ArticleLiterature Review

Contrast‐agent‐free State‐of‐the‐art Magnetic Resonance Imaging on Cerebral Small Vessel Disease – Part 2: DTI and fMRI

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Abstract

Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast‐agent‐free, state‐of‐the‐art MRI techniques, particularly Diffusion Tensor Imaging (DTI) and Functional Magnetic Resonance Imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published between 2000 and 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast‐agent‐free, state‐of‐the‐art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.

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... Among these, WMH is a typical feature of CSVD [10] , which is a signi cant contributor to dementia worldwide. However, there are some limitations to the relationship between the above brain imaging markers and cognitive impairment such as whether a threshold effect or anatomical distribution (strictly lobar vs deep vs mixed) is relevant [11] , and CSVD brain imaging markers are not consistent with the clinical manifestations of patients [12,13] . ...
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The current study integrated static (sFNC) and dynamic (dFNC) functional network connectivity to investigate the neurobiological mechanisms underlying alterations in static and dynamic functional network connectivity in subcortical vascular cognitive impairment (SVCI). We recruited 80 patients with SVCI (39 males, 41 females) and 83 healthy controls (HCs) (32 males, 51 females). Clinical and imaging data, including clinical history, neuropsychological assessments, and MRI scans, were collected. We analyzed sFNC changes using independent component analysis (ICA) with resting-state functional MRI data. Dynamic connectivity was examined using the sliding time window technique and cluster analysis to assess brain functional activity states and temporal properties. Differences in dFNC temporal properties (fractional occupancy, mean dwell time, and number of transitions) between groups were assessed with two-sample t-tests. Spearman correlation analyses were performed to explore relationships between sFNC and dFNC changes and cognitive function. In the sFNC analysis, the SVCI group showed significantly decreased interactions between the sensorimotor network (SMN) and visual network (VN), and between the left frontoparietal network (lFPN) and VN ( p < 0.05), and both of which were associated with cognitive function ( p < 0.05). In the dFNC analysis, brain functional activity was grouped into four highly structured functional connection states. The results revealed one strongly connected state dominated by reduced connectivity, two moderately connected states primarily characterized by connectivity reductions with minor increases, and one weakly connected state with a modular pattern. These findings illustrate the progression in SVCI from connectivity disruption to compensation, eventually leading to a diminished compensatory response. Fractional occupancy and mean dwell time of states were correlated with cognitive function (all p < 0.05). CSVD patients exhibit impairments in both sFNC and dFNC, linked to cognitive decline. Connectivity dynamics reflect the brain's adaptive capacity in response to cognitive impairment.
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Article
Background: Cerebral small vessel disease (CSVD) is a chronic disorder affecting small vessels within the brain, increasing the risk of stroke in patients with chronic kidney disease (CKD). Diffusion tensor imaging (DTI) is a newer quantitative method for diagnosing CSVD at an early stage of pathogenesis. Objectives: This study compares various DTI parameters in multiple white matter tracts of the brain in CKD patients undergoing maintenance hemodialysis with normal controls in the Indian population using the volume of interest (VOI) method. Additionally, it correlates these DTI parameters with each other at different locations to gain insights into the pathogenesis of CSVD. Methods: After obtaining institutional ethics approval, a cross-sectional study was conducted at a tertiary care hospital over one year (June 2022 to May 2023). The study comprised seventy-five patients in the hemodialysis group and twenty-five controls. All participants underwent MRI brain examinations on a 3 Tesla MRI scanner, and the four DTI parameters - fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) - were reviewed for nine white matter tracts to evaluate statistical differences and correlations. Results: Fractional anisotropy was significantly decreased at anterior locations – corpus callosum genu (P = 0. 357 × 10-7), right anterior corona radiata (P = 0.001), and left anterior corona radiata (P = 0.45 × 10-5). In these locations, FA negatively correlated with RD (R = -0.7904, P < 0.00001), and RD was also significantly increased. Axial diffusivity was significantly increased at posterior locations in the corpus callosum splenium (P = 0.108 × 10-5) and left posterior corona radiata (P = 0.244 × 10-5). However, none of the four DTI parameters showed significant differences between hemodialysis patients and the control group for the subset of patients with normal routine brain MRI features. The intraclass correlation coefficients (ICCs) were high for all four DTI parameters for both patients (0.78 to 0.85) and controls (0.82 to 0.89). Conclusions: This study on CKD patients undergoing maintenance hemodialysis reveals significant differences in some DTI parameters in widespread white matter tracts of the brain using the VOI method, with acceptable to excellent interobserver agreement.
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Cerebral small vessel disease (CSVD) is a group of pathological processes affecting small arteries, arterioles, capillaries, and small veins of the brain. It is one of the most common subtypes of cerebrovascular diseases, especially highly prevalent in elderly populations, and is associated with stroke occurrence and recurrence, cognitive impairment, gait disorders, psychological disturbance, and dysuria. Its diagnosis mainly depends on MRI, characterized by recent small subcortical infarcts, lacunes, white matter hyperintensities (WMHs), enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and brain atrophy. While the pathophysiological processes of CSVD are not fully understood at present, inflammation is noticed as playing an important role. Herein, we aimed to review the relationship between plasma inflammatory biomarkers and the MRI features of CSVD, to provide background for further research.
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Objective: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. Methods: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). Results: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. Conclusion: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.
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Cerebral small vessel disease (CSVD) encompasses several diseases affecting the small arteries, arterioles, venules, and capillaries of the brain and refers to several pathological processes and etiologies. Neuroimaging is considered the gold standard for detecting CSVD, which can present diverse features on MRI. Cerebral microbleeds (CMBs) in CSVD have been demonstrated to play a synergistic role in both cerebrovascular and neurodegenerative pathology. Considering previous studies on brain structural abnormalities in CSVD, in the present study, we aimed to explore altered spontaneous brain activity among CSVD patients using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) methods based on resting-state functional MRI. In this study, we recruited 24 CSVD patients with CMBs (CSVD-c), 42 CSVD patients without CMBs (CSVD-n) and 36 healthy controls from outpatient clinics in Shandong Provincial Hospital affiliated to Shandong First Medical University between September 2018 and June 2019. All subjects underwent 3-T MRI, including blood oxygen level-dependent (BOLD) and susceptibility-weighted imaging (SWI). Anatomic structures were segmented, ALFF/fALFF values were calculated, and ReHo maps were generated. Further statistical analysis was applied to study the difference in ALFF/fALFF/ReHo among the three groups and the association between ALFF/fALFF/ReHo changes in different brain regions and clinical characteristics. Twenty-four CSVD-c patients (age: 67.54 ± 6.00 years, 10 females), 42 CSVD-n patients (age: 66.33 ± 5.25 years, 22 females) and 36 healthy subjects (age: 64.14 ± 8.57 years, 19 females) were evaluated. Compared with controls, the CSVD-c group showed significantly increased ALFF values in the right insula, putamen and left precuneus; decreased fALFF values in the right precentral gyrus and postcentral gyrus; and increased ReHo values in the left precuneus, fusiform gyrus, right supplementary motor area (SMA), and superior frontal gyrus. Notably, the mean ALFF values of the right insula and putamen were not only significantly related to all clinical parameters but also demonstrated the best performance in Receiver Operating Characteristic (ROC) curve analysis. These findings reveal CSVD-c patients have dysfunctions in the default mode network, sensorimotor network and frontoparietal network, which may implicate the underlying neurophysiological mechanisms of intrinsic brain activity. The correlation between altered spontaneous neuronal activity and clinical parameters provides early useful diagnostic biomarkers for CSVD.
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Background and Purpose: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy caused by mutations in the NOTCH3 gene is a hereditary cerebral small vessel disease, manifesting with stroke, cognitive impairment, and mood disturbances. Functional or structural changes in the default mode network (DMN), which plays important role in cognitive and mental maintenance, have been found in several neurological and mental diseases. However, it remains unclear whether DMN is altered in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Methods: Multimodal imaging methods, including MRI and positron emission tomography (PET), were applied to evaluate the functional, structural, and metabolic characteristics of DMN in 25 patients with CADASIL and 42 healthy controls. Results: Compared with controls, patients with CADASIL had decreased nodal efficiency and degree centrality of the dorsal medial pre-frontal cortex and hippocampal formation within DMN. Structural MRI and diffusion tensor imaging (DTI) showed decreased gray matter volume and fiber tracks presented in the bilateral hippocampal formation. Meanwhile, PET imaging showed decreased metabolism within the whole DMN in CADASIL. Furthermore, correlation analyses showed that these nodal characteristics, gray matter volume, and metabolic signals of DMN were related to cognitive scores in CADASIL. Conclusions: Our results suggested that altered network characteristics of DMN might play important roles in cognitive deficits of CADASIL.
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This study aimed to investigate whole-brain spontaneous activities changes in patients with vascular mild cognitive impairment (VaMCI), and to evaluate the relationships between these brain alterations and their neuropsychological assessments. Thirty-one patients with VaMCI and thirty-one healthy controls (HCs) underwent structural MRI and resting-state functional MRI (rs-fMRI) and neuropsychological assessments. The functional alterations were determined by the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC). The gray matter volume (GMV) changes were analyzed using voxel-based morphometry (VBM). Linear regression analysis was used to evaluate the relationships between the structural and functional changes of brain regions and neuropsychological assessments. The VaMCI group had significantly lower scores in the Montreal Cognitive Assessment (MoCA), and higher scores on the Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD). Compared to the HCs, the VaMCI group exhibited GM atrophy in the right precentral gyrus (PreCG) and right inferior temporal gyrus (ITG). VaMCI patients further exhibited significantly decreased brain activity within the default mode network (DMN), including the bilateral precuneus (PCu), angular gyrus (AG), and medial frontal gyrus (medFG). Linear regression analysis revealed that the decreased ALFF was independently associated with lower MoCA scores, and the GM atrophy was independently associated with higher HAMD scores. The current finding suggested that aberrant spontaneous brain activity in the DMN might subserve as a potential biomarker of VaMCI, which may highlight the underlying mechanism of cognitive decline in cerebral small vessel disease.
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Objectives It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts. Methods Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined. Results The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures. Conclusions Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity.
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Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.
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Background To investigate changes in gait performance over time and how these changes are associated with the decline in structural network efficiency and cognition in older patients with cerebral small vessel disease (SVD). Methods In a prospective, single-center cohort with 217 older participants with SVD, we performed 1.5T MRI scans, cognitive tests and gait assessments evaluated by Timed UP and Go (TUG) test twice over 4 years. We reconstructed the white matter network for each subject based on diffusion tensor imaging tractography, followed by graph-theoretical analyses to compute the global efficiency. Conventional MRI markers for SVD, i.e., white matter hyperintensity (WMH) volume, number of lacunes and microbleeds, were assessed. Results Baseline global efficiency was not related to changes in gait performance, while decline in global efficiency over time was significantly associated with gait decline (i.e., increase in TUG time), independent of conventional MRI markers for SVD. Neither baseline cognitive performance nor cognitive decline was associated with gait decline. Conclusions We found that disruption of the white matter structural network was associated with gait decline over time, while the effect of cognitive decline was not. This suggests that structural network disruption has an important role in explaining the pathophysiology of gait decline in older patients with SVD, independent of cognitive decline.
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White matter hyperintensity (WMH) is common in healthy adults in their 60s and can be seen as early as in their 30s and 40s. Alterations in the brain structural and functional profiles in adults with WMH have been repeatedly studied but with a focus on late-stage WMH. To date, structural and functional MRI profiles during the very early stage of WMH remain largely unexplored. To address this, we investigated multimodal MRI (structural, diffusion, and resting-state functional MRI) profiles of community-dwelling asymptomatic adults with very early-stage WMH relative to age-, sex-, and education-matched non-WMH controls. The comparative results showed significant age-related and age-independent changes in structural MRI-based morphometric measures and resting-state fMRI-based measures in a set of specific gray matter (GM) regions but no global white matter changes. The observed structural and functional anomalies in specific GM regions in community-dwelling asymptomatic adults with very early-stage WMH provide novel data regarding very early-stage WMH and enhance understanding of the pathogenesis of WMH.
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Background: White matter hyperintensities (WMHs) are a common occurrence with aging and are associated with cognitive impairment. However, the neurobiological mechanisms of WMHs remain poorly understood. Functional magnetic resonance imaging (fMRI) is a prominent tool that helps in non-invasive examinations and is increasingly used to diagnose neuropsychiatric diseases. Degree centrality (DC) is a common and reliable index in fMRI, which counts the number of direct connections for a given voxel in a network and reflects the functional connectivity within brain networks. We explored the underlying mechanism of cognitive impairment in WMHs from the perspective of DC. Methods: A total of 104 patients with WMHs and 37 matched healthy controls (HCs) were enrolled in the current study. All participants underwent individual and overall cognitive function tests and resting-state fMRI (rs-fMRI). WMHs were divided into three groups (39 mild WMHs, 37 moderate WMHs, and 28 severe WMHs) according to their Fazekas scores, and the abnormal DC values in the WMHs and HCs groups were analyzed. Results: There was a significant difference in the right inferior frontal orbital gyrus and left superior parietal gyrus between the WMHs and HCs groups. The functional connectivity between the right inferior frontal orbital gyrus and left inferior temporal gyrus, left superior parietal gyrus, and left parietal inferior gyrus was also different in the WMHs group. Conclusion: The change in DC value may be one of the underlying mechanisms of cognitive impairment in individuals with WMHs, which provides us with a new approach to delaying cognitive impairment in WMHs.
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Objectives: We aim to investigate whether multi-dimensional diffusion tensor imaging (DTI) measures can sensitively identify different cognitive status of cerebral small vessel disease (CSVD) and to explore the underlying pattern of white matter disruption in CSVD. Methods: Two hundred and two participants were recruited, composed of 99 CSVD patients with mild cognitive impairment (VaMCI) and 60 with no cognitive impairment (NCI) and 43 healthy subjects as normal controls (NC). Full domain neuropsychological tests and diffusion-weighted imaging were performed on each subject. DTI metrics such as fractional anisotropy (FA), mean diffusivity (MD), the skeletonized mean diffusivity (PSMD), and structural brain network measures including network strength, global efficiency (EGlobal), and local efficiency (ELocal) were calculated. Region of interest (ROI) analysis of 42 white matter tracts was performed to examine the regional anatomical white matter disruption for each group. Results: Significant differences of multiple cognitive test scores across all cognitive domains especially processing and executive function existed among the three groups. DTI measures (FA, MD, and PSMD) showed significant group difference with the cognitive status changing. FA and EGlobal showed significant correlation with processing speed, executive function, and memory. ROI analysis found that white matter integrity impairment occurred from the preclinical stage of vascular cognitive impairment (VCI) due to CSVD. These lesions in the NCI group mainly involved some longitudinal fibers such as right superior longitudinal fasciculus (SLF-R), right superior fronto-occipital fasciculus (SFO-R), and right uncinate fasciculus (UNC-R), which might be more vulnerable to the cerebrovascular aging and disease process. Conclusions: DTI measures are sensitive neuroimaging markers in detecting the early cognitive impairment and able to differentiate the different cognitive status due to CSVD. Subtle changes of some vulnerable white matter tracts may be observed from the preclinical stage of VCI and have a local to general spreading pattern during the disease progression.
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Cerebral white matter hyperintensities (WMHs) represent macrostructural brain damage associated with various etiologies. However, the relative contributions of various etiologies to WMH volume, as assessed via different neuroimaging measures, is not well-understood. Here, we explored associations between three potential early markers of white matter hyperintensity volume. Specifically, the unique variance in total and regional WMH volumes accounted for by white matter microstructure, brain iron concentration and cerebral blood flow (CBF) was assessed. Regional volumes explored were periventricular and deep regions. Eighty healthy older adults (ages 60–86) were scanned at 3 Tesla MRI using fluid-attenuated inversion recovery, diffusion tensor imaging (DTI), multi-echo gradient-recalled echo and pseudo-continuous arterial spin labeling sequences. In a stepwise regression model, DTI-based radial diffusivity accounted for significant variance in total WMH volume (adjusted R2 change = 0.136). In contrast, iron concentration (adjusted R2 change = 0.043) and CBF (adjusted R2 change = 0.027) made more modest improvements to the variance accounted for in total WMH volume. However, there was an interaction between iron concentration and location on WMH volume such that iron concentration predicted deep (p = 0.034) but not periventricular (p = 0.414) WMH volume. Our results suggest that WM microstructure may be a better predictor of WMH volume than either brain iron or CBF but also draws attention to the possibility that some early WMH markers may be location-specific.
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Background White matter hyperintensities (WMHs) are one of the hallmarks of cerebral small vessel disease (CSVD), but the pathological mechanisms underlying WMHs remain unclear. Recent studies suggest that extracellular fluid (ECF) is increased in brain regions with WMHs. It has been hypothesized that ECF accumulation may have detrimental effects on white matter microstructure. To test this hypothesis, we used cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) as a unique CSVD model to investigate the relationships between ECF and fiber microstructural changes in WMHs. Methods Thirty-eight CADASIL patients underwent 3.0 T MRI with multi-model sequences. Parameters of free water (FW) and apparent fiber density (AFD) obtained from diffusion-weighted imaging (b = 0 and 1000 s/mm²) were respectively used to quantify the ECF and fiber density. WMHs were split into four subregions with four levels of FW using quartiles (FWq1 to FWq4) for each participant. We analyzed the relationships between FW and AFD in each subregion of WMHs. Additionally, we tested whether FW of WMHs were associated with other accompanied CSVD imaging markers including lacunes and microbleeds. Results We found an inverse correlation between FW and AFD in WMHs. Subregions of WMHs with high-level of FW (FWq3 and FWq4) were accompanied with decreased AFD and with changes in FW-corrected diffusion tensor imaging parameters. Furthermore, FW was also independently associated with lacunes and microbleeds. Conclusions Our study demonstrated that increased ECF was associated with WM degeneration and the occurrence of lacunes and microbleeds, providing important new insights into the role of ECF in CADASIL pathology. Improving ECF drainage might become a therapeutic strategy in future.
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Objective White matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is frequently presumed to be secondary to cerebral small vessel disease (CSVD) and associated with cognitive decline. The cerebellum plays a key role in cognition and has dense connections with other brain regions. Thus, the aim of this study was to investigate if cerebellar abnormalities could occur in CSVD patients with WMHs and the possible association with cognitive performances.MethodsA total of 104 right-handed patients with WMHs were divided into the mild WMHs group (n = 39), moderate WMHs group (n = 37), and severe WMHs group (n = 28) according to the Fazekas scale, and 36 healthy controls were matched for sex ratio, age, education years, and acquired resting-state functional MRI. Analysis of voxel-based morphometry of gray matter volume (GMV) and seed-to-whole-brain functional connectivity (FC) was performed from the perspective of the cerebellum, and their correlations with neuropsychological variables were explored.ResultsThe analysis revealed a lower GMV in the bilateral cerebellum lobule VI and decreased FC between the left- and right-sided cerebellar lobule VI with the left anterior cingulate gyri in CSVD patients with WMHs. Both changes in structure and function were correlated with cognitive impairment in patients with WMHs.Conclusion Our study revealed damaged GMV and FC in the cerebellum associated with cognitive impairment. This indicates that the cerebellum may play a key role in the modulation of cognitive function in CSVD patients with WMHs.
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Cerebral small vessel disease (SVD), including white matter hyperintensities (WMH), microbleeds, lacunes, was related to gait disturbances, while the underlying mechanism is unclear. Here, we investigated the relation between structural network efficiency, cognition and gait performance in 272 elderly subjects with SVD. All participants underwent 1.5 T MRI, gait and neuropsychological assessment. Conventional MRI markers for SVD, i.e. WMH volume, number of lacunes and microbleeds, were assessed. Diffusion tensor imaging-based tractog-raphy was used to reconstruct the brain network for each individual, followed by graph-theoretical analyses to compute the well-established network measure, global efficiency. We found that lower global efficiency was associated with worse gait performance, including slower gait speed and shorter stride length, independent of conventional MRI markers for SVD. This association was partly mediated via cognitive function. We identified subnetworks of white matter connections associated with gait and cognition, characterized by dominant involvement of frontal tracts. Our findings suggest that network disruption is associated with gait disturbances through cognitive dysfunction in elderly with SVD. Gait is a highly cognitive process and the crucial role of cognition should be considered when investigating gait disturbances in the elderly with SVD.
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To investigate the association between white matter free water (FW) and common imaging markers of cerebral small vessel diseases (CSVD) in two groups of subjects with different clinical status. One hundred and forty-four community subjects (mean age 60.5) and 84 CSVD subjects (mean age 61.2) were retrospectively included in the present study. All subjects received multi-modal magnetic resonance imaging and clinical assessments. The association between white matter FW and common CSVD imaging markers, including white matter hyperintensities (WMH), dilated perivascular space (PVS), lacunes, and microbleeds, were assessed using simple and multiple regression analysis. The association between FW and cognitive scores were also investigated. White matter FW was positively associated with WMH volume (β = 0.270, p = 0.001), PVS volume (β = 0.290, p < 0.001), number of microbleeds (β = 0.148, p = 0.043), and age (β = 0.170, p = 0.036) in the community cohort. In the CSVD cohort, FW was positively associated with WMH volume (β = 0.648, p < 0.001), PVS score (β = 0.224, p < 0.001), number of lacunes (β = 0.140, p = 0.046), and sex (β = 0.125, p = 0.036). The associations between FW and cognitive scores were stronger than conventional CSVD markers in both datasets. White matter FW is a potential composite marker that can sensitively detect cerebral small vessel degeneration and also reflect cognitive impairments.
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Asymptomatic (or “silent”) manifestations of cerebral small vessel disease (CSVD) are widely recognized through incidental findings of white matter hyperintensities (WMHs) as a result of magnetic resonance imaging (MRI). This study aims to examine the potential associations of surrogate markers for the evaluation of white matter integrity in CSVD among asymptomatic individuals through a battery of profiling involving QRISK2 cardiocerebrovascular risk prediction, neuroimaging, neurocognitive evaluation, and microparticles (MPs) titers. Sixty asymptomatic subjects (mean age: 39.83 ± 11.50 years) with low to moderate QRISK2 scores were recruited and underwent neurocognitive evaluation for memory and cognitive performance, peripheral venous blood collection for enumeration of selected MPs subpopulations, and 3T MRI brain scan with specific diffusion MRI (dMRI) sequences inclusive of diffusion tensor imaging (DTI). WMHs were detected in 20 subjects (33%). Older subjects (mean age: 46.00 ± 12.00 years) had higher WMHs prevalence, associated with higher QRISK2 score and reduced processing speed. They also had significantly higher mean percentage of platelet (CD62P)- and leukocyte (CD62L)-derived MPs. No association was found between reduced white matter integrity—especially at the left superior longitudinal fasciculus (LSLF)—with age and neurocognitive function; however, LSLF was associated with higher QRISK2 score, total MPs, and CD62L- and endothelial cell-derived MPs (CD146). Therefore, this study establishes these multimodal associations as potential surrogate markers for “silent” CSVD manifestations in the well-characterized cardiocerebrovascular demographic of relatively young, neurologically asymptomatic adults. Furthermore, to the best of our knowledge, this study is the first to exhibit elevated MP counts in asymptomatic CSVD (i.e., CD62P and CD62L), which warrants further delineation.
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Objective: To characterize earlier damage pattern of white matter (WM) microstructure in cerebral small vessel disease (CSVD) and its relationship with cognitive domain dysfunction. Methods: A total of 144 CSVD patients and 100 healthy controls who underwent neuropsychological measurements and diffusion tensor imaging (DTI) examination were recruited. Cognitive function, emotion, and gait were assessed in each participant. The automated fiber quantification (AFQ) technique was used to extract different fiber properties between groups, and partial correlation and general linear regression analyses were performed to assess the relationship between position-specific WM microstructure and cognitive function. Results: Specific segments in the association fibers, commissural WM regions of interest (ROIs), and projection fibers were damaged in the CSVD group [ P < 0.05, family-wise error (FWE) correction], and these damaged segments showed interhemispheric symmetry. In addition, the damage to specific tract profiles [including the posteromedial component of the right cingulum cingulate (CC), the occipital lobe portion of the callosum forceps major, the posterior portion of the left superior longitudinal fasciculus (SLF), and the bilateral anterior thalamic radiation (ATR)] was related to the dysfunction in specific cognitive domains. Among these tracts, we found the ATR to be the key set of tracts whose profiles were most associated with cognitive dysfunction. The left ATR was a specific fiber bundle associated with episode memory and language function, whereas the fractional anisotropy (FA) values of the intermediate component of the right ATR were negatively correlated with executive function and gait evaluation. It should be noted that the abovementioned relationships could not survive the Bonferroni correction ( p < 0.05/27), so we chose more liberal uncorrected statistical thresholds. Conclusions: Damage to the WM fiber bundles showed extensive interhemispheric symmetry and was limited to particular segments in CSVD patients. Disruption of strategically located fibers was associated with different cognitive deficits, especially the bilateral ATR.
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Background White matter hyperintensities (WMHs) is the most frequent type of cerebral small vessel diseases and a common incidental finding in MRI films of the geriatric population. The objectives of this work were to study the existence of occult cognitive and balance impairments in subjects with accidentally discovered WMHs. Methods The study was conducted on 44 subjects with accidentally discovered WMHs and 24 non-WMHs subjects submitted to the advanced activity of daily living scale (AADLs), a neurocognitive battery assessing different cognitive domains, Berg balance test (BBT), computerized dynamic posturography (CDP), and brain MRI diffusion tensor tractography (DTT). Results WMHs subjects showed a significant decrease in AADLs as well as visual and vestibular ratios of CDP. Regarding the neurocognitive battery, there were significant decreases in MoCA as well as arithmetic test and block design of Wechsler adult intelligence scale-IV in WMHs compared to non-WMHs subjects’ groups ( p value < 0.001). Concerning Wisconsin Card Sorting subtests, each preservative response, preservative errors, non-preservative errors and trials to complete the 1st category showed a highly significant increase in WMHs compared to non-WMHs subjects ( p values < 0.001). DTT showed a substantial reduction in fractional anisotropy (FA) of each corticospinal tract, thalamocortical connectivity, and arcuate fasciculi. Conclusion Subjects with WMHs have lower cognitive performance and subtle balance impairment which greatly impair their ADLs.
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Introduction: Cerebral small vessel disease (CSVD) is the leading cause of vascular and mixed degenerative cognitive impairment (CI). The variability in the rate of progression of CSVD justifies the search for sensitive predictors of CI. Materials: A total of 74 patients (48 women, average age 60.6 ± 6.9 years) with CSVD and CI of varying severity were examined using 3T MRI. The results of diffusion tensor imaging with a region of interest (ROI) analysis were used to construct a predictive model of CI using binary logistic regression, while phase-contrast magnetic resonance imaging and voxel-based morphometry were used to clarify the conditions for the formation of CI predictors. Results: According to the constructed model, the predictors of CI are axial diffusivity (AD) of the posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB), and mid-posterior corpus callosum (CC). These predictors showed a significant correlation with the volume of white matter hyperintensity; arterial and venous blood flow, pulsatility index, and aqueduct cerebrospinal fluid (CSF) flow; and surface area of the aqueduct, volume of the lateral ventricles and CSF, and gray matter volume. Conclusion: Disturbances in the AD of pvNAWM, CB, and CC, associated with axonal damage, are a predominant factor in the development of CI in CSVD. The relationship between AD predictors and both blood flow and CSF flow indicates a disturbance in their relationship, while their location near the floor of the lateral ventricle and their link with indicators of internal atrophy, CSF volume, and aqueduct CSF flow suggest the importance of transependymal CSF transudation when these regions are damaged.
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Gait disturbances are important clinical features of cerebral small vessel disease (CSVD) that increase the risk of falls and disability. Brain structural alterations and gait disturbances in CSVD patients have been well demonstrated. However, intrinsic resting cerebral function patterns in CSVD patients with gait disorders remain largely unknown. Fifty-eight CSVD patients were enrolled in our studies and categorized into the gait disorder group (CSVD-GD, n = 29) and no-gait disorder group (CSVD-NGD, n = 29) based on a gait examination. Gait was quantitatively assessed with the Timed Up and Go test and the intelligent device for energy expenditure and activity (IDEEA). Functional MRI and fractional amplitude of low-frequency fluctuation (fALFF) analyses were employed to explore local intrinsic neural oscillation alterations. Functional connectivity based on fALFF results was calculated to detect the potential changes in remote connectivity. Compared with the CSVD-NGD group, the CSVD-GD group showed decreased fALFF in regions mainly located in the sensorimotor network and frontoparietal network, such as the left supplementary motor area (SMA.L) and the left superior parietal gyrus, and increased fALFF in the right inferior frontal gyrus (orbital part), the left caudate, and the left precuneus. Moreover, the CSVD-GD patients exhibited lower connectivity between the SMA.L and temporal lobe, which was related to gait speed. The fALFF value of the SMA.L was associated with cadence. This study highlights the regional and network interaction abnormalities of the SMA in CSVD patients with gait disturbances. These findings could provide further insight into the neural mechanisms of gait disturbances in CSVD.
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Background and Aim The basal ganglia are critical for planned locomotion, but their role in age-related gait slowing is not well known. Spontaneous regional co-activation of brain activity at rest, known as resting state connectivity, is emerging as a biomarker of functional neural specialization of varying human processes, including gait. We hypothesized that greater connectivity amongst regions of the basal ganglia would be associated with faster gait speed in the elderly. We further investigated whether this association was similar in strength to that of other risk factors for gait slowing, specifically white matter hyperintensities (WMH). Methods A cohort of 269 adults (79–90 years, 146 females, 164 white) were assessed for gait speed (m/sec) via stopwatch; brain activation during resting state functional magnetic resonance imaging, WMH, and gray matter volume (GMV) normalized by intracranial volume via 3T neuroimaging; and risk factors of poorer locomotion via clinical exams (body mass index (BMI), muscle strength, vision, musculoskeletal pain, cardiometabolic conditions, depressive symptoms, and cognitive function). To understand whether basal ganglia connectivity shows distinct clusters of connectivity, we conducted a k-means clustering analysis of regional co-activation among the substantia nigra, nucleus accumbens, subthalamic nucleus, putamen, pallidum, and caudate. We conducted two multivariable linear regression models: (1) with gait speed as the dependent variable and connectivity, demographics, WMH, GMV, and locomotor risk factors as independent variables and (2) with basal ganglia connectivity as the dependent variable and demographics, WMH, GMV, and locomotor risk factors as independent variables. Results We identified two clusters of basal ganglia connectivity: high and low without a distinct spatial distribution allowing us to compute an average connectivity index of the entire basal ganglia regional connectivity (representing a continuous measure). Lower connectivity was associated with slower gait, independent of other locomotor risk factors, including WMH; the coefficient of this association was similar to those of other locomotor risk factors. Lower connectivity was significantly associated with lower BMI and greater WMH. Conclusions Lower resting state basal ganglia connectivity is associated with slower gait speed. Its contribution appears comparable to WMH and other locomotor risk factors. Future studies should assess whether promoting higher basal ganglia connectivity in older adults may reduce age-related gait slowing.
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Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment. Earlier studies showed that a higher degree of white matter network damage, indicated by lower global efficiency (a graph-theory measure assessing efficiency of network information transfer), was associated with lower scores on cognitive performance independent of MRI markers for SVD. However, it is unknown whether this global efficiency index is the strongest predictor for cognitive impairment, as there is a wide range of network measures. Here, we investigate which network measure is the most informative in explaining baseline cognitive performance and decline over a period of 8.7 years in SVD. We used data from the Radboud University Nijmegen Diffusion tensor and MRI Cohort (RUN DMC), which included 436 participants without dementia (65.2±8.8 years) but with evidence of SVD on neuroimaging. Binarized and weighted structural brain networks were reconstructed using diffusion tensor imaging and deterministic streamlining. Using graph-theory, we calculated 21 global network measures and performed linear regression analyses, elastic net analysis and linear mixed effect models to compare these measures. All analyses were adjusted for potential confounders (age, sex, educational level, depressive symptoms and conventional SVD MRI-markers (e.g. white matter hyperintensities (WMH), lacunes of presumed vascular origin and microbleeds). The elastic net analyses showed that, at baseline, global efficiency had the strongest association with cognitive index (CI), while characteristic path length showed the strongest association with psychomotor speed (PMS) and memory. Binary local efficiency showed the strongest association with attention & executive function (A&EF). In addition, linear mixed-effect models demonstrated that baseline global efficiency predicts decline in CI (χ2(1)=8.18, p=0.004),PMS (χ2(1)=7.75, p=0.005), memory (χ2(1)=27.28, p=0.000) over time and that binary local efficiency predicts decline in A&EF (χ2(1)=8.66, p=0.003) over time. Our results suggest that among all network measures, network efficiency measures, i.e. global efficiency and local efficiency, are the strongest predictors for cognitive functions at cross-sectional level and also predict faster cognitive decline in SVD, which is in line with earlier findings. These findings suggests that in our study sample network efficiency measures are the most suitable surrogate markers for cognitive performance in patients with cerebral SVD among all network measures and MRI markers, and play a key role in the genesis of cognitive decline in SVD.
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Objective To investigate cerebrovascular reactivity (CVR), blood flow, vascular and CSF pulsatility, and their independent relationship with cerebral small vessel disease (SVD) features in patients with minor ischemic stroke and MRI evidence of SVD. Methods We recruited patients with minor ischemic stroke and assessed CVR using blood oxygen level–dependent MRI during a hypercapnic challenge, cerebral blood flow (CBF), vascular and CSF pulsatility using phase-contrast MRI, and structural magnetic resonance brain imaging to quantify white matter hyperintensities (WMHs) and perivascular spaces (PVSs). We used multiple regression to identify parameters associated with SVD features, controlling for patient characteristics. Results Fifty-three of 60 patients completed the study with a full data set (age 68.0% ± 8.8 years, 74% male, 75% hypertensive). After controlling for age, sex, and systolic blood pressure, lower white matter CVR was associated with higher WMH volume (−0.01%/mm Hg per log10 increase in WMH volume, p = 0.02), basal ganglia PVS (−0.01%/mm Hg per point increase in the PVS score, p = 0.02), and higher venous pulsatility (superior sagittal sinus −0.03%/mm Hg, p = 0.02, per unit increase in the pulsatility index) but not with CBF ( p = 0.58). Lower foramen magnum CSF stroke volume was associated with worse white matter CVR (0.04%/mm Hg per mL increase in stroke volume, p = 0.04) and more severe basal ganglia PVS ( p = 0.09). Conclusions Lower CVR, higher venous pulsatility, and lower foramen magnum CSF stroke volume indicate that dynamic vascular dysfunctions underpin PVS dysfunction and WMH development. Further exploration of microvascular dysfunction and CSF dynamics may uncover new mechanisms and intervention targets to reduce SVD lesion development, cognitive decline, and stroke.
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Background Changes in white matter microstructural integrity are detectable before appearance of white matter lesions on magnetic resonance imaging as a manifestation of cerebral small‐vessel disease. The information relating poor white matter microstructural integrity to aortic stiffness, a hallmark of aging, is limited. We aimed to examine the association between aortic stiffness and white matter microstructural integrity among older adults. Methods and Results We conducted a cross‐sectional study to examine the association between aortic stiffness and white matter microstructural integrity among 1484 men and women (mean age, 76 years) at the 2011 to 2013 examination of the ARIC‐NCS (Atherosclerosis Risk in Communities Neurocognitive Study). Aortic stiffness was measured as carotid‐femoral pulse wave velocity. Cerebral white matter microstructural integrity was measured as fractional anisotropy and mean diffusivity using diffusion tensor imaging. Multivariable linear regression was used to examine the associations of carotid‐femoral pulse wave velocity with fractional anisotropy and mean diffusivity of the overall cerebrum and at regions of interest. Each 1‐m/s higher carotid‐femoral pulse wave velocity was associated with lower overall fractional anisotropy (β=−0.03; 95% CI , −0.05 to −0.02) and higher overall mean diffusivity (β=0.03; 95% CI , 0.02–0.04). High carotid‐femoral pulse wave velocity (upper 25th percentile) was associated with lower fractional anisotropy (β=−0.40; 95% CI , −0.61 to −0.20) and higher overall mean diffusivity (β=0.27; 95% CI , 0.10–0.43). Similar associations were observed at individual regions of interest. Conclusions High aortic stiffness is associated with low cerebral white matter microstructural integrity among older adults. Aortic stiffness may serve as a target for the prevention of poor cerebral white matter microstructural integrity.
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Background The peak width of skeletonized mean diffusivity (PSMD) has been proposed as a fully automated imaging marker of relevance to cerebral small vessel disease (SVD). We assessed PSMD in relation to conventional SVD markers, global measures of neurodegeneration, and cognition. Methods 145 participants underwent 3T brain MRI and cognitive assessment. 112 were patients with mild cognitive impairment, Alzheimer’s disease, progressive supranuclear palsy, dementia with Lewy bodies, or frontotemporal dementia. PSMD, SVD burden [white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), microbleeds, lacunes], average mean diffusivity (MD), gray matter (GM), white matter (WM), and total intracranial volume were quantified. Robust linear regression was conducted to examine associations between variables. Dominance analysis assessed the relative importance of markers in predicting various outcomes. Regional analyses examined spatial overlap between PSMD and WMH. Results PSMD was associated with global and regional SVD measures, especially WMH and microbleeds. Dominance analysis demonstrated that among SVD markers, WMH was the strongest predictor of PSMD. Furthermore, PSMD was more closely associated to WMH than with GM and WM volumes. PSMD was associated with WMH across all regions, and correlations were not significantly stronger in corresponding regions (e.g., frontal PSMD and frontal WMH) compared to non-corresponding regions. PSMD outperformed all four conventional SVD markers and MD in predicting cognition, but was comparable to GM and WM volumes. Discussion PSMD was robustly associated with established SVD markers. This new measure appears to be a marker of diffuse brain injury, largely due to vascular pathology, and may be a useful and convenient metric of overall cerebrovascular burden.
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While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test–retest reliability of functional network measures in sporadic SVD patients participating in a high‐frequency (monthly) serial imaging study (RUN DMC—InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto‐parietal task control network, FPCN; visual network, VN; hand somatosensory‐motor network, HSMN) were constructed based on resting‐state multi‐band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = −.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = −.20, p = .047; direct path: std. beta = −.19, p = .25; total effect: std. beta = −.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high‐frequency serial MRI dataset of the sporadic SVD patients revealed poor test–retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD‐related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age‐related comorbidities, impedes the analysis in elderly SVD patients.
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Abnormal structural connectivity of cerebral small-vessel disease (CSVD) is associated with cognitive impairment. But the different characteristics of structural connectivity have not been elucidated in early CSVD patients. The current study aimed to investigate the potential differences of structural connectivity in CSVD patients with mild cognitive impairment (MCI) and CSVD patients with normal cognition. Twenty-two CSVD patients with MCI, 34 CSVD patients with normal cognition, and 35 controls, who were age, sex, and education matched underwent diffusion tensor imaging and high resolution T1-weighted imaging. Clinical characteristics, lacunar infarct volume, white matter hyperintensity (WMH) volume, and global atrophy were quantitatively evaluated. Maps of fiber connectivity density (FiCD) were constructed and compared across groups in vertex levels. Pearson correlation was used to estimate the imaging–clinical relationships with control of general characteristics. CSVD patients with MCI had higher lesion load of WMH and lacunar infarcts, and correspondingly lower global FiCD value than CSVD patients with normal cognition (P < 0.01). Lacunar infarct (r = −0.318, P < 0.01) and WMH (r = −0.400, P < 0.01), but not global atrophy, age, or sex, were significantly correlated with the global FiCD value. CSVD patients with normal cognition showed decreased FiCD value mainly in the prefrontal areas (P < 0.01 with Monte Carlo correction). Compared with CSVD patients with normal cognition, CSVD patients with MCI showed significantly decreased FiCD value in enlarged frontal and parietal areas (P < 0.01 with Monte Carlo correction). Inter-group comparisons showed regional enhanced impairment of connectivity density in CSVD patients with MCI in the left superior frontal gyrus, the left precuneus, and the orbital part of the right inferior frontal gyrus (P < 0.01 with Monte Carlo correction). Regional FiCD value of frontal and parietal areas was associated with the cognitive function (P < 0.01). In conclusion, cognitively normal CSVD patients already have disruptions of structural connectivity. The extent and intensity of connectivity disruptions in frontal and parietal areas may underlie the mechanism of cognitive impairment in CSVD. Fiber connectivity density measurements may be helpful for quantitative description of structural cortical connectivity.
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Chronic systemic sterile inflammation is implicated in the pathogenesis of cerebrovascular disease and white matter injury. Non-invasive blood markers for risk stratification and dissection of inflammatory molecular substrates in vivo are lacking. We sought to identify whether an interconnected network of inflammatory biomarkers centered on IL-18 and all previously associated with white matter lesions could detect overt and antecedent white matter changes in two populations at risk for cerebral small vessel disease. In a cohort of 167 older adults (mean age: 76, SD 7.1, 83 females) that completed a cognitive battery, physical examination, and blood draw in parallel with MR imaging including DTI, we measured cerebral white matter hyperintensities (WMH) and free water (FW). Concurrently, serum levels of a biologic network of inflammation molecules including MPO, GDF-15, RAGE, ST2, IL-18, and MCP-1 were measured. The ability of a log-transformed population mean-adjusted inflammatory composite score (ICS) to associate with MR variables was demonstrated in an age and total intracranial volume adjusted model. In this cohort, ICS was significantly associated with WMH (β = 0.222, p = 0.013), FW (β = 0.3, p = 0.01), and with the number of vascular risk factor diagnoses (r = 0.36, p<0.001). In a second cohort of 131 subjects presenting for the evaluation of acute neurologic deficits concerning for stroke, we used serum levels of 11 inflammatory biomarkers in an unbiased principal component analysis which identified a single factor significantly associated with WMH. This single factor was strongly correlated with the six component ICS identified in the first cohort and was associated with WMH in a generalized linear regression model adjusted for age and gender (p = 0.027) but not acute stroke. A network of inflammatory molecules driven by IL-18 is associated with overt and antecedent white matter injury resulting from cerebrovascular disease and may be a promising peripheral biomarker for vascular white matter injury.
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Aims White matter hyperintensity (WMH) is the most common neuroimaging manifestation of cerebral small vessel disease and is related to cognitive dysfunction or dementia. This study aimed to investigate the mechanism and effective indicators to predict WMH‐related cognitive impairment. Methods We recruited 22 healthy controls (HC), 25 cases of WMH with normal cognition (WMH‐NC), and 23 cases of WMH with mild cognitive impairment (WMH‐MCI). All individuals underwent diffusion tensor imaging (DTI) and a standardized neuropsychological assessment. Automated Fiber Quantification was used to extract altered DTI metrics between groups, and partial correlation was performed to assess the associations between WM integrity and cognitive performance. Furthermore, machine learning analyses were performed to determine underlying imaging markers of WMH‐related cognitive impairment. Results Our study found that mean diffusivity (MD) values of several fiber bundles including the bilateral anterior thalamic radiation (ATR), the left inferior fronto‐occipital fasciculus (IFOF), the right inferior longitudinal fasciculus (ILF), and the right superior longitudinal fasciculus (SLF) were negatively correlated with memory function, while that of the anterior component of the right IFOF and the posterior and intermediate component of the right ILF showed significant negative correlation with MMSE and episodic memory, respectively. Furthermore, machine learning analyses showed that the accuracy of recognizing WMH‐MCI patients from the WMH populations was up to 80.5% and the intermediate and posterior components of the right ILF and the anterior component of the right IFOF contribute the most. Conclusions Changes in the properties of DTI may be the potential mechanism of WMH‐related MCI, especially the right IFOF and the right ILF, which may become imaging markers for predicting WMH‐related cognitive dysfunction.
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Objectives To investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD). Methods A prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume. Results The decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (β=0.18, p=0.03) and a trend with change in cognitive index (β=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76). Conclusion Disruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.
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Cerebral small vessel diseases play a crucial role in both vascular and non-vascular dementias. The location of white matter hyperintensities (WMHs), a neuroimaging marker of cerebral small vessel disease, has been found to vary between different types of dementias, and those in the basal ganglia (BG) have been particularly associated with vascular cognitive impairment (VCI). However, anatomical variation of WMHs across BG nuclei and its effect on brain network dysconnectivity has not been clearly elucidated. The study sample consisted of 40 patients with amnestic mild cognitive impairment (aMCI), 40 with subcortical vascular MCI (SVMCI), and 40 healthy control subjects. We examined the volume of WMH using T2-weighted magnetic resonance imaging. We also assessed the disturbances in BG-cortical communication by measuring resting-state functional connectivity (rsFC) from the functional magnetic resonance imaging signal. WMHs were more pronounced in the SVMCI group particularly in the caudate regions. In SVMCI patients, while higher WMHs in the dorsal caudate correlated with weaker FC with executive control regions and worse immediate recall performance, WMHs in the ventral caudate were associated with weaker FC with anterior default mode regions and worse delayed recall performance. In contrast, in aMCI patients, BG WMHs were not correlated with their changes in functional connectivity changes, which showed weaker connectivity with almost all BG structures, rather than restricting to specific BG subdivisions as observed in the SVMCI group. Our findings demonstrate that heterogeneously distributed BG WMHs are associated with changes in functional network interactions and verbal episodic memory performance only in SVMCI patients, which establishes a link between cerebrovascular-related structural abnormality, functional integrity of BG circuits, and episodic memory impairments in SVMCI, and may reflect a differential role of the cerebrovascular pathology in disrupting network-level communications and cognition between Alzheimer’s and subcortical vascular dementia.
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Aims: The prevalence of white matter hyperintensities (WMH) rises dramatically with aging. Both the progression of WMH and changing patterns of default mode network (DMN) have been proven to be closely associated with cognitive function. The present study hypothesized that changes in functional connectivity and structural connectivity of DMN contributed to WMH related cognitive impairment. Methods: A total of 116 subjects were enrolled from the Cerebral Small Vessel Disease Register in Drum Tower Hospital of Nanjing University, and were distributed across three categories according to Fazekas rating scale: WMH I (n = 57), WMH II (n = 34), and WMH III(n = 25). All participants underwent neuropsychological tests and multimodal MRI scans, including diffusion tensor imaging and resting-state fMRI imaging. The alterations of functional connectivity and structural connectivity within the DMN were further explored. Results: Age and hypertension were risk factors for WMH progression. Subjects with a higher WMH burden displayed higher DMN functional connectivity in the medial frontal gyrus, while lower DMN functional connectivity in the thalamus. After adjusting for aging, gender, and education, the increased DMN functional connectivity in the medial frontal gyrus, and the increased mean diffusivity of the white matter tracts between the hippocampus and posterior cingulate cortex were independent indicators of worse performance in memory. Moreover, the decreased DMN functional connectivity in the thalamus and increased mean diffusivity of the white matter tracts between the thalamus and posterior cingulate cortex were independent risk factors for a slower processing speed. Conclusion: The changes in functional connectivity and structural connectivity within the DMN attributed to WMH progression were responsible for the development of cognitive impairment.
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Background and Purpose Chronic hypoxia-ischemia is a putative mechanism underlying the development of white matter hyperintensities (WMH) and microstructural disruption in cerebral small vessel disease. WMH fall primarily within deep white matter (WM) watershed regions. We hypothesized that elevated oxygen extraction fraction (OEF), a signature of hypoxia-ischemia, would be detected in the watershed where WMH density is highest. We further hypothesized that OEF would be elevated in regions immediately surrounding WMH, at the leading edge of growth. Methods In this cross-sectional study conducted from 2016 to 2019 at an academic medical center in St Louis, MO, participants (age >50) with a range of cerebrovascular risk factors underwent brain magnetic resonance imaging using pseudocontinuous arterial spin labeling, asymmetric spin echo, fluid-attenuated inversion recovery and diffusion tensor imaging to measure cerebral blood flow (CBF), OEF, WMH, and WM integrity, respectively. We defined the physiologic watershed as a region where CBF was below the 10th percentile of mean WM CBF in a young healthy cohort. We conducted linear regression to evaluate the relationship between CBF and OEF with structural and microstructural WM injury defined by fluid-attenuated inversion recovery WMH and diffusion tensor imaging, respectively. We conducted ANOVA to determine if OEF was increased in proximity to WMH lesions. Results In a cohort of 42 participants (age 50–80), the physiologic watershed region spatially overlapped with regions of highest WMH lesion density. As CBF decreased and OEF increased, WMH density increased. Elevated watershed OEF was associated with greater WMH burden and microstructural disruption, after adjusting for vascular risk factors. In contrast, WM and watershed CBF were not associated with WMH burden or microstructural disruption. Moreover, OEF progressively increased while CBF decreased, in concentric contours approaching WMH lesions. Conclusions Chronic hypoxia-ischemia in the watershed region may contribute to cerebral small vessel disease pathogenesis and development of WMH. Watershed OEF may hold promise as an imaging biomarker to identify individuals at risk for cerebral small vessel disease progression.
Article
Cerebral small vessel disease (SVD) is highly prevalent and a common cause of ischemic and hemorrhagic stroke and dementia, yet the pathophysiology is poorly understood. Its clinical expression is highly varied, and prognostic implications are frequently overlooked in clinics; thus, treatment is currently confined to vascular risk factor management. Traditionally, SVD is considered the small vessel equivalent of large artery stroke (occlusion, rupture), but data emerging from human neuroimaging and genetic studies refute this, instead showing microvessel endothelial dysfunction impacting on cell–cell interactions and leading to brain damage. These dysfunctions reflect defects that appear to be inherited and secondary to environmental exposures, including vascular risk factors. Interrogation in preclinical models shows consistent and converging molecular and cellular interactions across the endothelial-glial-neural unit that increasingly explain the human macroscopic observations and identify common patterns of pathology despite different triggers. Importantly, these insights may offer new targets for therapeutic intervention focused on restoring endothelial-glial physiology. Expected final online publication date for the Annual Review of Physiology, Volume 84 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Article
Background: Altered white matter brain networks have been extensively studied in cerebral small vessel disease (SVD). However, there exists currently a deficiency of comprehending the performance of changes within the structural networks of the brain in cases with cerebral SVD and depression symptoms. The main aim of the present research is to study the network topology behaviors and features of rich-club organization in SVD patients using graph theory and diffusion tensor imaging (DTI) to characterize changes in the microstructure of the brain. Methods: DTI datasets were acquired from 26 SVD patients with symptoms of depression (SVD + D) and 26 SVD patients without symptoms of depression (SVD - D), and a series of neuropsychological assessments were completed. A structural network was created using a deterministic fiber tracking method. The analysis of rich-club was performed in company with analysis of the global network features of the network to characterize the topological properties of all subjects. Results: DTI data were obtained from SVD patients who manifested symptoms of depression (SVD + D) and from control SVD patients (SVD - D). In comparison with SVD - D patients, SVD + D cases demonstrated a diminished coefficient of clustering along with lower global efficiencies and longer path length characteristics. Rich-club analysis showed SVD + D patients had decreased feeder connectivity and local connectivity strengths compared to SVD - D patients. Our data also showed that the feeder connections in the brain correlated significantly with the severity of depression in SVD + D patients. Conclusions: Our study revealed that SVD patients with depressive symptoms have disrupted white matter networks that characteristically have reduced network efficiency compared to the networks in other SVD patients. Disrupted information interactions among the regions of nonrich-club and rich-club in SVD cases are related to the severity of depression. Our data suggest that DTI may be utilized as an appropriate biomarker for the diagnosis of depression in comorbid SVD patients.
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Few studies have focused on the connection between glymphatic dysfunction and cerebral small vessel disease (CSVD), partially due to the lack of non-invasive methods to measure glymphatic function. We established modified index for diffusion tensor image analysis along the perivascular space (mALPS-index), which was calculated on diffusion tensor image (DTI), compared it with the classical detection of glymphatic clearance function calculated on Glymphatic MRI after intrathecal administration of gadolinium (study 1), and analyzed the relationship between CSVD imaging markers and mALPS-index in CSVD patients from the CIRCLE study (ClinicalTrials.gov ID: NCT03542734) (study 2). Among 39 patients included in study 1, mALPS-index were significantly related to glymphatic clearance function calculated on Glymphatic MRI (r = -0.772∼-0.844, p < 0.001). A total of 330 CSVD patients were included in study 2. Severer periventricular and deep white matter hyperintensities (β = -0.332, p < 0.001; β = -0.293, p < 0.001), number of lacunas (β = -0.215, p < 0.001), number of microbleeds (β = -0.152, p = 0.005), and severer enlarged perivascular spaces in basal ganglia (β = -0.223, p < 0.001) were related to mALPS-index. Our results indicated that non-invasive mALPS-index might represent glymphatic clearance function, which could be applied in clinic in future. Glymphatic clearance function might play a role in the development of CSVD.
Article
Background and Purpose In cerebral small vessel disease, cerebral blood flow and autoregulation are impaired and therefore excessive blood pressure reduction could possibly accelerate white matter damage and worsen outcome. The trial determined, in severe symptomatic cerebral small vessel disease, whether intensive blood pressure lowering resulted in progression of white matter damage assessed using diffusion tensor imaging. Methods Randomized, parallel, multicenter controlled, blinded-outcomes clinical trial. One hundred eleven participants with magnetic resonance imaging confirmed symptomatic lacunar infarct and confluent white matter hyperintensities and were recruited and randomized to standard (systolic=130–140 mmHg) (N=56) or intensive (systolic<125 mmHg) (N=55) blood pressure targets. The primary end point was change in diffusion tensor imaging white matter mean diffusivity peak height between baseline and 24 months. Secondary end points were other magnetic resonance imaging markers and cognition. Results Patients were mean 68 years and 60% male. Mean (SD) blood pressure reduced by −15.3 (15.4) and −23.1 (22.04) mm Hg in the standard/intensive groups, respectively ( P <0.001). There was no difference between treatment groups for the primary end point: standard, adjusted mean (SE)=12.5×10 ⁻³ (0.2×10 ⁻³ ); intensive, 12.5×10 ⁻³ (0.2×10 ⁻³ ), P =0.92. In the whole population over 24 months follow-up, there was a significant deterioration in white matter microstructure but no detectable decrease in cognition. Conclusions Intensive blood pressure lowering in severe cerebral small vessel disease was not associated with progression of white matter damage on diffusion tensor imaging or magnetic resonance imaging. In a multicentre study setting over 2 years, multimodal diffusion tensor imaging-magnetic resonance imaging was more sensitive to detecting change than cognitive testing. REGISTRATION URL: https://www.isrctn.com ; Unique identifier: ISRCTN37694103.
Article
Background and purpose: Whole-brain network connectivity has been shown to be a useful biomarker of cerebral amyloid angiopathy and related cognitive impairment. We evaluated an automated DTI-based method, peak width of skeletonized mean diffusivity, in cerebral amyloid angiopathy, together with its association with conventional MRI markers and cognitive functions. Materials and methods: We included 24 subjects (mean age, 74.7 [SD, 6.0] years) with probable cerebral amyloid angiopathy and mild cognitive impairment and 62 patients with MCI not attributable to cerebral amyloid angiopathy (non-cerebral amyloid angiopathy-mild cognitive impairment). We compared peak width of skeletonized mean diffusivity between subjects with cerebral amyloid angiopathy-mild cognitive impairment and non-cerebral amyloid angiopathy-mild cognitive impairment and explored its associations with cognitive functions and conventional markers of cerebral small-vessel disease, using linear regression models. Results: Subjects with Cerebral amyloid angiopathy-mild cognitive impairment showed increased peak width of skeletonized mean diffusivity in comparison to those with non-cerebral amyloid angiopathy-mild cognitive impairment (P < .001). Peak width of skeletonized mean diffusivity values were correlated with the volume of white matter hyperintensities in both groups. Higher peak width of skeletonized mean diffusivity was associated with worse performance in processing speed among patients with cerebral amyloid angiopathy, after adjusting for other MRI markers of cerebral small vessel disease. The peak width of skeletonized mean diffusivity did not correlate with cognitive functions among those with non-cerebral amyloid angiopathy-mild cognitive impairment. Conclusions: Peak width of skeletonized mean diffusivity is altered in cerebral amyloid angiopathy and is associated with performance in processing speed. This DTI-based method may reflect the degree of white matter structural disruption in cerebral amyloid angiopathy and could be a useful biomarker for cognition in this population.
Article
The MarkVCID consortium was formed under cooperative agreements with the National Institute of Neurologic Diseases and Stroke (NINDS) and National Institute on Aging (NIA) in 2016 with the goals of developing and validating biomarkers for the cerebral small vessel diseases associated with the vascular contributions to cognitive impairment and dementia (VCID). Rigorously validated biomarkers have consistently been identified as crucial for multicenter studies to identify effective strategies to prevent and treat VCID, specifically to detect increased VCID risk, diagnose the presence of small vessel disease and its subtypes, assess prognosis for disease progression or response to treatment, demonstrate target engagement or mechanism of action for candidate interventions, and monitor disease progression during treatment. The seven project sites and central coordinating center comprising MarkVCID, working with NINDS and NIA, identified a panel of 11 candidate fluid‐ and neuroimaging‐based biomarker kits and established harmonized multicenter study protocols (see companion paper “MarkVCID cerebral small vessel consortium: I. Enrollment, clinical, fluid protocols” for full details). Here we describe the MarkVCID neuroimaging protocols with specific focus on validating their application to future multicenter trials. MarkVCID procedures for participant enrollment; clinical and cognitive evaluation; and collection, handling, and instrumental validation of fluid samples are described in detail in a companion paper. Magnetic resonance imaging (MRI) has long served as the neuroimaging modality of choice for cerebral small vessel disease and VCID because of its sensitivity to a wide range of brain properties, including small structural lesions, connectivity, and cerebrovascular physiology. Despite MRI's widespread use in the VCID field, there have been relatively scant data validating the repeatability and reproducibility of MRI‐based biomarkers across raters, scanner types, and time intervals (collectively defined as instrumental validity). The MRI protocols described here address the core MRI sequences for assessing cerebral small vessel disease in future research studies, specific sequence parameters for use across various research scanner types, and rigorous procedures for determining instrumental validity. Another candidate neuroimaging modality considered by MarkVCID is optical coherence tomography angiography (OCTA), a non‐invasive technique for directly visualizing retinal capillaries as a marker of the cerebral capillaries. OCTA has theoretical promise as a unique opportunity to visualize small vessels derived from the cerebral circulation, but at a considerably earlier stage of development than MRI. The additional OCTA protocols described here address procedures for determining OCTA instrumental validity, evaluating sources of variability such as pupil dilation, and handling data to maintain participant privacy. MRI protocol and instrumental validation The core sequences selected for the MarkVCID MRI protocol are three‐dimensional T1‐weighted multi‐echo magnetization‐prepared rapid‐acquisition‐of‐gradient‐echo (ME‐MPRAGE), three‐dimensional T2‐weighted fast spin echo fluid‐attenuated‐inversion‐recovery (FLAIR), two‐dimensional diffusion‐weighted spin‐echo echo‐planar imaging (DWI), three‐dimensional T2*‐weighted multi‐echo gradient echo (3D‐GRE), three‐dimensional T 2 ‐weighted fast spin‐echo imaging (T2w), and two‐dimensional T2*‐weighted gradient echo echo‐planar blood‐oxygenation‐level‐dependent imaging with brief periods of CO 2 inhalation (BOLD‐CVR). Harmonized parameters for each of these core sequences were developed for four 3 Tesla MRI scanner models in widespread use at academic medical centers. MarkVCID project sites are trained and certified for their instantiation of the consortium MRI protocols. Sites are required to perform image quality checks every 2 months using the Alzheimer's Disease Neuroimaging Initiative phantom. Instrumental validation for MarkVCID MRI‐based biomarkers is operationally defined as inter‐rater reliability, test‐retest repeatability, and inter‐scanner reproducibility. Assessments of these instrumental properties are performed on individuals representing a range of cerebral small vessel disease from mild to severe. Inter‐rater reliability is determined by distribution of an independent dataset of MRI scans to each analysis site. Test‐retest repeatability is determined by repeat MRI scans performed on individual participants on a single MRI scanner after a short (1‐ to 14‐day) interval. Inter‐scanner reproducibility is determined by repeat MRI scans performed on individuals performed across four MRI scanner models. OCTA protocol and instrumental validation The MarkVCID OCTA protocol uses a commercially available, Food and Drug Administration‐approved OCTA apparatus. Imaging is performed on one dilated and one undilated eye to assess the need for dilation. Scans are performed in quadruplicate. MarkVCID project sites participating in OCTA validation are trained and certified by this biomarker's lead investigator. Inter‐rater reliability for OCTA is assessed by distribution of OCTA datasets to each analysis site. Test‐retest repeatability is assessed by repeat OCTA imaging on individuals on the same day as their baseline OCTA and a different‐day repeat session after a short (1‐ to 14‐day) interval. Methods were developed to allow the OCTA data to be de‐identified by the sites before transmission to the central data management system. The MarkVCID neuroimaging protocols, like the other MarkVCID procedures, are designed to allow translation to multicenter trials and as a template for outside groups to generate directly comparable neuroimaging data. The MarkVCID neuroimaging protocols are available to the biomedical community and intended to be shared. In addition to the instrumental validation procedures described here, each of the neuroimaging MarkVCID kits will undergo biological validation to determine its ability to measure important aspects of VCID such as cognitive function. The analytic methods for the neuroimaging‐based kits and the results of these validation studies will be published separately. The results will ultimately determine the neuroimaging kits’ potential usefulness for multicenter interventional trials in small vessel disease–related VCID.
Article
Background- White matter hyperintensity (WMH) is closely associated with geriatric depressive symptoms, but its underlying neural mechanism is unclear. We aim to disentangle the contribution of vascular degeneration and fiber disruption to depressive symptoms in elderly subjects at different clinical status. Methods- One hundred and thirty-three normal elderly subjects, as well as 43 patients with cerebral small vessel disease (CSVD) were included. The Hamilton Depression Rating Scale (HAMD) was used to measure depressive symptoms. Based on the diffusion tensor imaging data, a free water elimination analytical model was adopted to reflect fiber tract disruption (measure: tissue fractional anisotropy, tFA) and increased white matter water content (measure: free water fraction, FW). Results- We found that WMH severity was significantly correlated with decreased tFA and increased FW in all subjects. In normal elderly subjects, the HAMD score was correlated with mean tFA, but not FW. Compared to the traditional fractional anisotropy measure, tFA showed stronger correlation with clinical symptoms. In CSVD subjects, the correlation was only significant for FW, and marginally significant for tFA. Limitations- Most subjects had only mild to moderate depressive symptoms. Further validation in patients with major depressive disorder is needed to confirm these findings. Conclusions- The neural mechanisms of depressive symptoms may be different in elderly people with or without severe vascular damage. The free water elimination model may disentangle the effects of fiber disruption and increased free water, providing sensitive imaging markers that could potentially be used on monitoring disease treatment.
Article
Background Lesions of cerebral small vessel disease, such as white matter hyperintensities (WMHs) in individuals with cardiometabolic risk factors, interfere with the trajectories of the white matter and eventually contribute to cognitive decline. However, there is no consensus yet about the precise underlying topological mechanism. Purpose To examine whether WMH and cognitive function are associated and whether any such association is mediated or explained by structural connectivity measures in an adult population. In addition, to investigate underlying local abnormalities in white matter by assessing the tract-specific WMH volumes and their tract-specific association with cognitive function. Materials and Methods In the prospective type 2 diabetes-enriched population-based Maastricht Study, structural and diffusion-tensor MRI was performed (December 2013 to February 2017). Total and tract-specific WMH volumes; network measures; cognition scores; and demographic, cardiovascular, and lifestyle characteristics were determined. Multivariable linear regression and mediation analyses were used to investigate the association of WMH volume, tract-specific WMH volumes, and network measures with cognitive function. Associations were adjusted for age, sex, education, diabetes status, and cardiovascular risk factors. Results A total of 5083 participants (mean age, 59 years ± 9 [standard deviation]; 2592 men; 1027 with diabetes) were evaluated. Larger WMH volumes were associated with stronger local (standardized β coefficient, 0.065; P < .001), but not global, network efficiency and lower information processing speed (standardized β coefficient, -0.073; P < .001). Moreover, lower local efficiency (standardized β coefficient, -0.084; P < .001) was associated with lower information processing speed. In particular, the relationship between WMHs and information processing speed was mediated (percentage mediated, 7.2% [95% CI: 3.5, 10.9]; P < .05) by the local network efficiency. Finally, WMH load was larger in the white matter tracts important for information processing speed. Conclusion White matter hyperintensity volume, local network efficiency, and information processing speed scores are interrelated, and local network properties explain lower cognitive performance due to white matter network alterations. © RSNA, 2020 Online supplemental material is available for this article.
Article
Previous diffusion tensor imaging (DTI) studies indicate that impaired microstructural integrity of the normal-appearing white matter (NAWM) is related to cognitive impairment in cerebral small vessel disease (SVD). This study aimed to investigate whether quantitative T 2 relaxometry is a suitable imaging biomarker for the assessment of tissue changes related to cognitive abnormalities in patients with SVD. 39 patients and 18 age-matched healthy control subjects underwent 3 T magnetic resonance imaging (MRI) with T2-weighted multiple spin echo sequences for T 2 relaxometry and DTI sequences, as well as comprehensive cognitive assessment. Averaged quantitative T 2 , fractional anisotropy (FA) and mean diffusivity (MD) were determined in the NAWM and related to cognitive parameters controlling for age, normalized brain volume, white matter hyperintensity volume and other conventional SVD markers. In SVD patients, quantitative T 2 values were significantly increased compared to controls (p = 0.002) and significantly negatively correlated with the global cognitive performance (r= –0.410, p = 0.014) and executive function (r= –0.399, p = 0.016). DTI parameters did not correlate with cognitive function. T 2 relaxometry of the NAWM seems to be sensitive to microstructural tissue damage associated with cognitive impairment in SVD and might be a promising imaging biomarker for evaluation of disease progression and possible effects of therapeutic interventions.
Article
Introduction: We have demonstrated that asymptomatic cerebral small vessel disease (cSVD) measured by white matter hyperintensity volume is associated with reduced manipulative manual dexterity on the Grooved Peg Board Test (GPBT) in middle-aged healthy individuals with a family history of early coronary artery disease. In this current study, we aim to identify the association of subcortical white matter microstructural impairment measured by diffusion tensor imaging, manual dexterity measured by GPBT and circulating serums ceramide, another marker for white matter injury. We hypothesize that lower regional fractional anisotropy (rFA) is associated with worse performance on GPBT and elevated serum ceramides in the same study population. Methods: rFA of 48 regions representing the subcortical white matters were analyzed in GeneSTAR participants in addition to serum ceramides and GPBT scores. Unadjusted univariable analyses with Bonferroni correction for multiple comparisons were completed using Spearman correlation for testing the associations between ceramides, rFA of subcortical white matter, and GPBT performance. Subsequently, sensitivity analyses were performed after excluding the participants that had any physical limitation that may influence their performance on GPBT. Finally, in the adjusted analysis using generalized estimating equation, linear regression models were performed for the areas that met significance threshold in the unadjusted analyses. Results: 112 subjects (age [49 ± 11], 51% female, 39.3% African American) were included. Adjusted analyses for the significant correlations that met the Bonferroni correction threshold in the unadjusted univariable analyses identified significant negative associations between rFA of the right fornix (RF) and log-GPBT score (β = -0.497, p = 0.037). In addition, rFA of RF negatively correlated with log serum ceramide levels (C18: β = -0.03, p = 0.003, C20: β = -0.0002, p = 0.004) and rFA of left genu of corpus callosum negatively correlated with log C18 level (β = -0.0103, p = 0.027). Conclusions: These results demonstrate that subcortical microstructural white matter disruption is associated with elevated serum ceramides and reduced manual dexterity in a population with cSVD. These findings suggest that injury to white matter tracts undermines neural networks, with functional consequences in a middle-aged population with cardiovascular risk factors.
Article
We examined the relationship between white matter hyperintensities (WMH) and cortical neurodegeneration in cerebral small vessel disease (CSVD) by investigating whether cortical thickness is a remote effect of WMH through structural fiber tract connectivity in a population at increased risk of CSVD. We measured cortical thickness on T1-weighted images and segmented WMH on FLAIR images in 930 participants of a population-based cohort study at baseline. DWI-derived whole-brain probabilistic tractography was used to define WMH connectivity to cortical regions. Linear mixed-effects models were applied to analyze the relationship between cortical thickness and connectivity to WMH. Factors associated with cortical thickness (age, sex, hemisphere, region, individual differences in cortical thickness) were added as covariates. Median age was 64 [IQR 46–76] years. Visual inspection of surface maps revealed distinct connectivity patterns of cortical regions to WMH. WMH connectivity to the cortex was associated with reduced cortical thickness ( p = 0.009) after controlling for covariates. This association was found for periventricular WMH ( p = 0.001) only. Our results indicate an association between WMH and cortical thickness via connecting fiber tracts. The results imply a mechanism of secondary neurodegeneration in cortical regions distant, yet connected to subcortical vascular lesions, which appears to be driven by periventricular WMH.
Article
Background: Alzheimer's disease (AD) is a chronic neurodegenerative disorder frequently accompanied by cerebral small vessel disease (CSVD). However, the influence of CSVD on the brain functional connectivity in subjects along the AD continuum is still largely unknown. The current study combined the static and dynamic functional network connectivity (FNC) to explore the underlying mechanism. Methods: In this study, we included 182 healthy controls (HC), 27 individuals with subjective cognitive decline (SCD), 27 with SCD+CSVD, 104 with mild cognitive impairment (MCI), 123 with MCI+CSVD, 16 with AD, and 62 with AD+CSVD. We examined the static and dynamic FNC within the default mode (DM), salience (SA), and cognitive control (CC) domains. We also assessed the association between atypical FNC patterns and cognitive impairments, as well as the pathologies. Results: Static FNC results showed progressively increased within-domain connectivity and decreased between-domain connectivity along AD continuum, especially in CSVD subjects. Dynamic FNC in CSVD subjects showed more occurrences in a highly-modularized state and fewer occurrences in the diffusely connected state. Further analysis showed that neuropathology and CSVD burden divergently affect the FNC changes. Conclusions: The overall results demonstrate divergent abnormalities of FNC in CSVD and non-CSVD individuals along the AD continuum, which were divergently affected by neuropathology and CSVD burden. Specifically, those with CSVD show more static and dynamic FNC impairments, associated with cognitive decline. These findings may advance our understanding of the effect of CSVD on AD onset and progression, and provide potential hints for clinical treatment.
Article
Objective: To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change and reproducibility of diffusion metrics. Methods: We included 50 sporadic and 59 genetically defined SVD patients (CADASIL) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 sporadic SVD patients with longitudinal high-frequency imaging (in total 459 MRIs). Inter-site reproducibility was determined in 10 CADASIL patients scanned back-to-back on 2 different 3T MRI scanners. Results: Metrics from DKI showed the strongest associations with processing speed performance (R 2 up to 21%) and the largest added benefit on top of conventional SVD imaging markers in sporadic SVD and CADASIL patients with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible. Conclusion: Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available inter-site dataset facilitates future studies. Classification of evidence: This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.
Article
Cerebral small vessel disease (CSVD) is a common disease among elderly individuals and recognized as a major cause of vascular cognitive impairment. Recent studies demonstrated that CSVD is a disconnection syndrome. However, due to the covert neurological symptoms and subtle changes in clinical performance, the connection alterations during the stage of preclinical cognitive impairment (PCI) and mild cognitive impairment (MCI) are usually neglected and still largely unknown. Using diffusion tensor imaging (DTI), we investigated the early structural network changes in PCI and MCI patients. The PCI group demonstrated well preserved rich-club organization, less nodal strength loss, and disruption of connections centered in the feeder and local connections. Nevertheless, The MCI group manifested a disruption in the rich-club organization, a worse nodal strength loss especially in hub nodes, and an overall disturbance in rich-club, feeder and local connections. Moreover, in all CSVD patients, the strength of the rich-club, feeder and local connections was significantly correlated with multiple cognitive scores, especially in attention, executive, and memory domains; while in MCI patients, only the strength of the rich-club connections was significantly correlated with cognition. Furthermore, based on the network-based statistic analysis, we also identified distinct network component disruption pattern between the PCI group and the MCI group, validating the results described above. These results suggest a disruption pattern from peripheral to central connections with the change of cognitive status, shedding light on the early identification and the underlying disruption of CSVD.
Article
INTRODUCTION: Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer’s disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. METHODS: We studied six samples (N=365 participants) covering the spectrum of AD and SVD, including genetically-defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid-beta, tau), SVD imaging markers, and diffusion measures. RESULTS: SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. DISCUSSION: In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.
Article
Background and purpose: Previous studies have shown that diffusion tensor imaging suggests a diffuse loss of white matter integrity in people with white matter hyperintensities or lacunes. The purpose of this study was to investigate whether the presence of cerebral microbleeds and their distribution are related to the integrity of white matter microstructures. Materials and methods: The study comprised 982 participants who underwent brain MR imaging to determine microbleed status. The cross-sectional relation between microbleeds and the microstructural integrity of the white matter was assessed by 2 statistical methods: a multilinear regression model based on the average DTI parameters of normal-appearing white matter and Tract-Based Spatial Statistics analysis, a tract-based voxelwise analysis. Fiber tractography was used to spatially describe the microstructural abnormalities along WM tracts containing a cerebral microbleed. Results: The presence of cerebral microbleeds was associated with lower mean fractional anisotropy and higher mean diffusivity, axial diffusivity, and radial diffusivity, and the association remained when cardiovascular risk factors and cerebral small-vessel disease markers were further adjusted. Tract-Based Spatial Statistics analysis indicated strictly lobar cerebral microbleeds associated with lower fractional anisotropy, higher mean diffusivity, and higher radial diffusivity in the internal capsule and corpus callosum after adjusting other cerebral small-vessel disease markers, while only a few voxels remained associated with deep cerebral microbleeds. Diffusion abnormalities gradients along WM tracts containing a cerebral microbleed were not found in fiber tractography analysis. Conclusions: Cerebral microbleeds are associated with widely distributed changes in white matter, despite their focal appearance on SWI.
Article
Deep medullary veins (DMVs) participate in the drainage of surrounding white matter. In cerebral small vessel disease (CSVD), disrupted DMVs were often observed together with damaged white matter, but the phenomenon lacked validation and explanation. We hypothesized that venous disruption might cause white matter damage through increased interstitial fluid resulting from hemodynamic alteration, and we designed a comprehensive multi-modality MRI study to testify our hypothesis. Susceptibility-weighted imaging was used to investigate the characteristics of DMVs and derive DMVs scores. Free water elimination diffusion tensor imaging model was used to analyze interstitial fluid fraction (fraction of free water, fFW) and white matter integrity (tissue fractional anisotropy, FAt). Totally, 104 CSVD patients were included. Total DMVs score was associated with FAt of DMVs drainage area. The effect of total DMVs score on FAt was mediated by fFW, after controlling for age, sex, hypertension, regional cerebral blood flow and lacune numbers. The relationships between DMVs score, fFW and FAt were also significant in most DMVs drainage subregions. Therefore, we discovered the DMVs disruption – increased interstitial fluid – white matter damage link in CSVD patients, which was independent of arterial perfusion variations.