Colonoscopy is central to colorectal cancer (CRC) prevention, with adenoma detection rate (ADR) serving as a key quality indicator. Artificial intelligence (AI)-based computer-aided detection (CADe) systems have been developed to assist endoscopists by highlighting subtle mucosal abnormalities during withdrawal. We report the case of a 67-year-old male who underwent AI-assisted colonoscopy for a positive faecal occult blood test, during which CADe prompted the detection and resection of 30 additional polyps not prospectively recognised during conventional white-light inspection. Histopathological analysis demonstrated predominantly tubular adenomas with low-grade dysplasia, as well as a tubulovillous adenoma with focal high-grade dysplasia. This case highlights the potential of CADe to lower the visual threshold for adenoma detection while also illustrating the associated procedural burden and clinical uncertainties surrounding extensive AI-guided lesion detection in routine practice.
Kim et al. (Mon,) studied this question.