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Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning
PURPOSE: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). METHODS: We collected data on...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590176/ https://www.ncbi.nlm.nih.gov/pubmed/34751742 http://dx.doi.org/10.1167/tvst.10.13.12 |
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author | Li, Junmeng Zhu, Lei Zhu, Ruilin Lu, Yanye Rong, Xin Zhang, Yadi Gu, Xiaopeng Wang, Yuwei Zhang, Zhiyue Ren, Qiushi Rong, Bei Yang, Liu |
author_facet | Li, Junmeng Zhu, Lei Zhu, Ruilin Lu, Yanye Rong, Xin Zhang, Yadi Gu, Xiaopeng Wang, Yuwei Zhang, Zhiyue Ren, Qiushi Rong, Bei Yang, Liu |
author_sort | Li, Junmeng |
collection | PubMed |
description | PURPOSE: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). METHODS: We collected data on 92 healthy children (92 eyes) from the Ophthalmology Department of Peking University First Hospital. The data were allocated to three groups: emmetropia (+0.50 diopters [D] to −0.50 D), low myopia (−0.75 D to −3.00 D), and moderate myopia (−3.25 D to −5.75 D). We performed standardized optical coherence tomography (OCT) and developed a new segmentation technique to measure choroidal thickness (CT), large-vessel choroidal layer (LVCL), medium-vessel choroidal layer (MVCL), and small-vessel choroidal layer thickness (SVCL), and evaluated the choroidal vascular system (choroidal vascular volume [VV], choroidal vascular index [CVI], and choroidal vascular density [CVD]). RESULTS: All choroidal sublayers (LVCL, MVCL, and SVCL) were significantly thinner in myopic than in emmetropic eyes (P < 0.05), the thinnest choroidal region being the nasal outer subfield (P < 0.05). In all choroidal regions of SVCL, a positive correlation was found between SER and thickness ratio (P < 0.001). In most subfields of MVCL, a similar correlation was found (P < 0.050), the exceptions being the two nasal subfields (0.050 < P < 0.300). In contrast, the thickness ratio of LVCL decreased in all subfields (P < 0.050). VV correlated with SER negatively in LVCL in all subfields (all P < 0.001) and most subfields in MVCL except for two temporal subfields (0.050 < P < 0.200). However, no significant correlations were found between CVI and SER in LVCL (P > 0.050) and MVCL (with the exception being the temporal inner subfield, P = 0.011). CONCLUSIONS: Thickness of choroidal sublayers was reduced with higher myopic SER, whereas changes in thickness ratio varied between sublayers. No significant correlations between CVI and SER suggested that both choroidal stromal and vascular volume decreases proportionately. TRANSLATIONAL RELEVANCE: Automatic segmentation model will be helpful for future clinical trials to quantify choroidal sublayer morphologic features in myopia. |
format | Online Article Text |
id | pubmed-8590176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-85901762021-11-24 Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning Li, Junmeng Zhu, Lei Zhu, Ruilin Lu, Yanye Rong, Xin Zhang, Yadi Gu, Xiaopeng Wang, Yuwei Zhang, Zhiyue Ren, Qiushi Rong, Bei Yang, Liu Transl Vis Sci Technol Article PURPOSE: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). METHODS: We collected data on 92 healthy children (92 eyes) from the Ophthalmology Department of Peking University First Hospital. The data were allocated to three groups: emmetropia (+0.50 diopters [D] to −0.50 D), low myopia (−0.75 D to −3.00 D), and moderate myopia (−3.25 D to −5.75 D). We performed standardized optical coherence tomography (OCT) and developed a new segmentation technique to measure choroidal thickness (CT), large-vessel choroidal layer (LVCL), medium-vessel choroidal layer (MVCL), and small-vessel choroidal layer thickness (SVCL), and evaluated the choroidal vascular system (choroidal vascular volume [VV], choroidal vascular index [CVI], and choroidal vascular density [CVD]). RESULTS: All choroidal sublayers (LVCL, MVCL, and SVCL) were significantly thinner in myopic than in emmetropic eyes (P < 0.05), the thinnest choroidal region being the nasal outer subfield (P < 0.05). In all choroidal regions of SVCL, a positive correlation was found between SER and thickness ratio (P < 0.001). In most subfields of MVCL, a similar correlation was found (P < 0.050), the exceptions being the two nasal subfields (0.050 < P < 0.300). In contrast, the thickness ratio of LVCL decreased in all subfields (P < 0.050). VV correlated with SER negatively in LVCL in all subfields (all P < 0.001) and most subfields in MVCL except for two temporal subfields (0.050 < P < 0.200). However, no significant correlations were found between CVI and SER in LVCL (P > 0.050) and MVCL (with the exception being the temporal inner subfield, P = 0.011). CONCLUSIONS: Thickness of choroidal sublayers was reduced with higher myopic SER, whereas changes in thickness ratio varied between sublayers. No significant correlations between CVI and SER suggested that both choroidal stromal and vascular volume decreases proportionately. TRANSLATIONAL RELEVANCE: Automatic segmentation model will be helpful for future clinical trials to quantify choroidal sublayer morphologic features in myopia. The Association for Research in Vision and Ophthalmology 2021-11-09 /pmc/articles/PMC8590176/ /pubmed/34751742 http://dx.doi.org/10.1167/tvst.10.13.12 Text en Copyright 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Article Li, Junmeng Zhu, Lei Zhu, Ruilin Lu, Yanye Rong, Xin Zhang, Yadi Gu, Xiaopeng Wang, Yuwei Zhang, Zhiyue Ren, Qiushi Rong, Bei Yang, Liu Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title | Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title_full | Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title_fullStr | Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title_full_unstemmed | Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title_short | Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning |
title_sort | automated analysis of choroidal sublayer morphologic features in myopic children using edi-oct by deep learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590176/ https://www.ncbi.nlm.nih.gov/pubmed/34751742 http://dx.doi.org/10.1167/tvst.10.13.12 |
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