Reproducibility and variation of diffusion measures in the squirrel monkey brain, in vivo and ex vivo

Kurt Schilling, Yurui Gao, Iwona Stepniewska, Ann S. Choe, Bennett A. Landman, Adam W. Anderson

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Purpose Animal models are needed to better understand the relationship between diffusion MRI (dMRI) and the underlying tissue microstructure. One promising model for validation studies is the common squirrel monkey, Saimiri sciureus. This study aims to determine (1) the reproducibility of in vivo diffusion measures both within and between subjects; (2) the agreement between in vivo and ex vivo data acquired from the same specimen and (3) normal diffusion values and their variation across brain regions. Methods Data were acquired from three healthy squirrel monkeys, each imaged twice in vivo and once ex vivo. Reproducibility of fractional anisotropy (FA), mean diffusivity (MD), and principal eigenvector (PEV) was assessed, and normal values were determined both in vivo and ex vivo. Results The calculated coefficients of variation (CVs) for both intra-subject and inter-subject MD were below 10% (low variability) while FA had a wider range of CVs, 2–14% intra-subject (moderate variability), and 3–31% inter-subject (high variability). MD in ex vivo tissue was lower than in vivo (30%–50% decrease), while FA values increased in all regions (30–39% increase). The mode of angular differences between in vivo and ex vivo PEVs was 12 degrees. Conclusion This study characterizes the diffusion properties of the squirrel monkey brain and serves as the groundwork for using the squirrel monkey, both in vivo and ex vivo, as a model for diffusion MRI studies.

Original languageEnglish (US)
Pages (from-to)29-38
Number of pages10
JournalMagnetic Resonance Imaging
Volume35
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Keywords

  • Cortex
  • DTI
  • Diffusion MRI
  • Primate
  • Squirrel monkey

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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