Comparative mouse brain tractography of diffusion magnetic resonance imaging

Randal X. Moldrich, Kerstin Pannek, Renee Hoch, John L. Rubenstein, Nyoman D. Kurniawan, Linda J. Richards

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1027-1036
Number of pages10
JournalNeuroImage
Volume51
Issue number3
DOIs
StatePublished - Jul 2010

Keywords

  • Constrained spherical deconvolution
  • Diffusion-weighted imaging
  • Fgf17
  • Mouse brain
  • Qball
  • Tractography

Fingerprint

Dive into the research topics of 'Comparative mouse brain tractography of diffusion magnetic resonance imaging'. Together they form a unique fingerprint.

Cite this