Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections

Background. Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis fo...

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Main Authors: Nayana Damiani Macedo, Aline Rodrigues Buzin, Isabela Bastos de Araujo, Breno Valentim Nogueira, Tadeu Uggere Andrade, Denise Coutinho Endringer, Dominik Lenz
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Immunology Research
Online Access:http://dx.doi.org/10.1155/2019/7232781
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author Nayana Damiani Macedo
Aline Rodrigues Buzin
Isabela Bastos de Araujo
Breno Valentim Nogueira
Tadeu Uggere Andrade
Denise Coutinho Endringer
Dominik Lenz
author_facet Nayana Damiani Macedo
Aline Rodrigues Buzin
Isabela Bastos de Araujo
Breno Valentim Nogueira
Tadeu Uggere Andrade
Denise Coutinho Endringer
Dominik Lenz
author_sort Nayana Damiani Macedo
collection DOAJ
description Background. Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia. Methods. Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells. Results. VEGF was detected and cells were counted with high sensitivity and specificity. Conclusion. With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.
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institution Kabale University
issn 2314-8861
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language English
publishDate 2019-01-01
publisher Wiley
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series Journal of Immunology Research
spelling doaj-art-8107a774963f40d2babbf94af87c224c2025-02-03T06:13:12ZengWileyJournal of Immunology Research2314-88612314-71562019-01-01201910.1155/2019/72327817232781Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue SectionsNayana Damiani Macedo0Aline Rodrigues Buzin1Isabela Bastos de Araujo2Breno Valentim Nogueira3Tadeu Uggere Andrade4Denise Coutinho Endringer5Dominik Lenz6University Vila Velha, Pharmaceutical Sciences, Vila Velha, BrazilUniversity Vila Velha, Pharmaceutical Sciences, Vila Velha, BrazilDepartment of Morphology, Federal University of Espírito Santo, Vitória, BrazilDepartment of Morphology, Federal University of Espírito Santo, Vitória, BrazilUniversity Vila Velha, Pharmaceutical Sciences, Vila Velha, BrazilUniversity Vila Velha, Pharmaceutical Sciences, Vila Velha, BrazilUniversity Vila Velha, Pharmaceutical Sciences, Vila Velha, BrazilBackground. Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia. Methods. Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells. Results. VEGF was detected and cells were counted with high sensitivity and specificity. Conclusion. With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.http://dx.doi.org/10.1155/2019/7232781
spellingShingle Nayana Damiani Macedo
Aline Rodrigues Buzin
Isabela Bastos de Araujo
Breno Valentim Nogueira
Tadeu Uggere Andrade
Denise Coutinho Endringer
Dominik Lenz
Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
Journal of Immunology Research
title Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
title_full Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
title_fullStr Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
title_full_unstemmed Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
title_short Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections
title_sort automated and reproducible detection of vascular endothelial growth factor vegf in renal tissue sections
url http://dx.doi.org/10.1155/2019/7232781
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