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X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis

Examination of histological or immunohistochemically stained 2D sections of embedded tissue is one of the most frequently used tools in biomedical research and clinical routine. Since to date, targeted sectioning of specific regions of interest (ROI) in the sample is not possible, we aimed at develo...

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Autores principales: Albers, Jonas, Markus, M. Andrea, Alves, Frauke, Dullin, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955938/
https://www.ncbi.nlm.nih.gov/pubmed/29769600
http://dx.doi.org/10.1038/s41598-018-26086-0
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author Albers, Jonas
Markus, M. Andrea
Alves, Frauke
Dullin, Christian
author_facet Albers, Jonas
Markus, M. Andrea
Alves, Frauke
Dullin, Christian
author_sort Albers, Jonas
collection PubMed
description Examination of histological or immunohistochemically stained 2D sections of embedded tissue is one of the most frequently used tools in biomedical research and clinical routine. Since to date, targeted sectioning of specific regions of interest (ROI) in the sample is not possible, we aimed at developing a guided sectioning approach based on x-ray 3D virtual histology for heavy ion stained murine lung samples. For this purpose, we increased the contrast to noise ratio of a standard benchtop microCT by 5–10-fold using free-propagation phase contrast imaging and thus substantially improved image quality. We then show that microCT 3D datasets deliver more precise anatomical information and quantification of the sample than traditional histological sections, which display deformations of the tissue. To quantify these deformations caused by sectioning we developed the “Displacement Index (DI)”, which combines block-matching with the calculation of the local mutual information. We show that the DI substantially decreases when a femtosecond laser microtome is used for sections as opposed to a traditional microtome. In conclusion, our microCT based virtual histology approach can be used as a supplement and a guidance tool for traditional histology, providing 3D measurement capabilities and offering the ability to perform sectioning directly at an ROI.
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spelling pubmed-59559382018-05-21 X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis Albers, Jonas Markus, M. Andrea Alves, Frauke Dullin, Christian Sci Rep Article Examination of histological or immunohistochemically stained 2D sections of embedded tissue is one of the most frequently used tools in biomedical research and clinical routine. Since to date, targeted sectioning of specific regions of interest (ROI) in the sample is not possible, we aimed at developing a guided sectioning approach based on x-ray 3D virtual histology for heavy ion stained murine lung samples. For this purpose, we increased the contrast to noise ratio of a standard benchtop microCT by 5–10-fold using free-propagation phase contrast imaging and thus substantially improved image quality. We then show that microCT 3D datasets deliver more precise anatomical information and quantification of the sample than traditional histological sections, which display deformations of the tissue. To quantify these deformations caused by sectioning we developed the “Displacement Index (DI)”, which combines block-matching with the calculation of the local mutual information. We show that the DI substantially decreases when a femtosecond laser microtome is used for sections as opposed to a traditional microtome. In conclusion, our microCT based virtual histology approach can be used as a supplement and a guidance tool for traditional histology, providing 3D measurement capabilities and offering the ability to perform sectioning directly at an ROI. Nature Publishing Group UK 2018-05-16 /pmc/articles/PMC5955938/ /pubmed/29769600 http://dx.doi.org/10.1038/s41598-018-26086-0 Text en © The Author(s) 2018 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
Albers, Jonas
Markus, M. Andrea
Alves, Frauke
Dullin, Christian
X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title_full X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title_fullStr X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title_full_unstemmed X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title_short X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
title_sort x-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955938/
https://www.ncbi.nlm.nih.gov/pubmed/29769600
http://dx.doi.org/10.1038/s41598-018-26086-0
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