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本文引用的文献

1
Deep Learning for Image Analysis in the Diagnosis and Management of Esophageal Cancer.深度学习在食管癌诊断与管理中的图像分析应用
Cancers (Basel). 2024 Sep 26;16(19):3285. doi: 10.3390/cancers16193285.
2
Analytical Validation of a DNA Methylation Biomarker Test for the Diagnosis of Barrett's Esophagus and Esophageal Adenocarcinoma from Samples Collected Using EsoCheck, a Non-Endoscopic Esophageal Cell Collection Device.使用非内镜食管细胞采集装置EsoCheck收集的样本进行DNA甲基化生物标志物检测以诊断巴雷特食管和食管腺癌的分析验证
Diagnostics (Basel). 2024 Aug 15;14(16):1784. doi: 10.3390/diagnostics14161784.
3
Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.用于胃肠道肿瘤图像分析的内镜人工智能
Digestion. 2024;105(6):419-435. doi: 10.1159/000540251. Epub 2024 Jul 26.
4
Deep Learning for Histopathological Assessment of Esophageal Adenocarcinoma Precursor Lesions.深度学习在食管腺癌前病变的组织病理学评估中的应用。
Mod Pathol. 2024 Aug;37(8):100531. doi: 10.1016/j.modpat.2024.100531. Epub 2024 Jun 1.
5
Development of an Artificial Intelligence Diagnostic System Using Linked Color Imaging for Barrett's Esophagus.利用链接彩色成像技术开发用于巴雷特食管的人工智能诊断系统
J Clin Med. 2024 Mar 29;13(7):1990. doi: 10.3390/jcm13071990.
6
Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett's esophagus: a tandem randomized and video trial.人工智能对内镜医师评估 Barrett 食管诊断性能的影响:一项串联随机和视频试验。
Endoscopy. 2024 Sep;56(9):641-649. doi: 10.1055/a-2296-5696. Epub 2024 Mar 28.
7
Advances in Screening for Barrett Esophagus and Esophageal Adenocarcinoma.巴雷特食管和食管腺癌筛查的进展。
Mayo Clin Proc. 2024 Mar;99(3):459-473. doi: 10.1016/j.mayocp.2023.07.014. Epub 2024 Jan 25.
8
The prospective validation of a scoring system to assess mucosal cleanliness during EGD.内镜检查时评估黏膜清洁度的评分系统的前瞻性验证。
Gastrointest Endosc. 2024 Jul;100(1):27-35. doi: 10.1016/j.gie.2024.01.012. Epub 2024 Jan 11.
9
Artificial intelligence system for the detection of Barrett's esophagus.人工智能系统用于 Barrett 食管的检测。
World J Gastroenterol. 2023 Dec 28;29(48):6198-6207. doi: 10.3748/wjg.v29.i48.6198.
10
Advanced endoscopic imaging for detection of Barrett's esophagus.用于检测巴雷特食管的先进内镜成像技术。
Clin Endosc. 2024 Jan;57(1):1-10. doi: 10.5946/ce.2023.031. Epub 2024 Jan 5.

食管腺癌图像增强内镜检查的未来

Future of image enhanced endoscopy of esophageal adenocarcinoma.

作者信息

Parlar Kerem, Cakir Mert, Ozer Ozlem, Sharma Prateek

机构信息

Department of Internal Medicine, Istanbul University Cerrahpasa Faculty of Medicine, Istanbul, Turkey.

Division of Gastroenterology and Hepatology, Department of Internal Medicine, Istanbul Demiroglu Bilim University Faculty of Medicine, Istanbul, Turkey.

出版信息

Clin Endosc. 2025 Jul;58(4):503-513. doi: 10.5946/ce.2024.324. Epub 2025 May 20.

DOI:10.5946/ce.2024.324
PMID:40394929
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12314617/
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.

摘要

巴雷特食管是食管腺癌的一种癌前病变,全球约1%的人口受其影响。食管腺癌死亡率高,五年生存率为15%至20%。通过内镜检查早期发现巴雷特食管和发育异常对于预防其进展为食管腺癌至关重要。新的成像技术,如图像增强内镜检查,简化了巴雷特食管、发育异常和食管腺癌的识别。窄带成像、蓝光成像和i-Scan是用于检测肿瘤形成的突出的图像增强内镜技术。在巴雷特食管的筛查和监测中,筛查人群、工具和间隔等关键方面需要明确界定并标准化,以便未来制定指南,提高癌前病变的检测率并降低食管腺癌的发病率。使图像增强内镜检查减少主观性并提高内镜检查期间的质量控制措施是关键步骤。质量控制措施的例子包括在内镜检查前清洁食管并留出足够的检查时间。人工智能系统可以帮助早期识别病变并减少主观性。