Three-dimensional characterization of non-gaussian water diffusion in humans using diffusion kurtosis imaging

Hanzhang Lu, Jens H. Jensen, Anita Ramani, Joseph A. Helpern

Research output: Contribution to journalArticle

279 Scopus citations

Abstract

Conventional diffusion tensor imaging (DTI) measures water diffusion parameters based on the assumption that the spin displacement distribution is a Gaussian function. However, water movement in biological tissue is often non-Gaussian and this non-Gaussian behavior may contain useful information related to tissue structure and pathophysiology. Here we propose an approach to directly measure the non-Gaussian property of water diffusion, characterized by a four-dimensional matrix referred to as the diffusion kurtosis tensor. This approach does not require the complete measurement of the displacement distribution function and, therefore, is more time efficient compared with the q-space imaging technique. A theoretical framework of the DK calculation is established, and experimental results are presented for humans obtained within a clinically feasible time of about 10 min. The resulting kurtosis maps are shown to be robust and reproducible. Directionally-averaged apparent kurtosis coefficients (AKC, a unitless parameter) are 0.74 ± 0.03, 1.09 ± 0.01 and 0.84 ± 0.02 for gray matter, white matter and thalamus, respectively. The three-dimensional kurtosis angular plots show tissue-specific geometry for different brain regions and demonstrate the potential of identifying multiple fiber structures in a single voxel. Diffusion kurtosis imaging is a useful method to study non-Gaussian diffusion behavior and can provide complementary information to that of DTI.

Original languageEnglish (US)
Pages (from-to)236-247
Number of pages12
JournalNMR in biomedicine
Volume19
Issue number2
DOIs
StatePublished - Apr 1 2006

Keywords

  • DKI
  • DTI
  • Diffusion
  • Kurtosis
  • Non-Gaussian

ASJC Scopus subject areas

  • Molecular Medicine
  • Radiology Nuclear Medicine and imaging
  • Spectroscopy

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