The effect of the total small vessel disease burden on the structural brain network

Dynamic Changes in Long-Standing Multiple Sclerosis Revealed by Longitudinal Structural Network Analysis Using Diffusion Tensor Imaging

BACKGROUND AND PURPOSE

DTI can be used to derive conventional diffusion measurements, which can measure WM abnormalities in multiple sclerosis. DTI can also be used to construct structural brain networks and derive network measurements. However, few studies have compared their sensitivity in detecting brain alterations, especially in longitudinal studies. Therefore, in this study, we aimed to determine which type of measurement is more sensitive in tracking the dynamic changes over time in MS.

MATERIALS AND METHODS

Eighteen patients with MS were recruited at baseline and followed up at 6 and 12 months. All patients underwent MR imaging and clinical evaluation at 3 time points. Diffusion and network measurements were derived, and their brain changes were evaluated.

RESULTS

None of the conventional DTI measurements displayed statistically significant changes during the follow-up period; however, the nodal degree, nodal efficiency, and nodal path length of the left middle frontal gyrus and bilateral inferior frontal gyrus, opercular part showed significant longitudinal changes between baseline and at 12 months, respectively.

CONCLUSIONS

The nodal degree, nodal efficiency, and nodal path length of the left middle frontal gyrus and bilateral inferior frontal gyrus, opercular part may be used to monitor brain changes over time in MS.

Decreased Local Specialization of Brain Structural Networks Associated with Cognitive Dysfuntion Revealed by Probabilistic Diffusion Tractography for Different Cerebral Small Vessel Disease Burdens

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Multiple Hypointense Vessels are Associated with Cognitive Impairment in Patients with Single Subcortical Infarction

We aimed to explore the relationship between multiple hypointense vessels and cognitive function in patients with single subcortical infarction (SSI) and the role of SSI with different etiological mechanisms in the above relationship. Multiple hypointense vessels were measured by the number of deep medullary veins (DMVs), DMVs score, and cortical veins (CVs) score. The Montreal Cognitive Assessment (MoCA), the Shape Trail Test (STT), and the Stroop Color and Word Test (SCWT) were assessed to evaluate cognitive function. SSI was dichotomized as branch atheromatous disease (BAD) and cerebral small vessel disease (CSVD)-related SSI by whole-brain vessel-wall magnetic resonance imaging. We included a total of 103 acute SSI patients. After adjustments were made for related risk factors of cognitive function, the SSI patients with higher DMVs score were more likely to have longer STT-B (P = 0.001) and smaller STT-B-1 min (P = 0.014), and the SSI patients with higher CVs score were more likely to have shorter STT-A (P = 0.049). In subgroup analysis, we found that the negative relationship between DMVs scores and cognitive function and the positive relationship between CVs scores and cognitive function were significantly stronger in BAD patients. We provided valuable insights into the associations between DMVs, CVs, and multi-domain cognitive impairment in SSI patients, which underscored the necessity to further study the dynamic alterations of venules and their specific influence on post-stroke cognitive impairment.

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease

Background

Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients.

Methods

Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing.

Results

Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm.

Conclusion

The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.

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

Background

Cognitive 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.

Methods

In 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).

Results

The 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.

Conclusions

The 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.

Systematic validation of structural brain networks in cerebral small vessel disease

Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability.Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.

Cerebral Small Vessel Disease and Prognosis in Intracerebral Hemorrhage: A Systematic Review and Meta-analysis of Cohort Studies

BACKGROUND

To investigate whether cerebral small vessel disease (CSVD) markers and the total CSVD burden are associated with functional outcome, mortality, stroke recurrence, and hematoma expansion in patients with spontaneous intracerebral hemorrhage (ICH).

METHODS

Following a previously registered protocol (PROSPERO protocol: CRD42021287743), we systematically searched PubMed, Web of Science, and EMBASE to identify relevant literature up to November 2021. Cohort studies that examined the association between CSVD markers (white matter hyperintensity [WMH], lacune, enlarged perivascular space [EPVS], cerebral microbleed [CMB], and brain atrophy) or CSVD burden and prognosis in patients with ICH were included. The pooled estimates were calculated using random effects models.

RESULTS

Forty-one studies with 19,752 ICH patients were pooled in the meta-analysis. WMH (OR=1.50, 95% CI=1.32 to 1.70), lacune (OR=1.32, 95% CI=1.18 to 1.49), CMB (OR=2.60, 95% CI=1.13 to 5.97) and brain atrophy (OR=2.22, 95% CI=1.48 to 3.31) were associated with worse functional outcome. CSVD markers concerning increased risk of mortality were WMH (OR=1.57, 95% CI=1.38 to 1.79) and brain atrophy (OR=1.84, 95% CI=1.11 to 3.04), while concerning increased risk of stroke recurrence were WMH (OR=1.62, 95% CI=1.28 to 2.04) and lacune (OR=3.00, 95% CI=1.68 to 5.37). EPVS was not related to prognosis. There was a lack of association between CSVD markers and hematoma expansion. CSVD burden increased the risk of worse functional outcome, mortality, and stroke recurrence by 57%, 150%, and 44%, respectively.

CONCLUSIONS

In patients with spontaneous ICH, WMH, lacune, CMB, brain atrophy, and the total CSVD burden are associated with substantially increased risk of worse functional outcome, mortality, or stroke recurrence.

Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy

White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. Two hundred and fifty‐four participants from the Coronary Artery Risk Development in Young Adults study were selected and stratified by WMH burden into Lo‐WMH (mean age = 50 ± 3.5 years) and Hi‐WMH (mean age = 51 ± 3.7 years) groups of equal size. We constructed group‐level covariance networks based on cerebral blood flow (CBF) and gray matter volume (GMV) maps across 74 gray matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo‐ and Hi‐WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no between‐group differences in either CBF or GMV covariance networks. In contrast, we found between‐group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence that WMH‐related network alterations are present at midlife.

Subclinical hypothyroidism is associated with basal ganglia enlarged perivascular spaces and overall cerebral small vessel disease load

Background

The association between subclinical hypothyroidism (SCH) and cerebral small vessel disease (CSVD) in the stroke-free population is currently unclear.

Methods

A total of 354 individuals without a history of stroke were enrolled in this study. Demographic data, medical history, vascular risk factors, carotid arteriosclerosis, and the results of laboratory tests were collated. SCH is defined as an elevation in thyroid-stimulating hormone levels, but with normal free thyroxine levels. Magnetic resonance imaging (MRI) was used to assess 4 markers of CSVD, including white matter hyperintensities (WMHs), lacunes, deep microbleeds, and enlarged perivascular spaces (EPVSs). The overall CSVD load was then ranked using an ordinal scale ranging from 0 to 4. Brain atrophy was measured semi-quantitatively on MRI. A binary logistic regression model was used to explore the association of SCH with each CSVD marker after adjusting for confounding factors. The ordinal regression model was used to explore the association of SCH with CSVD burden and brain atrophy after adjusting for confounding factors.

Results

The mean age of the participants (66.9% males) was 69.4±12.8 years. SCH was observed in 44 (12.4%) participants. MRI findings revealed 13% of cases with lacunes, 6.2% with microbleeds, 50.3% with confluent WMH, and 49.2% with extensive basal ganglia EPVS. Assessment of total CSVD burden showed that 29.1% scored 1, 30.5% scored 2, 6.5% scored 3, and 2.3% scored ≥3. SCH was associated with extensive basal ganglia EPVS [odds ratio (OR) =2.175; 95% confidence interval (CI): 1.075 to 4.401] and total CSVD load (OR =1.879; 95% CI: 1.028 to 3.438). SCH was not associated with advanced brain atrophy.

Conclusions

SCH is associated with the advanced total burden of CSVD and basal ganglia EPVS in the stroke-free population.

A Novel Imaging Biomarker for Cerebral Small Vessel Disease Associated With Cognitive Impairment: The Deep-Medullary-Veins Score

Objective: To explore the biomarkers of cerebral small vessel disease (CSVD) associated with cognitive impairment.

Methods: A total of 69 patients with CSVD were enrolled in the study, and baseline clinical and imaging data were reviewed retrospectively. The following neuroimaging biomarkers of CSVD were identified: high-grade white matter hyperintensity (HWMH), cerebral microbleeds (CMB), enlarged perivascular space (PVS), and lacunar infarct (LI). A total score for CSVD was calculated. The deep medullary veins (DMVs) were divided into six segments according to the regional anatomy. The total DMV score (0–18) was derived from the sum of the scores of the six individual segments, the scores of which ranged from 0 to 3, for a semiquantitative assessment of the DMV that was based on segmental continuity and visibility.

Results: The DMV score, patient age, and total CSVD score were independently associated with the presence or absence of cognitive impairment in patients with CSVD (P < 0.05). By integrating patient age and the total CSVD and DMV scores, the area under the curve of the receiver operating characteristic curve (AUROC) for predicting CSVD associated with cognitive impairment was 0.885, and the sensitivity and specificity were 64.71 and 94.23%, respectively.

Conclusions: The DMV score may be a novel imaging biomarker for CSVD associated with cognitive impairment. The integration of the DMV score with age and total CSVD score should increase the predictive value of the DMV score for CSVD associated with cognitive impairment.

Altered Neurovascular Coupling in Subcortical Ischemic Vascular Disease

Patients with subcortical ischemic vascular disease (SIVD) exhibit a high risk of cognitive impairment that might be caused by neurologic deficits and vascular injuries. However, the mechanism remains unknown. In current study, 24 normal controls (NC) and 54 SIVD patients, including 26 SIVD patients with no cognitive impairment (SIVD-NCI) and 28 SIVD patients with mild cognitive impairment (SIVD-MCI) underwent the resting-state functional MRI (rs-fMRI) and neuropsychological assessments. We combined regional homogeneity (ReHo) and cerebral blood flow (CBF) by using the global ReHo-CBF correlations coefficient and the ReHo/CBF ratio to detect the inner link between neuronal activity and vascular responses. Correlations between the ReHo/CBF ratio and neuropsychological assessments were explored in patients with SIVD. As a result, we identified significantly decreased global ReHo-CBF coupling in the SIVD-NCI group and SIVD- MCI group with respect to the NC. The SIVD-MCI group showed more serious decoupling of the global ReHo-CBF correlation. We also found a significantly abnormal ReHo/CBF ratio predominantly located in cognitive-related brain regions, including the left insula, right middle temporal gyrus, right precuneus, left precentral gyrus, and left inferior parietal lobule but not the supramarginal and angular gyri. The SIVD-MCI group showed more severe disorders of neurovascular coupling than the other two groups. Moreover, the ReHo/CBF ratio in the left precentral gyrus of the SIVD-NCI group exhibited a positive correlation with the MMSE scores. These findings suggested that patients with SIVD show abnormal neurovascular coupling at the early stage of the disease and during disease development. It might be associated with disease severity and cognitive impairment. Neurovascular decoupling in brain may be a possible neuropathological mechanism of SIVD.

Alterations of the Whole Cerebral Blood Flow in Patients With Different Total Cerebral Small Vessel Disease Burden

Background

Cerebral small vessel disease (CSVD) is a common age-related vascular disease of the brain associated with slowly accumulating tissue damage. At present, total CSVD burden score is a commonly used method to evaluate the severity of the disease.

Purpose

To observe whether global and regional cerebral perfusion is related to total CSVD score and to explore global and regional cerebral blood flow (CBF) changes in patients with different degrees of CSVD.

Methods

We collected 130 subjects with different total burden score of CSVD (0 point: 33 subjects, 1 point: 39 subjects, 2 points: 24 subjects, 3 points: 24 subjects, 4 points: 10 subjects). Total CSVD burden score was evaluated by clinically routine sequences (T2WI, T2-FLAIR, T1WI, DWI, and SWAN sequence). Global and regional CBF were calculated and correlation analysis was used to investigate the relationship between total CSVD score and CBF of the whole brain and several brain regions.

Results

The analysis results showed that there was a negative correlation between total CSVD burden score and global CBF (r = −0.33, p = 0.001). Total CSVD burden score also had moderately negative correlations with CBF of almost all the brain regions.

Conclusion

CSVD is a disease that affects the whole brain. With the increase of total CSVD burden score, the global and regional CBF decreased. The CSVD total burden score could be used to evaluate the overall condition of brain perfusion.

Cerebral small vessel disease is associated with gait disturbance among community-dwelling elderly individuals: the Taizhou imaging study

Gait disturbance is considered to be a significant clinical manifestation of cerebral small vessel disease (CSVD). We aimed to investigate the association between different imaging markers of CSVD or total CSVD burden and gait disturbance in a community-dwelling population. In the cross-sectional Taizhou Imaging Study (TIS), 314 participants free of neurological disorders underwent MRI scanning and gait assessment with quantitative wearable devices as well as clinical rating scales. In linear regression, after adjustment for demographics and vascular risks, total CSVD burden was associated with prolonged 3-m walking (β=0.118, P=0.035), shorter stride length (β=-0.106, P=0.042), and poorer Timed-Up-and-Go (TUG) performance (β=0.146, P=0.009). Lacunes were positively associated with 3-m walking (β=0.118, P=0.037) and duration of TUG test (β=0.112, P=0.047). White matter hyperintensities and cerebral microbleeds were associated with prolonged stride time (β=0.134, P=0.024) and increased stance phase time percentage (β=0.115, P=0.038), respectively. Logistic regression revealed that participants with high CSVD burden or more lacunes were more likely to have an impaired gait velocity and an impaired TUG test. These results suggest that total CSVD burden and CSVD imaging markers are associated with gait disturbance among community-dwelling elderly people. Different CSVD imaging markers may cause gait disturbance through different pathways.

Structural brain networks and functional motor outcome after stroke-a prospective cohort study

The time course of topological reorganization that occurs in the structural connectome after an ischaemic stroke is currently not well understood. We aimed to determine the evolution of structural brain networks in stroke patients with motor deficits and relate changes in their global topology to residual symptom burden and functional impairment. In this prospective cohort study, ischaemic stroke patients with supratentorial infarcts and motor symptoms were assessed longitudinally by advanced diffusion MRI and detailed clinical testing of upper extremity motor function at four time points from the acute to the chronic stage. For each time point, structural connectomes were reconstructed, and whole-hemisphere global network topology was quantified in terms of integration and segregation parameters. Using non-linear joint mixed-effects regression modelling, network evolution was related to lesion volume and clinical outcome. Thirty patients were included for analysis. Graph-theoretical analysis demonstrated that, over time, brain networks became less integrated and more segregated with decreasing global efficiency and increasing modularity. Changes occurred in both stroke and intact hemispheres and, in the latter, were positively associated with lesion volume. Greater change in topology was associated with larger residual symptom burden and greater motor impairment 1, 3 and 12 months after stroke. After ischaemic stroke, brain networks underwent characteristic changes in both ipsi- and contralesional hemispheres. Topological network changes reflect the severity of damage to the structural network and are associated with functional outcome beyond the impact of lesion volume.

Leukoaraiosis Is Associated With a Decline in Language Abilities in Chronic Aphasia

Background. A fraction of stroke survivors with chronic aphasia experience declines in language abilities over time, but the reason for this remains unclear. Objective. To evaluate the effect of leukoaraiosis on baseline aphasia severity and long-term changes in aphasia severity. This study directly compares the predictive capacity of leukoaraiosis severity to that of lesion damage, a factor known to account for a substantial proportion of variance in the degree of language impairment and recovery. Methods. Using a longitudinal database of behavioral and neuroimaging data from 35 individuals in the chronic stage of recovery after a single-event left-hemisphere stroke (9 females, mean stroke age = 55.8 ± 9.1 years, mean months poststroke at initial evaluation = 36.3 ± 40.8), we examined 2 lines of inquiry: (1) to what extent does leukoaraiosis severity at initial evaluation predict aphasia severity and (2) to what extent does leukoaraiosis severity at initial evaluation predict longitudinal change in aphasia severity. Participants underwent high-resolution magnetic resonance imaging for the purpose of lesion volume analysis and leukoaraiosis severity rating. Biographical information was also considered. Results. Lesion volume and time poststroke at initial assessment best predicted initial aphasia severity (adjusted R² = 0.37). Leukoaraiosis severity and initial aphasia severity significantly predicted decline in language abilities at follow-up, accounting for approximately one-third of the variance (adjusted R² = 0.33). More severe leukoaraiosis was associated with a 4.3 odds increase of decline. Conclusions. Leukoaraiosis is a significant risk factor for declining language abilities in aphasia and should be considered for better identification of individuals at risk for long-term decline, which can guide clinical decision making.

The efficiency of the brain connectome is associated with cerebrovascular reactivity in persons with white matter hyperintensities

The purpose of this study was to determine the relationship between the organization of the brain connectome and cerebrovascular reactivity (CVR) in persons with white matter hyperintensities. Diffusion tensor and CVR mapping 3T MRI scans were acquired in 31 participants with white matter hyperintensities. In each participant, the connectome was assessed by reconstructing all white matter tracts with tractography and segmenting the whole brain into multiple regions. Graph theory analysis was performed to quantify how effectively tracts connected brain regions by measuring the global and local efficiency of the connectome. CVR in white matter and gray matter was correlated with the global and local efficiency of the connectome, while adjusting for age, gender, and gray matter volume. For comparison, white matter hyperintensity volume was also correlated with global and local efficiency. White matter CVR was positively correlated with the global efficiency (coefficient: 23.3, p = .005) and local efficiency (coefficient: 2850, p = .004) of the connectome. Gray matter CVR was positively correlated with the global efficiency (coefficient: 21.3, p < .001) and local efficiency (coefficient: 2670, p < .001) of the connectome. White matter hyperintensity volume was negatively correlated with global efficiency (coefficient: -0.0002, p = .003) and local efficiency (coefficient: -0.024, p = .003) of the connectome. The association between CVR and the brain connectome suggests that impaired cerebrovascular function may be part of the pathophysiology of the disruption of the brain connectome in persons with white matter hyperintensities.