Correlation between White Matter Hyperintensities Related Gray Matter Volume and Cognition in Cerebral Small Vessel Disease

Automatic detection of cognitive impairment in patients with white matter hyperintensity and causal analysis of related factors using artificial intelligence of MRI

PURPOSE

White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH patients and to analyze the causal relationships among cognitive impairment and related factors.

MATERIALS AND METHODS

A total of 79 WMH patients from hospital 1 were randomly divided into a training set (62 patients) and a testing set (17 patients). Additionally, 29 patients from hospital 2 were included as an independent testing set. All participants underwent formal neuropsychological assessments to determine cognitive status. Automated identification and segmentation of WMH were conducted using VB-net, with extraction of radiomics features from cortex, white matter, and nuclei. Four machine learning classifiers were trained on the training set and validated on the testing set to detect cognitive impairment. Model performances were evaluated and compared. Causal analyses were conducted among cortex, white matter, nuclei alterations, and cognitive impairment.

RESULTS

Among the models, the logistic regression (LR) model based on white matter features demonstrated the highest performance, achieving an AUC of 0.819 in the external test dataset. Causal analyses indicated that age, education level, alterations in cortex, white matter, and nuclei were causal factors of cognitive impairment.

CONCLUSION

The LR model based on white matter features exhibited high accuracy in detecting cognitive impairment in WMH patients. Furthermore, the possible causal relationships among alterations in cortex, white matter, nuclei, and cognitive impairment were elucidated.

Quantifying neuroinflammation within deep gray matter in small vessel disease using diffusion tensor based free-water imaging: a longitudinal study

Purpose

Employing free water (FW) imaging, a cutting-edge diffusion MRI technique, we assessed neuroinflammation within deep gray matter (DGM) in small vessel disease (SVD) over 1-2 years.

Method

One hundred and seventy SVD patients and 21 healthy controls (HCs) underwent MRI scans and neuropsychological evaluations at baseline. These patients were then categorized into two groups: 67 displayed no cognitive impairment (NCI), while 103 exhibited vascular mild cognitive impairment (VaMCI). A follow-up study 1-2 years later included 23 from the NCI group and 28 from the VaMCI group. Calculation of FW values within DGM facilitated both cross-sectional and longitudinal analysis, revealing partial correlations between FW value changes and cognitive function alternations.

Results

Baseline examinations disclosed significant differences in DGM FW values among the three participant groups. We found increased mean FW values in the left pulvinar (Pul), bilateral lateral nuclei (LN) and bilateral internal medullary lamina of the thalamus in VaMCI participants compared with their NCI counterparts in longitudinal analysis. Notably, negative associations emerged between the FW value changes in the left Pul and the right LN of the thalamus and MoCA score changes in the VaMCI group over 1-2 years.

Conclusions

These findings support the hypothesis that increased FW value is present at the preclinical stage of SVD and remains persistent during the early course of the disease, potentially acting as the biomarker for the mechanism of underlying cognitive decline in SVD.

The thalamic covariance network is associated with cognitive deficits in patients with cerebral small vascular disease

OBJECTIVE

Abnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico-cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI).

METHODS

We performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD-CI), 85 patients without CI (CSVD-NC), and 108 healthy controls using source-based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population.

RESULTS

The results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD-CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD-NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier.

INTERPRETATION

Our findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients.

GABA in the anterior cingulate cortex mediates the association of white matter hyperintensities with executive function: a magnetic resonance spectroscopy study

White matter hyperintensities (WMH) and gamma-aminobutyric acid (GABA) are associated with executive function. Multiple studies suggested cortical alterations mediate WMH-related cognitive decline. The aim of this study was to investigate the crucial role of cortical GABA in the WMH patients. In the 87 WMH patients (46 mild and 41 moderate to severe) examined in this study, GABA levels in the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) assessed by the Meshcher-Garwood point resolved spectroscopy (MEGA-PRESS) sequence, WMH volume and executive function were compared between the two groups. Partial correlation and mediation analyses were carried out to examine the GABA levels in mediating the association between WMH volume and executive function. Patients with moderate to severe WMH had lower GABA+/Cr in the ACC (p = 0.034) and worse executive function (p = 0.004) than mild WMH patients. In all WMH cases, the GABA+/Cr levels in the ACC mediated the negative correlation between WMH and executive function (ab: effect = -0.020, BootSE = 0.010, 95% CI: -0.042 to -0.004). This finding suggested GABA+/Cr levels in the ACC might serve as a protective factor or potential target for preventing the occurrence and progression of executive function decline in WMH people.

Alzheimer's Related Neurodegeneration Mediates Air Pollution Effects on Medial Temporal Lobe Atrophy

Exposure to ambient air pollution, especially particulate matter with aerodynamic diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2), are environmental risk factors for Alzheimer's disease and related dementia. The medial temporal lobe (MTL) is an important brain region subserving episodic memory that atrophies with age, during the Alzheimer's disease continuum, and is vulnerable to the effects of cerebrovascular disease. Despite the importance of air pollution it is unclear whether exposure leads to atrophy of the MTL and by what pathways. Here we conducted a longitudinal study examining associations between ambient air pollution exposure and MTL atrophy and whether putative air pollution exposure effects resembled Alzheimer's disease-related neurodegeneration or cerebrovascular disease-related neurodegeneration. Participants included older women (n = 627; aged 71-87) who underwent two structural brain MRI scans (MRI-1: 2005-6; MRI-2: 2009-10) as part of the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Regionalized universal kriging was used to estimate annual concentrations of PM2.5 and NO2 at residential locations aggregated to 3-year averages prior to MRI-1. The outcome was 5-year standardized change in MTL volumes. Mediators included voxel-based MRI measures of the spatial pattern of neurodegeneration of Alzheimer's disease (Alzheimer's disease pattern similarity scores [AD-PS]) and whole-brain white matter small-vessel ischemic disease (WM-SVID) volume as a proxy of global cerebrovascular damage. Structural equation models were constructed to examine whether the associations between exposures with MTL atrophy were mediated by the initial level or concurrent change in AD-PS score or WM-SVID while adjusting for sociodemographic, lifestyle, clinical characteristics, and intracranial volume. Living in locations with higher PM2.5 (per interquartile range [IQR]=3.17μg/m3) or NO2 (per IQR=6.63ppb) was associated with greater MTL atrophy (βPM2.5 = -0.29, 95% confidence interval [CI]=[-0.41,-0.18]; βNO2 =-0.12, 95%CI=[-0.23,-0.02]). Greater PM2.5 was associated with larger increases in AD-PS (βPM2.5 = 0.23, 95%CI=[0.12,0.33]) over time, which partially mediated associations with MTL atrophy (indirect effect= -0.10; 95%CI=[-0.15, -0.05]), explaining approximately 32% of the total effect. NO2 was positively associated with AD-PS at MRI-1 (βNO2=0.13, 95%CI=[0.03,0.24]), which partially mediated the association with MTL atrophy (indirect effect= -0.01, 95% CI=[-0.03,-0.001]). Global WM-SVID at MRI-1 or concurrent change were not significant mediators between exposures and MTL atrophy. Findings support the mediating role of Alzheimer's disease-related neurodegeneration contributing to MTL atrophy associated with late-life exposures to air pollutants. Alzheimer's disease-related neurodegeneration only partially explained associations between exposure and MTL atrophy suggesting the role of multiple neuropathological processes underlying air pollution neurotoxicity on brain aging.

Altered brain spontaneous activity in patients with cerebral small vessel disease using the amplitude of low-frequency fluctuation of different frequency bands

Background

Previous studies showed that cerebral small vessel disease (cSVD) is a leading cause of cognitive decline in elderly people and the development of Alzheimer's disease. Although brain structural changes of cSVD have been documented well, it remains unclear about the properties of brain intrinsic spontaneous activity in patients with cSVD.

Methods

We collected resting-state fMRI (rs-fMRI) and T1-weighted 3D high-resolution brain structural images from 41 cSVD patients and 32 healthy controls (HC). By estimating the amplitude of low-frequency fluctuation (ALFF) under three different frequency bands (typical band: 0.01-0.1 Hz; slow-4: 0.027-0.073 Hz; and slow-5: 0.01-0.027 Hz) in the whole-brain, we analyzed band-specific ALFF differences between the cSVD patients and controls.

Results

The cSVD patients showed uniformly lower ALFF than the healthy controls in the typical and slow-4 bands (pFWE < 0.05). In the typical band, cSVD patients showed lower ALFF involving voxels of the fusiform, hippocampus, inferior occipital cortex, middle occipital cortex, insula, inferior frontal cortex, rolandic operculum, and cerebellum compared with the controls. In the slow-4 band, cSVD patients showed lower ALFF involving voxels of the cerebellum, hippocampus, occipital, and fusiform compared with the controls. However, there is no significant between-group difference of ALFF in the slow-5 band. Moreover, we found significant "group × frequency" interactions in the left precuneus.

Conclusion

Our results suggested that brain intrinsic spontaneous activity of cSVD patients was abnormal and showed a frequency-specific characteristic. The ALFF in the slow-4 band may be more sensitive to detecting a malfunction in cSVD patients.

Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease

This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (Eglob/Eloc) and decreased shortest path lengths (Lp), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (Eglob, Eloc, and Lp) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.

Apathy is associated with striatal atrophy and cognitive impairment in cerebral small vessel disease

BACKGROUND

Apathy has been considered a common neuropsychiatric symptom and an important contributor to cognitive impairment in cerebral small vessel disease (SVD). However, the mechanism leading to apathy in SVD and the process whereby apathy promotes cognitive impairments remain largely unknown. We aimed to explore the relationship between apathy, cognition, and structural changes of deep grey matter (DGM) in SVD patients.

METHODS

Participants were screened for SVD, completed assessments of apathy cognition, underwent magnetic resonance imaging (MRI) scanning, and then stratified into apathy and non-apathy groups. We used region of interest (ROI)-based, voxel-based volume, and vertex-based shape analyses to compare DGM structures between study groups. Using linear regression analysis, we examined the association between apathy, structural changes, and cognition, followed by a mediation analysis of these factors.

RESULTS

A total of sixty-four SVD participants were included, with thirty in the apathy group and thirty-four in the non-apathy group. Intergroup comparison showed significantly lower volumes in bilateral caudate, right putamen, and pallidum and smaller vertex-based shapes in the right caudate and pallidum in participants with apathy compared to those without apathy. Apathy was associated with the striatal atrophy (i.e., lower volumes and smaller shape) and independently contributed to cognitive impairments in SVD. However, the above structural differences did not mediate the association between apathy and cognitive impairments.

CONCLUSION

These results highlight the important role of striatal atrophy in apathy in SVD and call for additional studies to explore the relationship between apathy, cognition, and DGM.

[Predictors of the efficacy of non-drug treatments for non-dementia vascular cognitive impairment]

OBJECTIVE

To study the predictors of the efficacy of non-drug multimodal therapy in the treatment of mild vascular cognitive impairment.

MATERIAL AND METHODS

Thirty patients with mild vascular cognitive impairment, under the supervision of their physician, received a 1-month non-drug treatment program including cognitive training, detailed recommendations for physical activity, and dietary planning.

RESULTS

After the end of the course of treatment, improvements in the MoCa test were achieved by 22 patients (73%), which made up Group 1. In the remaining 8 patients, the treatment had no effect (Group 2). In Group 1, the dynamics of the MoCa test averaged 1.7±0.9, in the Group 2 it was (-0.4)±0.5. Patients of Group 1 had a significantly lower level of education (10.9±2.3) compared with Group 2 (14.9±2.0), a higher initial MoCa score, and a less pronounced white matter lesion on the Fazekas scale. After the regression analysis, the level of education (B -0.999, p<0.05) and white matter damage (B -2.761, p<0.01) were significant predictors.

CONCLUSION

When using non-drug multimodal therapy in the treatment of mild vascular cognitive impairment, lower levels of education and a lower degree of white matter vascular damage are reliable predictors of treatment efficacy.

White matter integrity mediates the associations between white matter hyperintensities and cognitive function in patients with silent cerebrovascular diseases

OBJECTIVE

To evaluate the relationships between cognitive function and white matter hyperintensity volume (WMHV) in patients with silent cerebrovascular disease and to investigate whether white matter integrity or brain atrophy play a role in this association.

METHODS

Automated Fiber Quantification and Voxel- based morphometry were used to track and identify the integrity of 20 well-defined white matter tracts and to measure the gray matter volume (GMV). A linear regression model was applied for examining the associations between cognitive function and WMHV and mediation analysis was used to identify the roles of white matter integrity or GMV in the influence of WMHV on cognitive function.

RESULTS

Two hundred and thirty-six individuals were included for analysis. Executive function was linearly associated with fractional anisotropy (FA) of the right interior frontal occipital fasciculus (IFOF) (β = 0.193; 95% CI, 0.126 to 1.218) and with WMHV (β = -0.188; 95% CI, -0.372 to -0.037). Information processing speed was linearly associated with WMHV (β = -0.357; 95% CI, -0.643 to -0.245), FA of the right anterior thalamic radiation (ATR) (β = 0.207; 95% CI, 0.116 to 0.920), and FA of the left superior longitudinal fasciculus (SLF) (β = 0.177; 95% CI, 0.103 to 1.315). The relationship between WMHV and executive function was mediated by FA of the right IFOF (effect size = -0.045, 95% CI, -0.015 to -0.092). Parallel mediation analysis showed that the association between WMHV and information processing speed was mediated by FA of the right ATR (effect size = -0.099, 95% CI, -0.198 to -0.038) and FA of the left SLF (effect size = -0.038, 95% CI, -0.080 to -0.003).

CONCLUSION

These findings suggest a mechanism by which WMH affects executive function and information processing speed by impairing white matter integrity. This may be helpful in providing a theoretical basis for rehabilitation strategies of cognitive function in patients with silent cerebrovascular diseases.

Cerebral Small Vessel Disease: A Bibliometric Analysis

Cerebral small vessel disease is a common neurological disease, and its incidence is increasing year by year worldwide. In recent years, research on cerebral small vessel disease has gained more and more attention. Our research aims to visualize publications to identify the hotspots and frontiers of cerebral small vessel disease research, and to provide reference and guidance for further research. Publications related to cerebral small vessel disease were searched from the Web of Science Core Collection and screened according to inclusion criteria. CiteSpace 5.8.R3 was used to evaluate and visualize results, including generating web maps and analyzing annual publications, countries, institutions, bibliographic and co-cited references, and keywords; in this article, we use CiteSpace and VOSviewer for the 2012 Cerebral small vessel disease and bibliometric analysis from January 1, 2022 to April 30, 2022. A total of 3037 papers related to cerebral small vessel disease were retrieved, and the number of published papers showed a steady upward trend. Among them, Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration, the most symbolic references in the field of cerebral small vessel disease have been cited a total of 438 times. Stroke is the most active journal (227 articles) and USA publishes up to 800 articles. Harvard Med SchUniv Edinburgh (133 papers) and Charidimou (85 papers) are the institutions and authors who have made the most contributions in this field, respectively. Among the keywords, most of them are related to the pathogenesis of cerebral small vessel disease. After 2018, gut-brain axis and cortex are the keywords with the strongest number of cited outbreaks. There is increasing evidence that cerebral small vessel disease is a research frontier and may remain a research hotspot in the future.

Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients

Background

Reliable and individualized biomarkers are crucial for identifying early cognitive impairment in subcortical small-vessel disease (SSVD) patients. Personalized brain age prediction can effectively reflect cognitive impairment. Thus, the present study aimed to investigate the association of brain age with cognitive function in SSVD patients and assess the potential value of brain age in clinical assessment of SSVD.

Materials and methods

A prediction model for brain age using the relevance vector regression algorithm was developed using 35 healthy controls. Subsequently, the prediction model was tested using 51 SSVD patients [24 subjective cognitive impairment (SCI) patients and 27 mild cognitive impairment (MCI) patients] to identify brain age-related imaging features. A support vector machine (SVM)-based classification model was constructed to differentiate MCI from SCI patients. The neurobiological basis of brain age-related imaging features was also investigated based on cognitive assessments and oxidative stress biomarkers.

Results

The gray matter volume (GMV) imaging features accurately predicted brain age in individual patients with SSVD (R² = 0.535, p < 0.001). The GMV features were primarily distributed across the subcortical system (e.g., thalamus) and dorsal attention network. SSVD patients with age acceleration showed significantly poorer Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores. The classification model based on GMV features could accurately distinguish MCI patients from SCI patients (area under the curve = 0.883). The classification outputs of the classification model exhibited significant associations with MoCA scores, Trail Making Tests A and B scores, Stroop Color and Word Test C scores, information processing speed total scores, and plasma levels of total antioxidant capacity in SSVD patients.

Conclusion

Brain age can be accurately quantified using GMV imaging data and shows potential clinical value for identifying early cognitive impairment in SSVD patients.

Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses

Purpose

The objective of this study was to evaluate whether altered gray matter volume (GMV) and white matter volume (WMV) are associated with the presence of cerebral microbleeds (CMBs) in cerebral small vessel disease (CSVD).

Materials and Methods

In this study, we included 26 CSVD patients with CMBs (CSVD-c), 43 CSVD patients without CMBs (CSVD-n) and 39 healthy controls. All participants underwent cognitive assessment testing. Both univariate analysis and multivariate pattern analysis (MVPA) approaches were applied to investigate differences in brain morphometry among groups.

Results

In univariate analysis, GMV and WMV differences were compared among groups using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL). Compared to healthy controls, the CSVD-c group and CSVD-n group showed significantly lower GMV than the control group in similar brain clusters, mainly including the right superior frontal gyrus (medial orbital), left anterior cingulate gyrus, right inferior frontal gyrus (triangular part) and left superior frontal gyrus (medial), while the CSVD-n group also showed significantly lower WMV in the cluster of the left superior frontal gyrus (medial). No significant GMV or WMV differences were found between the CSVD-c group and the CSVD-n group. Specifically, we applied the multiple kernel learning (MKL) technique in MVPA to combine GMV and WMV features, yielding an average of >80% accuracy for three binary classification problems, which was a considerable improvement over the individual modality approach. Consistent with the univariate analysis, the MKL weight maps revealed default mode network and subcortical region damage associated with CSVD compared to controls. On the other hand, when classifying the CSVD-c group and CSVD-n group in the MVPA analysis, we found that some WMVs were highly weighted regions (left olfactory cortex and right middle frontal gyrus), which hinted at the presence of different white matter alterations in the CSVD-c group.

Conclusion

Our findings not only suggested that the localized alterations in GMV and WMV appeared to be associated with the pathophysiology of CSVD but also indicated that altered brain morphometry could be a potential discriminative pattern to detect CSVD at the individual level.

Impaired functional network properties contribute to white matter hyperintensity related cognitive decline in patients with cerebral small vessel disease

Background

White matter hyperintensity (WMH) is one of the typical neuroimaging manifestations of cerebral small vessel disease (CSVD), and the WMH correlates closely to cognitive impairment (CI). CSVD patients with WMH own altered topological properties of brain functional network, which is a possible mechanism that leads to CI. This study aims to identify differences in the characteristics of some brain functional network among patients with different grades of WMH and estimates the correlations between these different brain functional network characteristics and cognitive assessment scores.

Methods

110 CSVD patients underwent 3.0 T Magnetic resonance imaging scans and neuropsychological cognitive assessments. WMH of each participant was graded on the basis of Fazekas grade scale and was divided into two groups: (A) WMH score of 1–2 points (n = 64), (B) WMH score of 3–6 points (n = 46). Topological indexes of brain functional network were analyzed using graph-theoretical method. T-test and Mann–Whitney U test was used to compare the differences in topological properties of brain functional network between groups. Partial correlation analysis was applied to explore the relationship between different topological properties of brain functional networks and overall cognitive function.

Results

Patients with high WMH scores exhibited decreased clustering coefficient values, global and local network efficiency along with increased shortest path length on whole brain level as well as decreased nodal efficiency in some brain regions on nodal level (p < 0.05). Nodal efficiency in the left lingual gyrus was significantly positively correlated with patients' total Montreal Cognitive Assessment (MoCA) scores (p < 0.05). No significant difference was found between two groups on the aspect of total MoCA and Mini-mental State Examination (MMSE) scores (p > 0.05).

Conclusion

Therefore, we come to conclusions that patients with high WMH scores showed less optimized small-world networks compared to patients with low WMH scores. Global and local network efficiency on the whole-brain level, as well as nodal efficiency in certain brain regions on the nodal level, can be viewed as markers to reflect the course of WMH.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00769-7.

Verifying small vessel disease and mild cognitive impairment with a computational мagnetic resonance imaging analysis

Aim. To illustrate capabilities of the computational brain мagnetic resonance imaging (MRI) analyses on a small vessel disease (SVD) sample. Materials and methods. Thirty-one patients underwent brain MRI in standard sequences. We used Lesion Segmentation Tool to assess white matter hyperintensities (WMH) volume and Computational Anatomy Toolbox to calculate cortical thickness. Both software plug-ins work within the Statistical Parametric Mapping 12 software for MATLAB. We also performed cognitive testing with the Montreal Cognitive Assessment test and tests to detect hippocampal and executive domain dysfunction. Results. Sixteen patients had mild vascular cognitive impairment. The Median Fazekas scale score was 2 and 2 points. The median intracranial volume fraction occupied by the WMH was 0.07%. It correlated with the executive domain performance but not with cortical thickness. Cortical thickness within several clusters of the prefrontal complex and temporal lobe correlated with performance in cognitive tests. Among the computed MRI markers of the SVD, the occipital lobe cortical thickness had an area under the curve of 70%, and among the cognitive tests, the cued recall measure had an area under the curve of 73.8% to detect mild cognitive impairment. Conclusion. The abovementioned metrics is a valuable tool to objectively estimate white and grey matter state in patients with small vessel disease. Performing those analyses helped to assess SVD properties in the sample further and register new correlations between MRI and cognitive markers.

Altered Spontaneous Brain Activity Related to Neurologic Dysfunction in Patients With Cerebral Small Vessel Disease

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.

Polygenic coronary artery disease association with brain atrophy in the cognitively impaired

While a number of low-frequency genetic variants of large effect size have been shown to underlie both cardiovascular disease and dementia, recent studies have highlighted the importance of common genetic variants of small effect size, which, in aggregate, are embodied by a polygenic risk score. We investigate the effect of polygenic risk for coronary artery disease on brain atrophy in Alzheimer's disease using whole-brain volume and put our findings in context with the polygenic risk for Alzheimer's disease and presumed small vessel disease as quantified by white-matter hyperintensities. We use 730 subjects from the Alzheimer's disease neuroimaging initiative database to investigate polygenic risk score effects (beyond APOE) on whole-brain volumes, total and regional white-matter hyperintensities and amyloid beta across diagnostic groups. In a subset of these subjects (N = 602), we utilized longitudinal changes in whole-brain volume over 24 months using the boundary shift integral approach. Linear regression and linear mixed-effects models were used to investigate the effect of white-matter hyperintensities at baseline as well as Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score on whole-brain atrophy and whole-brain atrophy acceleration, respectively. All genetic associations were examined under the oligogenic (P = 1e-5) and the more variant-inclusive polygenic (P = 0.5) scenarios. Results suggest no evidence for a link between the polygenic risk score and markers of Alzheimer's disease pathology at baseline (when stratified by diagnostic group). However, both Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score were associated with longitudinal decline in whole-brain volume (Alzheimer's disease-polygenic risk score t = 3.3, P _FDR = 0.007 over 24 months in healthy controls) and surprisingly, under certain conditions, whole-brain volume atrophy is statistically more correlated with cardiac polygenic risk score than Alzheimer's disease-polygenic risk score (coronary artery disease-polygenic risk score t = 2.1, P _FDR = 0.04 over 24 months in the mild cognitive impairment group). Further, in our regional analysis of white-matter hyperintensities, Alzheimer's disease-polygenic risk score beyond APOE is predictive of white-matter volume in the occipital lobe in Alzheimer's disease subjects in the polygenic regime. Finally, the rate of change of brain volume (or atrophy acceleration) may be sensitive to Alzheimer's disease-polygenic risk beyond APOE in healthy individuals (t = 2, P = 0.04). For subjects with mild cognitive impairment, beyond APOE, a more inclusive polygenic risk score including more variants, shows coronary artery disease-polygenic risk score to be more predictive of whole-brain volume atrophy, than an oligogenic approach including fewer larger effect size variants.

Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease

BACKGROUND

Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH).

METHODS

Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation.

RESULTS

Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single-leg stance, timed up-and-go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant-evaluated IADL, but not on self-evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up-and-go performance.

CONCLUSION

The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment.

Decline in executive function in patients with white matter hyperintensities from the static and dynamic perspectives of amplitude of low-frequency fluctuations

Cognitive impairments are characteristics of patients with white matter hyperintensities (WMHs), and hypoperfusion is currently a relatively recognized mechanism of WMHs. Brain activity is closely coupled to the regulation of local blood flow. This study aimed to investigate the abnormal local brain activity of patients with WMHs from the viewpoint of the static amplitude of low-frequency fluctuations (sALFF) and dynamic amplitude of low-frequency fluctuations (dALFF). Seventy-four patients with WMHs and 35 healthy controls (HCs) were included. Based on the Fazekas scale, patients with WMHs were further divided into a mild WMH group (n = 33, Fazekas score 1-2) and moderate-severe WMH group (n = 41, Fazekas score 3-6). The sALFF and dALFF values were calculated separately and neuropsychological tests including the Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Trail Making Test (TMT), and Boston Naming Test (BNT) were completed by all participants. Patients with WMHs showed increased sALFF and dALFF values in the bilateral thalamus and decreased performance in the MoCA test, AVLT-immediate, AVLT-delay, AVLT-recognition, TMT-A, and BNT. The dALFF values in the bilateral thalamus was correlated with the MoCA in HCs. The sALFF values in the bilateral thalamus correlated with TMT-B in patients with WMHs. Patients with WMHs showed abnormal brain activity and decreased functional stability of the bilateral thalamus, which may be a potential mechanism of decreased executive function.

Relation of a Socioeconomic Index with Cognitive Function and Neuroimaging in Hypertensive Individuals

BACKGROUND

Socioeconomic factors are important contributors to brain health. However, data from developing countries (where social inequalities are the most prominent) are still scarce, particularly about hypertensive individuals.

OBJECTIVE

To evaluate the relationship between socioeconomic index, cognitive function, and cortical brain volume, as well as determine whether white matter hyperintensities are mediators of the association of the socioeconomic index with cognitive function in hypertensive individuals.

METHODS

We assessed 92 hypertensive participants (mean age = 58±8.6 years, 65.2%female). Cognitive evaluation and neuroimaging were performed and clinical and sociodemographic data were collected using questionnaires. A socioeconomic index was created using education, income, occupation (manual or non-manual work), and race. The associations of the socioeconomic index with cognitive performance and brain volume were investigated using linear regression models adjusted for age, sex, time of hypertension since diagnosis, and comorbidities. A causal mediation analysis was also conducted.

RESULTS

Better socioeconomic status was associated with better visuospatial ability, executive function, and global cognition. We found associations between a better socioeconomic index and a higher parietal lobe volume. White matter hyperintensities were also not mediators in the relationship between the socioeconomic index and cognitive performance.

CONCLUSION

Socioeconomic disadvantages are associated with worse cognitive performance and brain volume in individuals with hypertension.