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Clin Colon Rectal Surg
DOI: 10.1055/a-2769-1233
Review Article

Artificial Intelligence and Its Role in Endoscopic Adenoma and Cancer Detection

Authors

  • Hannah R. Phillips

    1   Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, United States

  • Wilfor J. Diaz Fernandez

    1   Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, United States

  • Cadman L. Leggett

    1   Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, United States
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Abstract

Colorectal cancer incidence and mortality have declined over time, due in part to high-quality screening and surveillance colonoscopy. Nevertheless, postcolonoscopy colorectal cancer (PCCRC) occurs in up to 7% of cases and is inversely related to examination quality. Artificial intelligence-assisted colonoscopy aims to improve performance metrics and, ultimately, patient outcomes. Multiple randomized trials show that computer-aided polyp detection (CADe) increases adenoma detection, predominantly for diminutive lesions (≤5 mm). Computer-aided polyp characterization (CADx) enables real-time optical diagnosis, potentially shifting management of diminutive polyps by supporting resect-and-discard and diagnose-and-leave in situ strategies. Computer-aided quality assessment (CAQ) systems monitor key metrics—including cecal intubation rate, withdrawal time, speed, and mucosal exposure. Whether CADe alone leads to a reduction in PCCRC or cancer-related mortality remains to be determined; in the near term, a combined approach using CADe, CADx, and CAQ is most likely to deliver the greatest improvements in patient outcomes.

Keywords

artificial intelligence - colonoscopy - colorectal polyps - colorectal cancer


Publication History

Article published online:
07 January 2026

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