A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.

<h4>Background</h4>Manual axon histomorphometry (AH) is time- and resource-intensive, which has inspired many attempts at automation. However, there has been little investigation on implementation of automated programs for widespread use. Ideally such a program should be able to perform...

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Autores principales:	Alison L Wong, Nicholas Hricz, Harsha Malapati, Nicholas von Guionneau, Michael Wong, Thomas Harris, Mathieu Boudreau, Julien Cohen-Adad, Sami Tuffaha
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1ee9b4bd1e4a4c92b5b7b3c9e2a7f800
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spelling	oai:doaj.org-article:1ee9b4bd1e4a4c92b5b7b3c9e2a7f8002021-12-02T20:05:10ZA simple and robust method for automating analysis of naïve and regenerating peripheral nerves.1932-620310.1371/journal.pone.0248323https://doaj.org/article/1ee9b4bd1e4a4c92b5b7b3c9e2a7f8002021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0248323https://doaj.org/toc/1932-6203<h4>Background</h4>Manual axon histomorphometry (AH) is time- and resource-intensive, which has inspired many attempts at automation. However, there has been little investigation on implementation of automated programs for widespread use. Ideally such a program should be able to perform AH across imaging modalities and nerve states. AxonDeepSeg (ADS) is an open source deep learning program that has previously been validated in electron microscopy. We evaluated the robustness of ADS for peripheral nerve axonal histomorphometry in light micrographs prepared using two different methods.<h4>Methods</h4>Axon histomorphometry using ADS and manual analysis (gold-standard) was performed on light micrographs of naïve or regenerating rat median nerve cross-sections prepared with either toluidine-resin or osmium-paraffin embedding protocols. The parameters of interest included axon count, axon diameter, myelin thickness, and g-ratio.<h4>Results</h4>Manual and automatic ADS axon counts demonstrated good agreement in naïve nerves and moderate agreement on regenerating nerves. There were small but consistent differences in measured axon diameter, myelin thickness and g-ratio; however, absolute differences were small. Both methods appropriately identified differences between naïve and regenerating nerves. ADS was faster than manual axon analysis.<h4>Conclusions</h4>Without any algorithm retraining, ADS was able to appropriately identify critical differences between naïve and regenerating nerves and work with different sample preparation methods of peripheral nerve light micrographs. While there were differences between absolute values between manual and ADS, ADS performed consistently and required much less time. ADS is an accessible and robust tool for AH that can provide consistent analysis across protocols and nerve states.Alison L WongNicholas HriczHarsha MalapatiNicholas von GuionneauMichael WongThomas HarrisMathieu BoudreauJulien Cohen-AdadSami TuffahaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0248323 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Alison L Wong Nicholas Hricz Harsha Malapati Nicholas von Guionneau Michael Wong Thomas Harris Mathieu Boudreau Julien Cohen-Adad Sami Tuffaha A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
description	<h4>Background</h4>Manual axon histomorphometry (AH) is time- and resource-intensive, which has inspired many attempts at automation. However, there has been little investigation on implementation of automated programs for widespread use. Ideally such a program should be able to perform AH across imaging modalities and nerve states. AxonDeepSeg (ADS) is an open source deep learning program that has previously been validated in electron microscopy. We evaluated the robustness of ADS for peripheral nerve axonal histomorphometry in light micrographs prepared using two different methods.<h4>Methods</h4>Axon histomorphometry using ADS and manual analysis (gold-standard) was performed on light micrographs of naïve or regenerating rat median nerve cross-sections prepared with either toluidine-resin or osmium-paraffin embedding protocols. The parameters of interest included axon count, axon diameter, myelin thickness, and g-ratio.<h4>Results</h4>Manual and automatic ADS axon counts demonstrated good agreement in naïve nerves and moderate agreement on regenerating nerves. There were small but consistent differences in measured axon diameter, myelin thickness and g-ratio; however, absolute differences were small. Both methods appropriately identified differences between naïve and regenerating nerves. ADS was faster than manual axon analysis.<h4>Conclusions</h4>Without any algorithm retraining, ADS was able to appropriately identify critical differences between naïve and regenerating nerves and work with different sample preparation methods of peripheral nerve light micrographs. While there were differences between absolute values between manual and ADS, ADS performed consistently and required much less time. ADS is an accessible and robust tool for AH that can provide consistent analysis across protocols and nerve states.
format	article
author	Alison L Wong Nicholas Hricz Harsha Malapati Nicholas von Guionneau Michael Wong Thomas Harris Mathieu Boudreau Julien Cohen-Adad Sami Tuffaha
author_facet	Alison L Wong Nicholas Hricz Harsha Malapati Nicholas von Guionneau Michael Wong Thomas Harris Mathieu Boudreau Julien Cohen-Adad Sami Tuffaha
author_sort	Alison L Wong
title	A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
title_short	A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
title_full	A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
title_fullStr	A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
title_full_unstemmed	A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
title_sort	simple and robust method for automating analysis of naïve and regenerating peripheral nerves.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/1ee9b4bd1e4a4c92b5b7b3c9e2a7f800
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A simple and robust method for automating analysis of naïve and regenerating peripheral nerves.

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