Feed

The resect-and-discard strategy for colorectal cancer prevention involves real-time optical diagnosis during colonoscopy to eliminate the need for histopathological analysis of diminutive colorectal polyps (1-5 mm). Although endorsed by international gastroenterology societies and supported by extensive evidence of diagnostic accuracy, implementation remains limited due to barriers including clinician confidence, medico-legal concerns, and procedural complexities. The emergence of artificial intelligence (AI)-based diagnostic systems has renewed interest in this strategy by potentially improving accuracy and clinician acceptance. While early real-world data indicate high patient approval and significant cost and environmental benefits, critical questions remain unanswered, including optimal techniques for accurate polyp size estimation and AI-based differentiation of specific histological features. Additionally, uncertainties regarding medico-legal liability and standardization of quality assurance processes require further clarification. This review highlights current evidence, identifies major implementation barriers, and proposes areas of future research necessary to facilitate widespread adoption of the resect-and-discard strategy.