Rapid Quantification of White Matter Disconnection in the Human Brain

Abstract

With an estimated five million new stroke survivors every year and a rapidly aging population suffering from hyperintensities and diseases of presumed vascular origin that affect white matter and contribute to cognitive decline, it is critical that we understand the impact of white matter damage on brain structure and behavior. Current techniques for assessing the impact of lesions consider only location, type, and extent, while ignoring how the affected region was connected to the rest of the brain. Regional brain function is a product of both local structure and its connectivity. Therefore, obtaining a map of white matter disconnection is a crucial step that could help us predict the behavioral deficits that patients exhibit. In the present work, we introduce a new practical method for computing lesion-based white matter disconnection maps that require only moderate computational resources. We achieve this by creating diffusion tractography models of the brains of healthy adults and assessing the connectivity between small regions. We then interrupt these connectivity models by projecting patients' lesions into them to compute predicted white matter disconnection. A quantified disconnection map can be computed for an individual patient in approximately 35 seconds using a single core CPU-based computation. In comparison, a similar quantification performed with other tools provided by MRtrix3 takes 5.47 minutes.

White Matter Microstructural Correlates of Cognitive and Motor Functioning Revealed via Multimodal Multivariate Analysis

“…For each significant LV, we chose a maximum of 3 regions of spatially connected voxels with large weights in order to individually identify the set of streamlines passing through them. This approach is identical to that used in identifying the network effects of brain lesions (Karnath et al, 2018; Talozzi et al, 2023; Thiebaut de Schotten et al, 2020; Zayed et al, 2020). Here, we used a previously constructed streamline connectivity model that consisted of 10 million representative streamlines between all GM regions in our template space.…”

Spatial–temporal patterns of brain disconnectome in Alzheimer's disease

“…Recently, structural disconnectome has been proposed to characterize the disruptions caused by local lesions on connectivity by spatially mapping white matter fiber tracts with regional brain lesions (Carolyn D. Langen et al, 2017 ; Zayed et al, 2020 ). Studies using 3714 participants from Rotterdam Study found that WMH‐related disconnectome was especially related to worse executive functioning and concluded that WMH‐related disconnectome explains more variation in cognitive function than regional lesion volumes (C. D. Langen et al, 2018 ).…”