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Updated: Sep 11, 2025

Diffusion Imaging in the Rat Cervical Spinal Cord
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Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric

Jake Hamilton1,2, Kathy Xu3,4, Nicole Geremia3,4

  • 1Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Canada.

Imaging Neuroscience (Cambridge, Mass.)
|August 13, 2025
PubMed
Summary
This summary is machine-generated.

Frequency-dependent diffusion MRI with oscillating gradients and diffusional kurtosis imaging (DKI) can reveal tissue microstructure. A new DKI fitting algorithm enables robust directional kurtosis mapping with efficient encoding, improving sensitivity to cellular changes.

Keywords:
diffusion MRIdiffusion dispersiondiffusional kurtosisoscillating gradientspatial regularization

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Area of Science:

  • Neuroimaging
  • Biophysics
  • Medical Physics

Background:

  • Diffusion MRI (dMRI) provides insights into tissue microstructure.
  • Frequency-dependent dMRI and diffusional kurtosis imaging (DKI) offer advanced microstructural information.
  • Combining oscillating gradient encoding with DKI is challenging due to b-value limitations.

Purpose of the Study:

  • To develop and validate a DKI fitting algorithm for efficient, frequency-dependent directional kurtosis estimation.
  • To overcome technical challenges in generating high b-values with oscillating gradient diffusion encoding.
  • To enable robust DKI mapping using a 10-direction scheme with improved sensitivity to microstructural changes.

Main Methods:

  • Investigated a DKI fitting algorithm combining axisymmetric DKI fitting, a symmetry axis prior, and spatial regularization.
  • Utilized an efficient 10-direction encoding scheme enabling higher b-values.
  • Applied the method to mouse and human data with oscillating gradient frequencies (0, 60, 120 Hz).

Main Results:

  • The proposed axisymmetric DKI fitting algorithm achieved comparable or improved image and DKI map quality versus traditional methods.
  • Enforcing consistent symmetry axes across frequencies enhanced fitting accuracy.
  • Spatial regularization preserved image features better than pre-fitting Gaussian filtering.
  • The 10-direction scheme with the novel fitting algorithm provided robust frequency-dependent directional kurtosis maps.

Conclusions:

  • The developed DKI fitting algorithm successfully enables robust frequency-dependent directional kurtosis mapping with efficient encoding schemes.
  • This approach offers increased sensitivity to cytoarchitectural alterations across various spatial scales.
  • The findings have implications for studying microstructural changes in aging and disease.