Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease.

Area of Science:

• Neuroimaging
• White Matter Diseases
• Diffusion MRI

Background:

• Small vessel disease (SVD) causes microstructural white matter alterations impacting cognition.
• Current diffusion models may not fully capture these changes.

Purpose of the Study:

• To evaluate if multi-shell diffusion models enhance characterization of SVD-related microstructural changes.
• To assess associations with processing speed, disease progression, and reproducibility.

Main Methods:

• 50 sporadic SVD and 59 CADASIL patients underwent 3T MRI with multi-shell diffusion imaging.
• Diffusion Tensor Imaging (DTI), Diffusion Kurtosis Imaging (DKI), and Neurite Orientation Dispersion and Density Imaging (NODDI) models were applied.
• Associations with processing speed, longitudinal changes, and inter-site reproducibility were analyzed.

Main Results:

• DKI metrics showed strongest associations with processing speed (R² up to 21%) and improved characterization over conventional markers.
• DTI and DKI metrics demonstrated similar performance in detecting disease progression.
• DTI and DKI metrics exhibited excellent reproducibility (ICC >0.93), while NODDI metrics were less reproducible.

Conclusions:

• Multi-shell diffusion imaging, particularly DKI, improves detection and characterization of SVD-related white matter alterations.
• Diffusion MRI metrics are reproducible and suitable for SVD research and clinical applications.
• A publicly available dataset is provided to support future research.