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Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data

PURPOSE: To assess the clinical efficacy for early detection of glaucoma using custom-built image software visualizing translucent retinal nerve fiber layer thickness (RNFLT) that is graphed based on a normative database. METHODS: This prospective study was conducted using a normative database const...

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Autores principales: Jang, Hyoju, Lee, Sang Min, Ahn, Jaehong, Rho, Seungsoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Ophthalmological Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462467/
https://www.ncbi.nlm.nih.gov/pubmed/30977319
http://dx.doi.org/10.3341/kjo.2018.0060
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author Jang, Hyoju
Lee, Sang Min
Ahn, Jaehong
Rho, Seungsoo
author_facet Jang, Hyoju
Lee, Sang Min
Ahn, Jaehong
Rho, Seungsoo
author_sort Jang, Hyoju
collection PubMed
description PURPOSE: To assess the clinical efficacy for early detection of glaucoma using custom-built image software visualizing translucent retinal nerve fiber layer thickness (RNFLT) that is graphed based on a normative database. METHODS: This prospective study was conducted using a normative database constructed with RNFLT data of 151 healthy Korean eyes. The reference lines of the mean, the lower 5%, and the lower 1% limit were visualized as a translucent RNFLT graph produced by our software after inputting each subject's major retinal artery position and overlaying the results onto the RNFLT measurements. Fifty-eight additional healthy control and 79 early-glaucoma eyes were collected for the validation group. If a subject's RNFLT graph was outside the reference line of the lower 1% limit, the graph was defined as abnormal. The lower 1% limit, which was generated by three criteria (criterion 1, built-in software; criterion 2, axial-length data; criterion 3, major retinal artery data), was used to address the difference of agreement with a standard answer. RESULTS: For criteria 1, 2, and 3, the accuracy of our custom-built software was significantly higher than that of the manufacturer's database (kappa of 0.475 vs. 0.852 vs. 0.940; sensitivity of 62.0% vs. 91.1% vs. 97.5%, respectively) maintaining high specificity (87.9% vs. 94.8% vs. 96.6%, respectively). CONCLUSIONS: The custom-built imaging software with the constructed RNFLT normative database showed high clinical efficiency for early detection of glaucoma with negligible user-related variability.
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spelling pubmed-64624672019-04-21 Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data Jang, Hyoju Lee, Sang Min Ahn, Jaehong Rho, Seungsoo Korean J Ophthalmol Original Article PURPOSE: To assess the clinical efficacy for early detection of glaucoma using custom-built image software visualizing translucent retinal nerve fiber layer thickness (RNFLT) that is graphed based on a normative database. METHODS: This prospective study was conducted using a normative database constructed with RNFLT data of 151 healthy Korean eyes. The reference lines of the mean, the lower 5%, and the lower 1% limit were visualized as a translucent RNFLT graph produced by our software after inputting each subject's major retinal artery position and overlaying the results onto the RNFLT measurements. Fifty-eight additional healthy control and 79 early-glaucoma eyes were collected for the validation group. If a subject's RNFLT graph was outside the reference line of the lower 1% limit, the graph was defined as abnormal. The lower 1% limit, which was generated by three criteria (criterion 1, built-in software; criterion 2, axial-length data; criterion 3, major retinal artery data), was used to address the difference of agreement with a standard answer. RESULTS: For criteria 1, 2, and 3, the accuracy of our custom-built software was significantly higher than that of the manufacturer's database (kappa of 0.475 vs. 0.852 vs. 0.940; sensitivity of 62.0% vs. 91.1% vs. 97.5%, respectively) maintaining high specificity (87.9% vs. 94.8% vs. 96.6%, respectively). CONCLUSIONS: The custom-built imaging software with the constructed RNFLT normative database showed high clinical efficiency for early detection of glaucoma with negligible user-related variability. The Korean Ophthalmological Society 2019-04 2019-04-08 /pmc/articles/PMC6462467/ /pubmed/30977319 http://dx.doi.org/10.3341/kjo.2018.0060 Text en © 2019 The Korean Ophthalmological Society http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Jang, Hyoju
Lee, Sang Min
Ahn, Jaehong
Rho, Seungsoo
Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title_full Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title_fullStr Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title_full_unstemmed Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title_short Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
title_sort clinical efficacy of custom-built software for the early detection of glaucoma: a comparison of axial-length and major retinal artery location data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462467/
https://www.ncbi.nlm.nih.gov/pubmed/30977319
http://dx.doi.org/10.3341/kjo.2018.0060
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