This study evaluates whether an artificial intelligence system (GI Genius, Medtronic), already approved by Health Canada, can help doctors accurately identify, in real time during colonoscopy, which small colorectal polyps (5 mm or less) need to be monitored (adenomas) versus those that do not (for example, hyperplastic polyps). For each small polyp found, the endoscopist will first record a diagnosis without the help of the artificial intelligence system, then activate the system and record a second diagnosis after seeing its assessment. Both diagnoses will be compared to the final result from standard pathology testing, which remains the reference standard. This is an observational diagnostic accuracy study: it does not change any clinical care. All polyps continue to be removed and sent for pathology analysis as usual, whether or not the artificial intelligence system agrees with the doctor. The study will take place during colonoscopies already scheduled for standard clinical reasons (screening, surveillance, or diagnostic work-up), with no additional visits, blood draws, imaging, or sedation. Approximately 840 participants will be enrolled across three Canadian centres (Santé Québec - CHUM, McGill University Health Centre, and St. Paul's Hospital, Vancouver). The goal is to determine whether this AI-assisted approach helps doctors reach the internationally recognized performance thresholds (at least 80% sensitivity and 80% specificity) needed to support clinical adoption of real-time optical diagnosis, which could eventually reduce unnecessary pathology testing.
Inclusion Criteria:
Exclusion Criteria:
daniel.von.renteln.med@ssss.gouv.qc.ca
Consecutive patients aged 45-80 undergoing elective colonoscopy (screening, surveillance, or diagnostic) at CHUM, CUSM, and St. Paul's Hospital who provide written informed consent before the colonoscopy and before sedation, and in whom at least one diminutive polyp (≤5 mm) is detected during the procedure. For each diminutive polyp, the endoscopist first records a CADx-unassisted optical diagnosis and confidence level (electronically locked before device activation), then activates the GI Genius CADx module, and records a final CADx-assisted optical diagnosis and confidence level after viewing the device-provided characterization. All polyps are resected and sent for histopathological examination, which serves as the reference standard.
samira.hanin.chum@ssss.gouv.qc.ca514-890-8000 ext. 30916
Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps
Real-time Diagnosis of Diminutive Colorectal Polyps Using AI
AI-Assisted Real-Time Endoscopic Characterization of Diminutive Colorectal Polyps in Non-Academic Hospitals
Real-World Validation of an Artificial Intelligence Characterization Support (CADx) System
Artificial Intelligence (AI) Assisted Real-time Adenoma Detection and Classification During Colonoscopies
Accuracy of CADx System for White Light Colonic Polyp Characterization
Autonomous Artificial Intelligence Versus AI Assisted Human Optical Diagnosis
Impact of Computer-aided Optical Diagnosis (CAD) in Predicting Histology of Diminutive Rectosigmoid Polyps: a Multicenter Prospective Trial (ABC Study).