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Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs

PURPOSE: The sunset glow fundus (SGF) appearance in Vogt-Koyanagi-Harada (VKH) disease was evaluated by means of adaptive binarization of patients’ fundus photographs. METHODS: Twenty-nine Japanese patients with acute VKH were enrolled in this study. We evaluated one eye of each patient, and thereby...

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Autores principales: Komuku, Yuki, Ishikawa, Hiroto, Ide, Atsuya, Matsuoka, Taiki, Fukuyama, Hisashi, Okadome, Takeshi, Gomi, Fumi
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/PMC7552939/
https://www.ncbi.nlm.nih.gov/pubmed/33133773
http://dx.doi.org/10.1167/tvst.9.11.10
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author Komuku, Yuki
Ishikawa, Hiroto
Ide, Atsuya
Matsuoka, Taiki
Fukuyama, Hisashi
Okadome, Takeshi
Gomi, Fumi
author_facet Komuku, Yuki
Ishikawa, Hiroto
Ide, Atsuya
Matsuoka, Taiki
Fukuyama, Hisashi
Okadome, Takeshi
Gomi, Fumi
author_sort Komuku, Yuki
collection PubMed
description PURPOSE: The sunset glow fundus (SGF) appearance in Vogt-Koyanagi-Harada (VKH) disease was evaluated by means of adaptive binarization of patients’ fundus photographs. METHODS: Twenty-nine Japanese patients with acute VKH were enrolled in this study. We evaluated one eye of each patient, and thereby divided the patients into two groups; SGF+ and SGF− at 6 months after treatment. We compared patient age, gender, and spherical equivalent refractive error (SERE) and choroidal thickness measured using optical coherence tomography. We also compared the choroidal vascular appearance index (CVAI), derived by adaptive binarization image processing of fundus photographs, between the two groups. Measurements of choroidal thickness and CVAI were taken at the onset of disease, and 1, 3, and 6 months after treatment. The sunset glow index (SGI), as previously reported, was calculated using color fundus photographs, and compared to the CVAI. RESULTS: Eight patients (27.6%) were categorized into the SGF+ group. At all time points, the mean CVAI in the SGF+ group was significantly greater than that in the SGF− group. No significant difference was observed in choroidal thicknesses at any time point. The SGI was significantly greater in the SGF+ group at 6 months. CONCLUSIONS: CVAI could be a new predictive biomarker for the development of SGF in patients with VKH disease. TRANSLATIONAL RELEVANCE: Detecting SGF is important for management of patients with VKH, and CVAI may indicate the possibility of developing into SGF, although the color fundus photographs do not yet show SGF at that time.
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spelling pubmed-75529392020-10-30 Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs Komuku, Yuki Ishikawa, Hiroto Ide, Atsuya Matsuoka, Taiki Fukuyama, Hisashi Okadome, Takeshi Gomi, Fumi Transl Vis Sci Technol Article PURPOSE: The sunset glow fundus (SGF) appearance in Vogt-Koyanagi-Harada (VKH) disease was evaluated by means of adaptive binarization of patients’ fundus photographs. METHODS: Twenty-nine Japanese patients with acute VKH were enrolled in this study. We evaluated one eye of each patient, and thereby divided the patients into two groups; SGF+ and SGF− at 6 months after treatment. We compared patient age, gender, and spherical equivalent refractive error (SERE) and choroidal thickness measured using optical coherence tomography. We also compared the choroidal vascular appearance index (CVAI), derived by adaptive binarization image processing of fundus photographs, between the two groups. Measurements of choroidal thickness and CVAI were taken at the onset of disease, and 1, 3, and 6 months after treatment. The sunset glow index (SGI), as previously reported, was calculated using color fundus photographs, and compared to the CVAI. RESULTS: Eight patients (27.6%) were categorized into the SGF+ group. At all time points, the mean CVAI in the SGF+ group was significantly greater than that in the SGF− group. No significant difference was observed in choroidal thicknesses at any time point. The SGI was significantly greater in the SGF+ group at 6 months. CONCLUSIONS: CVAI could be a new predictive biomarker for the development of SGF in patients with VKH disease. TRANSLATIONAL RELEVANCE: Detecting SGF is important for management of patients with VKH, and CVAI may indicate the possibility of developing into SGF, although the color fundus photographs do not yet show SGF at that time. The Association for Research in Vision and Ophthalmology 2020-10-09 /pmc/articles/PMC7552939/ /pubmed/33133773 http://dx.doi.org/10.1167/tvst.9.11.10 Text en Copyright 2020 The Authors http://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
Komuku, Yuki
Ishikawa, Hiroto
Ide, Atsuya
Matsuoka, Taiki
Fukuyama, Hisashi
Okadome, Takeshi
Gomi, Fumi
Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title_full Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title_fullStr Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title_full_unstemmed Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title_short Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs
title_sort predictive biomarker for progression into the sunset glow fundus of vogt-koyanagi-harada disease, using adaptive binarization of fundus photographs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552939/
https://www.ncbi.nlm.nih.gov/pubmed/33133773
http://dx.doi.org/10.1167/tvst.9.11.10
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