dc.contributor.author | Parlar, Kerem | |
dc.contributor.author | Cakir, Mert | |
dc.contributor.author | Ozer, Ozlem | |
dc.contributor.author | Sharma, Prateek | |
dc.date.accessioned | 2025-10-06T06:29:27Z | |
dc.date.available | 2025-10-06T06:29:27Z | |
dc.date.issued | 2025 | |
dc.identifier.issn | 2234-2443 | |
dc.identifier.issn | 2234-2400 | |
dc.identifier.uri | https://doi.org/10.5946/ce.2024.324 | |
dc.identifier.uri | http://hdl.handle.net/11446/5436 | |
dc.description.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 adeno-carcinoma. 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 esoph-ageal 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. © 2025 Elsevier B.V., All rights reserved. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Korean Society of Gastrointestinal Endoscopy | en_US |
dc.relation.ispartof | Clinical Endoscopy | en_US |
dc.identifier.doi | 10.5946/ce.2024.324 | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Barrett Esophagus | en_US |
dc.subject | Esophageal Neoplasms | en_US |
dc.subject | Image-enhanced Endoscopy | en_US |
dc.subject | Upper Gastrointestinal Endoscopy | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Barrett Esophagus | en_US |
dc.subject | Blue Light | en_US |
dc.subject | Clinical Practice Guideline | en_US |
dc.subject | Diagnosis | en_US |
dc.subject | Endoscopy | en_US |
dc.subject | Esophageal Adenocarcinoma | en_US |
dc.subject | Esophagus | en_US |
dc.subject | Esophagus Tumor | en_US |
dc.subject | Gastrointestinal Endoscopy | en_US |
dc.subject | Human | en_US |
dc.subject | Mortality Rate | en_US |
dc.subject | Narrow Band Imaging | en_US |
dc.subject | Practice Guideline | en_US |
dc.subject | Review | en_US |
dc.title | Future of image enhanced endoscopy of esophageal adenocarcinoma | en_US |
dc.type | review | en_US |
dc.department | DBÜ | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.volume | 58 | en_US |
dc.identifier.startpage | 503 | en_US |
dc.identifier.endpage | 513 | en_US |
dc.relation.publicationcategory | other | en_US |
dc.department-temp | Parlar, Kerem, Department of Internal Medicine, İstanbul University-Cerrahpaşa Cerrahpaşa Faculty of Medicine, Istanbul, Turkey; Cakir, Mert, Department of Internal Medicine, Demiroglu Bilim University, Istanbul, Turkey; Ozer, Ozlem, Department of Internal Medicine, Demiroglu Bilim University, Istanbul, Turkey; Sharma, Prateek, Division of Gastroenterology and Hepatology, University of Kansas School of Medicine, Kansas City, United States | en_US |
dc.identifier.scopus | 2-s2.0-105013232507 | en_US |
dc.identifier.scopusquality | Q2 | en_US |
dc.snmz | KA_Scopus_20251006 | |
dc.indekslendigikaynak | Scopus | en_US |