Effect of artificial intelligence implementation to the latest generation 4K colonoscopy

Indroduction: Colonoscopy is an acclaimed screening test to detect colorectal cancer (CRC). The most important quality indicators for colonoscopy are adenoma detection rate (ADR), cecal intubation rate (CIR), withdrawal time (WT), and bowel preparation (Boston Bowel Preparation Scale; BBPS). In modern endoscopy practice, the human eye is enhanced by highdefinition white-light visualization and advanced imaging technology. The main limitation of this procedure is the detection rate of suspicious lesions. The next generation of endoscopes with 4K resolution and computer-aided detection (CADe) based on artificial intelligence (AI) may be the next step to improve the quality of tests performed. Aim: The aim was to assess the effect of CADe implementation in the environment of the latest generation of endoscopes and 4K visualization in retrospective analysis. Methods: The study included 2,000 patients over 18 years old who underwent colonoscopy for various indications. Olympus Endo-Aid CADe AI system was used, together with the latest X1 series endoscope set using LED lighting and 4K ultra high-resolution technology. Group I consisted of 1,000 consecutive tests performed using Endo-Aid CADe, and group II the first 1,000 consecutive tests without the CADe system. ADR, Advanced adenoma detection rate (AADR), polyp detection rate (PDR), and mean polyp per patient score (MPP) were assessed in each group Results: A total of 2,000 participants were included in the analysis, divided into two groups regarding CADe implementation. The overall PDR was similar in the analyzed groups (AI: 46.7% vs. non-AI: 44.9%, P = 0.419). Both ADR (29.7 vs. 28.9%, P = 0.694) and AADR (6.9 vs. 7.1%, P = 0.861) changed unremarkably. However, a significant elevation in MPP was noted. The MPP rose from 0.85 in the non-AI group to 1.26 in the AI group (P