Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty

Abstract Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet’s membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be cha...

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Autores principales:	Friso G. Heslinga, Ruben T. Lucassen, Myrthe A. van den Berg, Luuk van der Hoek, Josien P. W. Pluim, Javier Cabrerizo, Mark Alberti, Mitko Veta
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a2b1072003d94eaa89fa8526c38c721b
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spelling	oai:doaj.org-article:a2b1072003d94eaa89fa8526c38c721b2021-12-02T16:15:07ZCorneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty10.1038/s41598-021-93186-92045-2322https://doaj.org/article/a2b1072003d94eaa89fa8526c38c721b2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93186-9https://doaj.org/toc/2045-2322Abstract Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet’s membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 μm for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.Friso G. HeslingaRuben T. LucassenMyrthe A. van den BergLuuk van der HoekJosien P. W. PluimJavier CabrerizoMark AlbertiMitko VetaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Friso G. Heslinga Ruben T. Lucassen Myrthe A. van den Berg Luuk van der Hoek Josien P. W. Pluim Javier Cabrerizo Mark Alberti Mitko Veta Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
description	Abstract Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet’s membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 μm for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.
format	article
author	Friso G. Heslinga Ruben T. Lucassen Myrthe A. van den Berg Luuk van der Hoek Josien P. W. Pluim Javier Cabrerizo Mark Alberti Mitko Veta
author_facet	Friso G. Heslinga Ruben T. Lucassen Myrthe A. van den Berg Luuk van der Hoek Josien P. W. Pluim Javier Cabrerizo Mark Alberti Mitko Veta
author_sort	Friso G. Heslinga
title	Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
title_short	Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
title_full	Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
title_fullStr	Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
title_full_unstemmed	Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty
title_sort	corneal pachymetry by as-oct after descemet’s membrane endothelial keratoplasty
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a2b1072003d94eaa89fa8526c38c721b
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Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty

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