
AbstractHigh resolution diffusion tensor images of the mouse brain were acquired using the pulsed gradient spin echo sequence and the oscillating gradient spin echo sequence. The oscillating gradient spin echo tensor images demonstrated frequency‐dependent changes in diffusion measurements, including apparent diffusion coefficient and fractional anisotropy, in major brain structures. Maps of the rate of change in apparent diffusion coefficient with oscillating gradient frequency revealed novel tissue contrast in the mouse hippocampus, cerebellum, and cerebral cortex. The observed frequency‐dependent contrasts resembled neuronal soma‐specific Nissl staining and nuclei‐specific 4′,6‐diamidino‐2‐phenylindole (DAPI) staining in the mouse brain, which suggests that the contrasts might be related to key features of cytoarchitecture in the brain. In the mouse cuprizone model, oscillating gradient spin echo‐based diffusion MRI revealed significantly higher frequency‐dependence of perpendicular diffusivity (λ⊥) in the demyelinated caudal corpus callosum at 4 weeks after cuprizone treatment when compared with control mice and mice at 6 weeks after cuprizone treatment. The elevated frequency‐dependence of λ⊥coincided with the infiltration of activated microglia/macrophages and disruption of axons during acute demyelination in the caudal corpus callosum. The results demonstrate the potential of oscillating gradient spin echo‐based diffusion MRI for providing tissue contrasts complimentary to conventional pulsed gradient spin echo‐based diffusion MRI. Magn Reson Med 67:98–109, 2012. © 2011 Wiley Periodicals, Inc.
Brain, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Mice, Inbred C57BL, Mice, Diffusion Magnetic Resonance Imaging, Oscillometry, Image Interpretation, Computer-Assisted, Animals, Female, Algorithms
Brain, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Mice, Inbred C57BL, Mice, Diffusion Magnetic Resonance Imaging, Oscillometry, Image Interpretation, Computer-Assisted, Animals, Female, Algorithms
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