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Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.

Publication ,  Journal Article
Pierce, TT; Calabrese, E; White, LE; Chen, SD; Platt, SR; Provenzale, JM
Published in: AJR Am J Roentgenol
January 2014

OBJECTIVE: We set out to determine functional white matter (WM) connections passing through the canine corpus callosum; these WM connections would be useful for subsequent studies of canine brains that serve as models for human WM pathway disease. Based on prior studies, we anticipated that the anterior corpus callosum would send projections to the anterior cerebral cortex whereas progressively posterior segments would send projections to more posterior cortex. MATERIALS AND METHODS: A postmortem canine brain was imaged using a 7-T MRI system producing 100-μm-isotropic-resolution diffusion-tensor imaging analyzed by tractography. Using regions of interest (ROIs) within cortical locations, which were confirmed by a Nissl stain that identified distinct cortical architecture, we successfully identified six important WM pathways. We also compared fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity, and axial diffusivity in tracts passing through the genu and splenium. RESULTS: Callosal fibers were organized on the basis of cortical destination (e.g., fibers from the genu project to the frontal cortex). Histologic results identified the motor cortex on the basis of cytoarchitectonic criteria that allowed placement of ROIs to discriminate between frontal and parietal lobes. We also identified cytoarchitecture typical of the orbital frontal, anterior frontal, and occipital regions and placed ROIs accordingly. FA, ADC, radial diffusivity, and axial diffusivity values were all higher in posterior corpus callosum fiber tracts. CONCLUSION: Using six cortical ROIs, we identified six major WM tracts that reflect major functional divisions of the cerebral hemispheres, and we derived quantitative values that can be used for study of canine models of human WM pathologic states.

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Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

January 2014

Volume

202

Issue

1

Start / End Page

W19 / W25

Location

United States

Related Subject Headings

  • Staining and Labeling
  • Nuclear Medicine & Medical Imaging
  • Nerve Fibers, Myelinated
  • Dogs
  • Diffusion Tensor Imaging
  • Corpus Callosum
  • Anisotropy
  • Animals
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

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ICMJE
MLA
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Pierce, T. T., Calabrese, E., White, L. E., Chen, S. D., Platt, S. R., & Provenzale, J. M. (2014). Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography. AJR Am J Roentgenol, 202(1), W19–W25. https://doi.org/10.2214/AJR.12.9791
Pierce, Theodore T., Evan Calabrese, Leonard E. White, Steven D. Chen, Simon R. Platt, and James M. Provenzale. “Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.AJR Am J Roentgenol 202, no. 1 (January 2014): W19–25. https://doi.org/10.2214/AJR.12.9791.
Pierce TT, Calabrese E, White LE, Chen SD, Platt SR, Provenzale JM. Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography. AJR Am J Roentgenol. 2014 Jan;202(1):W19–25.
Pierce, Theodore T., et al. “Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.AJR Am J Roentgenol, vol. 202, no. 1, Jan. 2014, pp. W19–25. Pubmed, doi:10.2214/AJR.12.9791.
Pierce TT, Calabrese E, White LE, Chen SD, Platt SR, Provenzale JM. Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography. AJR Am J Roentgenol. 2014 Jan;202(1):W19–W25.

Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

January 2014

Volume

202

Issue

1

Start / End Page

W19 / W25

Location

United States

Related Subject Headings

  • Staining and Labeling
  • Nuclear Medicine & Medical Imaging
  • Nerve Fibers, Myelinated
  • Dogs
  • Diffusion Tensor Imaging
  • Corpus Callosum
  • Anisotropy
  • Animals
  • 3202 Clinical sciences
  • 1103 Clinical Sciences