NeuroImage (Nov 2021)

A multicontrast MR atlas of the Wistar rat brain

  • G. Allan Johnson,
  • Rick Laoprasert,
  • Robert J. Anderson,
  • Gary Cofer,
  • James Cook,
  • Forrest Pratson,
  • Leonard E. White

Journal volume & issue
Vol. 242
p. 118470

Abstract

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Abstract We describe a multi-contrast, multi-dimensional atlas of the Wistar rat acquired at microscopic spatial resolution using magnetic resonance histology (MRH). Diffusion weighted images, and associated scalar images were acquired of a single specimen with a fully sampled Fourier reconstruction, 61 angles and b=3000 s/mm2 yielding 50 um isotropic spatial resolution. The higher angular sampling allows use of the GQI algorithm improving the angular invariance of the scalar images and yielding an orientation distribution function to assist in delineating subtle boundaries where there are crossing fibers and track density images providing insight into local fiber architecture. A multigradient echo image of the same specimen was acquired at 25 um isotropic spatial resolution. A quantitative susceptibility map enhances fiber architecture relative to the magnitude images. An accompanying multi-specimen atlas (n=6) was acquired with compressed sensing with the same diffusion protocol as used for the single specimen atlas. An average was created using diffeomorphic mapping. Scalar volumes from the diffusion data, a T2* weighted volume, a quantitative susceptibility map, and a track density volume, all registered to the same space provide multiple contrasts to assist in anatomic delineation. The new template provides significantly increased contrast in the scalar DTI images when compared to previous atlases. A compact interactive viewer based on 3D Slicer is provided to facilitate comparison among the contrasts in the multiple volumes. The single volume and average atlas with multiple 3D volumes provide an improved template for anatomic interrogation of the Wistar rat brain. The improved contrast to noise in the scalar DTI images and the addition of other volumes (eg. QA,QSM,TDI ) will facilitate automated label registration for MR histology and preclinical imaging.

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