Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.

Journal: The lancet. Gastroenterology & hepatology
Published Date: Dec 6, 2018

Abstract

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance. Pooled miss rates for polyps are as high as 22%, and associated interval colorectal cancers after colonoscopy are of concern. Optical biopsy, whereby in-vivo classification of polyps based on enhanced imaging replaces histopathology, has not been incorporated into routine practice because it is limited by interobserver variability and generally only meets accepted standards in expert settings. Real-time decision-support software has been developed to detect and characterise polyps, and also to offer feedback on the technical quality of inspection. Some of the current algorithms, particularly with recent advances in artificial intelligence techniques, match human expert performance for optical biopsy. In this Review, we summarise the evidence for clinical applications of computer-aided diagnosis and artificial intelligence in colonoscopy.

Authors

  • Omer F Ahmad
    Department of Gastroenterology, University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2BU, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, Charles Bell House, 43-45 Foley Street, London, W1W 7TS, United Kingdom. Electronic address: ofahmad123@gmail.com.
  • Antonio S Soares
    Division of Surgery & Interventional Science, University College London, London, UK.
  • Evangelos Mazomenos
    Wellcome/EPSRC Centre for Interventional & Surgical Sciences, University College London, London, UK.
  • Patrick Brandao
    Wellcome/EPSRC Centre for Interventional & Surgical Sciences, University College London, London, UK.
  • Roser Vega
    Gastrointestinal Services, University College London Hospital, London, UK.
  • Edward Seward
    Gastrointestinal Services, University College London Hospital, London, UK.
  • Danail Stoyanov
    University College London, London, UK.
  • Manish Chand
    Division of Surgery & Interventional Science, University College London, London, UK; Gastrointestinal Services, University College London Hospital, London, UK.
  • Laurence B Lovat
    Division of Surgery & Interventional Science, University College London, London, UK.

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