Cargando…

Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain

Diffusion MRI (dMRI) is widely used to measure microstructural features of brain white matter, but commonly used dMRI measures have limited capacity to resolve the orientation structure of complex fiber architectures. While several promising new approaches have been proposed, direct quantitative val...

Descripción completa

Detalles Bibliográficos
Autores principales: Leergaard, Trygve B., White, Nathan S., de Crespigny, Alex, Bolstad, Ingeborg, D'Arceuil, Helen, Bjaalie, Jan G., Dale, Anders M.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2802592/
https://www.ncbi.nlm.nih.gov/pubmed/20062822
http://dx.doi.org/10.1371/journal.pone.0008595
_version_ 1782176010777657344
author Leergaard, Trygve B.
White, Nathan S.
de Crespigny, Alex
Bolstad, Ingeborg
D'Arceuil, Helen
Bjaalie, Jan G.
Dale, Anders M.
author_facet Leergaard, Trygve B.
White, Nathan S.
de Crespigny, Alex
Bolstad, Ingeborg
D'Arceuil, Helen
Bjaalie, Jan G.
Dale, Anders M.
author_sort Leergaard, Trygve B.
collection PubMed
description Diffusion MRI (dMRI) is widely used to measure microstructural features of brain white matter, but commonly used dMRI measures have limited capacity to resolve the orientation structure of complex fiber architectures. While several promising new approaches have been proposed, direct quantitative validation of these methods against relevant histological architectures remains missing. In this study, we quantitatively compare neuronal fiber orientation distributions (FODs) derived from ex vivo dMRI data against histological measurements of rat brain myeloarchitecture using manual recordings of individual myelin stained fiber orientations. We show that accurate FOD estimates can be obtained from dMRI data, even in regions with complex architectures of crossing fibers with an intrinsic orientation error of approximately 5–6 degrees in these regions. The reported findings have implications for both clinical and research studies based on dMRI FOD measures, and provide an important biological benchmark for improved FOD reconstruction and fiber tracking methods.
format Text
id pubmed-2802592
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-28025922010-01-09 Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain Leergaard, Trygve B. White, Nathan S. de Crespigny, Alex Bolstad, Ingeborg D'Arceuil, Helen Bjaalie, Jan G. Dale, Anders M. PLoS One Research Article Diffusion MRI (dMRI) is widely used to measure microstructural features of brain white matter, but commonly used dMRI measures have limited capacity to resolve the orientation structure of complex fiber architectures. While several promising new approaches have been proposed, direct quantitative validation of these methods against relevant histological architectures remains missing. In this study, we quantitatively compare neuronal fiber orientation distributions (FODs) derived from ex vivo dMRI data against histological measurements of rat brain myeloarchitecture using manual recordings of individual myelin stained fiber orientations. We show that accurate FOD estimates can be obtained from dMRI data, even in regions with complex architectures of crossing fibers with an intrinsic orientation error of approximately 5–6 degrees in these regions. The reported findings have implications for both clinical and research studies based on dMRI FOD measures, and provide an important biological benchmark for improved FOD reconstruction and fiber tracking methods. Public Library of Science 2010-01-07 /pmc/articles/PMC2802592/ /pubmed/20062822 http://dx.doi.org/10.1371/journal.pone.0008595 Text en Leergaard 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Leergaard, Trygve B.
White, Nathan S.
de Crespigny, Alex
Bolstad, Ingeborg
D'Arceuil, Helen
Bjaalie, Jan G.
Dale, Anders M.
Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title_full Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title_fullStr Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title_full_unstemmed Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title_short Quantitative Histological Validation of Diffusion MRI Fiber Orientation Distributions in the Rat Brain
title_sort quantitative histological validation of diffusion mri fiber orientation distributions in the rat brain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2802592/
https://www.ncbi.nlm.nih.gov/pubmed/20062822
http://dx.doi.org/10.1371/journal.pone.0008595
work_keys_str_mv AT leergaardtrygveb quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT whitenathans quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT decrespignyalex quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT bolstadingeborg quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT darceuilhelen quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT bjaaliejang quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain
AT daleandersm quantitativehistologicalvalidationofdiffusionmrifiberorientationdistributionsintheratbrain