Advanced Imaging and Sampling in Barrett's Esophagus: Artificial Intelligence to the Rescue?

Maarten R. Struyvenberg, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With, Vani J. A. Konda, Wouter L. Curvers

Research output: Contribution to JournalReview articleAcademicpeer-review

1 Citation (Scopus)

Abstract

Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neoplastic lesions, many new endoscopic imaging and sampling techniques have been developed. None of these techniques, however, have significantly increased the diagnostic yield of BE neoplasia. In fact, these techniques have led to an increase in the amount of visible information, yet endoscopists and pathologists inevitably suffer from variations in intra- and interobserver agreement. Artificial intelligence systems have the potential to overcome these endoscopist-dependent limitations.
Original languageEnglish
Pages (from-to)91-103
Number of pages13
JournalGastrointestinal endoscopy clinics of North America
Volume31
Issue number1
Early online date2020
DOIs
Publication statusPublished - Jan 2021

Keywords

  • Artificial intelligence
  • Barrett's esophagus
  • Early neoplasia
  • Endoscopy

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