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Quantitative assessment of diffusional kurtosis anisotropy
Author(s) -
Glenn G. Russell,
Helpern Joseph A.,
Tabesh Ali,
Jensen Jens H.
Publication year - 2015
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.3271
Subject(s) - kurtosis , anisotropy , fractional anisotropy , diffusion mri , tensor (intrinsic definition) , diffusion , nuclear magnetic resonance , gaussian , statistical physics , physics , chemistry , mathematics , optics , statistics , geometry , magnetic resonance imaging , thermodynamics , computational chemistry , medicine , radiology
Diffusional kurtosis imaging (DKI) measures the diffusion and kurtosis tensors to quantify restricted, non‐Gaussian diffusion that occurs in biological tissue. By estimating the kurtosis tensor, DKI accounts for higher order diffusion dynamics, when compared with diffusion tensor imaging (DTI), and consequently can describe more complex diffusion profiles. Here, we compare several measures of diffusional anisotropy which incorporate information from the kurtosis tensor, including kurtosis fractional anisotropy (KFA) and generalized fractional anisotropy (GFA), with the diffusion tensor‐derived fractional anisotropy (FA). KFA and GFA demonstrate a net enhancement relative to FA when multiple white matter fiber bundle orientations are present in both simulated and human data. In addition, KFA shows net enhancement in deep brain structures, such as the thalamus and the lenticular nucleus, where FA indicates low anisotropy. Thus, KFA and GFA provide additional information relative to FA with regard to diffusional anisotropy, and may be particularly advantageous for the assessment of diffusion in complex tissue environments. Copyright © 2015 John Wiley & Sons, Ltd.