Predicting cardiovascular disease risk using retinal optical coherence tomography imaging.

ABSTRACT:

Introduction

Cardiovascular Diseases (CVD) are the leading cause of death globally. Non-invasive, cost-effective imaging techniques play a crucial role in early detection and prevention of CVD. Optical Coherence Tomography (OCT) has gained recognition as a noninvasive method of detecting microvascular alterations that might enable earlier identification and targeting of at-risk patients. In this study, we investigated the potential of OCT as an additional imaging technique to predict future CVD events.

Methods

We analyzed retinal OCT data from the UK Biobank. The dataset included 612 patients who suffered a Myocardial Infarction (MI) or stroke within five years of imaging and 2,234 controls without CVD (total: 2,846 participants). A self-supervised deep learning approach bas

SUBMITTER: Maldonado-Garcia C 

PROVIDER: S-EPMC12669110 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature