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Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography
To quantitatively evaluate brain tissue and its corresponding function, knowledge of the 3D cellular distribution is essential. The gold standard to obtain this information is histology, a destructive and labor-intensive technique where the specimen is sliced and examined under a light microscope, p...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142271/ https://www.ncbi.nlm.nih.gov/pubmed/29915047 http://dx.doi.org/10.1073/pnas.1801678115 |
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author | Töpperwien, Mareike van der Meer, Franziska Stadelmann, Christine Salditt, Tim |
author_facet | Töpperwien, Mareike van der Meer, Franziska Stadelmann, Christine Salditt, Tim |
author_sort | Töpperwien, Mareike |
collection | PubMed |
description | To quantitatively evaluate brain tissue and its corresponding function, knowledge of the 3D cellular distribution is essential. The gold standard to obtain this information is histology, a destructive and labor-intensive technique where the specimen is sliced and examined under a light microscope, providing 3D information at nonisotropic resolution. To overcome the limitations of conventional histology, we use phase-contrast X-ray tomography with optimized optics, reconstruction, and image analysis, both at a dedicated synchrotron radiation endstation, which we have equipped with X-ray waveguide optics for coherence and wavefront filtering, and at a compact laboratory source. As a proof-of-concept demonstration we probe the 3D cytoarchitecture in millimeter-sized punches of unstained human cerebellum embedded in paraffin and show that isotropic subcellular resolution can be reached at both setups throughout the specimen. To enable a quantitative analysis of the reconstructed data, we demonstrate automatic cell segmentation and localization of over 1 million neurons within the cerebellar cortex. This allows for the analysis of the spatial organization and correlation of cells in all dimensions by borrowing concepts from condensed-matter physics, indicating a strong short-range order and local clustering of the cells in the granular layer. By quantification of 3D neuronal “packing,” we can hence shed light on how the human cerebellum accommodates 80% of the total neurons in the brain in only 10% of its volume. In addition, we show that the distribution of neighboring neurons in the granular layer is anisotropic with respect to the Purkinje cell dendrites. |
format | Online Article Text |
id | pubmed-6142271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-61422712018-09-19 Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography Töpperwien, Mareike van der Meer, Franziska Stadelmann, Christine Salditt, Tim Proc Natl Acad Sci U S A Physical Sciences To quantitatively evaluate brain tissue and its corresponding function, knowledge of the 3D cellular distribution is essential. The gold standard to obtain this information is histology, a destructive and labor-intensive technique where the specimen is sliced and examined under a light microscope, providing 3D information at nonisotropic resolution. To overcome the limitations of conventional histology, we use phase-contrast X-ray tomography with optimized optics, reconstruction, and image analysis, both at a dedicated synchrotron radiation endstation, which we have equipped with X-ray waveguide optics for coherence and wavefront filtering, and at a compact laboratory source. As a proof-of-concept demonstration we probe the 3D cytoarchitecture in millimeter-sized punches of unstained human cerebellum embedded in paraffin and show that isotropic subcellular resolution can be reached at both setups throughout the specimen. To enable a quantitative analysis of the reconstructed data, we demonstrate automatic cell segmentation and localization of over 1 million neurons within the cerebellar cortex. This allows for the analysis of the spatial organization and correlation of cells in all dimensions by borrowing concepts from condensed-matter physics, indicating a strong short-range order and local clustering of the cells in the granular layer. By quantification of 3D neuronal “packing,” we can hence shed light on how the human cerebellum accommodates 80% of the total neurons in the brain in only 10% of its volume. In addition, we show that the distribution of neighboring neurons in the granular layer is anisotropic with respect to the Purkinje cell dendrites. National Academy of Sciences 2018-07-03 2018-06-18 /pmc/articles/PMC6142271/ /pubmed/29915047 http://dx.doi.org/10.1073/pnas.1801678115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Töpperwien, Mareike van der Meer, Franziska Stadelmann, Christine Salditt, Tim Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title | Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title_full | Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title_fullStr | Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title_full_unstemmed | Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title_short | Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography |
title_sort | three-dimensional virtual histology of human cerebellum by x-ray phase-contrast tomography |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142271/ https://www.ncbi.nlm.nih.gov/pubmed/29915047 http://dx.doi.org/10.1073/pnas.1801678115 |
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