학술논문

Artificial Intelligence in the Management of Barrett’s Esophagus and Early Esophageal Adenocarcinoma
Document Type
article
Source
Cancers, Vol 14, Iss 8, p 1918 (2022)
Subject
artificial intelligence
gastro-esophageal reflux disease
Barrett’s esophagus
early adenocarcinoma of the esophagus
deep convolutional neuronal networks
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Language
English
ISSN
2072-6694
Abstract
Esophageal adenocarcinoma is increasing in incidence and is the most common subtype of esophageal cancer in Western societies. The stepwise progression of Barrett´s metaplasia to high-grade dysplasia and invasive adenocarcinoma provides an opportunity for screening and surveillance. There are important unresolved issues, which include (i) refining the definition of the screening population in order to avoid unnecessary invasive diagnostics, (ii) a more precise prediction of the (very heterogeneous) individual progression risk from metaplasia to invasive cancer in order to better tailor surveillance recommendations, (iii) improvement of the quality of endoscopy in order to reduce the high miss rate for early neoplastic lesions, and (iv) support for the diagnosis of tumor infiltration depth in order to guide treatment decisions. Artificial intelligence (AI) systems might be useful as a support to better solve the above-mentioned issues.