AI in Colonoscopy Polyp Detection

Colorectal cancer usually develops from adenomas, a type of polyp. The key quality measure for colonoscopy is the adenoma detection rate (ADR): the share of screening procedures in which at least one adenoma is found. A widely cited 2014 study in the New England Journal of Medicine linked higher endoscopist ADR to lower risk of cancers appearing between screenings, roughly a 3 percent reduction in risk for each 1 percentage point increase in ADR. CADe systems connect to the endoscopy video processor and analyze each frame. When the model detects a likely polyp, it overlays a box, often with a sound. Medtronic's GI Genius became the first CADe device authorized by the FDA, in 2021; others include Olympus ENDO-AID, Fujifilm CAD EYE and Wision EndoScreener. Many randomized trials and meta-analyses show CADe increases ADR and adenomas found per colonoscopy. The gains are mostly in small and diminutive adenomas under about 5 mm, which have lower cancer risk than larger or flat advanced lesions. CADe also increases removal of non-neoplastic polyps, adding pathology cost and slight procedure time. Some real-world, non-randomized studies have found smaller or no improvements, possibly because endoscopists in trials know they are being measured. Deskilling is a growing concern. A 2025 observational study from Poland reported that endoscopists' ADR on procedures done without AI fell after they had been routinely using AI, suggesting reliance may dull unaided vigilance. That study was not randomized and does not settle the question, but it shows the need to monitor skills. A common misconception is that CADe improves detection by seeing what humans cannot. Much of its benefit is catching polyps that were visible on screen but not noticed. It cannot help with mucosa the camera never shows, so bowel preparation and careful withdrawal technique still matter.