A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze im...

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Authors: Díez Sotelo, Marta, Díaz, M., Abraldes Lopez-Veiga, Maximino, Gómez-Ulla, F., G Penedo, M., Ortega, M.
Format: article
Publication Date:2019
Country:España
Institution:Servizo Galego de Saúde (SERGAS)
Repository:RUNA. Repositorio da Consellería de Sanidade e Sergas
OAI Identifier:oai:runa.sergas.gal:20.500.11940/15424
Online Access:https://www.ncbi.nlm.nih.gov/pubmed/31547127
http://hdl.handle.net/20.500.11940/15424
Access Level:Open access
Keyword:Retinal Vein Occlusion
CHUS
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spelling A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography AngiographyDíez Sotelo, MartaDíaz, M.Abraldes Lopez-Veiga, MaximinoGómez-Ulla, F.G Penedo, M.Ortega, M.Retinal Vein OcclusionCHUSThe assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.2019info:eu-repo/semantics/articlehttps://www.ncbi.nlm.nih.gov/pubmed/31547127http://hdl.handle.net/20.500.11940/15424reponame:RUNA. Repositorio da Consellería de Sanidade e Sergasinstname:Servizo Galego de Saúde (SERGAS)Ingléshttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:runa.sergas.gal:20.500.11940/154242026-06-12T08:40:47Z
dc.title.none.fl_str_mv A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
title A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
spellingShingle A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
Díez Sotelo, Marta
Retinal Vein Occlusion
CHUS
title_short A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
title_full A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
title_fullStr A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
title_full_unstemmed A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
title_sort A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
dc.creator.none.fl_str_mv Díez Sotelo, Marta
Díaz, M.
Abraldes Lopez-Veiga, Maximino
Gómez-Ulla, F.
G Penedo, M.
Ortega, M.
author Díez Sotelo, Marta
author_facet Díez Sotelo, Marta
Díaz, M.
Abraldes Lopez-Veiga, Maximino
Gómez-Ulla, F.
G Penedo, M.
Ortega, M.
author_role author
author2 Díaz, M.
Abraldes Lopez-Veiga, Maximino
Gómez-Ulla, F.
G Penedo, M.
Ortega, M.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Retinal Vein Occlusion
CHUS
topic Retinal Vein Occlusion
CHUS
description The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://www.ncbi.nlm.nih.gov/pubmed/31547127
http://hdl.handle.net/20.500.11940/15424
url https://www.ncbi.nlm.nih.gov/pubmed/31547127
http://hdl.handle.net/20.500.11940/15424
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:RUNA. Repositorio da Consellería de Sanidade e Sergas
instname:Servizo Galego de Saúde (SERGAS)
instname_str Servizo Galego de Saúde (SERGAS)
reponame_str RUNA. Repositorio da Consellería de Sanidade e Sergas
collection RUNA. Repositorio da Consellería de Sanidade e Sergas
repository.name.fl_str_mv
repository.mail.fl_str_mv
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