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

Cerebral small vessel disease and glymphatic system dysfunction in multiple sclerosis: A narrative review

As the multiple sclerosis (MS) population ages, the prevalence of vascular comorbidities increases, potentially accelerating disease progression and brain atrophy. Recent studies highlight the prevalence of cerebral small vessel disease (CSVD) in MS, suggesting a potential link between vascular comorbidities and accelerated disability. CSVD affects the brain's small vessels, often leading to identifiable markers on MRI such as enlarged perivascular spaces (EPVS). EPVS are increasingly recognized also in MS and have been associated with vascular comorbidities, lower percentage of MS-specific perivenular lesions, brain atrophy and aging. The exact sequence of event leading to MRI visible EPVS is yet to be determined, but an impaired perivascular brain fluid drainage appears a possible physiopathological explanation for EPVS in both CSVD and MS. In this context, a dysfunction of the brain fluid clearance system - also known as "glymphatic system" - appears associated in MS to aging, neuroinflammation, and vascular dysfunction. Advanced imaging techniques show an impaired glymphatic function in both MS and CSVD. Additionally, lifestyle factors such as physical exercise, diet, and sleep quality appear to influence glymphatic function, potentially revealing novel therapeutic strategies to mitigate microangiopathy and neuroinflammation in MS. This review underscores the potential role of glymphatic dysfunction in the complex and not-yet elucidated interplay between neuroinflammation and CSVD in MS.

Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease

BACKGROUND

There are currently no effective prediction methods for evaluating the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD).

AIMS

To investigate the risk factors for cognitive dysfunction in patients with CSVD and to construct a risk prediction model.

METHODS

A retrospective study was conducted on 227 patients with CSVD. All patients were assessed by brain magnetic resonance imaging (MRI), and the Montreal Cognitive Assessment (MoCA) was used to assess cognitive status. In addition, the patient's medical records were also recorded. The clinical data were divided into a normal cognitive function group and a cognitive impairment group. A MoCA score < 26 (an additional 1 point for education < 12 years) is defined as cognitive dysfunction.

RESULTS

A total of 227 patients (mean age 66.7 ± 6.99 years) with CSVD were included in this study, of whom 68.7% were male and 100 patients (44.1%) developed cognitive impairment. Age (OR = 1.070; 95% CI = 1.015 ~ 1.128, p < 0.05), hypertension (OR = 2.863; 95% CI = 1.438 ~ 5.699, p < 0.05), homocysteine(HCY) (OR = 1.065; 95% CI = 1.005 ~ 1.127, p < 0.05), lacunar infarct score(Lac_score) (OR = 2.732; 95% CI = 1.094 ~ 6.825, P < 0.05), and CSVD total burden (CSVD_score) (OR = 3.823; 95% CI = 1.496 ~ 9.768, P < 0.05) were found to be independent risk factors for cognitive decline in the present study. The above 5 variables were used to construct a nomogram, and the model was internally validated by using bootstrapping with a C-index of 0.839. The external model validation C-index was 0.867.

CONCLUSIONS

The nomogram model based on brain MR images and clinical data helps in individualizing the probability of cognitive impairment progression in patients with CSVD.

A novel rat model of cerebral small vessel disease based on vascular risk factors of hypertension, aging, and cerebral hypoperfusion

Cerebral small vessel disease (CSVD) is a major cause of vascular cognitive impairment and functional loss in elderly patients. Progressive remodeling of cerebral microvessels due to arterial hypertension or other vascular risk factors, such as aging, can cause dementia or stroke. Typical imaging characteristics of CSVD include cerebral microbleeds (CMB), brain atrophy, small subcortical infarctions, white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS). Nevertheless, no animal models that reflect all the different aspects of CSVD have been identified. Here, we generated a new CSVD animal model using D-galactose (D-gal) combined with cerebral hypoperfusion in spontaneously hypertensive rats (SHR), which showed all the hallmark pathological features of CSVD and was based on vascular risk factors. SHR were hypodermically injected with D-gal (400 mg/kg/d) and underwent modified microcoil bilateral common carotid artery stenosis surgery. Subsequently, neurological assessments and behavioral tests were performed, followed by vascular ultrasonography, electron microscopy, flow cytometry, and histological analyses. Our rat model showed multiple cerebrovascular pathologies, such as CMB, brain atrophy, subcortical small infarction, WMH, and EPVS, as well as the underlying causes of CSVD pathology, including oxidative stress injury, decreased cerebral blood flow, structural and functional damage to endothelial cells, increased blood-brain barrier permeability, and inflammation. The use of this animal model will help identify new therapeutic targets and subsequently aid the development and testing of novel therapeutic interventions. Main process of the study: Firstly, we screened for optimal conditions for mimicking aging by injecting D-gal into rats for 4 and 8 weeks. Subsequently, we performed modified microcoil BCAS intervention for 4 and 8 weeks in rats to screen for optimal hypoperfusion conditions. Finally, based on these results, we combined D-gal for 8 weeks and modified microcoil BCAS for 4 weeks to explore the changes in SHR.

No association between markers of systemic inflammation and endothelial dysfunction with Alzheimer's disease progression: a longitudinal study

INTRODUCTION

Systemic inflammation and endothelial dysfunction are potentially modifiable factors implicated in Alzheimer's disease (AD), which offer potential therapeutic targets to slow disease progression.

METHODS

We investigated the relationship between baseline circulating levels of inflammatory (TNF-α, IL-1ß) and endothelial cell markers (VCAM-1, ICAM-1, E-selectin) and 18-month cognitive decline (ADAS-cog12) in 266 mild-to-moderate AD patients from the NILVAD study. We employed individual growth models to examine associations, potential mediation, and interaction effects while adjusting for confounders.

RESULTS

The average increase in ADAS-cog12 scores over all patients was 8.1 points in 18 months. No significant association was found between the markers and the rate of cognitive decline. Mediation analysis revealed no mediating role for endothelial cell markers, and interaction effects were not observed.

DISCUSSION

Our results do not support the role of systemic inflammation or endothelial dysfunction in progression in persons with AD.

Effect of Menopause Status on Brain Perfusion Hemodynamics

BACKGROUND

The menopause transition is associated with an increasing risk of cerebrovascular disorders. However, the direct effect of menopause status on brain perfusion hemodynamics remains unclear. This study aimed to explore the influence of menopause status on cerebral blood flow (CBF) using arterial spin labeling magnetic resonance imaging.

METHODS

In this cross-sectional study, 185 subjects underwent arterial spin labeling magnetic resonance imaging at a hospital in China between September 2020 and December 2022, including 38 premenopausal women (mean age, 47.74±2.02 years), 42 perimenopausal women (mean age, 50.62±3.15 years), 42 postmenopausal women (mean age, 54.02±4.09 years), and 63 men (mean age, 52.70±4.33 years) of a similar age range. Mean CBF values in the whole brain, gray matter, white matter, cortical gray matter, subcortical gray matter, juxtacortical white matter, deep white matter, and periventricular white matter were extracted. ANCOVA was used to compare mean CBF among the 4 groups, controlling for confounding factors. Student t test was applied to compare mean CBF between the 3 female groups and age-matched males, respectively. Multivariable regression analysis was used to analysis the effect of age, sex, and menopause status on the CBF of the whole brain, gray matter, white matter, and subregions.

RESULTS

Perimenopausal and postmenopausal women showed a higher proportion of white matter hyperintensities compared with the other 2 groups (P<0.001). Premenopausal women exhibited higher CBF in the whole brain, gray matter, white matter, and subregions, compared with perimenopausal, postmenopausal women and men (P≤0.001). Multivariable regression analysis demonstrated significant effect of age and insignificant effect of sex on CBF for all participants. In addition, menopause status and the interaction between age and menopause status on CBF of whole brain, gray matter, white matter, and the subregions were observed in female participants, except for the deep and periventricular white matter regions, with premenopausal women exhibited a slight increase in CBF with age, while perimenopausal and postmenopausal women exhibited declines in CBF with age.

CONCLUSIONS

The current findings suggest that alterations of brain perfusion hemodynamics begin during the perimenopause period, which may be due to the increased burden of white matter hyperintensities.

Deep Medullary Vein and MRI Markers Were Related to Cerebral Hemorrhage Subtypes

BACKGROUND

To explore the performance of deep medullary vein (DMV) and magnetic resonance imaging (MRI) markers in different intracerebral hemorrhage (ICH) subtypes in patients with cerebral small vessel disease (CSVD).

METHODS

In total, 232 cases of CSVD with ICH were included in this study. The clinical and image data were retrospectively analyzed. Patients were divided into hypertensive arteriopathy (HTNA)-related ICH, cerebral amyloid angiopathy (CAA)-related ICH, and mixed ICH groups. The DMV score was determined in the cerebral hemisphere contralateral to the ICH.

RESULTS

The DMV score was different between the HTNA-related and mixed ICH groups (p < 0.01). The MRI markers and CSVD burden score were significant among the ICH groups (p < 0.05). Compared to mixed ICH, HTNA-related ICH diagnosis was associated with higher deep white matter hyperintensity (DWMH) (OR: 0.452, 95% CI: 0.253-0.809, p < 0.05) and high-degree perivascular space (PVS) (OR: 0.633, 95% CI: 0.416-0.963, p < 0.05), and CAA-related ICH diagnosis was associated with increased age (OR: 1.074; 95% CI: 1.028-1.122, p = 0.001). The DMV score correlated with cerebral microbleed (CMB), PVS, DWMH, periventricular white matter hyperintensity (PWMH), and CSVD burden score (p < 0.05) but not with lacuna (p > 0.05). Age was an independent risk factor for the severity of DMV score (OR: 1.052; 95% CI: 0.026-0.076, p < 0.001).

CONCLUSION

DMV scores, CSVD markers, and CSVD burden scores were associated with different subtypes of ICH. In addition, DMV scores were associated with the severity of CSVD and CSVD markers.

Imputation models and error analysis for phase contrast MR cerebral blood flow measurements

Cerebral blood flow (CBF) supports brain metabolism. Diseases impair CBF, and pharmacological agents modulate CBF. Many techniques measure CBF, but phase contrast (PC) MR imaging through the four arteries supplying the brain is rapid and robust. However, technician error, patient motion, or tortuous vessels degrade quality of the measurements of the internal carotid (ICA) or vertebral (VA) arteries. We hypothesized that total CBF could be imputed from measurements in subsets of these 4 feeding vessels without excessive penalties in accuracy. We analyzed PC MR imaging from 129 patients, artificially excluded 1 or more vessels to simulate degraded imaging quality, and developed models of imputation for the missing data. Our models performed well when at least one ICA was measured, and resulted in R ² values of 0.998-0.990, normalized root mean squared error values of 0.044-0.105, and intra-class correlation coefficient of 0.982-0.935. Thus, these models were comparable or superior to the test-retest variability in CBF measured by PC MR imaging. Our imputation models allow retrospective correction for corrupted blood vessel measurements when measuring CBF and guide prospective CBF acquisitions.

Perfusion heterogeneity of cerebral small vessel disease revealed via arterial spin labeling MRI and machine learning

Cerebral small vessel disease (CSVD) is associated with altered cerebral perfusion. However, global and regional cerebral blood flow (CBF) are highly heterogeneous across CSVD patients. The aim of this study was to identify subtypes of CSVD with different CBF patterns using an advanced machine learning approach. 121 CSVD patients and 53 healthy controls received arterial spin label MRI, T1 structural MRI and clinical measurements. Regional CBF were used to identify distinct perfusion subtypes of CSVD via a semi-supervised machine learning algorithm. Statistical analyses were used to explore alterations in CBF, clinical measures, gray and white matter volume between healthy controls and different subtypes of CSVD. Correlation analysis was used to assess the association between clinical measures and altered CBF in each CSVD subtype. Three subtypes of CSVD with distinct CBF patterns were found. Subtype 1 showed decreased CBF in the temporal lobe and increased CBF in the parietal and occipital lobe. Subtype 2 exhibited decreased CBF in the right hemisphere of the brain, and increased CBF in the left cerebrum. Subtype 3 demonstrated decreased CBF in the posterior part of the brain, and increased CBF in anterior part of the brain. The three subtypes also differed significantly in gender (p = 0.005), the proportion of subjects with lacune (p = 0.002), with periventricular white matter hyperintensity (p = 0.043), and CSVD burden score (p = 0.048). In subtype 3, it was found that widespread decreased CBF was correlated with total CSVD burden score (r = -0.324, p = 0.029). Compared with healthy controls, the three CSVD subtypes also showed distinct volumetric patterns of white matter. The current results associate different subtypes with different clinical and imaging phenotypes, which can improve the understanding of brain perfusion alterations of CSVD and can facilitate precision diagnosis of CSVD.

Contrast-agent-free state-of-the-art MRI on cerebral small vessel disease-part 1. ASL, IVIM, and CVR

Cerebral small vessel disease (cSVD), a common cause of stroke and dementia, is traditionally considered the small vessel equivalent of large artery occlusion or rupture that leads to cortical and subcortical brain damage. Microvessel endothelial dysfunction can also contribute to it. Brain imaging, including MRI, is useful to show the presence of lesions of several types, although the association between conventional MRI measures and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast-agent-free, state-of-the-art MRI techniques such as arterial spin labeling (ASL), diffusion tensor imaging, functional MRI, and intravoxel incoherent motion (IVIM) applied to cSVD in the existing literature. We performed a review following the PICO Worksheet and Search Strategy, including original papers in English, published between 2000 and 2022. For each MRI method, we extracted information about their contributions, in addition to those established with traditional MRI methods and related information about the origins, pathology, markers, and clinical outcomes in cSVD. This paper presents the first part of the review, which includes 37 studies focusing on ASL, IVIM, and cerebrovascular reactivity (CVR) measures. In general, they have shown that, in addition to white matter hyperintensities, alterations in other neuroimaging parameters such as blood flow and CVR also indicate the presence of cSVD. Such quantitative parameters were also related to cSVD risk factors. Therefore, they are promising, noninvasive tools to explore questions that have not yet been clarified about this clinical condition. However, protocol standardization is essential to increase their clinical use.

Advances in the Role of Endothelial Cells in Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) poses a serious socio-economic burden due to its high prevalence and severe impact on the quality of life of elderly patients. Pathological changes in CSVD mainly influence small cerebral arteries, microarteries, capillaries, and small veins, which are usually caused by multiple vascular risk factors. CSVD is often identified on brain magnetic resonance imaging (MRI) by recent small subcortical infarcts, white matter hyperintensities, lacune, cerebral microbleeds (CMBs), enlarged perivascular spaces (ePVSs), and brain atrophy. Endothelial cell (EC) dysfunction is earlier than clinical symptoms. Immune activation, inflammation, and oxidative stress may be potential mechanisms of EC injury. ECs of the blood–brain–barrier (BBB) are the most important part of the neurovascular unit (NVU) that ensures constant blood flow to the brain. Impaired cerebral vascular autoregulation and disrupted BBB cause cumulative brain damage. This review will focus on the role of EC injury in CSVD. Furthermore, several specific biomarkers will be discussed, which may be useful for us to assess the endothelial dysfunction and explore new therapeutic directions.

Contribution of Inflammation and Hypoperfusion to White Matter Hyperintensities-Related Cognitive Impairment

White matter hyperintensities (WMHs) of presumed vascular origin are one of the most important neuroimaging markers of cerebral small vessel disease (CSVD), which are closely associated with cognitive impairment. The aim of this study was to elucidate the pathogenesis of WMHs from the perspective of inflammation and hypoperfusion mechanisms. A total of 65 patients with WMHs and 65 healthy controls were enrolled in this study. Inflammatory markers measurements [hypersensitive C-reactive protein (hsCRP) and lipoprotein-associated phospholipase A2 (Lp-PLA2)], cognitive evaluation, and pseudocontinuous arterial spin labeling (PCASL) MRI scanning were performed in all the subjects. The multivariate logistic regression analysis showed that Lp-PLA2 was an independent risk factor for WMHs. Cerebral blood flow (CBF) in the whole brain, gray matter (GM), white matter (WM), left orbital medial frontal gyrus [MFG.L (orbital part)], left middle temporal gyrus (MTG.L), and right thalamus (Tha.R) in the patients was lower than those in the controls and CBF in the left triangular inferior frontal gyrus [IFG.L (triangular part)] was higher in the patients than in the controls. There was a significant correlation between Lp-PLA2 levels and CBF in the whole brain (R = -0.417, p < 0.001) and GM (R = -0.278, p = 0.025), but not in the WM in the patients. Moreover, CBF in the MFG.L (orbital part) and the Tha.R was, respectively, negatively associated with the trail making test (TMT) and the Stroop color word test (SCWT), suggesting the higher CBF, the better executive function. The CBF in the IFG.L (triangular part) was negatively correlated with attention scores in the Cambridge Cognitive Examination-Chinese Version (CAMCOG-C) subitems (R = -0.288, p = 0.020). Our results revealed the vascular inflammation roles in WMHs, which may through the regulation of CBF in the whole brain and GM. Additionally, CBF changes in different brain regions may imply a potential role in the modulation of cognitive function in different domains.

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.

The Contribution of White Matter Diffusion and Cortical Perfusion Pathology to Vascular Cognitive Impairment: A Multimode Imaging-Based Machine Learning Study

Widespread impairments in white matter and cerebrovascular integrity have been consistently implicated in the pathophysiology of patients with small vessel disease (SVD). However, the neural circuit mechanisms that underlie the developing progress of clinical cognitive symptoms remain largely elusive. Here, we conducted cross-modal MRI scanning including diffusion tensor imaging and arterial spin labeling in a cohort of 113 patients with SVD, which included 74 patients with vascular mild cognitive impairment (vMCI) and 39 patients without vMCI symptoms, and hence developed multimode imaging-based machine learning models to identify markers that discriminated SVD subtypes. Diffusion and perfusion features, respectively, extracted from individual white matter and gray matter regions were used to train three sets of classifiers in a nested 10-fold fashion: diffusion-based, perfusion-based, and combined diffusion-perfusion-based classifiers. We found that the diffusion-perfusion combined classifier achieved the highest accuracy of 72.57% with leave-one-out cross-validation, with the diffusion features largely spanning the capsular lateral pathway of the cholinergic tracts, and the perfusion features mainly distributed in the frontal-subcortical-limbic areas. Furthermore, diffusion-based features within vMCI group were associated with performance on executive function tests. We demonstrated the superior accuracy of using diffusion-perfusion combined multimode imaging features for classifying vMCI subtype out of a cohort of patients with SVD. Disruption of white matter integrity might play a critical role in the progression of cognitive impairment in patients with SVD, while malregulation of coritcal perfusion needs further study.

Gait Impairment and Upper Extremity Disturbance Are Associated With Total Magnetic Resonance Imaging Cerebral Small Vessel Disease Burden

Background and Purpose: Cerebral small vessel disease (cSVD)—including white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), lacunes, and enlarged perivascular spaces (EPVS)—is related to gait impairment. However, the association between the total magnetic resonance imaging (MRI) cSVD burden and gait and upper extremity function remains insufficiently investigated. This study aimed to assess the correlation between the total MRI cSVD burden score and gait impairment as well as upper extremity impairment.

Method: A total of 224 participants underwent MRI scans, and the presence of lacunes, WMHs, CMBs, and EPVS was evaluated and recorded as a total MRI cSVD burden score (range 0–4). Gait was assessed by 4-m walkway, Tinetti, Timed Up and Go (TUG), and Short Physical Performance Battery (SPPB) tests. Upper extremity function was assessed by 10-repeat hand pronation-supination time, 10-repeat finger-tapping time, and 10-repeat hand opening and closing time.

Result: The mean age of the 224 participants was 60.6 ± 10.5 years, and 64.3% were men. Independent of age, sex, height, and vascular risk factors, multivariable linear regression analyses showed that a higher total MRI cSVD burden score was related to a shorter stride length, wider step width, higher cadence, and poorer performance on the Tinetti, TUG, and SPPB tests and upper extremity tests (all P < 0.05).

Conclusion: Total MRI cSVD burden was associated with gait impairment and upper extremity disturbances, suggesting that total MRI cSVD burden might contribute to motor function decline. Longitudinal studies are required to determine whether there is a causal relationship between total MRI cSVD burden and motor function decline.

New Insights in Addressing Cerebral Small Vessel Disease: Association With the Deep Medullary Veins

Objective

To assess the suitability of deep medullary vein visibility in susceptibility weighted imaging-magnetic resonance imaging studies as a method for the diagnosis and evaluation of cerebral small vessel disease progression.

Methods

A total of 92 patients with CSVD were enrolled and baseline clinical and imaging data were reviewed retrospectively. Neuroimaging biomarkers of CSVD including high-grade white matter hyperintensity (HWMH), cerebral microbleed (CMB), enlarged perivascular space (PVS), and lacunar infarct (LI) were identified and CSVD burden was calculated. Cases were grouped accordingly as mild, moderate, or severe. The DMV was divided into six segments according to the regional anatomy. The total DMV score (0-18) was calculated as the sum of the six individual segmental scores, which ranged from 0 to 3, for a semi-quantitative assessment of the DMV based on segmental continuity and visibility.

Results

The DMV score was independently associated with the presence of HWMH, PVS, and LI (P < 0.05), but not with presence and absence of CMB (P > 0.05). Correlation between the DMV score and the CSVD burden was significant (P < 0.05) [OR 95% C.I., 1.227 (1.096-1.388)].

Conclusion

The DMV score was associated with the presence and severity of CSVD.