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A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment

Authors :
Clément Germanèse
Fabrice Meriaudeau
Pétra Eid
Ramin Tadayoni
Dominique Ginhac
Atif Anwer
Steinberg Laure-Anne
Charles Guenancia
Catherine Creuzot-Garcher
Pierre-Henry Gabrielle
Louis Arnould
Source :
Data, Vol 8, Iss 10, p 147 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

In the context of exponential demographic growth, the imbalance between human resources and public health problems impels us to envision other solutions to the difficulties faced in the diagnosis, prevention, and large-scale management of the most common diseases. Cardiovascular diseases represent the leading cause of morbidity and mortality worldwide. A large-scale screening program would make it possible to promptly identify patients with high cardiovascular risk in order to manage them adequately. Optical coherence tomography angiography (OCT-A), as a window into the state of the cardiovascular system, is a rapid, reliable, and reproducible imaging examination that enables the prompt identification of at-risk patients through the use of automated classification models. One challenge that limits the development of computer-aided diagnostic programs is the small number of open-source OCT-A acquisitions available. To facilitate the development of such models, we have assembled a set of images of the retinal microvascular system from 499 patients. It consists of 814 angiocubes as well as 2005 en face images. Angiocubes were captured with a swept-source OCT-A device of patients with varying overall cardiovascular risk. To the best of our knowledge, our dataset, Retinal oct-Angiography and cardiovascular STAtus (RASTA), is the only publicly available dataset comprising such a variety of images from healthy and at-risk patients. This dataset will enable the development of generalizable models for screening cardiovascular diseases from OCT-A retinal images.

Details

Language :
English
ISSN :
23065729
Volume :
8
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Data
Publication Type :
Academic Journal
Accession number :
edsdoj.f84d1b1e30ed4a5ea0ca1d195b424cf9
Document Type :
article
Full Text :
https://doi.org/10.3390/data8100147