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Automated 3D Axonal Morphometry of White Matter

Axonal structure underlies white matter functionality and plays a major role in brain connectivity. The current literature on the axonal structure is based on the analysis of two-dimensional (2D) cross-sections, which, as we demonstrate, is precarious. To be able to quantify three-dimensional (3D) a...

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Autores principales: Abdollahzadeh, Ali, Belevich, Ilya, Jokitalo, Eija, Tohka, Jussi, Sierra, Alejandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465365/
https://www.ncbi.nlm.nih.gov/pubmed/30988411
http://dx.doi.org/10.1038/s41598-019-42648-2
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author Abdollahzadeh, Ali
Belevich, Ilya
Jokitalo, Eija
Tohka, Jussi
Sierra, Alejandra
author_facet Abdollahzadeh, Ali
Belevich, Ilya
Jokitalo, Eija
Tohka, Jussi
Sierra, Alejandra
author_sort Abdollahzadeh, Ali
collection PubMed
description Axonal structure underlies white matter functionality and plays a major role in brain connectivity. The current literature on the axonal structure is based on the analysis of two-dimensional (2D) cross-sections, which, as we demonstrate, is precarious. To be able to quantify three-dimensional (3D) axonal morphology, we developed a novel pipeline, called ACSON (AutomatiC 3D Segmentation and morphometry Of axoNs), for automated 3D segmentation and morphometric analysis of the white matter ultrastructure. The automated pipeline eliminates the need for time-consuming manual segmentation of 3D datasets. ACSON segments myelin, myelinated and unmyelinated axons, mitochondria, cells and vacuoles, and analyzes the morphology of myelinated axons. We applied the pipeline to serial block-face scanning electron microscopy images of the corpus callosum of sham-operated (n = 2) and brain injured (n = 3) rats 5 months after the injury. The 3D morphometry showed that cross-sections of myelinated axons were elliptic rather than circular, and their diameter varied substantially along their longitudinal axis. It also showed a significant reduction in the myelinated axon diameter of the ipsilateral corpus callosum of rats 5 months after brain injury, indicating ongoing axonal alterations even at this chronic time-point.
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spelling pubmed-64653652019-04-18 Automated 3D Axonal Morphometry of White Matter Abdollahzadeh, Ali Belevich, Ilya Jokitalo, Eija Tohka, Jussi Sierra, Alejandra Sci Rep Article Axonal structure underlies white matter functionality and plays a major role in brain connectivity. The current literature on the axonal structure is based on the analysis of two-dimensional (2D) cross-sections, which, as we demonstrate, is precarious. To be able to quantify three-dimensional (3D) axonal morphology, we developed a novel pipeline, called ACSON (AutomatiC 3D Segmentation and morphometry Of axoNs), for automated 3D segmentation and morphometric analysis of the white matter ultrastructure. The automated pipeline eliminates the need for time-consuming manual segmentation of 3D datasets. ACSON segments myelin, myelinated and unmyelinated axons, mitochondria, cells and vacuoles, and analyzes the morphology of myelinated axons. We applied the pipeline to serial block-face scanning electron microscopy images of the corpus callosum of sham-operated (n = 2) and brain injured (n = 3) rats 5 months after the injury. The 3D morphometry showed that cross-sections of myelinated axons were elliptic rather than circular, and their diameter varied substantially along their longitudinal axis. It also showed a significant reduction in the myelinated axon diameter of the ipsilateral corpus callosum of rats 5 months after brain injury, indicating ongoing axonal alterations even at this chronic time-point. Nature Publishing Group UK 2019-04-15 /pmc/articles/PMC6465365/ /pubmed/30988411 http://dx.doi.org/10.1038/s41598-019-42648-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Abdollahzadeh, Ali
Belevich, Ilya
Jokitalo, Eija
Tohka, Jussi
Sierra, Alejandra
Automated 3D Axonal Morphometry of White Matter
title Automated 3D Axonal Morphometry of White Matter
title_full Automated 3D Axonal Morphometry of White Matter
title_fullStr Automated 3D Axonal Morphometry of White Matter
title_full_unstemmed Automated 3D Axonal Morphometry of White Matter
title_short Automated 3D Axonal Morphometry of White Matter
title_sort automated 3d axonal morphometry of white matter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465365/
https://www.ncbi.nlm.nih.gov/pubmed/30988411
http://dx.doi.org/10.1038/s41598-019-42648-2
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