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Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis

A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of...

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Autores principales: Ghanian, Zahra, Staniszewski, Kevin, Jamali, Nasim, Sepehr, Reyhaneh, Wang, Shoujian, Sorenson, Christine M., Sheibani, Nader, Ranji, Mahsa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855887/
https://www.ncbi.nlm.nih.gov/pubmed/27186534
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author Ghanian, Zahra
Staniszewski, Kevin
Jamali, Nasim
Sepehr, Reyhaneh
Wang, Shoujian
Sorenson, Christine M.
Sheibani, Nader
Ranji, Mahsa
author_facet Ghanian, Zahra
Staniszewski, Kevin
Jamali, Nasim
Sepehr, Reyhaneh
Wang, Shoujian
Sorenson, Christine M.
Sheibani, Nader
Ranji, Mahsa
author_sort Ghanian, Zahra
collection PubMed
description A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner.
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spelling pubmed-48558872016-05-16 Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis Ghanian, Zahra Staniszewski, Kevin Jamali, Nasim Sepehr, Reyhaneh Wang, Shoujian Sorenson, Christine M. Sheibani, Nader Ranji, Mahsa J Med Signals Sens Original Article A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4855887/ /pubmed/27186534 Text en Copyright: © 2016 Journal of Medical Signals & Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Ghanian, Zahra
Staniszewski, Kevin
Jamali, Nasim
Sepehr, Reyhaneh
Wang, Shoujian
Sorenson, Christine M.
Sheibani, Nader
Ranji, Mahsa
Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title_full Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title_fullStr Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title_full_unstemmed Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title_short Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis
title_sort quantitative assessment of retinopathy using multi-parameter image analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4855887/
https://www.ncbi.nlm.nih.gov/pubmed/27186534
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