Polyp of ColonCAD-ARTIPODNCT04442607
Clinical vAliDation of ARTificial Intelligence in POlyp Detection
A study testing artificial intelligence image processing in people with Polyp of Colon, run by Universitaire Ziekenhuizen KU Leuven at 1 site in Belgium.
Trial summary
This study is an open label, unblinded, non-randomized interventional study, comparing the investigational artificial intelligence tool with the current "gold standard": Data acquisition will be obtained during one scheduled colonoscopic procedure by a trained endoscopist. Read more about this study
- Who is it for?
- Ages 40 years and olderHealthy volunteers can take part
- Conditions the study is for
- Polyp of Colon
- What is being tested?
- artificial intelligence image processing
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 856 participants
- Where
- 1 siteBelgium
- Study dates
- 13 Oct 2020to 29 Nov 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 40 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Age ≥40 years
- Referral for screening, surveillance or diagnostic colonoscopy
- Able to give informed consent by the patient or by a legal representative
Who cannot join
- <40 years old
- Referral for a therapeutic colonoscopy
- Known Lynch syndrome or Familial Adenomatous Polyposis syndrome
- Any contraindication for colonoscopy or biopsies of the colon
- Uncontrolled coagulopathy
- Confirmed diagnosis of inflammatory bowel disease prior to the scheduled colonoscopy
Show all 11Show fewer
- Short bowel or ileostomy
- Pregnancy
- Colonic inflammation of > 30cm during colonoscopy
- Incomplete colonoscopy for any reason
- Incomplete recording or technical failure of the artificial intelligence system
Trial locations and contacts
1 site in 1 country.
About this study
This study is an open label, unblinded, non-randomized interventional study, comparing the investigational artificial intelligence tool with the current "gold standard": Data acquisition will be obtained during one scheduled colonoscopic procedure by a trained endoscopist. During insertion, no action will be taken, colonoscopy is performed following the standard of care. Once withdrawal is started, a second observer (not a trained endoscopist but person trained in polyp recognition) will start the bedside Artificial intelligence (AI) tool, connected to the endoscope's tower, for detection. This second observer is trained in assessing endoscopic images to define the AI tool's outcome. Due to the second observer watching the separate AI screen, the endoscopist is blinded of the AI outcome. When a detection is made by the AI system that is not recognized by the endoscopist, the endoscopist will be asked to relocate that same detection and to reassess the lesion and the possible need of therapeutic action. All detections are separately counted and categorized by the second observer. All polyp detections will be removed following standard of care for histological assessment. The entire colonoscopic procedure is recorded via a separate linked video-recorder.
Read the detailed description
This is an investigator-initiated non-randomized prospective interventional trial to validate the performance of a novel state-of-the-art computer-aided detection (CADe) tool for colorectal polyp detection implemented as second observer during routine diagnostic colonoscopy and to evaluate its feasibility in daily endoscopy. Consecutive patients referred for a screening, surveillance or diagnostic colonoscopy will be included.
Patients will undergo a standard colonoscopy performed by a trained endoscopist. A second observer, who is not a trained endoscopist, will follow the procedure on a bedside AI-tool to count the number of detections made by the AI system and categorize the results into positive or negative results as follows (1) true positive, (2) false negative or (3) false positive. In case of a detection of the AI-system that was not seen by the endoscopist or unclear to the second observer, the second observer will ask to re-evaluate the indicated region to determine whether after second look the endoscopist has to take extra action. The entire procedure will be recorded.
There are no additional risks specific to the use of the AI tool to be taken into account. General risk of colonoscopy (i.e.: perforation, bleeding or post-polypectomy syndrome) could occur with the same frequency as that of a colonoscopy without the use of this AI tool.
All patients will receive a standard of care protocol during their colonoscopy. The AI system can only have a beneficial outcome for the patient, a better polyp detection, as it has shown to be non-inferior in terms of accuracy when compared to high detecting endoscopist in our pilot trial
- Conditions
- Polyp of Colon
- Being tested
- artificial intelligence image processing
- Keywords
- colonic polyps, endoscopy, artificial intelligence
- Medical subject headings
- Colonic Polyps
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
artificial intelligence image processingDevice
Patients will undergo a standard colonoscopy performed by a trained endoscopist. A second observer, who is not a trained endoscopist, will follow the procedure on a bedside AI-tool to count the number of detections made by the AI system and categorize the results into positive or negative results as follows (1) true positive, (2) false negative or (3) false positive.
| Study group | Role | What they receive |
|---|---|---|
| AI arm | Experimental | Only one arm in this study. Every patient who is eligible for this study and is included, after informed consent, will receive a standard colonoscopy combined with real-time AI video analysis Receives: Device: artificial intelligence image processing |
What is being measured
The primary outcome is the main question the study is designed to answer.
Total polyp detection during single pass colonoscopy by the artificial intelligence tool in comparison to polyp detection by the endoscopist with endoscopic diagnosis as a gold standard
Measured: 1.5 year
Secondary outcomes (5)
Total polyp detection during single pass colonoscopy by the artificial intelligence tool in comparison to polyp detection by the endoscopist with histological diagnosis as a gold standard.
Measured: 1.5 year
The number of extra detected polyps by artificial intelligence with the endoscopic diagnosis as a gold standard.
Measured: 1.5 year
The number of extra detected polyps by artificial intelligence with the histological diagnosis as a gold standard
Measured: 1.5 year
The endoscopist's polyp miss rate defined as the additional detection of polyps during colonoscopy
Measured: 1.5 year
The false positive rate during clean withdrawal.
Measured: 1.5 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2020
- Study start13 Oct 2020
- Primary completion28 Oct 2022
- Study completion29 Nov 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Polyp of ColonStudies of the same condition, open and under way.
- More trials run by Universitaire Ziekenhuizen KU LeuvenThe sponsor's other registered studies.
- 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
- Not applicable
- Intervention model
- Single group
- Model description
- This is an investigator-initiated non-randomized prospective interventional trial to validate the performance of a novel state-of-the-art computer-aided detection (CADe) tool for colorectal polyp detection implemented as second observer during routine diagnostic colonoscopy and to evaluate its feasibility in daily endoscopy.
- Masking
- None (open label)
- Enrolment
- 856 participants (actual)
Sponsor and investigators
- Lead sponsor
- Universitaire Ziekenhuizen KU Leuven
- Sponsor type
- University, hospital or other
- Collaborators
- Nuovo Regina Margherita Hospital, Rome, Italy, Krankenhaus Barmherzige Brüder, Regensburg, Germany, Centre Hospitalier Universitaire de Nantes, Nantes, France, Centrum Onkologii-Instytut im. Marii Skłodowskiej-Curie, Warschau, Poland, Spire Portsmouth Hospital, Portsmouth, United Kingdom, Amsterdam UMC, location VUmc, University Hospital, Ghent
- Responsible party
- Sponsor
- Investigators
- Raf Bisschops, MD,PhD, Principal investigator, Universitaire Ziekenhuizen KU Leuven
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04442607
- Sponsor's protocol ID
- S64243
- Acronym
- CAD-ARTIPOD
- Status last verified
- Nov 2022
- First submitted
- 18 Jun 2020
- Last updated
- 30 Nov 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: We do not plan to make individual participant data available. We might share a overview of anonymized data with the collaborating institutions.
Publications
Dubois V, Lefebvre P, Staels B, Eeckhoute J. Nuclear receptors: pathophysiological mechanisms and drug targets in liver disease. Gut. 2024 Aug 8;73(9):1562-1569. doi: 10.1136/gutjnl-2023-331741.
PubMed 38862216
Study at a glance
From the registry record, last updated by the sponsor on 30 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical vAliDation of ARTificial Intelligence in POlyp Detection
- ClinicalTrials.gov ID
- NCT04442607
- Acronym / sponsor ID
- CAD-ARTIPOD / S64243
- Conditions
- Polyp of Colon
- Keywords
- colonic polyps, endoscopy, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 856 participants (actual)
- Lead sponsor
- Universitaire Ziekenhuizen KU LeuvenUniversity, hospital or other
- Collaborators
- Nuovo Regina Margherita Hospital, Rome, Italy, Krankenhaus Barmherzige Brüder, Regensburg, Germany, Centre Hospitalier Universitaire de Nantes, Nantes, France, Centrum Onkologii-Instytut im. Marii Skłodowskiej-Curie, Warschau, Poland, Spire Portsmouth Hospital, Portsmouth, United Kingdom, Amsterdam UMC, location VUmc, University Hospital, Ghent
- Study start
- 13 Oct 2020 (actual)
- Primary completion
- 28 Oct 2022 (actual)
- Study completion
- 29 Nov 2022 (actual)
- First posted
- 22 Jun 2020 (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.
This study is an open label, unblinded, non-randomized interventional study, comparing the investigational artificial intelligence tool with the current "gold standard": Data acquisition will be obtained during one scheduled colonoscopic procedure by a trained endoscopist. During insertion, no action will be taken, colonoscopy is performed following the standard of care. Once withdrawal is started, a second observer (not a trained endoscopist but person trained in polyp recognition) will start the bedside Artificial intelligence (AI) tool, connected to the endoscope's tower, for detection. This second observer is trained in assessing endoscopic images to define the AI tool's outcome. Due to the second observer watching the separate AI screen, the endoscopist is blinded of the AI outcome. When a detection is made by the AI system that is not recognized by the endoscopist, the endoscopist will be asked to relocate that same detection and to reassess the lesion and the possible need of therapeutic action. All detections are separately counted and categorized by the second observer. All polyp detections will be removed following standard of care for histological assessment. The entire colonoscopic procedure is recorded via a separate linked video-recorder.
Detailed description
This is an investigator-initiated non-randomized prospective interventional trial to validate the performance of a novel state-of-the-art computer-aided detection (CADe) tool for colorectal polyp detection implemented as second observer during routine diagnostic colonoscopy and to evaluate its feasibility in daily endoscopy. Consecutive patients referred for a screening, surveillance or diagnostic colonoscopy will be included.
Patients will undergo a standard colonoscopy performed by a trained endoscopist. A second observer, who is not a trained endoscopist, will follow the procedure on a bedside AI-tool to count the number of detections made by the AI system and categorize the results into positive or negative results as follows (1) true positive, (2) false negative or (3) false positive. In case of a detection of the AI-system that was not seen by the endoscopist or unclear to the second observer, the second observer will ask to re-evaluate the indicated region to determine whether after second look the endoscopist has to take extra action. The entire procedure will be recorded.
There are no additional risks specific to the use of the AI tool to be taken into account. General risk of colonoscopy (i.e.: perforation, bleeding or post-polypectomy syndrome) could occur with the same frequency as that of a colonoscopy without the use of this AI tool.
All patients will receive a standard of care protocol during their colonoscopy. The AI system can only have a beneficial outcome for the patient, a better polyp detection, as it has shown to be non-inferior in terms of accuracy when compared to high detecting endoscopist in our pilot trial
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- This is an investigator-initiated non-randomized prospective interventional trial to validate the performance of a novel state-of-the-art computer-aided detection (CADe) tool for colorectal polyp detection implemented as second observer during routine diagnostic colonoscopy and to evaluate its feasibility in daily endoscopy.
| Arm | Type | Receives |
|---|---|---|
| AI arm | Experimental | Device: artificial intelligence image processingOnly one arm in this study. Every patient who is eligible for this study and is included, after informed consent, will receive a standard colonoscopy combined with real-time AI video analysis |
Who may qualify
- Ages
- 40 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Age ≥40 years
- Referral for screening, surveillance or diagnostic colonoscopy
- Able to give informed consent by the patient or by a legal representative
Key exclusion criteria (11 listed)
- <40 years old
- Referral for a therapeutic colonoscopy
- Known Lynch syndrome or Familial Adenomatous Polyposis syndrome
- Any contraindication for colonoscopy or biopsies of the colon
- Uncontrolled coagulopathy
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 |
|---|---|---|
| artificial intelligence image processingPatients will undergo a standard colonoscopy performed by a trained endoscopist. A second observer, who is not a trained endoscopist, will follow the procedure on a bedside AI-tool to count the number of detections made by the AI system and categorize the results into positive or negative results as follows (1) true positive, (2) false negative or (3) false positive. | Device | AI arm |
Primary outcome
Total polyp detection during single pass colonoscopy by the artificial intelligence tool in comparison to polyp detection by the endoscopist with endoscopic diagnosis as a gold standard
Time frame: 1.5 year
5 secondary outcomes
Total polyp detection during single pass colonoscopy by the artificial intelligence tool in comparison to polyp detection by the endoscopist with histological diagnosis as a gold standard.
Time frame: 1.5 year
The number of extra detected polyps by artificial intelligence with the endoscopic diagnosis as a gold standard.
Time frame: 1.5 year
The number of extra detected polyps by artificial intelligence with the histological diagnosis as a gold standard
Time frame: 1.5 year
The endoscopist's polyp miss rate defined as the additional detection of polyps during colonoscopy
Time frame: 1.5 year
The false positive rate during clean withdrawal.
Time frame: 1.5 year
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Nov 2022.
- Derived from this study: PubMed 38862216Dubois V, Lefebvre P, Staels B, Eeckhoute J. Nuclear receptors: pathophysiological mechanisms and drug targets in liver disease. Gut. 2024 Aug 8;73(9):1562-1569. doi: 10.1136/gutjnl-2023-331741.
- Individual participant dataSharing planned: No. We do not plan to make individual participant data available. We might share a overview of anonymized data with the collaborating institutions.
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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. This study is not recruiting at the moment.
Raf Bisschops, MD,PhD principal investigator
Universitaire Ziekenhuizen KU Leuven
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing artificial intelligence image processing in people with Polyp of Colon, run by Universitaire Ziekenhuizen KU Leuven 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 3 inclusion and 11 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: finished, as of the sponsor's last update on 30 Nov 2022. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Total polyp detection during single pass colonoscopy by the artificial intelligence tool in comparison to polyp detection by the endoscopist with endoscopic diagnosis as a gold standard (time frame: 1.5 year). 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 NCT04442607, which also lists 1 linked publication.
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 30 Nov 2022.