Background: Dilated brain perivascular spaces (PVSs) are found to be associated with many conditions, including aging, dementia, and Alzheimer's disease (AD). Conventionally, PVS assessment is mainly based on subjective observations of the number, size and shape of PVSs in MR images collected at clinical field strengths (≤3T). This study tests the feasibility of imaging and quantifying brain PVS with an ultra-high 7T whole-body MRI scanner.
New method: 3D high resolution T2-weighted brain images from healthy subjects (n=3) and AD patients (n=5) were acquired on a 7T whole-body MRI scanner. To automatically segment the small hyperintensive fluid-filling PVS structures, we also developed a quantitative program based on algorithms for spatial gradient, component connectivity, edge-detection, k-means clustering, etc., producing quantitative results of white matter PVS volume densities.
Results: The 3D maps of automatically segmented PVS show an apparent increase in PVS density in AD patients compared to age-matched healthy controls due to the PVS dilation (8.0±2.1 v/v% in AD vs. 4.9±1.3 v/v% in controls, p<0.05).
Comparison with existing method: We demonstrated that 7T provides sufficient SNR and resolution for quantitatively measuring PVSs in deep white matter that is challenging with clinical MRI systems (≤3T). Compared to the conventional visual counting and rating for the PVS assessment, the quantitation method we developed is automatic and objective.
Conclusions: Quantitative PVS MRI at 7T may serve as a non-invasive and endogenous imaging biomarker for diseases with PVS dilation.
Keywords: Alzheimer's disease; MRI; Perivascular drainage; Perivascular space.
Published by Elsevier B.V.