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Cited by 113Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsMRI in cancer diagnosis

Quantitative assessment of diffusional kurtosis anisotropy

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Glenn, G. Russell, Helpern, Joseph A., Tabesh, Ali, Jensen, Jens H.·2015·NMR in Biomedicine
DOI 10.1002/nbm.3271PMC PMC4378654
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Abstract

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.

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  • DKI can provide directional metrics such as axial kurtosis and radial kurtosis, and diffusional kurtosis anisotropy, which quantify how non-Gaussian diffusion varies with fiber orientation and may reveal microstructural features not captured by conventional diffusion anisotropy alone.

    “Diffusion kurtosis imaging can, therefore, provide directional metrics such as axial kurtosis and radial kurtosis, and more specifically diffusional kurtosis anisotropy, which quantify how non-Gaussian diffusion varies with fiber orientation and may reveal microstructural features not captured by conventional diffusion anisotropy alone (Glenn et al., 2015).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Glenn et al., 2015

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  1. [1]Basser PJ Pierpaoli C Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI J Magn Reson B 1996 6 111 3 209 19 8661285
  2. [2]Pierpaoli C Basser PJ Toward a quantitative assessment of diffusion anisotropy Magn Reson Med 1996 36 893 906 8946355
  3. [3]Alexander AL Hasan KM Lazar M Tsuruda JS Parker DL Analysis of partial volume effects in diffusion-tensor MRI Magn Reson Med 2001 45 770 80 11323803
  4. [4]Alexander DC Barker GJ Arridge SR Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data Magn Reson Med 2002 48 331 40 12210942
  5. [5]Bhagat YA Beaulieu C Diffusion anisotropy in subcortical white matter and cortical gray matter: changes with aging and the role of CSF-suppression J Magn Reson Imaging 2004 20 216 27 15269946
  6. [6]Ma X Kadah YM LaConte SM Hu X Enhancing measured diffusion anisotropy in gray matter by eliminating CSF contamination with FLAIR Magn Reson Med 2004 51 423 14755672
  7. [7]Vos SB Jones DK Viergever MA Leemans A Partial volume effect as a hidden covariate in DTI analyses Neuroimage 2011 55 1566 76 21262366
  8. [8]Szczepankiewicz F Lätt J Wirestam R Leemans A Sundgren P van Westen D Ståhlberg F Nilsson M Variability in diffusion kurtosis imaging: impact on study design, statistical power and interpretation Neuroimage 2013 76 145 54 23507377
  9. [9]Yang AW Jensen JH Hu CC Tabesh A Falangola MF Helpern JA Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging J Magn Reson Imaging 2013 37 365 71 23034866 PMC3538115
  10. [11]Jensen JH Helpern JA Ramani A Lu H Kaczynski K Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging Magn Reson Med 2005 53 1432 40 15906300
  11. [12]Jensen JH Helpern JA MRI quantification of non-Gaussian water diffusion by kurtosis analysis NMR Biomed 2010 23 698 710 20632416 PMC2997680
  12. [13]Hui ES Cheung MM Qi L Wu EX Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis Neuroimage 2008 8 1 42 1 122 34 18524628
  13. [14]Poot DH den Dekker AJ Achten E Verhoye M Sijbers J Optimal experimental design for diffusion kurtosis imaging IEEE Trans Med Imaging 2010 3 29 3 819 29 20199917
  14. [15]Hansen B Lund TE Sangill R Jespersen SN Experimentally and computationally fast method for estimation of a mean kurtosis Magn Reson Med 2013 6 69 6 1754 60 23589312
  15. [17]Lazar M Jensen JH Xuan L Helpern JA Estimation of the orientation distribution function from diffusional kurtosis imaging Magn Reson Med 2008 60 774 81 18816827 PMC2562250
  16. [18]Jensen JH Helpern JA Tabesh A Leading non-Gaussian corrections for diffusion orientation distribution functions NMR Biomed 2014 27 202 11 24738143 PMC4115643
  17. [19]Lazar M Mapping brain anatomical connectivity using white matter tractography NMR Biomed 2010 23 821 35 20886567 PMC4503207
  18. [21]Wedeen VJ Hagmann P Tseng WY Reese TG Weisskoff RM Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging Magn Reson Med 2005 54 1377 1386 16247738
  19. [22]Tuch DS Reese TG Wiegell MR Wedeen VJ Diffusion MRI of complex neural architecture Neuron 2003 40 885 895 14659088
  20. [23]Aganj I Lenglet C Sapiro G Yacoub E Ugurbil K Harel N Multiple Q-shell ODF reconstruction in q-ball imaging Med Image Comput Comput Assist Interv 2009 12 Pt 2 423 431 20426140 PMC4360971
  21. [24]Aganj I Lenglet C Sapiro G Yacoub E Ugurbil K Harel N Reconstruction of the orientation distribution function in single- and multipleshell q-ball imaging within constant solid angle Magn Reson Med 2010 64 554 566 20535807 PMC2911516
  22. [25]Tabesh A Jensen JH Ardekani BA Helpern JA Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging Magn Reson Med 2011 65 823 36 21337412 PMC3042509
  23. [26]Mori S Wakana S Nagae-Poetscher LM van Zijl PC MRI atlas of human white matter Elsevier Amsterdam, The Netherlands 2005
  24. [27]Heiervang E Behrens TE Mackay CE Robson MD Johansen-Berg H Between session reproducibility and between subject variability of diffusion MR and tractography measures Neuroimage 2006 33 867 77 17000119
  25. [28]Liu X Yang Y Sun J Yu G Xu J Niu C Tian H Lin P Reproducibility of diffusion tensor imaging in normal subjects: an evaluation of different gradient sampling schemes and registration algorithm Neuroradiology 2014 56 497 510 24609528
  26. [29]Vollmar C O'Muircheartaigh J Barker GJ Symms MR Thompson P Kumari V Duncan JS Richardson MP Koepp MJ Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners Neuroimage 2010 51 1384 94 20338248 PMC3163823
  27. [30]Glenn GR Tabesh A Jensen JH A Simple Noise Correction Scheme for Diffusional Kurtosis Imaging Magn Reson Imaging 2014 Epub ahead of print PMC4268031 25172990
  28. [31]Shemesh N Ozarslan E Komlosh ME Basser PJ Cohen Y From single-pulsed field gradient to double-pulsed field gradient MR: gleaning new microstructural information and developing new forms of contrast in MRI NMR Biomed 2010 23 757 80 20690130 PMC3139994
  29. [32]Lawrenz M Koch MA Finsterbusch J A tensor model and measures of microscopic anisotropy for double-wave-vector diffusion-weighting experiments with long mixing times J Magn Reson 2010 1 202 1 43 56 19854085
  30. [33]Jespersen SN Lundell H Sønderby CK Dyrby TB Orientationally invariant metrics of apparent compartment eccentricity from double pulsed field gradient diffusion experiments NMR Biomed 2013 26 1647 62 24038641
  31. [34]Jensen JH Hui ES Helpern JA Double-pulsed diffusional kurtosis imaging NMR Biomed 2014 4 27 4 363 70 24623712
  32. [35]Szczepankiewicz F Lasič S van Westen D Sundgren PC Englund E Westin CF Ståhlberg F Lätt J Topgaard D Nilsson M Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: Applications in healthy volunteers and in brain tumors Neuroimage 2015 104 241 52 25284306 PMC4252798

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Authors
Glenn, G. R., Helpern, J. A., Tabesh, A., & Jensen, J. H.
Affiliations
Medical University of South Carolina (US)
Corresponding author
Glenn, G. Russell
ORCID
Venue
NMR in Biomedicine
Publisher
Wiley
Published
2015-02-26
Volume
28
Issue
4
Pages
448-459
ISSN
  • 0952-3480 (ISSN-L)
  • 1099-1492
DOI
10.1002/nbm.3271
PMC
PMC4378654
OpenAlex
W1931116562
Cited by
113
References
3
Citations by year
2026: 8 · 2025: 14 · 2024: 6 · 2023: 9 · 2022: 14 · 2021: 18 · 2020: 6 · 2019: 7 · 2018: 7 · 2017: 11 · 2016: 9 · 2015: 4
FWCI
8.38
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • NMR in Biomedicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institutes of Health (T32 GM008716)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
Keywords
diffusion kurtosis imaging, fractional anisotropy, generalized fractional anisotropy, diffusion anisotropy, non-Gaussian diffusion, white matter fiber bundles, thalamus, lentiform nucleus, deep brain structures, diffusion tensor imaging
MeSH terms
Adult, Algorithms, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Normal Distribution, Anisotropy, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, White Matter, Datasets as Topic

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