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Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery

Following refractive surgery, the cornea is denervated and re-innervated, hence a reproducible tool to objectively quantify this change is warranted. This study aimed to determine the repeatability and reproducibility of corneal nerve quantification between automated (ACCMetrics) and manual software...

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Autores principales: Chin, Jia Ying, Yang, Lily Wei Yun, Ji, Angel Jung Se, Nubile, Mario, Mastropasqua, Leonardo, Allen, John Carson, Mehta, Jodhbir S., Liu, Yu-Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400400/
https://www.ncbi.nlm.nih.gov/pubmed/32708510
http://dx.doi.org/10.3390/diagnostics10070493
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author Chin, Jia Ying
Yang, Lily Wei Yun
Ji, Angel Jung Se
Nubile, Mario
Mastropasqua, Leonardo
Allen, John Carson
Mehta, Jodhbir S.
Liu, Yu-Chi
author_facet Chin, Jia Ying
Yang, Lily Wei Yun
Ji, Angel Jung Se
Nubile, Mario
Mastropasqua, Leonardo
Allen, John Carson
Mehta, Jodhbir S.
Liu, Yu-Chi
author_sort Chin, Jia Ying
collection PubMed
description Following refractive surgery, the cornea is denervated and re-innervated, hence a reproducible tool to objectively quantify this change is warranted. This study aimed to determine the repeatability and reproducibility of corneal nerve quantification between automated (ACCMetrics) and manual software (CCMetrics) following refractive surgery. A total of 1007 in vivo confocal microscopy images from 20 post-small incision lenticule extraction (SMILE) or post-laser-assisted in situ keratomileusis (LASIK) patients were evaluated by two independent observers using CCMetrics for corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fibre length (CNFL). Intra-observer and inter-observer reproducibility and repeatability, as well as agreement and correlation between the measurements obtained by ACCMetrics and CCMetrics, were assessed. We found that CNFL demonstrated the best intra- and inter-observer agreement followed by CNFD (intra-class correlation coefficient (ICC) = 0.799 and 0.740, respectively for CNFL; 0.757 and 0.728 for CNFD). CNBD demonstrated poorest intra- and inter-observer ICC. There was an underestimation in ACCMetrics measurements compared to CCMetrics measurements, although the differences were not significant. Our data suggested that both automated and manual methods can be used as reliable tools for the evaluation of corneal nerve status following refractive surgery. However, the measurements obtained with different methods are not interchangeable.
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spelling pubmed-74004002020-08-23 Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery Chin, Jia Ying Yang, Lily Wei Yun Ji, Angel Jung Se Nubile, Mario Mastropasqua, Leonardo Allen, John Carson Mehta, Jodhbir S. Liu, Yu-Chi Diagnostics (Basel) Article Following refractive surgery, the cornea is denervated and re-innervated, hence a reproducible tool to objectively quantify this change is warranted. This study aimed to determine the repeatability and reproducibility of corneal nerve quantification between automated (ACCMetrics) and manual software (CCMetrics) following refractive surgery. A total of 1007 in vivo confocal microscopy images from 20 post-small incision lenticule extraction (SMILE) or post-laser-assisted in situ keratomileusis (LASIK) patients were evaluated by two independent observers using CCMetrics for corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fibre length (CNFL). Intra-observer and inter-observer reproducibility and repeatability, as well as agreement and correlation between the measurements obtained by ACCMetrics and CCMetrics, were assessed. We found that CNFL demonstrated the best intra- and inter-observer agreement followed by CNFD (intra-class correlation coefficient (ICC) = 0.799 and 0.740, respectively for CNFL; 0.757 and 0.728 for CNFD). CNBD demonstrated poorest intra- and inter-observer ICC. There was an underestimation in ACCMetrics measurements compared to CCMetrics measurements, although the differences were not significant. Our data suggested that both automated and manual methods can be used as reliable tools for the evaluation of corneal nerve status following refractive surgery. However, the measurements obtained with different methods are not interchangeable. MDPI 2020-07-18 /pmc/articles/PMC7400400/ /pubmed/32708510 http://dx.doi.org/10.3390/diagnostics10070493 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chin, Jia Ying
Yang, Lily Wei Yun
Ji, Angel Jung Se
Nubile, Mario
Mastropasqua, Leonardo
Allen, John Carson
Mehta, Jodhbir S.
Liu, Yu-Chi
Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title_full Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title_fullStr Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title_full_unstemmed Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title_short Validation of the Use of Automated and Manual Quantitative Analysis of Corneal Nerve Plexus Following Refractive Surgery
title_sort validation of the use of automated and manual quantitative analysis of corneal nerve plexus following refractive surgery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400400/
https://www.ncbi.nlm.nih.gov/pubmed/32708510
http://dx.doi.org/10.3390/diagnostics10070493
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