A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment
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 t...
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MDPI AG
2023-09-01
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| Online Access: | https://www.mdpi.com/2306-5729/8/10/147 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Clément Germanèse |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T21:20:12Z |
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| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-10T21:20:12Z |
| publishDate | 2023-09-01 |
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| record_format | Article |
| series | Data |
| spelling | doaj.art-f84d1b1e30ed4a5ea0ca1d195b424cf92023-11-19T16:11:24ZengMDPI AGData2306-57292023-09-0181014710.3390/data8100147A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk AssessmentClément Germanèse0Fabrice Meriaudeau1Pétra Eid2Ramin Tadayoni3Dominique Ginhac4Atif Anwer5Steinberg Laure-Anne6Charles Guenancia7Catherine Creuzot-Garcher8Pierre-Henry Gabrielle9Louis Arnould10Department of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceArtificial Vision and Imaging (ImViA), Imagerie Fonctionnelle et Moléculaire et Traitement des Images Médicales (IFTIM), (EA 7535), Faculty of Health Sciences, Université de Bourgogne Franche-Comté, 21078 Dijon, FranceDepartment of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceDepartment of Ophthalmology, Université Paris Cité, AP-HP, Lariboisière, Saint Louis and Adolphe de Rothschild Fondation Hospitals, 75000 Paris, FranceArtificial Vision and Imaging (ImViA), Imagerie Fonctionnelle et Moléculaire et Traitement des Images Médicales (IFTIM), (EA 7535), Faculty of Health Sciences, Université de Bourgogne Franche-Comté, 21078 Dijon, FranceArtificial Vision and Imaging (ImViA), Imagerie Fonctionnelle et Moléculaire et Traitement des Images Médicales (IFTIM), (EA 7535), Faculty of Health Sciences, Université de Bourgogne Franche-Comté, 21078 Dijon, FranceDepartment of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceDepartment of Cardiology, Dijon University Hospital, 21079 Dijon CEDEX, FranceDepartment of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceDepartment of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceDepartment of Ophthalmology, Dijon University Hospital, 21079 Dijon CEDEX, FranceIn 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.https://www.mdpi.com/2306-5729/8/10/147retinaswept-sourceoptical coherence tomography angiographycardiovascular riskCHA<sub>2</sub>DS<sub>2</sub>-VASc |
| spellingShingle | 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 A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment Data retina swept-source optical coherence tomography angiography cardiovascular risk CHA<sub>2</sub>DS<sub>2</sub>-VASc |
| title | A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment |
| title_full | A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment |
| title_fullStr | A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment |
| title_full_unstemmed | A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment |
| title_short | A Retinal Oct-Angiography and Cardiovascular STAtus (RASTA) Dataset of Swept-Source Microvascular Imaging for Cardiovascular Risk Assessment |
| title_sort | retinal oct angiography and cardiovascular status rasta dataset of swept source microvascular imaging for cardiovascular risk assessment |
| topic | retina swept-source optical coherence tomography angiography cardiovascular risk CHA<sub>2</sub>DS<sub>2</sub>-VASc |
| url | https://www.mdpi.com/2306-5729/8/10/147 |
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