Bibliographic Details
| Title: |
Advanced endoscopic imaging for detection of Barrett's esophagus. |
| Authors: |
Zilberstein, Netanel1, Godbee, Michelle1, Mehta, Neal A.1, Waxman, Irving1 Irving_waxman@rush.edu |
| Source: |
Clinical Endoscopy. Jan2024, Vol. 57 Issue 1, p1-10. 10p. |
| Subject Terms: |
*BARRETT'S esophagus, *SAMPLING errors, *DIAGNOSIS, *ARTIFICIAL intelligence |
| Geographic Terms: |
SEATTLE (Wash.) |
| Abstract: |
Barrett's esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC), and is caused by chronic gastroesophageal reflux. BE can progress over time from metaplasia to dysplasia, and eventually to EAC. EAC is associated with a poor prognosis, often due to advanced disease at the time of diagnosis. However, if BE is diagnosed early, pharmacologic and endoscopic treatments can prevent progression to EAC. The current standard of care for BE surveillance utilizes the Seattle protocol. Unfortunately, a sizable proportion of early EAC and BE-related high-grade dysplasia (HGD) are missed due to poor adherence to the Seattle protocol and sampling errors. New modalities using artificial intelligence (AI) have been proposed to improve the detection of early EAC and BE-related HGD. This review will focus on AI technology and its application to various endoscopic modalities such as high-definition white light endoscopy, narrow-band imaging, and volumetric laser endomicroscopy. [ABSTRACT FROM AUTHOR] |
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| Database: |
Academic Search Complete |
