Background and Aims
Several artificial intelligence (AI) systems for polyp detection during colonoscopy have emerged in the gastroenterology literature and continue to demonstrate significant improvements in quality outcomes. This study assesses clinical quality outcomes during white-light colonoscopy with and without a novel AI computer-aided detection system, DEtection of Elusive Polyps (DEEP2), using Fuji 7000 series colonoscopes (Fujifilm, Singapore).
Methods
An unblinded, randomized (1:1), controlled, prospective study was performed at a single ambulatory care endoscopy center under institutional review board approval. Included participants ages 40 to 85 years were scheduled to undergo colonoscopy for screening, surveillance, or symptoms. Exclusion criteria were inflammatory bowel disease, prior colorectal surgery, known polyp referral, pregnancy, inadequate bowel prep, and incomplete colonoscopies. DEEP2 was trained and validated only on white-light imaging, excluding the use of continuous digital chromoendoscopy.