Artificial IntelligenceAI-ODNCT06059378
Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps
A study testing Artificial intelligence-assisted classification (CADx) in people with Artificial Intelligence, run by Centre hospitalier de l'Université de Montréal (CHUM) at 1 site in Canada.
Trial summary
This is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard. Read more about this study
- Who is it for?
- Ages 45 to 80 years
- Conditions the study is for
- Artificial Intelligence
- What is being tested?
- Artificial intelligence-assisted classification (CADx)
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 204 participants
- Where
- 1 siteCanada
- Study dates
- 1 Sep 2023to 31 Aug 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 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age 45-80 years
- Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
- Signed informed consent form
Who cannot join
- Inflammatory Bowel Disease;
- Active colitis;
- Hereditary CRC syndrome;
- Coagulopathy;
- American Society of Anesthesiologists (ASA) status >3
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using Artificial Intelligence-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps
This is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard.
The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are:
- To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard.
- To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists.
- To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input).
- To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.
Read the detailed description
All patients who meet the inclusion criteria can be enrolled. Eligible patients will be informed about the study through a consent form that includes information on optical diagnosis (resect and discard, diagnose and leave) and AI/CADx systems. We will ask the patients' willingness to undergo AI-assisted optical diagnosis with endoscopists' input (the first 102 patients) and automomous AI-assisted optical diagnosis (from patient 103 to 204). Subsequently, patients will be asked if they are willing to participate in the study, using AI-assisted optical diagnosis and the "resect and discard" and "diagnose and leave" strategy. If a patient declines to undergo optical diagnosis, they will be asked about the reason for their refusal to participate in the study. The options for their response include:
- Concerns regarding undergoing an optical diagnosis.
- Reluctance to participate in research projects in general.
- Other reasons.
- Preference not to answer the question.
Patients who agree to participate in the study will undergo standard colonoscopy procedures with AI-assisted optical diagnosis for all diminutive colorectal polyps identified. High-definition colonoscopes with a joint computer-assisted classification (CADx) support (CAD-EYE software EW10-EC02) will be used.
For the first 102 patients (i.e., the CAD-assisted optical diagnosis with endoscopist's input), the endoscopists will use the CAD-EYE blue light imaging (BLI) mode to enhance the visualization of polyp features. During the optical diagnosis using CADx, the most probable diagnosis (neoplastic or hyperplastic) will be displayed on the endoscopy screen. If the serrated pathology subtype is determined as the most probable histology, the endoscopists will make the final decision. They will also indicate whether their optical diagnosis was made with low or high confidence.
For the second group of 102 patients (i.e., autonomous CADx-assisted optical diagnosis), endoscopists will use CADx and BLI mode to perform optical diagnosis. Based on the CADx diagnosis, all 1-5 mm polyps diagnosed as hyperplastic or neoplastic will be resected and discarded, while those located in the rectosigmoid and diagnosed as hyperplastic will be left in the colon. When high-risk histology features are observed using BLI, in any patient, the endoscopists will inform the research assistant to document them, and the polyp will be sent for pathology examination in accordance with the ASGE PIVI guidelines recommendations. All polyps >5mm will be send for pathology evaluation. Polyp size will be measured using virtual scale technology integrated in the computer-assisted system (CAD) to ensure an accurate polyp sizing.18 A research assistant will document the characteristics of the detected polyps (i.e., location, size, morphology, AI-assisted intracolonoscopy and endoscopists optical diagnoses). All identified colorectal polyps will be removed following standard polypectomy practices. The entire colonoscopy procedures will be video recorded for quality assurance purposes. All diminutive polyps will be resected and discarded as part of the resect and discard strategy. Additionally, diminutive polyps located in the rectosigmoid colon will be detected and left in situ (diagnose and leave strategy) if no high-risk features are present.
- Conditions
- Artificial Intelligence
- Being tested
- Artificial intelligence-assisted classification (CADx)
- Keywords
- Artificial intelligenc, Optical diagnosis, Colonoscopy, Resect and Discard
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence-assisted classification (CADx)Device
Also called CAD-eye
CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted classification with endoscopist's input | Other | AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with input from the endoscopist in the case of serrated polyps, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. Receives: Device: Artificial intelligence-assisted classification (CADx) |
| Autonomous AI-assisted classification | Other | AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with no input from the endoscopist, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. Receives: Device: Artificial intelligence-assisted classification (CADx) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of the intracolonoscopy AI-assisted optical diagnosis
Using the optical diagnosis obtained from 2 experts as the reference, the accuracy of the intracolonoscopy AI-assisted optical diagnosis (OD, with endoscopist input or autonomous) is measured as the number of correct ODs out of all ODs (%).
Measured: 120 days
Secondary outcomes (6)
Proportion of patients who accept study participation
Number of patients who accept to participate out of all patients approached
Measured: 120 days
Proportion of the patients unwilling to participate due to concerns regarding undergoing an optical diagnosis
The proportion of the patients unwilling to participate in the study due to the concerns of resect and discard or diagnose and leave strategies (with endoscopist input or autonomous) and preference upon histopathological evaluation of all detected polyps
Measured: 120 days
Agreement between the intracolonoscopy AI-assisted optical diagnosis and the AI-assisted optical diagnosis by experts
The agreement between AI-assisted OD (with and without endoscopist's input) and the experts' OD is measured as the number of cases where both ODs are the same out of all cases (%).
Measured: 120 days
Diagnostic characteristics of AI-assisted optical diagnosis using adjudication by two expert endoscopists as the reference standard
To calculate the accuracy, sensitivity, specificity, positive predictive value, negative predictive value of (CADx) assisted optical diagnosis (resect and discard) strategy using adjudication by two expert endoscopists as the reference standard.
Measured: 120 days
Proportion of polyps with a low-confidence diagnosis
Proportion of polyps with a low-confidence diagnosis intracolonoscopy and later by the expert independent reviewers
Measured: 120 days
Assessing cost savings through AI-assisted optical diagnosis
The reduction in costs of the supplies and the pathology assessments according to the expenses reported by the CHUM gastroenterology and pathology departments including the expenses related to the supplies (e.g., snares, containers), immediate and delayed complications, specimen processing and equipment and physician fees.
Measured: 120 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Sep 2023
- Study start1 Sep 2023
- Primary completion1 May 2025
- Study completion31 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial IntelligenceStudies of the same condition, open and under way.
- More trials run by Centre hospitalier de l'Université de Montréal (CHUM)The 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
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 204 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Daniel von Renteln, MD, Principal investigator, Centre hospitalier de l'Université de Montréal (CHUM)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06059378
- Sponsor's protocol ID
- 2024-11557/23.095
- Acronym
- AI-OD
- Status last verified
- Feb 2026
- First submitted
- 22 Sep 2023
- Last updated
- 21 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Artificial Intelligence-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps
- ClinicalTrials.gov ID
- NCT06059378
- Acronym / sponsor ID
- AI-OD / 2024-11557/23.095
- Conditions
- Artificial Intelligence
- Keywords
- Artificial intelligenc, Optical diagnosis, Colonoscopy, Resect and Discard
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 204 participants (estimated)
- Lead sponsor
- Centre hospitalier de l'Université de Montréal (CHUM)University, hospital or other
- Study start
- 1 Sep 2023 (actual)
- Primary completion
- 1 May 2025 (actual)
- Study completion
- 31 Aug 2027 (estimated)
- First posted
- 28 Sep 2023 (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 is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard.
The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are:
- To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard.
- To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists.
- To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input).
- To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.
Detailed description
All patients who meet the inclusion criteria can be enrolled. Eligible patients will be informed about the study through a consent form that includes information on optical diagnosis (resect and discard, diagnose and leave) and AI/CADx systems. We will ask the patients' willingness to undergo AI-assisted optical diagnosis with endoscopists' input (the first 102 patients) and automomous AI-assisted optical diagnosis (from patient 103 to 204). Subsequently, patients will be asked if they are willing to participate in the study, using AI-assisted optical diagnosis and the "resect and discard" and "diagnose and leave" strategy. If a patient declines to undergo optical diagnosis, they will be asked about the reason for their refusal to participate in the study. The options for their response include:
- Concerns regarding undergoing an optical diagnosis.
- Reluctance to participate in research projects in general.
- Other reasons.
- Preference not to answer the question.
Patients who agree to participate in the study will undergo standard colonoscopy procedures with AI-assisted optical diagnosis for all diminutive colorectal polyps identified. High-definition colonoscopes with a joint computer-assisted classification (CADx) support (CAD-EYE software EW10-EC02) will be used.
For the first 102 patients (i.e., the CAD-assisted optical diagnosis with endoscopist's input), the endoscopists will use the CAD-EYE blue light imaging (BLI) mode to enhance the visualization of polyp features. During the optical diagnosis using CADx, the most probable diagnosis (neoplastic or hyperplastic) will be displayed on the endoscopy screen. If the serrated pathology subtype is determined as the most probable histology, the endoscopists will make the final decision. They will also indicate whether their optical diagnosis was made with low or high confidence.
For the second group of 102 patients (i.e., autonomous CADx-assisted optical diagnosis), endoscopists will use CADx and BLI mode to perform optical diagnosis. Based on the CADx diagnosis, all 1-5 mm polyps diagnosed as hyperplastic or neoplastic will be resected and discarded, while those located in the rectosigmoid and diagnosed as hyperplastic will be left in the colon. When high-risk histology features are observed using BLI, in any patient, the endoscopists will inform the research assistant to document them, and the polyp will be sent for pathology examination in accordance with the ASGE PIVI guidelines recommendations. All polyps >5mm will be send for pathology evaluation. Polyp size will be measured using virtual scale technology integrated in the computer-assisted system (CAD) to ensure an accurate polyp sizing.18 A research assistant will document the characteristics of the detected polyps (i.e., location, size, morphology, AI-assisted intracolonoscopy and endoscopists optical diagnoses). All identified colorectal polyps will be removed following standard polypectomy practices. The entire colonoscopy procedures will be video recorded for quality assurance purposes. All diminutive polyps will be resected and discarded as part of the resect and discard strategy. Additionally, diminutive polyps located in the rectosigmoid colon will be detected and left in situ (diagnose and leave strategy) if no high-risk features are present.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted classification with endoscopist's input | Other | Device: Artificial intelligence-assisted classification (CADx)AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with input from the endoscopist in the case of serrated polyps, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. |
| Autonomous AI-assisted classification | Other | Device: Artificial intelligence-assisted classification (CADx)AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with no input from the endoscopist, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps. |
Who may qualify
- Ages
- 45 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Age 45-80 years
- Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
- Signed informed consent form
Key exclusion criteria (5 listed)
- Inflammatory Bowel Disease;
- Active colitis;
- Hereditary CRC syndrome;
- Coagulopathy;
- American Society of Anesthesiologists (ASA) status >3
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-assisted classification (CADx)Also: CAD-eyeCADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon. | Device | AI-assisted classification with endoscopist's input, Autonomous AI-assisted classification |
Primary outcome
Accuracy of the intracolonoscopy AI-assisted optical diagnosis
Time frame: 120 days
Using the optical diagnosis obtained from 2 experts as the reference, the accuracy of the intracolonoscopy AI-assisted optical diagnosis (OD, with endoscopist input or autonomous) is measured as the number of correct ODs out of all ODs (%).
6 secondary outcomes
Proportion of patients who accept study participation
Time frame: 120 days
Proportion of the patients unwilling to participate due to concerns regarding undergoing an optical diagnosis
Time frame: 120 days
Agreement between the intracolonoscopy AI-assisted optical diagnosis and the AI-assisted optical diagnosis by experts
Time frame: 120 days
Diagnostic characteristics of AI-assisted optical diagnosis using adjudication by two expert endoscopists as the reference standard
Time frame: 120 days
Proportion of polyps with a low-confidence diagnosis
Time frame: 120 days
Assessing cost savings through AI-assisted optical diagnosis
Time frame: 120 days
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 21 Sep 2026.
- Individual participant dataSharing planned: No
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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.
Daniel von Renteln, MD principal investigator
Centre hospitalier de l'Université de Montréal (CHUM)
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-assisted classification (CADx) in people with Artificial Intelligence, run by Centre hospitalier de l'Université de Montréal (CHUM) at 1 site in Canada.
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 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: under way, not looking for participants, as of the sponsor's last update on 21 Sep 2026. 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 Canada. 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?
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?
Accuracy of the intracolonoscopy AI-assisted optical diagnosis (time frame: 120 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Sep 2026.