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Comparative mouse brain tractography of diffusion magnetic resonance imaging

Diffusion magnetic resonance imaging (dMRI) tractography can be employed to simultaneously analyze three-dimensional white matter tracts in the brain. Numerous methods have been proposed to model diffusion-weighted magnetic resonance data for tractography, and we have explored the functionality of s... Full description

Journal Title: NeuroImage 1 July 2010, Vol.51(3), pp.1027-1036
Main Author: Moldrich, Randal X.
Other Authors: Pannek, Kerstin , Hoch, Renee , Rubenstein, John L. , Kurniawan, Nyoman D. , Richards, Linda J.
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 1053-8119 ; DOI: 10.1016/j.neuroimage.2010.03.035
Link: http://dx.doi.org/10.1016/j.neuroimage.2010.03.035
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recordid: sciversesciencedirect_elsevierS1053-8119(10)00322-8
title: Comparative mouse brain tractography of diffusion magnetic resonance imaging
format: Article
creator:
  • Moldrich, Randal X.
  • Pannek, Kerstin
  • Hoch, Renee
  • Rubenstein, John L.
  • Kurniawan, Nyoman D.
  • Richards, Linda J.
subjects:
  • Mouse Brain
  • Diffusion-Weighted Imaging
  • Tractography
  • Constrained Spherical Deconvolution
  • Qball
  • Fgf17
ispartof: NeuroImage, 1 July 2010, Vol.51(3), pp.1027-1036
description: Diffusion magnetic resonance imaging (dMRI) tractography can be employed to simultaneously analyze three-dimensional white matter tracts in the brain. Numerous methods have been proposed to model diffusion-weighted magnetic resonance data for tractography, and we have explored the functionality of some of these for studying white and grey matter pathways in ex vivo mouse brain. Using various deterministic and probabilistic algorithms across a range of regions of interest we found that probabilistic tractography provides a more robust means of visualizing both white and grey matter pathways than deterministic tractography. Importantly, we demonstrate the sensitivity of probabilistic tractography profiles to streamline number, step size, curvature, fiber orientation distribution threshold, and wholebrain versus region of interest seeding. Using anatomically well-defined corticothalamic pathways, we show how projection maps can permit the topographical assessment of probabilistic tractography. Finally, we show how different tractography approaches can impact on dMRI assessment of tract changes in a mouse deficient for the frontal cortex morphogen, fibroblast growth factor 17. In conclusion, probabilistic tractography can elucidate the phenotypes of mice with neurodegenerative or neurodevelopmental disorders in a quantitative manner.
language: eng
source:
identifier: ISSN: 1053-8119 ; DOI: 10.1016/j.neuroimage.2010.03.035
fulltext: fulltext
issn:
  • 10538119
  • 1053-8119
url: Link


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titleComparative mouse brain tractography of diffusion magnetic resonance imaging
creatorMoldrich, Randal X. ; Pannek, Kerstin ; Hoch, Renee ; Rubenstein, John L. ; Kurniawan, Nyoman D. ; Richards, Linda J.
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identifierISSN: 1053-8119 ; DOI: 10.1016/j.neuroimage.2010.03.035
subjectMouse Brain ; Diffusion-Weighted Imaging ; Tractography ; Constrained Spherical Deconvolution ; Qball ; Fgf17
descriptionDiffusion magnetic resonance imaging (dMRI) tractography can be employed to simultaneously analyze three-dimensional white matter tracts in the brain. Numerous methods have been proposed to model diffusion-weighted magnetic resonance data for tractography, and we have explored the functionality of some of these for studying white and grey matter pathways in ex vivo mouse brain. Using various deterministic and probabilistic algorithms across a range of regions of interest we found that probabilistic tractography provides a more robust means of visualizing both white and grey matter pathways than deterministic tractography. Importantly, we demonstrate the sensitivity of probabilistic tractography profiles to streamline number, step size, curvature, fiber orientation distribution threshold, and wholebrain versus region of interest seeding. Using anatomically well-defined corticothalamic pathways, we show how projection maps can permit the topographical assessment of probabilistic tractography. Finally, we show how different tractography approaches can impact on dMRI assessment of tract changes in a mouse deficient for the frontal cortex morphogen, fibroblast growth factor 17. In conclusion, probabilistic tractography can elucidate the phenotypes of mice with neurodegenerative or neurodevelopmental disorders in a quantitative manner.
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abstractDiffusion magnetic resonance imaging (dMRI) tractography can be employed to simultaneously analyze three-dimensional white matter tracts in the brain. Numerous methods have been proposed to model diffusion-weighted magnetic resonance data for tractography, and we have explored the functionality of some of these for studying white and grey matter pathways in ex vivo mouse brain. Using various deterministic and probabilistic algorithms across a range of regions of interest we found that probabilistic tractography provides a more robust means of visualizing both white and grey matter pathways than deterministic tractography. Importantly, we demonstrate the sensitivity of probabilistic tractography profiles to streamline number, step size, curvature, fiber orientation distribution threshold, and wholebrain versus region of interest seeding. Using anatomically well-defined corticothalamic pathways, we show how projection maps can permit the topographical assessment of probabilistic tractography. Finally, we show how different tractography approaches can impact on dMRI assessment of tract changes in a mouse deficient for the frontal cortex morphogen, fibroblast growth factor 17. In conclusion, probabilistic tractography can elucidate the phenotypes of mice with neurodegenerative or neurodevelopmental disorders in a quantitative manner.
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