Machine learning-based identification and characterization of mast cells in eosinophilic esophagitis.

ABSTRACT:

Background

Eosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.

Objectives

Using machine learning, we localized and characterized esophageal mast cells (MCs) to decipher their potential role in disease pathology.

Methods

Esophageal biopsy samples (EoE, control) were stained for MCs by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize MCs, designated Mast Cell-Artificial Intelligence (MC-AI).

Results

MC-AI enumerated cell counts with high accuracy. During active EoE, epithelial MCs increased and lamina propri

SUBMITTER: Zhang S 

PROVIDER: S-EPMC11070310 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature