An interventional study of CADx (AI) system in Colonic Polyp and Artificial Intelligence, sponsored by Centre hospitalier de l'Université de Montréal (CHUM). Recruiting at 1 site in Canada. Open to participants aged 45 Years to 80 Years. Per ClinicalTrials.gov, last updated 2026-09-21.
Sponsored by Centre hospitalier de l'Université de Montréal (CHUM) · Not applicable, Interventional, and Diagnostic
Computer-aided image-enhanced endoscopy can predict the nature of colorectal polyps with over 90% accuracy. This technology uses artificial intelligence (AI) to analyze video recordings of polyps, learning to make diagnoses in real-time. This means that doctors can get immediate predictions about small polyps during the procedure, reducing the need for separate pathology exams and saving costs, ultimately improving patient care.
Human and AI interactions are complex and a framework to reap synergistic effects CADx systems when used by humans to harness optimal performance needs to be established. AI solutions in medicine are usually developed to be used as assistive devices, however, then they rely on humans to correct AI errors. Optical polyp diagnosis is a complex task. Non experts usually achieve diagnostic accuracy in 70-80%. CADx systems have a similar diagnostic accuracy when used autonomously. Clinical evaluation of CADx systems showed that CADx assisted OD performs equally to the operator performance when using non CADx assisted OD. To harness a benefit of clinical CADx implementation we would have to find a way that synergies between human and CADx come into play to eliminate cases in which CADx assisted and/ or human OD results in low diagnostic accuracy and also addresses the problem of serrated polyp recognition.
Our study hypothesis is that for CADx implementation, instead of using the high/low confidence framework, identifying cases with suboptimal diagnostic accuracy could be facilitated through identifying cases in which CADx and endoscopist disagreed in their diagnosis. Eliminating such cases might separate out cases with low accuracy when using CADx assisted OD. Since endoscopists have a high sensitivity but low specificity for serrated polyp OD, this framework will also allow us to implement a strategy to adequately manage serrated polyps found in the cohort.
377 studies on the registry are indexed under Colonic Polyps; 57 are open to participants now.
This study's planned enrollment of 540 is above the median of 274 across 250 interventional studies indexed under Colonic Polyps.
Browse Colonic Polyps studies →Centre hospitalier de l'Université de Montréal (CHUM) is the lead sponsor of 376 studies on the registry; 110 are open to participants now.
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Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
The anaesthetists’ scale of health before surgery: I is healthy, II has a mild illness that is under control, III a severe one, IV a severe illness that is a constant threat to life. V and VI are used for the critically ill and for organ donors.
ASA physical status
The anaesthetists’ scale of health before surgery: I is healthy, II has a mild illness that is under control, III a severe one, IV a severe illness that is a constant threat to life. V and VI are used for the critically ill and for organ donors.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
The endoscopist will make an optical diagnosis (OD) prediction for all small polyps (up to 10 mm) in white light (WL). Then, the endoscopist will make another OD prediction using image enhanced endoscopy (IEE) modes. After that, CADx will be activated in the IEE mode and a CADx prediction will be documented. Finally, after seeing the CADx prediction, the endoscopist will make a final prediction, which can agree or disagree with the autonomous CADx one. Polyps will be resected and sent to a pathology lab, where a pathologic diagnosis (blinded to the endoscopist's predictions) will be rendered.
Other: CADx (AI) system
The CADx system will be used to predict the histopathology of the polyp detected.
Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis
Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis , when histopathology results are used as the reference
Time frame: up to 100 weeks
Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis
Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis, when histopathology results are used as the reference
Time frame: up to 100 weeks
Test characteristics, including recall, specificity, positive and negative predictive values (PPV/NPV), and particularly the NPV of rectosigmoid neoplastic polyps.
A ≥90% NPV will be used as a quality benchmark for a strategy to not resect such diminutive polyps.
Time frame: up to 100 weeks
Agreement of surveillance interval recommendations of AI-A and AI-H compared with the pathology-based recommendations
For surveillance interval assignment, the pathology results of concomitant polyps \>5 mm (including multiple concomitant polyps of all sizes and histology) will be considered when calculating the surveillance interval recommendation. Surveillance recommendations will be based on the 2020 United States Multi Society Task Force Guidelines as is current standard of practice at our center.
Time frame: up to 100 weeks
Proportion of patients for whom an immediate surveillance recommendation can be directly provided for each approach, and how often histopathology-based polyp examination would have been avoided.
The potential cost-effectiveness of OD (either approaches) will be evaluated using the measured described above.
Time frame: up to 100 weeks
Variability of OD (AI-A and AI-H) across participating endoscopists.
Each participating endoscopist will conduct a similar number of optical diagnoses to assess endoscopist-related factors.
Time frame: up to 100 weeks
Cost-effectiveness of OD ((AI-A and AI-H)
A cost-effectiveness model will be applied to better quantify costs and understand cost impact including key cost drivers when generalized to a broader screening population.
Time frame: up to 100 weeks
Started Nov 2024 (actual). Primary completion is estimated for Oct 2026, 23 months after the start.
Of 132 non-industry interventional studies with no phase under Colonic Polyps, half reached primary completion within 18 months of starting (the median), counting those still running; a quarter within 10 and three quarters within 35. This study's planned 23 months is above that.
Counting every sponsor, half of 149 studies reached it within 17 months; a quarter within 9 and three quarters within 35.
How these figures are worked out, and which studies are left out of them.
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