Small Vessel Disease Cognitive Impairment Research Articles

Cortical surface-based morphometry in cognitive impairment in sporadic cerebral small vessel disease

Background: Analysis of structural MR images plays a key role in assessing the underlying substrate of cognitive impairment (CI) in sporadic age-related cerebral small vessel disease (SVD), leading to up to 45% of all cases of dementia. The variety of MR-morphometry results in SVD requires extensive research and comparisons with clinical data. Aims: to assess the characteristics of brain atrophy in cognitive impairment in patients with SVD using surface-based morphometry (SBM). Materials and methods: A prospective study was conducted assessing patients with SVD and CI of varying severity (subjective - subCI, moderate - MCI and dementia) and a group of volunteers matched by gender and age. MRI was performed with subsequent analysis of MRI signs of SVD and calculation of the general SVD index and processing of T1mpr images using the SBM method with general and regional quantitative assessment of the brain, including the thickness of the cerebral cortex. Results: the main group with SVD consisted of 173 patients, the control group included 47 healthy volunteers. As the severity of structural changes in the brain and the severity of CI increased, there was a significant (p0.05) decrease in the thickness of the cortex of certain regions according to a similar pattern: the cingulate gyri, mainly their posterior sections; medial and middle sections of the frontal lobes, various parts of the insular cortex, temporo-parietal areas (especially the supramarginal gyri). The volume of the brain itself (total volume, gray and white matter) in SVD had significant differences only with controls, but not between groups of patients with different severity of CI. The volume of white matter hyperintensities was significantly different between the groups with dementia and MCI, dementia and sub-CI (p 0.0001). Conclusions: The data obtained during the study confirm the secondary/mixed nature of atrophy in SVD. The wide variety of regions with significant thinning of the cortex limits the specification of the progression of CI in SVD based on their atrophy. This allows the quantitative measurement of the cortex to be used only as an auxiliary method in assessing the prediction of SVD progression.

Regional cortical thinning, demyelination, and iron loss in cerebral small vessel disease.

The link between white matter hyperintensities (WMH) and cortical thinning is thought to be an important pathway by which WMH contributes to cognitive deficits in cerebral small vessel disease (SVD). However, the mechanism behind this association and the underlying tissue composition abnormalities are unclear. The objective of this study is to determine the association between WMH and cortical thickness, and the in-vivo tissue composition abnormalities in the WMH-connected cortical regions. In this cross-sectional study, we included 213 participants with SVD who underwent standardized protocol including multimodal neuroimaging scans and cognitive assessment (i.e., processing speed, executive function, and memory). We identified the cortex connected to WMH using probabilistic tractography starting from the WMH and defined the WMH-connected regions at three connectivity levels (low, medium, and high connectivity level). We calculated the cortical thickness, myelin and iron of the cortex based on T1-weighted, quantitative R1, R2*, and susceptibility maps. We used diffusion-weighted imaging to estimate the mean diffusivity (MD) of the connecting white matter tracts. We found that cortical thickness, R1, R2*, and susceptibility values in the WMH-connected regions were significantly lower than in the WMH-unconnected regions (all p-corrected<0.001). Linear regression analyses showed that higher MD of the connecting white matter tracts were related to lower thickness (β=-0.30, p-corrected<0.001), R1 (β=-0.26, p-corrected=0.001), R2* (β=-0.32, p-corrected<0.001) and susceptibility values (β=-0.39, p-corrected<0.001) of WMH-connected cortical regions at high connectivity level. In addition, lower scores on processing speed were significantly related to lower cortical thickness (β=0.20, p-corrected=0.030), lower R1 values (β=0.20, p-corrected=0.006), lower R2* values (β=0.29, p-corrected=0.006), and lower susceptibility values (β=0.19, p-corrected=0.024) of the WMH-connected regions at high connectivity level, independent of WMH volumes and the cortical measures of WMH-unconnected regions. Together, our study demonstrated that the microstructural integrity of white matter tracts passing through WMH is related to the regional cortical abnormalities as measured by thickness, R1, R2* and susceptibility values in the connected cortical regions. These findings are indicative of cortical thinning, demyelination and iron loss in the cortex, which is most likely through the disruption of the connecting white matter tracts and may contribute to processing speed impairment in SVD, a key clinical feature of SVD. These findings may have implications for finding intervention targets for the treatment of cognitive impairment in SVD by preventing secondary degeneration.

Altered neurovascular coupling in patients with vascular cognitive impairment: a combined ASL-fMRI analysis.

This study aims to examine the role of neurovascular coupling (NVC) in vascular cognitive impairment (VCI) by investigating the relationship between white matter lesion (WML) burden, NVC, and cognitive deficits. Additionally, we aim to explore the potential of NVC as a tool for understanding the neural mechanisms underlying VCI. This study included thirty-eight small vessel disease cognitive impairment (SVCI) patients, 34 post-stroke cognitive impairment (PSCI) patients, and 43 healthy controls (HC). Comprehensive assessments, including neuroimaging and neuropsychological testing, were conducted to evaluate cognitive function. WML burden was measured and correlated with NVC coefficients to examine the relationship between white matter pathology and NVC. Mediation analysis was employed to explore the link relationship between NVC, WML burden, and cognitive function. The present study showed that NVC was significantly reduced in the SVCI and PSCI groups compared with HCs at both whole-brain and brain region level. The analysis revealed notable findings regarding NVC in relation to WML burden and cognitive function in VCI patients. Specifically, reduced NVC coefficients were observed within higher order brain systems responsible for cognitive control and emotion regulation. Mediation analysis demonstrated that NVC played a mediating role in the relationship between WML burden and cognitive impairment. This study reveals the mediating role of NVC in the relationship between WML burden and cognitive function in VCI patients. The results demonstrate the potential of the NVC as an accurate measure of cognitive impairment and its ability to identify specific neural circuits affected by WML burden.

Dissociable Contributions of Thalamic-Subregions to Cognitive Impairment in Small Vessel Disease.

Structural network damage is a potentially important mechanism by which cerebral small vessel disease (SVD) can cause cognitive impairment. As a central hub of the structural network, the role of thalamus in SVD-related cognitive impairments remains unclear. We aimed to determine the associations between the structural alterations of thalamic subregions and cognitive impairments in SVD. In this cross-sectional study, 205 SVD participants without thalamic lacunes from the third follow-up (2020) of the prospective RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort), which was initiated in 2006, Nijmegen, were included. Cognitive functions included processing speed, executive function, and memory. Probabilistic tractography was performed from thalamus to 6 cortical regions, followed by connectivity-based thalamic segmentation to assess each thalamic subregion volume and connectivity (measured by mean diffusivity [MD] of the connecting white matter tracts) with the cortex. Least absolute shrinkage and selection operator regression analysis was conducted to identify the volumes or connectivity of the total thalamus and 6 thalamic subregions that have the strongest association with cognitive performance. Linear regression and mediation analyses were performed to test the association of least absolute shrinkage and selection operator-selected thalamic subregion volume or MD with cognitive performance, while adjusting for age and education. We found that higher MD of the thalamic-motor tract was associated with worse processing speed (β=-0.27; P<0.001), higher MD of the thalamic-frontal tract was associated with worse executive function (β=-0.24; P=0.001), and memory (β=-0.28; P<0.001), respectively. The mediation analysis showed that MD of thalamocortical tracts mediated the association between corresponding thalamic subregion volumes and the cognitive performances in 3 domains. Our results suggest that the structural alterations of thalamus are linked to cognitive impairment in SVD, largely depending on the damage pattern of the white matter tracts connecting specific thalamic subregions and cortical regions.

Structural network efficiency mediates the association between glymphatic function and cognition in mild VCI: a DTI-ALPS study.

Background and objective: Vascular cognitive impairment (VCI) can be caused by multiple types of cerebrovascular pathology and is considered a network disconnection disorder. The heterogeneity hinders research progress in VCI. Glymphatic failure has been considered as a key common pathway to dementia recently. The emergence of a new method, Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS), makes it possible to investigate the changes of the glymphatic function in humans non-invasively. We aimed to investigate alterations of glymphatic function in VCI and its potential impact on network connectivity. Methods: We recruited 79 patients with mild VCI, including 40 with cerebral small vessel disease cognitive impairment (SVCI) and 39 with post-stroke cognitive impairment (PSCI); and, 77 normal cognitive (NC) subjects were recruited. All subjects received neuropsychological assessments and multimodal magnetic resonance imaging scans. ALPS-index was calculated and structural networks were constructed by deterministic tractography, and then, the topological metrics of these structural connectivity were evaluated. Results: The ALPS-index of VCI patients was significantly lower than that of NC subjects (P < 0.001). Multiple linear regression analysis showed that ALPS-index affects cognitive function independently (β = 0.411, P < 0.001). The results of correlation analysis showed that the ALPS-index was correlated with overall vascular risk factor burden (r = -0.263, P = 0.001) and multiple cerebrovascular pathologies (P < 0.05). In addition, global efficiency (Eg) of network was correlated with ALPS-index in both SVCI (r = 0.348, P = 0.028) and PSCI (r = 0.732, P < 0.001) patients. Finally, the results of mediation analysis showed that Eg partially mediated in the impact of glymphatic dysfunction on cognitive impairment (indirect effect = 7.46, 95% CI 4.08-11.48). Conclusion: In both major subtypes of VCI, the ALPS-index was decreased, indicating impaired glymphatic function in VCI. Glymphatic dysfunction may affect cognitive function in VCI by disrupting network connectivity, and, may be a potential common pathological mechanism of VCI. ALPS-index is expected to become an emerging imaging marker for VCI.

Analysis of risk factors for the development of cognitive dysfunction in patients with cerebral small vessel disease and the construction of a predictive model.

BackgroundCognitive dysfunction in cerebral small vessel disease (CSVD) is a common cause of vascular dementia. The purpose of this study was to find independent risk factors for the development of cognitive dysfunction in patients with CSVD and establish a risk prediction model, in order to provide a reference for clinical diagnosis and treatment of such patients.MethodsIn this study, clinical data of patients with CSVD admitted to the Department of Neurology in Gansu Provincial Hospital from December 2019 to December 2021 were collected, and 159 patients were finally included after strict screening according to the inclusion and exclusion criteria. There were 43 patients with normal function and 116 patients with cerebral small vessel disease cognitive impairment (CSVDCI). The logistic multivariable regression model was used to screen out the independent risk factors of cognitive dysfunction in patients with CSVD, and the nomogram of cognitive dysfunction in patients with CSVD was constructed based on the results of the logistic multivariable regression analysis. Finally, the accuracy of the prediction model was evaluated by C-index, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).ResultsThe results of multivariable logistic regression analysis showed that hypertension (OR = 2.683, 95% CI 1.119–6.432, P = 0.027), homocysteine (Hcy) (OR = 1.083, 95% CI 1.026–1.143, P = 0.004), total CSVD MRI Score (OR = 1.593, 95% CI 1.025–2.475, P = 0.039) and years of schooling (OR = 0.883, 95% CI 0.798–0.978, P = 0.017) were independent risk factors for the development of cognitive dysfunction in patients with CSVD. The C-index of this prediction model was 0.806 (95% CI 0.735–0.877), and the calibration curve, ROC curve, and DCA curve all showed good predictive power in the nomogram.ConclusionsThe nomogram constructed in this study has high accuracy and clinical utility in predicting the occurrence of cognitive dysfunction in patients with CSVD. For patients with CSVD with the above risk factors, active clinical intervention and prevention are required during clinical consultation and disease management to avoid cognitive impairment as much as possible.

Exosomal miRNA-223-3p as potential biomarkers in patients with cerebral small vessel disease cognitive impairment.

BackgroundCerebrovascular disease is a common clinical illness. Many patients with cerebrovascular disease can be accompanied by cognitive impairment. The exosomal microRNA (miRNA)-223-3p is related to vascular endothelial injury, synaptic function, inflammatory response, and other mechanisms. In this study, we investigated the levels of plasma exosomal miRNA-223-3p in patients with cerebral small vessel disease (CSVD), in order to determine whether it could be used as a more accessible potential biomarker for the early diagnosis and treatment of CSVD. This study aimed to explore whether the development of cognitive impairment can be explained by differentially expressed miRNA-223-3p by detecting the level of miRNA-223-3p, which is abundant in peripheral blood exosomes related to cognitive impairment in CSVD.MethodsThe three groups of participants included 40 patients with CSVD cognitive impairment (CSVDCI), 38 patients with CSVD, and 35 normal controls (NC). The real-time polymerase chain reaction (RT-PCR) was used to detect the expression level of blood exosomal miRNA-223-3p. In addition, we also studied the relationship between exosomal miRNA-223-3p and blood Hcy and C-reactive protein (CRP). Receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic efficacy of plasma exosomal miRNA-223-3p.ResultsThe expression of exosomal miRNA-223-3p in CSVD increased, and the expression of miRNA-223-3p increased significantly with the occurrence of cognitive impairment. Exosomal miRNA-223-3p was positively correlated with the expression levels of Hcy and CRP in the blood.ConclusionsThe expression of plasma exosomal miRNA-223-3p is associated with the development of cognitive impairment in patients with CSVD. It may be involved in the pathogenesis of CSVD and cognitive impairment, and can be used as a sensitive predictive biomarker.

T2 relaxation time of the normal-appearing white matter is related to the cognitive status in cerebral small vessel disease

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 T2 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 T2 relaxometry and DTI sequences, as well as comprehensive cognitive assessment. Averaged quantitative T2, 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 T2 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. T2 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.

Structural brain network measures are superior to vascular burden scores in predicting early cognitive impairment in post stroke patients with small vessel disease.

ObjectivesIn this cross-sectional study, we aimed to explore the mechanisms of early cognitive impairment in a post stroke non-dementia cerebral small vessel disease (SVD) cohort by comparing the SVD score with the structural brain network measures.Method127 SVD patients were recruited consecutively from a stroke clinic, comprising 76 individuals with mild cognitive impairment (MCI) and 51 with no cognitive impairment (NCI). Detailed neuropsychological assessments and multimodal MRI were performed. SVD scores were calculated on a standard scale, and structural brain network measures were analyzed by diffusion tensor imaging (DTI). Between-group differences were analyzed, and logistic regression was applied to determine the predictive value of SVD and network measures for cognitive status. Mediation analysis with structural equation modeling (SEM) was used to better understand the interactions of SVD burden, brain networks and cognitive deficits.ResultsGroup difference was found on all global brain network measures. After adjustment for age, gender, education and depression, significant correlations were found between global brain network measures and diverse neuropsychological tests, including TMT-B (r = −0.209, p < .05), DSST (r = 0.206, p < .05), AVLT short term free recall (r = 0.233, p < .05), AVLT long term free recall (r = 0.264, p < .05) and Rey-O copy (r = 0.272, p < .05). SVD score showed no group difference and was not correlated with cognition tests. Network global efficiency (EGlobal) was significantly related to cognitive state (p < .01) but not the SVD score. Mediation analysis showed that the standardized total effect (p = .013) and the standardized indirect effect (p = .016) of SVD score on cognition was significant, but the direct effect was not.ConclusionsBrain network measures, but not the SVD score, are significantly correlated with cognition in post-stroke SVD patients. Mediation analysis showed that the cerebral vascular lesions produce cognitive dysfunction by interfering with the structural brain network in SVD patients. The brain network measures may be regarded as direct and independent surrogate markers of cognitive impairment in SVD.

The SNP43 (G/A) polymorphism in CAPN10 gene confers an increased risk of cognitive impairment in cerebral small vessel disease.

Cognitive impairment, significantly reducing processing speed and executive function, is the critical consequence of cerebral small vessel disease (SVD), in which genetic variations have been studied. In this study, we explore the role of SNP43 (G/A) and SNP63 (C/T) polymorphism in the CAPN10 on cognitive impairment process in cerebral SVD. Cerebral SVD patients (n=224) and healthy controls (n=187) were recruited. The relationship between frequency distribution of SNP43 (G/A) and SNP63 (T/C) genotype and allele in CAPN10 gene, and cognitive impairment was examined. The independent risk factors for cognitive impairment in SVD were determined by logistic regression analysis. Accordingly, the frequency distribution of genotype and allele at SNP43 (G/A) was significantly different between cerebral SVD patients and healthy controls. Cerebral SVD patients with GG genotype were more susceptible for cognitive impairment, whereas cerebral SVD patients with GA+AA genotype were less possible to suffer from cognitive impairment, compared with those with GG genotype. And also, cerebral SVD does not include SNP63 (C/T) to associate with cognitive impairment, and SNP43 (G/A), total cholesterol, triglyceride, low-density lipoprotein, and high-density lipoprotein were independent risk factors for cognitive impairment in SVD. Our study provides evidence that SNP43 (G/A) in the CAPN10 gene increases the risk of cognitive impairment in SVD patients. Besides it is proven that, patients with G allele are more susceptible to suffer from cerebral SVD with worse cognitive impairment.

Deep microbleeds and periventricular white matter disintegrity are independent predictors of attention/executive dysfunction in non-dementia patients with small vessel disease.

Cerebral small vessel disease (SVD) is the common cause of cognitive decline in the old population. MRI can be used to clarify its mechanisms. However, the surrogate markers of MRI for early cognitive impairment in SVD remain uncertain to date. We investigated the cognitive impacts of cerebral microbleeds (CMBs), diffusion tensor imaging (DTI), and brain volumetric measurements in a cohort of post-stroke non-dementia SVD patients. Fifty five non-dementia SVD patients were consecutively recruited and categorized into two groups as no cognitive impairment (NCI) (n = 23) or vascular mild cognitive impairment (VaMCI) (n = 32). Detailed neuropsychological assessment and multimodal MRI were completed. The two groups differed significantly on Z scores of all cognitive domains (all p < 0.01) except for the language. There were more patients with hypertension (p = 0.038) or depression (p = 0.019) in the VaMCI than those in the NCI group. Multiple regression analysis of cognition showed periventricular mean diffusivity (MD) (β = -0.457, p < 0.01) and deep CMBs numbers (β = -0.352, p < 0.01) as the predictors of attention/executive function, which explained 45.2% of the total variance. Periventricular MD was the independent predictor for either memory (β = -0.314, p < 0.05) or visuo-spatial function (β = -0.375, p < 0.01); however, only small proportion of variance could be accounted for (9.8% and 12.4%, respectively). Language was not found to be correlated with any of the MRI parameters. No correlation was found between brain atrophic indices and any of the cognitive measures. Arteriosclerotic CMBs and periventricular white matter disintegrity seem to be independent MRI surrogated markers in the early stage of cognitive impairment in SVD.

Disruption of rich club organisation in cerebral small vessel disease.

Cerebral small vessel disease (SVD) is an important cause of vascular cognitive impairment. Recent studies have demonstrated that structural connectivity of brain networks in SVD is disrupted. However, little is known about the extent and location of the reduced connectivity in SVD. Here they investigate the rich club organisation—a set of highly connected and interconnected regions—and investigate whether there is preferential rich club disruption in SVD. Diffusion tensor imaging (DTI) and cognitive assessment were performed in a discovery sample of SVD patients (n = 115) and healthy control subjects (n = 50). Results were replicated in an independent dataset (49 SVD with confluent WMH cases and 108 SVD controls) with SVD patients having a similar SVD phenotype to that of the discovery cases. Rich club organisation was examined in structural networks derived from DTI followed by deterministic tractography. Structural networks in SVD patients were less dense with lower network strength and efficiency. Reduced connectivity was found in SVD, which was preferentially located in the connectivity between the rich club nodes rather than in the feeder and peripheral connections, a finding confirmed in both datasets. In discovery dataset, lower rich club connectivity was associated with lower scores on psychomotor speed (β = 0.29, P < 0.001) and executive functions (β = 0.20, P = 0.009). These results suggest that SVD is characterized by abnormal connectivity between rich club hubs in SVD and provide evidence that abnormal rich club organisation might contribute to the development of cognitive impairment in SVD. Hum Brain Mapp 38:1751–1766, 2017. © 2017 Wiley Periodicals, Inc.

White Matter Microstructural Damage on Diffusion Tensor Imaging in Cerebral Small Vessel Disease

Cerebral small vessel disease (SVD) is a major health problem for its contribution to ≈45% of dementias, and about a fifth of all strokes worldwide, representing one of the most important causes of disabilities.1 The term SVD refers to a group of pathological processes with various etiologies that affect the small arteries, arterioles, venules, and capillaries of the brain. The most common forms are age- and hypertension-related SVD and cerebral amyloid angiopathy (CAA).2 Vessel wall changes may lead to both ischemic and hemorrhagic consequences: (1) a state of chronic hypoperfusion or vascular dysfunction responsible for incomplete infarction,3,4 (2) acute focal necrosis (lacunar infarct), or (3) vessel rupture manifesting as hemorrhagic SVD. The clinical consequences of SVD are various and mainly consist of cognitive, mood, and motor dysfunctions leading to functional disability in the late stages of the disease. Magnetic resonance imaging (MRI) has become crucial in the diagnosis of SVD enabling the evaluation of the disease progression both in the clinical and research settings. However, correlations between clinical features of SVD and conventional MRI measures have been partially discordant. Some authors suggested that the cumulative effect of SVD lesions, rather than the individual lesions themselves determines the clinical impact,5 whereas others suggested that the presence and severity of alterations nonvisible on conventional MRI might also be an explanation.6 In the past decade, diffusion tensor imaging (DTI) has been increasingly used for the evaluation of SVD patients because it is sensitive to tissue damage and can show abnormalities in both areas of white matter hyperintensities (WMH) and in normal appearing WM (NAWM). Despite the high sensitivity in detecting cerebral damage, DTI has a low specificity in detecting the underlying cause. In fact, we can only infer that DTI changes reflect a loss of WM …

Clinical efficacy of Yangxueqingnao granule improve cerebral small vessel disease cognitive impairment

Objective To explore the effect of Yangxueqingnao granule in treatment of cerebral small vessel disease (SVD) patients with mild cognitive dysfunction (MCI). Methods 52 patients with SVD related MCI were selected.They were treated with Yangxueqingnao granule, each 4.0 g, 3 times a day, 3 months for a course of treatment.Montreal cognitive scale (MoCA), simple mental state scale (MMSE) and event related potential (P300) were detected before and after treatment, and the clinical effect was observed. Results After a course of treatment by Yangxueqingnao granule, the cognitive function and memory of 52 patients were improved to some extent.In addition to the attention of an MoCA meter to a foreign project[Visual space: before taking the medicine (2.92±0.26)points, after taking the medicine (3.25±0.66)points; Named: before taking the medicine (2.26±0.70)points, after taking the medicine(2.92±0.49)points; Language: before taking the medicine (1.47±0.70)points, after taking the medicine (2.17±0.98)points; Abstraction: before taking the medicine (0.45±0.38)points, after taking the medicine (0.68±0.63)points; Delayed recall: before taking the medicine (1.67±0.74)points, after taking the medicine (2.52±1.50)points; Directional: before taking the medicine (4.73±0.35)points, after taking the medicine (5.52±0.57)points ]and total score[Before taking the medicine (18.75±0.66)points, after taking the medicine (19.12±1.45)points], the differences were statistically significant (the total score: t=7.56, P=0.000; Visual space: t=5.86, P=0.002; Named: t=5.42, P=0.000; Be careful: t=1.23, P=0.121; Language: t=4.52, P=0.000; Abstraction: t=2.65, P=0.001; Delayed memory: t=7.96, P=0.000). While the total score of MMSE scale[before taking the medicine (25.36±1.89)points, after taking the medicine (28.53±2.91)points], memory [before taking the medicine (2.64±0.42)points, after taking the medicine (2.75±0.53)points] and recall [before taking the medicine (1.52±0.48)points, after taking the medicine (1.98±0.78)points ], the differences were statistically significant(the total score: t=2.78, Memory: t=1.95, Recall: t=3.43, all P<0.05). P300 before and after treatment[before taking the medicine P300 latency of (389±21)ms, after taking the medicine P300 latency of (341±18)ms)], the difference was significant (t=12.514, P<0.001). Conclusion Yangxueqingnao granule had therapeutic effect in patients with SVD-MCI. Key words: Cerebrovascular trauma; Yangxueqingnao granule; Cognitive disorders

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

Objective:To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment.Methods:A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested.Results:Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed.Conclusions:Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies.

Strategic lacunes and their relationship to cognitive impairment in cerebral small vessel disease

ObjectivesLacunes are an important disease feature of cerebral small vessel disease (SVD) but their relationship to cognitive impairment is not fully understood. To investigate this we determined (1) the relationship between lacune count and total lacune volume with cognition, (2) the spatial distribution of lacunes and the cognitive impact of lacune location, and (3) the whole brain anatomical covariance associated with these strategically located regions of lacune damage.MethodsOne hundred and twenty one patients with symptomatic lacunar stroke and radiological leukoaraiosis were recruited and multimodal MRI and neuropsychological data acquired. Lacunes were mapped semi-automatically and their volume calculated. Lacune location was automatically determined by projection onto atlases, including an atlas which segments the thalamus based on its connectivity to the cortex. Lacune locations were correlated with neuropsychological results. Voxel based morphometry was used to create anatomical covariance maps for these ‘strategic’ regions.ResultsLacune number and lacune volume were positively associated with worse executive function (number p < 0.001; volume p < 0.001) and processing speed (number p < 0.001; volume p < 0.001). Thalamic lacunes, particularly those in regions with connectivity to the prefrontal cortex, were associated with impaired processing speed (Bonferroni corrected p = 0.016). Regions of associated anatomical covariance included the medial prefrontal, orbitofrontal, anterior insular cortex and the striatum.ConclusionLacunes are important predictors of cognitive impairment in SVD. We highlight the importance of spatial distribution, particularly of anteromedial thalamic lacunes which are associated with impaired information processing speed and may mediate cognitive impairment via disruption of connectivity to the prefrontal cortex.

Mechanisms of Cognitive Impairment in Cerebral Small Vessel Disease: Multimodal MRI Results from the St George's Cognition and Neuroimaging in Stroke (SCANS) Study

Cerebral small vessel disease (SVD) is a common cause of vascular cognitive impairment. A number of disease features can be assessed on MRI including lacunar infarcts, T2 lesion volume, brain atrophy, and cerebral microbleeds. In addition, diffusion tensor imaging (DTI) is sensitive to disruption of white matter ultrastructure, and recently it has been suggested that additional information on the pattern of damage may be obtained from axial diffusivity, a proposed marker of axonal damage, and radial diffusivity, an indicator of demyelination. We determined the contribution of these whole brain MRI markers to cognitive impairment in SVD. Consecutive patients with lacunar stroke and confluent leukoaraiosis were recruited into the ongoing SCANS study of cognitive impairment in SVD (n = 115), and underwent neuropsychological assessment and multimodal MRI. SVD subjects displayed poor performance on tests of executive function and processing speed. In the SVD group brain volume was lower, white matter hyperintensity volume higher and all diffusion characteristics differed significantly from control subjects (n = 50). On multi-predictor analysis independent predictors of executive function in SVD were lacunar infarct count and diffusivity of normal appearing white matter on DTI. Independent predictors of processing speed were lacunar infarct count and brain atrophy. Radial diffusivity was a stronger DTI predictor than axial diffusivity, suggesting ischaemic demyelination, seen neuropathologically in SVD, may be an important predictor of cognitive impairment in SVD. Our study provides information on the mechanism of cognitive impairment in SVD.

Brief Memory and Executive Test: evaluation of a new screening test for cognitive impairment due to small vessel disease

cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment (VCI). Despite this, there is a paucity of rapid simple screening tools to identify cognitive impairment in SVD and differentiate it from other common dementia types. to validate a new screening test for cognitive impairment in SVD, the Brief Memory and Executive Test (BMET) battery, and examine its ability to detect SVD and differentiate it from Alzheimer's disease (AD). 45 patients with SVD, 27 patients with AD and 80 normal controls. the BMET includes brief tests of executive functioning and processing speed, with comparative tests of memory and orientation. Group discrimination was calculated using discriminant function analysis. the BMET took an average of 10min to administer. It showed high sensitivity (91%) and specificity (85%) in differentiating SVD patients with cognitive impairment from AD patients. As a comparison the mini-mental state examination had lower sensitivity (63%) and specificity (62%). the BMET is a simple and quick to administer clinical tool for the detection of VCI in SVD and its differentiation from AD impairment. Further multicentre studies are required to evaluate and compare it with other existing screening tests.