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Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying p...

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Autores principales: Luciano, Nicholas J, Sati, Pascal, Nair, Govind, Guy, Joseph R, Ha, Seung-Kwon, Absinta, Martina, Chiang, Wen-Yang, Leibovitch, Emily C, Jacobson, Steven, Silva, Afonso C, Reich, Daniel S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226356/
https://www.ncbi.nlm.nih.gov/pubmed/28060281
http://dx.doi.org/10.3791/54780
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author Luciano, Nicholas J
Sati, Pascal
Nair, Govind
Guy, Joseph R
Ha, Seung-Kwon
Absinta, Martina
Chiang, Wen-Yang
Leibovitch, Emily C
Jacobson, Steven
Silva, Afonso C
Reich, Daniel S.
author_facet Luciano, Nicholas J
Sati, Pascal
Nair, Govind
Guy, Joseph R
Ha, Seung-Kwon
Absinta, Martina
Chiang, Wen-Yang
Leibovitch, Emily C
Jacobson, Steven
Silva, Afonso C
Reich, Daniel S.
author_sort Luciano, Nicholas J
collection PubMed
description Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.
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spelling pubmed-52263562017-01-26 Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning Luciano, Nicholas J Sati, Pascal Nair, Govind Guy, Joseph R Ha, Seung-Kwon Absinta, Martina Chiang, Wen-Yang Leibovitch, Emily C Jacobson, Steven Silva, Afonso C Reich, Daniel S. J Vis Exp Neuroscience Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans. MyJove Corporation 2016-12-06 /pmc/articles/PMC5226356/ /pubmed/28060281 http://dx.doi.org/10.3791/54780 Text en Copyright © 2016, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Neuroscience
Luciano, Nicholas J
Sati, Pascal
Nair, Govind
Guy, Joseph R
Ha, Seung-Kwon
Absinta, Martina
Chiang, Wen-Yang
Leibovitch, Emily C
Jacobson, Steven
Silva, Afonso C
Reich, Daniel S.
Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title_full Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title_fullStr Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title_full_unstemmed Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title_short Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
title_sort utilizing 3d printing technology to merge mri with histology: a protocol for brain sectioning
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226356/
https://www.ncbi.nlm.nih.gov/pubmed/28060281
http://dx.doi.org/10.3791/54780
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