Autonomous Artificial Intelligence Versus AI Assisted Human Optical Diagnosis
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age45-80
SponsorCentre hospitalier de l'Université de Montréal (CHUM)
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Indication for full colonoscopy.
Disqualifiers
Known inflammatory bowel disease
Active colitis
coagulopathy
familial polyposis syndrome
Trial design
Design model
Single group
Treatments tested in this trial
CADx (AI) system
Other interventionThe CADx system will be used to predict the histopathology of the polyp detected.
Treatment groups
540 Participants
are divided into 1 treatment groupGroup A: All participantsOther 1 intervention
Trial outcomes
Primary outcomes
1
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 weeksSecondary outcomes
1
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 weeks2
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 weeks3
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 weeks4
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 weeksSponsors and contacts
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Source ClinicalTrials.gov