Higher spatial resolution diffusion-weighted imaging improves characterization of white matter disconnection in Alzheimer's disease.
In addition to the accumulation of neuropathologies (i.e., amyloid beta, neurofibrillary tangles), Alzheimer's disease (AD) is associated with the degradation of white matter (WM) structural pathways that connect distributed brain regions. However, previous studies of AD-related decreases in WM structural connectivity have primarily used standard spatial resolution diffusion-weighted imaging (DWI) acquisitions, which cannot adequately resolve WM connections in fine-grained regions with crossing fibers or high curvature. To better assess more subtle WM tissue degradation in AD, this DWI study compared measures of structural connectivity derived from a high-resolution multi-shot multiplexed sensitivity encoding (MUSE) acquisition (1 mm isotropic voxels; 1 µl volume) and a standard resolution acquisition (1.5 mm isotropic voxels; 3.375 µl volume), using a sample of 24 participants with AD and 24 demographically matched healthy controls. Graph theoretical measures of within-network connectivity, between-network connectivity, and system segregation were obtained from a standard network partition. As expected, results indicated larger AD-related decreases in between-network than within-network connectivity, leading to increased network segregation for both DWI acquisitions. However, the high-resolution MUSE DWI acquisition achieved higher sensitivity and specificity to AD-related differences in structural connectivity than the standard resolution DWI protocol, consistent with prior findings from rodents and healthy adults across the lifespan. Together, these findings suggest that this clinically feasible, high-resolution MUSE DWI methodology may detect more subtle AD-related differences in WM connectivity than standard resolution DWI acquisitions.
