Colonoscopy in the artificial intelligence era: Spotlight on adenoma miss rate

This letter addresses the recent systematic review and meta-analysis by Wang <i>et al</i>, which evaluated the role of artificial intelligence-based computer-aided detection (CADe) in reducing adenoma and polyp miss rates during colonoscopy. We commend the authors for highlighting adenoma miss rate (AMR) as a more clinically meaningful endpoint than the traditionally used adenoma detection rate. Their findings demonstrate a significant reduction in AMR and polyp miss rate with CADe-assisted colonoscopy, particularly in small and sessile serrated lesions. However, limitations, including limited study numbers, tandem study design of included studies, and heterogeneity of CADe systems, warrant cautious interpretation. We discuss the broader implications of these findings for real-world practice and future research directions. This letter reinforces the importance of AMR as a performance metric and supports the continued integration and evaluation of artificial intelligence technologies in endoscopic practice to enhance colorectal cancer prevention strategies.