Abstract
Here we describe and provide diffusion magnetic resonance imaging (dMRI) data that was acquired in neural tissue and a physical phantom. Data acquired in biological tissue includes: fixed rat brain (acquired at 9.4 T) and spinal cord (acquired at 16.4 T) and in normal human brain (acquired at 3 T). This data was recently used for evaluation of diffusion kurtosis imaging (DKI) contrasts and for comparison to diffusion tensor imaging (DTI) parameter contrast. The data has also been used to optimize b-values for ex vivo and in vivo fast kurtosis imaging. The remaining data was obtained in a physical phantom with three orthogonal fiber orientations (fresh asparagus stems) for exploration of the kurtosis fractional anisotropy. However, the data may have broader interest and, collectively, may form the basis for image contrast exploration and simulations based on a wide range of dMRI analysis strategies.
Highlights
Background & SummaryDiffusion weighted MRI is highly sensitive to tissue microstructure, which makes it important as a tool in research and diagnostics
mean kurtosis (MK)'s potential value has been reported in several other neurological applications: Parkinson’s disease[12], epilepsy[13], gliomas[14,15], chronic mild stress[16], attention deficit hyperactivity disorder (ADHD)[17], traumatic brain injury[18] and review in[19], and normal development[20,21]
The data provided here allows users to perform both traditional diffusion kurtosis imaging (DKI) analysis and fast kurtosis analysis from data sets acquired in fixed rat brain and in human brain
Summary
Diffusion weighted MRI (dMRI) is highly sensitive to tissue microstructure, which makes it important as a tool in research and diagnostics. The microstructure of biological tissues, influences the diffusion process and causes the spin phase distribution to deviate from normal. This deviation is partially described by including the kurtosis term in the cumulant expansion[3]. In an effort to remove these limitations, strategies for fast kurtosis imaging have recently been proposed[22,23,24] These strategies employ nine distinct diffusion encoding directions acquired at two different b-values to efficiently estimate the mean kurtosis using a definition based on the kurtosis tensor, W. The data provided here allows users to perform both traditional DKI analysis and fast kurtosis analysis from data sets acquired in fixed rat brain and in human brain. Formats, and organization are provided in the Data Records section and Table 1
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