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Future of image enhanced endoscopy of esophageal adenocarcinoma

Authors: Kerem Parlar; Mert Cakir; Ozlem Ozer; Prateek Sharma;

Future of image enhanced endoscopy of esophageal adenocarcinoma

Abstract

Barrett’s esophagus is a premalignant precursor lesion of esophageal adenocarcinoma that affects approximately 1% of the population worldwide. Esophageal adenocarcinoma has a high mortality rate with a five-year survival of 15% to 20%. Early detection of Barrett's esophagus and dysplasia via endoscopy is crucial for preventing its progression to esophageal adenocarcinoma. New imaging techniques, such as image-enhanced endoscopy, have simplified the identification of Barrett’s esophagus, dysplasia, and esophageal adenocarcinoma. Narrow-band imaging, blue-light imaging, and i-Scan are the prominent image-enhanced endoscopic techniques used to detect neoplasia. In Barrett’s screening and surveillance, key aspects such as the screening population, tools, and intervals need to be clearly defined and standardized for future guidelines to improve the detection of precursor lesions and reduce the incidence of esophageal adenocarcinoma. Making image-enhanced endoscopy less subjective and enhancing the quality measures during endoscopy are crucial steps. Examples of quality measures include cleaning the esophagus before endoscopy and allowing sufficient time for inspection. Artificial intelligence systems can aid the early identification of lesions and reduce subjectivity.

Country
Turkey
Keywords

Artificial intelligence, Barrett esophagus, RC799-869, Review, Diseases of the digestive system. Gastroenterology, artificial intelligence, RC31-1245, barrett esophagus, image-enhanced endoscopy, upper gastrointestinal endoscopy, Esophageal neoplasms, Upper gastrointestinal endoscopy, esophageal neoplasmsc, Image-enhanced endoscopy, Internal medicine

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold