Year: 2025
Type: article
Abstract: , 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.
Authors: Kalpana Panda, Girish K Pati, Devi P Dash
Institution: Institute of Medical Sciences and Sum Hospital
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funder: Boston Scientific Corporation
OpenAlex ID: W4415389228