Clin Endosc.  2023 Jan;56(1):14-22. 10.5946/ce.2022.247.

Role of artificial intelligence in diagnosing Barrett’s esophagus-related neoplasia

• Meinikheim M
• Messmann H
• Ebigbo A

• KMID: 2538747
• DOI: http://doi.org/10.5946/ce.2022.247

Abstract

Barrett’s esophagus is associated with an increased risk of adenocarcinoma. Thorough screening during endoscopic surveillance is crucial to improve patient prognosis. Detecting and characterizing dysplastic or neoplastic Barrett’s esophagus during routine endoscopy are challenging, even for expert endoscopists. Artificial intelligence-based clinical decision support systems have been developed to provide additional assistance to physicians performing diagnostic and therapeutic gastrointestinal endoscopy. In this article, we review the current role of artificial intelligence in the management of Barrett’s esophagus and elaborate on potential artificial intelligence in the future.

Keyword

Adenocarcinoma; Artificial intelligence; Barrett esophagus; Deep learning; Endoscopy

Figure

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  Fig. 1. Images of Barrett’s esophagus-related neoplasia during endoscopy with an Olympus Evis X1 system (Olympus, Tokyo, Japan) in high-definition white light endoscopy (A), narrow band imaging (B), acetic acid chromoendoscopy (C), and chromoendoscopy with indigo carmine (D).

• 

  Fig. 2. Detection and characterization of Barrett’s esophagus-related neoplasia during endoscopy with Olympus Evis X1 system using an AI system developed by the University Hospital of Augsburg and Ostbayerische Technische Hochschule Regensburg (OTH-Regensburg) with classification and segmentation in narrow band imaging (A), texture and color enhancement imaging (B) and high-definition white light endoscopy (C). The corresponding heatmaps are available at the top left corner of the user interface.

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