Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment

Abstract

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels (‘bullseye’ parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.

Equalization of Brain State Occupancy Accompanies Cognitive Impairment in Cerebral Small Vessel Disease

“…The observed pattern of neuropsychological deficits with greatest impairments in executive functions and relative sparing of cortical functions, such as episodic memory, is typical for vascular cognitive impairment (61)(62)(63), confirming ischemic WM disease as a predominantly subcortical pathology (64,65). Supplemental analyses (Figures S5 and S6) suggest that the association between WMH and executive dysfunction might be driven in large part by periventricular lesions, supporting the recent notion that these might differ in pathophysiology and clinical sequelae from lesions in the deep white WM (43,(66)(67)(68)(69).…”

White matter hyperintensities in Burning Mouth Syndrome assessed according to the Age-Related White Matter Changes scale

“…Thereby the treatment of hypertension and hypercholesterolemia along with the therapeutic modulation may both reduce the WMH progression and improve the BMS patients’ prognosis. The high prevalence of WMHs in patients with BMS, taking in account that WMH dynamic progression in brain parenchyma has a rate ranging from 0.1 to 2.2 ml/year ( Jiménez-Balado et al, 2022 ), increasing the risk of developing cognitive decline, dementia and disability, confirms the usefulness of requesting MRI of the brain during the first consultation. This early screening could allow the evaluation of WMHs and the measurement of their progression and/or regression over time, after controlling for vascular risk factors ( Debette et al, 2019 ).…”

Comparison between tools for automatic segmentation of white matter hyperintensities of presumed vascular origin in aging: which one, how and why to choose the most suitable for your purpose?

“…The detection of small lesions is of paramount interest in the clinical and scientific fields, especially in studies focused on healthy aging or premorbid stages of pathological aging, where vascular damage is usually mild, or in longitudinal studies intended to follow the evolution of the disease from the growth of the subtle lesion. For instance, the WMH location and pattern of distribution (i.e., extent or symmetry) in the brain have been also associated with different underlying pathologies (Balakrishnan et al, 2021;Dadar et al, 2022) and with the degree of impairment for different cognitive functions (Jiménez-Balado et al, 2022). Therefore, in studies like ours, this factor is key, because most automatic segmentation tools have been optimized by maximizing Dice's sensitivity, precision, and score values.…”