Quantitative assessment of diffusional kurtosis anisotropy

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.

[1]  C. Sønderby,et al.  Orientationally invariant metrics of apparent compartment eccentricity from double pulsed field gradient diffusion experiments , 2013, NMR in biomedicine.

[2]  Brian Hansen,et al.  Experimentally and computationally fast method for estimation of a mean kurtosis , 2013, Magnetic resonance in medicine.

[3]  S. Arridge,et al.  Detection and modeling of non‐Gaussian apparent diffusion coefficient profiles in human brain data , 2002, Magnetic resonance in medicine.

[4]  John S. Duncan,et al.  Identical, but not the same: Intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0 T scanners , 2010, NeuroImage.

[5]  Carl-Fredrik Westin,et al.  Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: Applications in healthy volunteers and in brain tumors , 2015, NeuroImage.

[6]  M. F. Falangola,et al.  Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging , 2013, Journal of magnetic resonance imaging : JMRI.

[7]  Gang Yu,et al.  Reproducibility of diffusion tensor imaging in normal subjects: an evaluation of different gradient sampling schemes and registration algorithm , 2014, Neuroradiology.

[8]  Thomas R. Knösche,et al.  White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI , 2013, NeuroImage.

[9]  J. Helpern,et al.  MRI quantification of non‐Gaussian water diffusion by kurtosis analysis , 2010, NMR in biomedicine.

[10]  Max A. Viergever,et al.  Partial volume effect as a hidden covariate in DTI analyses , 2011, NeuroImage.

[11]  Christian Beaulieu,et al.  Diffusion anisotropy in subcortical white matter and cortical gray matter: Changes with aging and the role of CSF‐suppression , 2004, Journal of magnetic resonance imaging : JMRI.

[12]  B. Ardekani,et al.  Estimation of tensors and tensor‐derived measures in diffusional kurtosis imaging , 2011, Magnetic resonance in medicine.

[13]  Daniel C. Alexander,et al.  NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.

[14]  M. Koch,et al.  A tensor model and measures of microscopic anisotropy for double-wave-vector diffusion-weighting experiments with long mixing times. , 2010, Journal of magnetic resonance.

[15]  Liang Xuan,et al.  Estimation of the orientation distribution function from diffusional kurtosis imaging , 2008, Magnetic resonance in medicine.

[16]  Xiaoping P. Hu,et al.  Enhancing measured diffusion anisotropy in gray matter by eliminating CSF contamination with FLAIR , 2004, Magnetic resonance in medicine.

[17]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[18]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[19]  J. Helpern,et al.  Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[20]  Yoram Cohen,et al.  From single‐pulsed field gradient to double‐pulsed field gradient MR: gleaning new microstructural information and developing new forms of contrast in MRI , 2010, NMR in biomedicine.

[21]  Timothy Edward John Behrens,et al.  Between session reproducibility and between subject variability of diffusion MR and tractography measures , 2006, NeuroImage.

[22]  Ed X. Wu,et al.  Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis , 2008, NeuroImage.

[23]  Essa Yacoub,et al.  Multiple Q-Shell ODF Reconstruction in Q-Ball Imaging , 2009, MICCAI.

[24]  C. Westin,et al.  Quanti fi cation of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure : Applications in healthy volunteers and in brain tumors , 2016 .

[25]  D. Parker,et al.  Analysis of partial volume effects in diffusion‐tensor MRI , 2001, Magnetic resonance in medicine.

[26]  J. Jensen,et al.  A simple noise correction scheme for diffusional kurtosis imaging. , 2015, Magnetic resonance imaging.

[27]  G. Sapiro,et al.  Reconstruction of the orientation distribution function in single‐ and multiple‐shell q‐ball imaging within constant solid angle , 2010, Magnetic resonance in medicine.

[28]  J. Helpern,et al.  Double-pulsed diffusional kurtosis imaging. , 2014, NMR in biomedicine.

[29]  D. Tuch Q‐ball imaging , 2004, Magnetic resonance in medicine.

[30]  Eric Achten,et al.  Optimal Experimental Design for Diffusion Kurtosis Imaging , 2010, IEEE Transactions on Medical Imaging.

[31]  Mariana Lazar,et al.  Mapping brain anatomical connectivity using white matter tractography , 2010, NMR in biomedicine.

[32]  P. Szeszko,et al.  MRI atlas of human white matter , 2006 .

[33]  J. Helpern,et al.  Leading non‐Gaussian corrections for diffusion orientation distribution function , 2014, NMR in biomedicine.

[34]  P. Hagmann,et al.  Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[35]  V. Wedeen,et al.  Diffusion MRI of Complex Neural Architecture , 2003, Neuron.

[36]  Alexander Leemans,et al.  Variability in diffusion kurtosis imaging: Impact on study design, statistical power and interpretation , 2013, NeuroImage.