AI Article Synopsis

  • Alterations in white matter microstructure are linked to neurodegenerative disorders, and traditional analysis requires tissue samples, while MRI diffusion-weighted imaging offers a non-invasive alternative.
  • The study evaluated two analysis methods (ROI-based and voxel-based) alongside four mathematical models to assess white matter features, using mouse samples imaged at different MRI strengths.
  • Findings revealed that RBA-ACD and VBA-AAD methods provided the most reliable data for analyzing white matter properties efficiently, with a comparative guide for selecting the best models for specific research needs.

Article Abstract

Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter AxD¯, packing fraction f, intra-cellular and D and extra-cellular D diffusion coefficients, as well as the frequency dependence of D, β for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.

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http://dx.doi.org/10.1016/j.mri.2024.110221DOI Listing

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Article Synopsis
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  • The study evaluated two analysis methods (ROI-based and voxel-based) alongside four mathematical models to assess white matter features, using mouse samples imaged at different MRI strengths.
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