Inferring diameters of spheres and cylinders using interstitial water

Sheryl L Herrera1, Morgan E Mercredi2, Richard Buist3

  • 1Physics and Astronomy, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada. umherres@myumanitoba.ca.

Abstract

Insights

Oscillating gradient (OG) magnetic resonance imaging (MRI) successfully inferred small axon diameters (3-10 μm) and tube sizes. This diffusion spectroscopy method advances understanding of brain connectivity.

Area of Science:

  • Neuroimaging
  • Biophysics
  • Diffusion MRI

Background:

  • Early magnetic resonance imaging (MRI) methods for axon diameter distribution inference were limited to larger axons (> 5 μm).
  • Oscillating gradient (OG) sequences offer potential for studying smaller axons, crucial for cortical connections.
  • Previous simulations suggested a breakdown of constant extra-axonal diffusion models at OG frequencies.

Purpose of the Study:

  • To experimentally validate the use of OG sequences for inferring axon diameter distributions.
  • To test a time-varying interstitial apparent diffusion coefficient model.
  • To assess the accuracy of OG diffusion spectroscopy in phantoms.

Main Methods:

  • Diffusion spectra were acquired using OG sequences in phantoms containing water-filled beads (3, 6, 10 μm) and tubes (151 μm).
  • Bead diameters and tube surface-to-volume ratios were measured.
  • Interstitial models were applied to infer structural parameters.

Main Results:

  • Inferred bead pore radii ranged from 0.54±0.06 μm to 1.0±0.1 μm, corresponding to bead diameters of 2.6±0.3 μm to 9±1 μm.
  • The estimated surface-to-volume ratio for the tubes was 0.06±0.02 μm-1, indicating a diameter of 180±70 μm.
  • The OG diffusion spectroscopy accurately estimated the dimensions of the phantoms.

Conclusions:

  • Interstitial models utilizing OG successfully inferred bead diameters (3-10 μm) and tube diameters (151 μm).
  • The findings support the utility of OG diffusion spectroscopy for characterizing small axonal structures.
  • This technique holds promise for advancing the study of brain microstructure and connectivity.

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