Cargando…

Multi-parametric quantitative MRI reveals three different white matter subtypes

INTRODUCTION: Magnetic resonance imaging (MRI) shows slight spatial variations in brain white matter (WM). We used quantitative multi-parametric MRI to evaluate in what respect these inhomogeneities could correspond to WM subtypes with specific characteristics and spatial distribution. MATERIALS AND...

Descripción completa

Detalles Bibliográficos
Autores principales: Foucher, Jack R., Mainberger, Olivier, Lamy, Julien, Santin, Mathieu D., Vignaud, Alexandre, Roser, Mathilde M., de Sousa, Paulo L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003690/
https://www.ncbi.nlm.nih.gov/pubmed/29906284
http://dx.doi.org/10.1371/journal.pone.0196297
_version_ 1783332393743024128
author Foucher, Jack R.
Mainberger, Olivier
Lamy, Julien
Santin, Mathieu D.
Vignaud, Alexandre
Roser, Mathilde M.
de Sousa, Paulo L.
author_facet Foucher, Jack R.
Mainberger, Olivier
Lamy, Julien
Santin, Mathieu D.
Vignaud, Alexandre
Roser, Mathilde M.
de Sousa, Paulo L.
author_sort Foucher, Jack R.
collection PubMed
description INTRODUCTION: Magnetic resonance imaging (MRI) shows slight spatial variations in brain white matter (WM). We used quantitative multi-parametric MRI to evaluate in what respect these inhomogeneities could correspond to WM subtypes with specific characteristics and spatial distribution. MATERIALS AND METHODS: Twenty-six controls (12 women, 38 ±9 Y) took part in a 60-min session on a 3T scanner measuring 7 parameters: R(1) and R(2), diffusion tensor imaging which allowed to measure Axial and Radial Diffusivity (AD, RD), magnetization transfer imaging which enabled to compute the Macromolecular Proton Fraction (MPF), and a susceptibility-weighted sequence which permitted to quantify R(2)* and magnetic susceptibility (χ(m)). Spatial independent component analysis was used to identify WM subtypes with specific combination of quantitative parameters values. RESULTS: Three subtypes could be identified. t-WM (track) mostly mapped on well-formed projection and commissural tracts and came with high AD values (all p < 10(−18)). The two other subtypes were located in subcortical WM and overlapped with association fibers: f-WM (frontal) was mostly anterior in the frontal lobe whereas c-WM (central) was underneath the central cortex. f-WM and c-WM had higher MPF values, indicating a higher myelin content (all p < 1.7 10(−6)). This was compatible with their larger χ(m) and R(2), as iron is essentially stored in oligodendrocytes (all p < 0.01). Although R(1) essentially showed the same, its higher value in t-WM relative to c-WM might be related to its higher cholesterol concentration. CONCLUSIONS: Thus, f- and c-WMs were less structured, but more myelinated and probably more metabolically active regarding to their iron content than WM related to fasciculi (t-WM). As known WM bundles passed though different WM subtypes, myelination might not be uniform along the axons but rather follow a spatially consistent regional variability. Future studies might examine the reproducibility of this decomposition and how development and pathology differently affect each subtype.
format Online
Article
Text
id pubmed-6003690
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-60036902018-06-25 Multi-parametric quantitative MRI reveals three different white matter subtypes Foucher, Jack R. Mainberger, Olivier Lamy, Julien Santin, Mathieu D. Vignaud, Alexandre Roser, Mathilde M. de Sousa, Paulo L. PLoS One Research Article INTRODUCTION: Magnetic resonance imaging (MRI) shows slight spatial variations in brain white matter (WM). We used quantitative multi-parametric MRI to evaluate in what respect these inhomogeneities could correspond to WM subtypes with specific characteristics and spatial distribution. MATERIALS AND METHODS: Twenty-six controls (12 women, 38 ±9 Y) took part in a 60-min session on a 3T scanner measuring 7 parameters: R(1) and R(2), diffusion tensor imaging which allowed to measure Axial and Radial Diffusivity (AD, RD), magnetization transfer imaging which enabled to compute the Macromolecular Proton Fraction (MPF), and a susceptibility-weighted sequence which permitted to quantify R(2)* and magnetic susceptibility (χ(m)). Spatial independent component analysis was used to identify WM subtypes with specific combination of quantitative parameters values. RESULTS: Three subtypes could be identified. t-WM (track) mostly mapped on well-formed projection and commissural tracts and came with high AD values (all p < 10(−18)). The two other subtypes were located in subcortical WM and overlapped with association fibers: f-WM (frontal) was mostly anterior in the frontal lobe whereas c-WM (central) was underneath the central cortex. f-WM and c-WM had higher MPF values, indicating a higher myelin content (all p < 1.7 10(−6)). This was compatible with their larger χ(m) and R(2), as iron is essentially stored in oligodendrocytes (all p < 0.01). Although R(1) essentially showed the same, its higher value in t-WM relative to c-WM might be related to its higher cholesterol concentration. CONCLUSIONS: Thus, f- and c-WMs were less structured, but more myelinated and probably more metabolically active regarding to their iron content than WM related to fasciculi (t-WM). As known WM bundles passed though different WM subtypes, myelination might not be uniform along the axons but rather follow a spatially consistent regional variability. Future studies might examine the reproducibility of this decomposition and how development and pathology differently affect each subtype. Public Library of Science 2018-06-15 /pmc/articles/PMC6003690/ /pubmed/29906284 http://dx.doi.org/10.1371/journal.pone.0196297 Text en © 2018 Foucher et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Foucher, Jack R.
Mainberger, Olivier
Lamy, Julien
Santin, Mathieu D.
Vignaud, Alexandre
Roser, Mathilde M.
de Sousa, Paulo L.
Multi-parametric quantitative MRI reveals three different white matter subtypes
title Multi-parametric quantitative MRI reveals three different white matter subtypes
title_full Multi-parametric quantitative MRI reveals three different white matter subtypes
title_fullStr Multi-parametric quantitative MRI reveals three different white matter subtypes
title_full_unstemmed Multi-parametric quantitative MRI reveals three different white matter subtypes
title_short Multi-parametric quantitative MRI reveals three different white matter subtypes
title_sort multi-parametric quantitative mri reveals three different white matter subtypes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003690/
https://www.ncbi.nlm.nih.gov/pubmed/29906284
http://dx.doi.org/10.1371/journal.pone.0196297
work_keys_str_mv AT foucherjackr multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT mainbergerolivier multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT lamyjulien multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT santinmathieud multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT vignaudalexandre multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT rosermathildem multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes
AT desousapaulol multiparametricquantitativemrirevealsthreedifferentwhitemattersubtypes