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Mapping Neuroinflammation With Diffusion-Weighted Magnetic Resonance Imaging: A Randomized Crossover Study.

Julia R Plank1, Catherine A Morgan2, Flavio Dell'Acqua3

  • 1School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.

Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
|May 16, 2025
PubMed
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This summary is machine-generated.

Advanced MRI techniques detected brain microstructural changes from inflammation. This non-invasive neuroimaging approach shows promise for studying psychiatric disorders and their inflammatory links.

Area of Science:

  • Neuroimaging
  • Neuroinflammation
  • Psychiatric Disorders

Background:

  • Neuroinflammation's role in psychiatric conditions is unclear.
  • Non-invasive in vivo methods are needed to measure neuroinflammation.
  • Diffusion-weighted MRI was explored for detecting low-level neuroinflammation.

Purpose of the Study:

  • To investigate advanced diffusion-weighted MRI techniques for detecting neuroinflammation.
  • To assess potential applications in psychiatric disorders.

Main Methods:

  • A randomized, placebo-controlled, crossover study with 20 healthy volunteers.
  • MRI scans (diffusion tensor, diffusion kurtosis, NODDI) before and after placebo/vaccine.
  • Analysis of thirteen white matter tracts and 15 grey matter regions using region-of-interest and tractography.
Keywords:
Diffusion kurtosis imagingDiffusion tensor imagingNeurite orientation density and dispersion imagingNeuroinflammationTyphoid vaccine

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Main Results:

  • Global reduction in mean diffusivity (MD) in white matter tracts (p=.040).
  • Increased axial kurtosis in white matter (p<.001) and mean/radial kurtosis in grey matter (p=.038).
  • Correlations observed between interleukin-6 (IL-6) and diffusion parameters.

Conclusions:

  • Diffusion-weighted MRI is sensitive to inflammation-induced microstructural brain changes.
  • This technique may help understand neuroinflammation in psychiatric disorders.
  • Further research integrating complementary methods is recommended.