Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

ABSTRACT: Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The Cytosponge-TFF3 test, a non-endoscopic minimally invasive procedure, has been used for diagnosing intestinal metaplasia in Barrett's. However, it depends on pathologist's assessment of two slides stained with H&E and the immunohistochemical biomarker TFF3. This resource-intensive clinical workflow limits large-scale screening in the at-risk population. To improve screening capacity, we propose a deep learning approach for detecting Barrett's from routinely stained H&E slides. The approach solely relies on diagnostic labels, eliminating the need for expensive localized expert annotations. We train and independently validate our approach on two clinical t

SUBMITTER: Bouzid K 

PROVIDER: S-EPMC10928093 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature