Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy

Purpose To investigate the correlation between quantifiable vessel density, computed in an automated fashion, from ultra-widefield fluorescein angiography (UWFFA) images from patients with proliferative diabetic retinopathy (PDR) with visual acuity and macular thickness. Methods We performed a secon...

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Main Authors: Mohammad H. Bawany, Li Ding, Rajeev S. Ramchandran, Gaurav Sharma, Charles C. Wykoff, Ajay E. Kuriyan, Alfred S Lewin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485882/?tool=EBI
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spelling doaj-97d3238cd5dc477b9fa439a68e6b51182020-11-25T01:19:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01159Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathyMohammad H. BawanyLi DingRajeev S. RamchandranGaurav SharmaCharles C. WykoffAjay E. KuriyanAlfred S LewinPurpose To investigate the correlation between quantifiable vessel density, computed in an automated fashion, from ultra-widefield fluorescein angiography (UWFFA) images from patients with proliferative diabetic retinopathy (PDR) with visual acuity and macular thickness. Methods We performed a secondary analysis of a prospective randomized controlled trial. We designed and trained an algorithm to automate retinal vessel detection from input UWFFA images. We then used our algorithm to study the correlation between baseline vessel density and best corrected visual acuity (BCVA) and CRT for patients in the RECOVERY study. Reliability of the algorithm was tested using the intraclass correlation (ICC). 42 patients from the Intravitreal Aflibercept for Retinal Non-Perfusion in Proliferative Diabetic Retinopathy (RECOVERY) trial who had both baseline UWFFA images and optical coherence tomography (OCT) data were included in our study. These patients had PDR without significant center-involving diabetic macular edema (central retinal thickness [CRT] ≤320μm). Results Our algorithm analyzed UWFFA images with a reliability measure (ICC) of 0.98. A positive correlation (r = 0.4071, p = 0.0075) was found between vessel density and BCVA. No correlation was found between vessel density and CRT. Conclusions Our algorithm is capable of reliably quantifying vessel density in an automated fashion from baseline UWFFA images. We found a positive correlation between computed vessel density and BCVA in PDR patients without center-involving macular edema, but not CRT. Translational relevance Our work is the first to offer an algorithm capable of quantifying vessel density in an automated fashion from UWFFA images, allowing us to work toward studying the relationship between retinal vascular changes and important clinical endpoints, including visual acuity, in ischemic eye diseases.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485882/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Mohammad H. Bawany
Li Ding
Rajeev S. Ramchandran
Gaurav Sharma
Charles C. Wykoff
Ajay E. Kuriyan
Alfred S Lewin
spellingShingle Mohammad H. Bawany
Li Ding
Rajeev S. Ramchandran
Gaurav Sharma
Charles C. Wykoff
Ajay E. Kuriyan
Alfred S Lewin
Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
PLoS ONE
author_facet Mohammad H. Bawany
Li Ding
Rajeev S. Ramchandran
Gaurav Sharma
Charles C. Wykoff
Ajay E. Kuriyan
Alfred S Lewin
author_sort Mohammad H. Bawany
title Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
title_short Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
title_full Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
title_fullStr Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
title_full_unstemmed Automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
title_sort automated vessel density detection in fluorescein angiography images correlates with vision in proliferative diabetic retinopathy
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description Purpose To investigate the correlation between quantifiable vessel density, computed in an automated fashion, from ultra-widefield fluorescein angiography (UWFFA) images from patients with proliferative diabetic retinopathy (PDR) with visual acuity and macular thickness. Methods We performed a secondary analysis of a prospective randomized controlled trial. We designed and trained an algorithm to automate retinal vessel detection from input UWFFA images. We then used our algorithm to study the correlation between baseline vessel density and best corrected visual acuity (BCVA) and CRT for patients in the RECOVERY study. Reliability of the algorithm was tested using the intraclass correlation (ICC). 42 patients from the Intravitreal Aflibercept for Retinal Non-Perfusion in Proliferative Diabetic Retinopathy (RECOVERY) trial who had both baseline UWFFA images and optical coherence tomography (OCT) data were included in our study. These patients had PDR without significant center-involving diabetic macular edema (central retinal thickness [CRT] ≤320μm). Results Our algorithm analyzed UWFFA images with a reliability measure (ICC) of 0.98. A positive correlation (r = 0.4071, p = 0.0075) was found between vessel density and BCVA. No correlation was found between vessel density and CRT. Conclusions Our algorithm is capable of reliably quantifying vessel density in an automated fashion from baseline UWFFA images. We found a positive correlation between computed vessel density and BCVA in PDR patients without center-involving macular edema, but not CRT. Translational relevance Our work is the first to offer an algorithm capable of quantifying vessel density in an automated fashion from UWFFA images, allowing us to work toward studying the relationship between retinal vascular changes and important clinical endpoints, including visual acuity, in ischemic eye diseases.
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485882/?tool=EBI
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