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Updated: Dec 2, 2025
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Assessment of the structural complexity of diffusion MRI voxels using 3D electron microscopy in the rat brain
Raimo A Salo1, Ilya Belevich2, Eija Jokitalo2
1A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland.
Abstract:
Validation and interpretation of diffusion magnetic resonance imaging (dMRI) requires detailed understanding of the actual microstructure restricting the diffusion of water molecules. In this study, we used serial block-face scanning electron microscopy (SBEM), a three-dimensional electron microscopy (3D-EM) technique, to image seven white and grey matter volumes in the rat brain. SBEM shows excellent contrast of cellular membranes, which are the major components restricting the diffusion of water in tissue. Additionally, we performed 3D structure tensor (3D-ST) analysis on the SBEM volumes and parameterised the resulting orientation distributions using Watson and angular central Gaussian (ACG) probability distributions as well as spherical harmonic (SH) decomposition. We analysed how these parameterisations described the underlying orientation distributions and compared their orientation and dispersion with corresponding parameters from two dMRI methods, neurite orientation dispersion and density imaging (NODDI) and constrained spherical deconvolution (CSD). Watson and ACG parameterisations and SH decomposition captured well the 3D-ST orientation distributions, but ACG and SH better represented the distributions due to its ability to model asymmetric dispersion. The dMRI parameters corresponded well with the 3D-ST parameters in the white matter volumes, but the correspondence was less evident in the more complex grey matter. SBEM imaging and 3D-ST analysis also revealed that the orientation distributions were often not axially symmetric, a property neatly captured by the ACG distribution. Overall, the ability of SBEM to image diffusion barriers in intricate detail, combined with 3D-ST analysis and parameterisation, provides a step forward toward interpreting and validating the dMRI signals in complex brain tissue microstructure.
Insights
Serial block-face scanning electron microscopy (SBEM) and 3D structure tensor analysis provide detailed insights into brain microstructure. This helps validate diffusion magnetic resonance imaging (dMRI) by revealing diffusion barriers and orientation distributions.
Area of Science:
- Neuroscience
- Biophysics
- Microscopy
Background:
- Diffusion magnetic resonance imaging (dMRI) interpretation relies on understanding water diffusion barriers within brain tissue microstructure.
- Current dMRI validation methods lack detailed microstructural information, particularly in complex grey matter regions.
Purpose of the Study:
- To utilize serial block-face scanning electron microscopy (SBEM) and 3D structure tensor (3D-ST) analysis to characterize brain microstructure.
- To compare microstructural orientation distributions derived from SBEM/3D-ST with parameters from dMRI techniques (NODDI, CSD).
- To advance the interpretation and validation of dMRI signals in brain tissue.
Main Methods:
- Imaging of rat brain white and grey matter using serial block-face scanning electron microscopy (SBEM).
- 3D structure tensor (3D-ST) analysis of SBEM volumes to determine orientation distributions.
- Parameterization of orientation distributions using Watson, angular central Gaussian (ACG), and spherical harmonic (SH) models.
- Comparison of 3D-ST derived parameters with neurite orientation dispersion and density imaging (NODDI) and constrained spherical deconvolution (CSD) parameters.
Main Results:
- SBEM provided high-contrast visualization of cellular membranes, crucial diffusion barriers.
- ACG and SH models better captured orientation distributions, especially asymmetric ones, compared to Watson.
- dMRI parameters showed good correspondence with 3D-ST parameters in white matter, but less so in grey matter.
- SBEM and 3D-ST analysis revealed non-axially symmetric orientation distributions, well-described by ACG.
Conclusions:
- SBEM combined with 3D-ST analysis offers detailed microstructural insights for dMRI validation.
- The ability to model asymmetric dispersion improves the characterization of complex neural architecture.
- This approach represents a significant step towards accurate interpretation of dMRI signals in diverse brain tissues.
