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OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma

PURPOSE: To develop and assess an automatic procedure for classifying and staging glaucomatous vascular damage based on optical coherence tomography angiography (OCTA) imaging. METHODS: OCTA scans (Zeiss Cirrus 5000 HD-OCT) from a random eye of 39 healthy subjects and 82 glaucoma patients were used...

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Autores principales: Andrade De Jesus, Danilo, Sánchez Brea, Luisa, Barbosa Breda, João, Fokkinga, Ella, Ederveen, Vera, Borren, Noor, Bekkers, Amerens, Pircher, Michael, Stalmans, Ingeborg, Klein, Stefan, van Walsum, Theo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674004/
https://www.ncbi.nlm.nih.gov/pubmed/33224631
http://dx.doi.org/10.1167/tvst.9.2.58
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author Andrade De Jesus, Danilo
Sánchez Brea, Luisa
Barbosa Breda, João
Fokkinga, Ella
Ederveen, Vera
Borren, Noor
Bekkers, Amerens
Pircher, Michael
Stalmans, Ingeborg
Klein, Stefan
van Walsum, Theo
author_facet Andrade De Jesus, Danilo
Sánchez Brea, Luisa
Barbosa Breda, João
Fokkinga, Ella
Ederveen, Vera
Borren, Noor
Bekkers, Amerens
Pircher, Michael
Stalmans, Ingeborg
Klein, Stefan
van Walsum, Theo
author_sort Andrade De Jesus, Danilo
collection PubMed
description PURPOSE: To develop and assess an automatic procedure for classifying and staging glaucomatous vascular damage based on optical coherence tomography angiography (OCTA) imaging. METHODS: OCTA scans (Zeiss Cirrus 5000 HD-OCT) from a random eye of 39 healthy subjects and 82 glaucoma patients were used to develop a new classification algorithm based on multilayer and multisector information. The averaged circumpapillary retinal nerve fiber layer (RNFL) thickness was also collected. Three models, support vector machine (SVM), random forest (RF), and gradient boosting (xGB), were developed and optimized for classifying between healthy and glaucoma patients, primary open-angle glaucoma (POAG) and normal-tension glaucoma (NTG), and glaucoma severity groups. RESULTS: All the models, the SVM (area under the receiver operating characteristic [AUROC] 0.89 ± 0.06), the RF (AUROC 0.86 ± 0.06), and the xGB (AUROC 0.85 ± 0.07), with 26, 22, and 29 vascular features obtained after feature selection, respectively, presented a similar performance to the RNFL thickness (AUROC 0.85 [Formula: see text] 0.06) in classifying healthy and glaucoma patients. The superficial vascular plexus was the most informative layer with the infero temporal sector as the most discriminative region of interest. No significant differentiation was obtained in discriminating the POAG from the NTG group. The xGB model, after feature selection, presented the best performance in classifying the severity groups (AUROC 0.76 [Formula: see text] 0.06), outperforming the RNFL (AUROC 0.67 [Formula: see text] 0.06). CONCLUSIONS: OCTA multilayer and multisector information has similar performance to RNFL for glaucoma diagnosis, but it has an added value for glaucoma severity classification, showing promising results for staging glaucoma progression. TRANSLATIONAL RELEVANCE: OCTA, in its current stage, has the potential to be used in clinical practice as a complementary imaging technique in glaucoma management.
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spelling pubmed-76740042020-11-20 OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma Andrade De Jesus, Danilo Sánchez Brea, Luisa Barbosa Breda, João Fokkinga, Ella Ederveen, Vera Borren, Noor Bekkers, Amerens Pircher, Michael Stalmans, Ingeborg Klein, Stefan van Walsum, Theo Transl Vis Sci Technol Special Issue PURPOSE: To develop and assess an automatic procedure for classifying and staging glaucomatous vascular damage based on optical coherence tomography angiography (OCTA) imaging. METHODS: OCTA scans (Zeiss Cirrus 5000 HD-OCT) from a random eye of 39 healthy subjects and 82 glaucoma patients were used to develop a new classification algorithm based on multilayer and multisector information. The averaged circumpapillary retinal nerve fiber layer (RNFL) thickness was also collected. Three models, support vector machine (SVM), random forest (RF), and gradient boosting (xGB), were developed and optimized for classifying between healthy and glaucoma patients, primary open-angle glaucoma (POAG) and normal-tension glaucoma (NTG), and glaucoma severity groups. RESULTS: All the models, the SVM (area under the receiver operating characteristic [AUROC] 0.89 ± 0.06), the RF (AUROC 0.86 ± 0.06), and the xGB (AUROC 0.85 ± 0.07), with 26, 22, and 29 vascular features obtained after feature selection, respectively, presented a similar performance to the RNFL thickness (AUROC 0.85 [Formula: see text] 0.06) in classifying healthy and glaucoma patients. The superficial vascular plexus was the most informative layer with the infero temporal sector as the most discriminative region of interest. No significant differentiation was obtained in discriminating the POAG from the NTG group. The xGB model, after feature selection, presented the best performance in classifying the severity groups (AUROC 0.76 [Formula: see text] 0.06), outperforming the RNFL (AUROC 0.67 [Formula: see text] 0.06). CONCLUSIONS: OCTA multilayer and multisector information has similar performance to RNFL for glaucoma diagnosis, but it has an added value for glaucoma severity classification, showing promising results for staging glaucoma progression. TRANSLATIONAL RELEVANCE: OCTA, in its current stage, has the potential to be used in clinical practice as a complementary imaging technique in glaucoma management. The Association for Research in Vision and Ophthalmology 2020-11-05 /pmc/articles/PMC7674004/ /pubmed/33224631 http://dx.doi.org/10.1167/tvst.9.2.58 Text en Copyright 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Special Issue
Andrade De Jesus, Danilo
Sánchez Brea, Luisa
Barbosa Breda, João
Fokkinga, Ella
Ederveen, Vera
Borren, Noor
Bekkers, Amerens
Pircher, Michael
Stalmans, Ingeborg
Klein, Stefan
van Walsum, Theo
OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title_full OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title_fullStr OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title_full_unstemmed OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title_short OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma
title_sort octa multilayer and multisector peripapillary microvascular modeling for diagnosing and staging of glaucoma
topic Special Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674004/
https://www.ncbi.nlm.nih.gov/pubmed/33224631
http://dx.doi.org/10.1167/tvst.9.2.58
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