Artificial intelligence (AI), including computer-aided detection (CADe), could revolutionize endoscopy. The adenoma detection rate (ADR) is inversely associated with the risk of postcolonoscopy colorectal cancer. The first CADe device approved in the United States (GI Genius; Medtronic, Minneapolis, MN) significantly increased the ADR and adenomas per colonoscopy (APC) and decreased the adenoma miss rate in randomized trials.
We assessed the CADe device in a 3-month trial that leveraged our Stanford Colonoscopy Quality Assurance Program infrastructure to address a research priority identified by a Delphi process with international experts: studies of real-world endoscopist–AI interaction in intended clinical pathways, reporting relevant patient outcomes. We performed a pragmatic implementation study in routine practice of the impact of CADe on a comprehensive set of colonoscopy quality metrics. By design, we used a minimalist deployment strategy, including standard startup training, but no additional measures that could affect endoscopist behavior. We hypothesized that lesion detection rates would be higher (particularly for endoscopists with lower baseline detection rates), procedure times would be longer, and non-neoplastic resection rates would be higher with vs without CADe.