajski M, Bretthauer M, Rees CJ, Dekker E, Hoff G, Jover R, Suchanek S, Ferlitsch M, Anderson J, Roesch T, Hultcranz R, Racz I, Kuipers EJ, Garborg K, East JE, Rupinski M, Seip B, Bennett C, Senore C, Minozzi S, Bisschops R, Domagk D, Valori R, Spada C, Hassan C, Dinis-Ribeiro M, Rutter MD. Performance measures for lower gastrointestinal endoscopy: a European Society of Gastrointestinal Endoscopy (ESGE) quality improvement initiative. United European Gastroenterol J. 2017 Apr;5(3):309-334. doi: 10.1177/2050640617700014. Epub 2017 Mar 16.
PubMed 28507745Hassan C, Antonelli G, Dumonceau JM, Regula J, Bretthauer M, Chaussade S, Dekker E, Ferlitsch M, Gimeno-Garcia A, Jover R, Kalager M, Pellise M, Pox C, Ricciardiello L, Rutter M, Helsingen LM, Bleijenberg A, Senore C, van Hooft JE, Dinis-Ribeiro M, Quintero E. Post-polypectomy colonoscopy surveillance: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2020. Endoscopy. 2020 Aug;52(8):687-700. doi: 10.1055/a-1185-3109. Epub 2020 Jun 22.
PubMed 32572858Brenner H, Hoffmeister M, Stegmaier C, Brenner G, Altenhofen L, Haug U. Risk of progression of advanced adenomas to colorectal cancer by age and sex: estimates based on 840,149 screening colonoscopies. Gut. 2007 Nov;56(11):1585-9. doi: 10.1136/gut.2007.122739. Epub 2007 Jun 25.
PubMed 17591622Saftoiu A, Hassan C, Areia M, Bhutani MS, Bisschops R, Bories E, Cazacu IM, Dekker E, Deprez PH, Pereira SP, Senore C, Capocaccia R, Antonelli G, van Hooft J, Messmann H, Siersema PD, Dinis-Ribeiro M, Ponchon T. Role of gastrointestinal endoscopy in the screening of digestive tract cancers in Europe: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy. 2020 Apr;52(4):293-304. doi: 10.1055/a-1104-5245. Epub 2020 Feb 12.
PubMed 32052404Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.
PubMed 32598963
Study at a glance
From the registry record, last updated by the sponsor on 24 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT06792292
- Acronym / sponsor ID
- Delta-AI / 2024 Chirec Delta Colo-AI
- Keywords
- colo-rectal cancer screening, artificial intelligence assisted colonoscopy
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 765 participants (estimated)
- Lead sponsor
- ChirecUniversity, hospital or other
- Study start
- 1 Feb 2025 (estimated)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 1 Jun 2027 (estimated)
- First posted
- 24 Jan 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Arm 1- Conventional colonoscopy Arm 2- Colonoscopy assisted by artificial intelligence system
| Arm | Type | Receives |
|---|---|---|
| CCP: conventional colonoscopy procedure | Active comparator | Other: conventional colonoscopy procedureThe conventional colonoscopy arm subjects will undergo a screening colonoscopy without assistance from artificial intelligence. |
| ACP: artificial intelligence-assisted colonoscopy procedure | Active comparator | Other: artificial intelligence-assisted colonoscopy procedureThe artificial intelligence-assisted colonoscopy arm subjects will undergo a screening colonoscopy with assistance from an artificial intelligence module. |
Who may qualify
- Ages
- 45 to 74 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| conventional colonoscopy procedureStudy subjects in this interventional arm will undergo conventional colonoscopy. | Other | CCP: conventional colonoscopy procedure |
| artificial intelligence-assisted colonoscopy procedureStudy 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. | Other | ACP: artificial intelligence-assisted colonoscopy procedure |
Primary outcome
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).
8 secondary outcomes
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
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 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
The difference in detection rate of colorectal adenomas based on dysplastic grade by group
Time frame: 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
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 depending on the time of day .
Time frame: 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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jan 2025.
- Background: PubMed 35081745Spadaccini M, Marco A, Franchellucci G, Sharma P, Hassan C, Repici A. Discovering the first US FDA-approved computer-aided polyp detection system. Future Oncol. 2022 Apr;18(11):1405-1412. doi: 10.2217/fon-2021-1135. Epub 2022 Jan 27.
- Background: PubMed 32371116Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1.
- Background: PubMed 32044106Gupta S, Lieberman D, Anderson JC, Burke CA, Dominitz JA, Kaltenbach T, Robertson DJ, Shaukat A, Syngal S, Rex DK. Recommendations for Follow-Up After Colonoscopy and Polypectomy: A Consensus Update by the US Multi-Society Task Force on Colorectal Cancer. Gastrointest Endosc. 2020 Mar;91(3):463-485.e5. doi: 10.1016/j.gie.2020.01.014. Epub 2020 Feb 7. No abstract available.
- Background: PubMed 28507745Kaminski MF, Thomas-Gibson S, Bugajski M, Bretthauer M, Rees CJ, Dekker E, Hoff G, Jover R, Suchanek S, Ferlitsch M, Anderson J, Roesch T, Hultcranz R, Racz I, Kuipers EJ, Garborg K, East JE, Rupinski M, Seip B, Bennett C, Senore C, Minozzi S, Bisschops R, Domagk D, Valori R, Spada C, Hassan C, Dinis-Ribeiro M, Rutter MD. Performance measures for lower gastrointestinal endoscopy: a European Society of Gastrointestinal Endoscopy (ESGE) quality improvement initiative. United European Gastroenterol J. 2017 Apr;5(3):309-334. doi: 10.1177/2050640617700014. Epub 2017 Mar 16.
- Background: PubMed 32572858Hassan C, Antonelli G, Dumonceau JM, Regula J, Bretthauer M, Chaussade S, Dekker E, Ferlitsch M, Gimeno-Garcia A, Jover R, Kalager M, Pellise M, Pox C, Ricciardiello L, Rutter M, Helsingen LM, Bleijenberg A, Senore C, van Hooft JE, Dinis-Ribeiro M, Quintero E. Post-polypectomy colonoscopy surveillance: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2020. Endoscopy. 2020 Aug;52(8):687-700. doi: 10.1055/a-1185-3109. Epub 2020 Jun 22.
- Background: PubMed 17591622Brenner H, Hoffmeister M, Stegmaier C, Brenner G, Altenhofen L, Haug U. Risk of progression of advanced adenomas to colorectal cancer by age and sex: estimates based on 840,149 screening colonoscopies. Gut. 2007 Nov;56(11):1585-9. doi: 10.1136/gut.2007.122739. Epub 2007 Jun 25.
- Background: PubMed 32052404Saftoiu A, Hassan C, Areia M, Bhutani MS, Bisschops R, Bories E, Cazacu IM, Dekker E, Deprez PH, Pereira SP, Senore C, Capocaccia R, Antonelli G, van Hooft J, Messmann H, Siersema PD, Dinis-Ribeiro M, Ponchon T. Role of gastrointestinal endoscopy in the screening of digestive tract cancers in Europe: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy. 2020 Apr;52(4):293-304. doi: 10.1055/a-1104-5245. Epub 2020 Feb 12.
- Background: PubMed 32598963Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.
- Individual participant dataSharing planned: Yes. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Denis Franchimont, M.D., PhD study chair
Chirec
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing conventional colonoscopy procedure and artificial intelligence-assisted colonoscopy procedure in people with Artificial Intelligence and Colonic Adenoma, run by Chirec at 1 site in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 24 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Erik Francois, M.D. (32 495 77 00 60, drfrancois.chirec@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Adenoma Detection Rate in Conventional versus Artificial Intelligence-Assisted Colonoscopy (time frame: 1 day). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06792292, which also lists 8 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jan 2025.