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Background and objectives. White matter hyperintensities (WMHs) on brain magnetic resonance imaging (MRI) are linked to cognitive decline, but clinical assessment still relies mainly on visual grading (Fazekas), which is coarse and rater-dependent. We described the lesion volume of WMHs and the association of the anatomical distribution with the severity of cognitive impairment using automated lesion analysis. In addition, we evaluated whether automated volumetric quantification is more strongly associated with cognitive performance than visual grading. Materials and Methods. In a retrospective cross-sectional study, forty-one adults referred for cognitive concerns underwent standardised 3.0 tesla MRI. White matter hyperintensities were automatically segmented using Icometrix software to obtain total and regional volumes (periventricular, subcortical, brainstem, cerebellum). Visual grading used the Fazekas scale separately for periventricular and deep white matter, with a combined grade defined by the higher of the two. Cognitive performance was grouped based on the Montreal Cognitive Assessment (MoCA) into high (≥26), moderate (18–25), and low (≤17). Statistics included Spearman’s correlation and the Kruskal–Wallis test with Dunn’s post hoc test where applicable. Results. Higher total white matter hyperintensity volume was associated with lower Montreal Cognitive Assessment scores and showed significant differences across cognitive groups. The Fazekas combined grade correlated more weakly with the MoCA score. Regional volumetric differences showed trends, but were not statistically significant. Total volumetric burden increased stepwise across combined Fazekas categories, supporting convergent validity between methods. Conclusions. Our study found that automated volumetric quantification provides a more objective, sensitive, and scalable measure of white matter hyperintensity burden than visual grading, aligns more closely with cognitive status, and is better suited for longitudinal monitoring and research endpoints.

Objective: To investigate the influence of deep white matter hyperintensities (DWMH) and periventricular white matter hyperintensities (PVWMH) on progression of cognitive decline in non-demented elderly people. Methods: All data come from the nested MRI sub-study of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). We performed a 3 year follow up study on 554 subjects of the PROSPER study using both repeated magnetic resonance imaging and cognitive testing. Cognitive decline and its dependency on WMH severity was assessed using linear regression models adjusted for sex, age, education, treatment group, and test version when applicable. Results: We found that the volume of PVWMH at baseline was longitudinally associated with reduced mental processing speed (p = 0.0075). In addition, we found that the progression in PVWMH volume paralleled the decline in mental processing speed (p = 0.024). In contrast, neither presence nor progression of DWMH was associated with change in performance on any of the cognitive tests. Conclusion: PVWMH should not be considered benign but probably underlie impairment in cognitive processing speed.

Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer’s disease (AD) pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, AD imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods We identified 1144 participants from the Mayo Clinic Study of Aging consisting of a population-based sample from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET, and tau-PET standardized uptake value ratio, automated WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, ( p  < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis ( R  = 0.07, p  = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.82 and 0.74). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97) and showed poor correlation with amyloid and tau PET markers similar to the visual grading. Conclusion Our study investigated risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

The goal of this paper is to introduce the hypothesis that white matter (WM) and vascular injury are long‐term consequences of repetitive head impacts (RHI) that result in a novel T2 fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging pattern. A non‐systematic literature review of autopsy and FLAIR studies of RHI‐exposed adults was first conducted as a foundation for our hypothesis. A case series of RHI‐exposed participants is presented to illustrate the unique FLAIR WM hyperintensities (WMH) pattern. Current literature shows a direct link between RHI and later‐life WM/vascular neuropathologies, and that FLAIR WMH are associated with RHI, independent of modifiable vascular risk factors. Initial observations suggest a distinctive pattern of WMH in RHI‐exposed participants, termed RHI‐associated WMH (RHI‐WMH). RHI‐WMH defining features are as follows: (1) small, punctate, non‐confluent, (2) spherical, and (3) proximal to the gray matter. Our hypothesis serves as a call for research to empirically validate RHI‐WMH and clarify their biological and clinical correlates. Highlights Repetitive head impacts (RHI) have been associated with later‐life white matter (WM) and vascular neuropathologies. T2 FLAIR MRI of RHI‐exposed participants reveals a potentially unique WM hyperintensity (WMH) pattern that is termed RHI‐associated WMH (RHI‐WMH). RHI‐WMH are characterized as (1) small, punctate, and non‐confluent, (2) spherical, and (3) proximal to the gray matter at an area anatomically susceptible to impact injury, such as the depths of the cortical sulci.

Objectives: Cerebral white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) are a recognised risk factor for post-stroke dementia. Their specific relations to cognitive impairment are still not well known. The purpose of this study was to explore how the severity and location of WMHs predict neuropsychological test performance in the context of other brain lesions in elderly stroke patients. Methods: In the Helsinki Stroke Aging Memory Study, 323 patients, aged from 55 to 85 years, completed a detailed neuropsychological test battery and MRI 3 months after an ischaemic stroke. The demographic and MRI predictors of cognition were studied with sequential linear regression analyses. Results: After age, education and total infarct volume were controlled for, the overall degree of WMHs predicted poor performance in tests of mental speed, executive functions, memory, and visuospatial functions, but not in those of short term memory storage or verbal conceptualisation. However, the contribution of separate white matter regions was relatively low. Only the lesions along the bodies of lateral ventricles were independently associated with speed and executive measures. Additionally, general cortical atrophy clearly predicted a wide range of cognitive deficits while infarct volume had less relevance. Further analyses revealed that executive functions act as a strong mediator between the relationship of WMHs to memory and visuospatial functions. Conclusions: The degree of WMHs is independently related to post-stroke cognitive decline. The most affected cognitive domains seem to be executive functions and speed of mental processing, which may lead to secondary deficits of memory and visuospatial functions.

White matter hyperintensities (WMH) on T2-weighted brain magnetic resonance imaging (MRI) are common in aging and associated with small vessel cerebrovascular disease. Standard segmentation methods treat these lesions as uniform binary entities, fundamentally reducing WMH signal by flattening a complex spectrum of tissue damage into a single label. Most WMH methods threshold voxel intensities to estimate lesion volume, missing richer characterization achievable by combining fluid-attenuated inversion recovery (FLAIR) with diffusion MRI. We introduce Voxel-wise Correlation of Neighbors (VCON), a cross-modal framework that quantifies voxel-level relationships between intensity values on T2-weighted FLAIR scans and fractional anisotropy (FA) on diffusion MRI within individuals. VCON generates hypothesis-driven WMH labels by identifying regions where increased FLAIR signal is negatively correlated with FA, suggesting underlying microstructural damage. Using MRI data from over 2,500 participants in community-based aging cohorts, we validated VCON through multi-scale analysis, age-association modeling, scanner comparisons, and intensity-based clustering of WMH into spatially coherent zones with distinct microstructural profiles. VCON revealed a gradient of WMH signal variation that tracks with age and diffusion metrics across scanners and segmentation methods. These results demonstrate that binary WMH masks may obscure clinically important variation in lesion characteristics. VCON reframes lesion segmentation as characterizing microstructural heterogeneity, offering additional structure-informed characterization beyond conventional binary methods by leveraging multimodal MRI signal variation.

White matter hyperintensity (WMH) is associated with vascular hemodynamic alterations and reflects white matter injury. To date, the sex difference of tract‐specific WMH and the relationship between high blood pressure (BP) and tract‐specific WMH remain unclear. We recruited 515 subjects from the Shanghai Changfeng study (range 53–89 years, mean age 67.33 years). Systolic and diastolic blood pressure (SBP and DBP) were collected and used to calculate pulse pressure (PP). Magnetic resonance T1 and T2 FLAIR images were acquired to measure WMH and calculate WMH index. The ANCOVA test was performed to test the difference between sexes, and the linear regression model was used to examine the associations between BP and WMH index. Men showed higher WMH index than women in all white matter tracts (p < .001, respectively) except for the bilateral superior longitudinal fasciculus (SLF) and its left temporal part (tSLF). High SBP and PP was associated with a lower WMH index on the left corticospinal tract (CST), SLF, tSLF and right cingulum in hippocampus (p ≤ .001, respectively) in women, while high DBP was associated with a higher WMH index on the bilateral CST (left p < .001; right p = .001), left inferior longitudinal fasciculus (p < .001) and inferior fronto‐occipital fasciculus (p = .002) in men. Men tend to have more WMH compared to women. A high SBP/PP relates to a lower WMH burden in women. This suggests that women could benefit from higher blood pressure in older age. This middle‐aged and elderly community‐based study revealed that men had significantly greater WMH index than women in all of the white‐matter tracts except for the bilateral superior longitudinal fasciculus and its left temporal part, which highlight the health advantage for women in older age. Higher SBP/PP was found to be correlated with lower WMH index in women, suggesting that women may benefit from a higher blood pressure in older age. Blood pressure was found to be associated with WMH index in a different way in both sexes, suggesting sex stratification is important when considering vascular risk on WMH with increasing age.

Interest in white matter hyperintensities (WMH), a radiological biomarker of small vessel disease, is continuously increasing. This is, in most part, due to our better understanding of their association with various clinical disorders, such as stroke and Alzheimer’s disease, and the overlapping pathology of WMH with these afflictions. Although post-mortem histological studies have reported various underlying pathophysiological substrates, in vivo research has not been specific enough to fully corroborate these findings. Furthermore, post-mortem studies are not able to capture which pathological processes are the driving force of the WMH severity. The current study attempts to fill this gap by non-invasively investigating the influence of WMH on brain tissue using quantitative MRI (qMRI) measurements of the water content (H2O), the longitudinal (T1) and effective transverse relaxation times (T2∗), as well as the semi-quantitative magnetization transfer ratio (MTR), and bound proton fraction (ƒbound). In total, seventy subjects (age range 50–80 years) were selected from a population-based aging cohort study, 1000BRAINS. Normal appearing grey (NAGM) and white matter (NAWM), as well as deep (DWMH) and periventricular (PWMH) white matter hyperintensities, were segmented and characterized in terms of their quantitative properties. The subjects were then further divided into four grades according to the Fazekas rating scale of severity. Groupwise analyses of the qMRI values in each tissue class were performed. All five qMRI parameters showed significant differences between WMH and NAWM (p < 0.001). Importantly, the parameters differed between DWMH and PWMH, the latter having higher H2O, T1, T2∗ and lower MTR and ƒbound values (p < 0.001). Following grading according to the Fazekas scale, DWMH showed an increase in the water content, T1 and a decrease in bound proton fraction corresponding to severity, exhibiting significant changes in grade 3 (p < 0.001), while NAWM revealed significantly higher H2O values in grade 3 compared to grade 0 (p < 0.001). PWMH demonstrated an increase in T2∗ values (significant in grade 3, P < 0.001). These results are in agreement with previous histopathological studies and support the interpretation that both edema and myelin loss due to a possible breakdown of the blood-brain barrier and inflammation are the major pathological substrates turning white matter into DWMH. Edema being an earlier contributing factor to the pathology, as expressed in the elevated water content values in NAWM with increasing severity. In the case of PWMH, an altered fluid dynamic and cerebrospinal fluid leakage exacerbate the changes. It was also found that the pathology, as monitored by qMRI, evolves faster in DWMH than in the PWMH following the severity. •Quantitative MRI differentiates between deep and periventricular white matter hyperintensities.•H2O, T1 and T2∗ are increased, while MTR and ƒbound are decreased in white matter hyperintensities.•H2O and ƒbound are altered in normal appearing white matter following the Fazekas severity scale.•Increasing H2O might be the driving force behind the increase in WMH severity.

Background: Cognitive dysfunction in cerebral small vessel disease (CSVD) patients is associated with white matter hyperintensity (WMH), which demonstrates frequency-dependent correlations with brain functional activities. However, the neural mechanisms underlying the relationship between these structural and functional abnormalities and cognitive impairment remain unclear. Methods: We recruited 34 CSVD patients (mean age 63.74 ± 4.85 years, 19 males) and 45 age-matched healthy controls (mean age 63.69 ± 6.15 years, 15 males). All participants underwent magnetic resonance imaging (MRI) scanning and comprehensive cognitive assessments, including three behavioral tasks and a cognitive questionnaire battery. Regional brain activity and network topological properties were separately compared between the two groups for each of the three frequency bands (slow-4, slow-5, and typical band) using two-sample t-tests. Simple and multiple mediation analyses were performed to examine the relationships among WMH, functional brain measures, and global cognition. Results: CSVD patients exhibited frequency-specific alterations in regional activity and reduced global functional organization in the slow-4 band. Frequency-dependent functional measures in the slow-4 band significantly mediated the relationship between deep WMH and cognitive performance. Conclusion: Our findings demonstrate the frequency-specific mediating role of abnormal brain functions in the pathophysiological pathway linking WMHs to cognitive impairment. This study provides new insight into the pathological mechanisms underlying WMH-related cognitive dysfunction. Clinical Trial Registration: ChiCTR2100043346, 02 November 2021, https://www.chictr.org.cn/showproj.html?proj=52285.

Although white matter hyperintensities (WMH) are radiologically classified as deep WMH (DWMH) and periventricular WMH (PVWMH) based on spatial distribution, the distinct metabolic perturbations driving their pathogenesis remain incompletely characterized. This study integrated untargeted metabolomics with MRI phenotyping to delineate metabolic perturbations of WMH in arteriosclerotic cerebral small vessel disease (aCSVD) patients ( ) versus controls ( ). Plasma metabolic profiles were analyzed using UPLC-MS. Weighted gene correlation network analysis (WGCNA) evaluated associations between metabolite clusters and clinical traits, including DWMH volume, PVWMH volume and total WMH (TWMH) volume. We identified 15, 16, and 16 key metabolites meeting both differential expression and WGCNA hub criteria for DWMH, PVWMH, and TWMH, respectively. Pathway Enrichment identified α-linolenic acid and linoleic acid metabolism as common pathway perturbed across both WMH categories. Key metabolites of the pathway, including docosahexaenoic acid (DHA) and stearidonic acid (SDA), demonstrated robust inverse associations with WMH volumes in confounder-adjusted linear regression models. Notably, both WMH categories share common metabolites, particularly polyunsaturated fatty acids (PUFA), while PVWMH-specific metabolites were primarily carnitine derivatives, and DWMH-specific metabolites were prostaglandin E2 and etodolac. These findings offer new insights into the metabolic mechanisms underlying DWMH and PVWMH in aCSVD. However, the cross-sectional nature of the study does not allow for causal conclusions. Future longitudinal studies are needed to validate the temporal relationships between metabolic perturbations and WMH progression.