Deep learning assisted retinal microvasculature assessment and cerebral small vessel disease in Fabry disease.

ABSTRACT:

Purpose

The aim of this study was to assess retinal microvascular parameters (RMPs) in Fabry disease (FD) using deep learning, and analyze the correlation with brain lesions related to cerebral small vessel disease (CSVD).

Methods

In this retrospective case control study, fundus images from 27 FD patients and 27 age- and sex-matched healthy subjects were collected. RMPs, encompassing diameter, density, symmetry, bifurcation, and tortuosity, were quantified. Laboratory examination results, Mainz severity score index (MSSI) scores, and a brain magnetic resonance imaging scan for CSVD scores were extracted and their relationships with RMPs was analyzed.

Results

Utilizing artificial intelligence-assisted analysis, compared with controls, FD patients exhibited reduced diam

SUBMITTER: Li Y 

PROVIDER: S-EPMC11969690 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature