Impact of thresholding on the consistency and sensitivity of diffusion MRI-based brain networks in patients with cerebral small vessel disease.

Introduction: Thresholding of low-weight connections of diffusion MRI-based brain networks has been proposed to remove false-positive connections. It has been previously established that this yields more reproducible scan-rescan network architecture in healthy subjects. In patients with brain disease, network measures are applied to assess inter-individual variation and changes over time.

Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease.

Objectives: Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects.

Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease.

A popular solution to control for edge density variability in structural brain network analysis is to threshold the networks to a fixed density across all subjects. However, it remains unclear how this type of thresholding affects the basic network architecture in terms of edge weights, hub location, and hub connectivity and, especially, how it affects the sensitivity to detect disease-related abnormalities. We investigated these two questions in a cohort of patients with cerebral small vessel disease and age-matched controls.

Cortical Microinfarcts and White Matter Connectivity in Memory Clinic Patients.

Cerebral microinfarcts (CMIs) are associated with cognitive impairment and dementia. CMIs might affect cognitive performance through disruption of cerebral networks. We investigated in memory clinic patients whether cortical CMIs are clustered in specific brain regions and if presence of cortical CMIs is associated with reduced white matter (WM) connectivity in tracts projecting to these regions.