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

Tension at the gate: sensing mechanical forces at the blood-brain barrier in health and disease

Microvascular brain endothelial cells tightly limit the entry of blood components and peripheral cells into the brain by forming the blood-brain barrier (BBB). The BBB is regulated by a cascade of mechanical and chemical signals including shear stress and elasticity of the adjacent endothelial basement membrane (BM). During physiological aging, but especially in neurological diseases including multiple sclerosis (MS), stroke, small vessel disease, and Alzheimer's disease (AD), the BBB is exposed to inflammation, rigidity changes of the BM, and disturbed cerebral blood flow (CBF). These altered forces lead to increased vascular permeability, reduced endothelial reactivity to vasoactive mediators, and promote leukocyte transmigration. Whereas the molecular players involved in leukocyte infiltration have been described in detail, the importance of mechanical signalling throughout this process has only recently been recognized. Here, we review relevant features of mechanical forces acting on the BBB under healthy and pathological conditions, as well as the endothelial mechanosensory elements detecting and responding to altered forces. We demonstrate the underlying complexity by focussing on the family of transient receptor potential (TRP) ion channels. A better understanding of these processes will provide insights into the pathogenesis of several neurological disorders and new potential leads for treatment.

The influence of alterations in the composition of intestinal microbiota on neurovascular coupling and cognitive dysfunction in individuals afflicted with CSVD

INTRODUCTION

An expanding body of research has explored the crucial role of gut microbiota in cerebral small vessel disease (CSVD). The objective of this study is to investigate alterations in the gut microbiota structure among CSVD patients, to explore the correlation between differential taxonomic levels and the neurovascular coupling index as well as cognitive function and to elucidate the imaging and biomarkers of mild cognitive impairment (MCI) in CSVD.

METHODS

We enrolled 104 patients with CSVD and 40 healthy controls (HC). Based on cognitive test scores, CSVD patients were categorized into a cognitively normal group (CSVD-NCI, n=61) and a mild cognitive impairment group (CSVD-MCI, n=43). Performing magnetic resonance imaging (MRI) scans, gut microbiota analysis, as well as clinical and neuropsychological assessments for all participants. Based on arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) imaging data, cerebral blood flow (CBF) and neural activity indices are computed. The coupling indices of CBF/mReHo, CBF/mfALFF, CBF/mALFF, and CBF/mDC are calculated to assess the whole-brain neurovascular coupling changes in patients with CSVD.

RESULTS

Species annotation revealed differences in the composition at the phylum and genus levels among the HC, CSVD-NCI, and CSVD-MCI groups. Additionally, differential analysis using the Kruskal-Wallis test demonstrated specific dominant microbial communities in all three groups. The relative abundance of certain dominant microbial communities in CSVD patients exhibited correlations with neurovascular coupling and cognitive function. The combined assessment of Bacteroides genus and CBF/mDC proved effective in distinguishing between CSVD-NCI and CSVD-MCI, providing a novel non-invasive approach for the diagnosis of MCI in CSVD.

Linking peripheral atherosclerosis to blood-brain barrier disruption: elucidating its role as a manifestation of cerebral small vessel disease in vascular cognitive impairment

Aging plays a pivotal role in the pathogenesis of cerebral small vessel disease (CSVD), contributing to the onset and progression of vascular cognitive impairment and dementia (VCID). In older adults, CSVD often leads to significant pathological outcomes, including blood-brain barrier (BBB) disruption, which in turn triggers neuroinflammation and white matter damage. This damage is frequently observed as white matter hyperintensities (WMHs) in neuroimaging studies. There is mounting evidence that older adults with atherosclerotic vascular diseases, such as peripheral artery disease, ischemic heart disease, and carotid artery stenosis, face a heightened risk of developing CSVD and VCID. This review explores the complex relationship between peripheral atherosclerosis, the pathogenesis of CSVD, and BBB disruption. It explores the continuum of vascular aging, emphasizing the shared pathomechanisms that underlie atherosclerosis in large arteries and BBB disruption in the cerebral microcirculation, exacerbating both CSVD and VCID. By reviewing current evidence, this paper discusses the impact of endothelial dysfunction, cellular senescence, inflammation, and oxidative stress on vascular and neurovascular health. This review aims to enhance understanding of these complex interactions and advocate for integrated approaches to manage vascular health, thereby mitigating the risk and progression of CSVD and VCID.

Establishment and validation of a risk stratification model for stroke risk within three years in patients with cerebral small vessel disease using a combined MRI and machine learning algorithm

BACKGROUND

Cerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a crucial role in patient prevention and treatment. The study aimed to establish and validate a risk stratification model for stroke within three years in patients with CSVD using a combined MRI and machine learning algorithm approach.

METHODS

The assessment encompassed demographic, clinical, biochemical, and MRI-derived parameters. Correlation analysis, logistic regression, receiver operating characteristic (ROC) curve analysis, and nnet neural network algorithm were employed to evaluate the predictive value of machine learning algorithms and MRI parameters for stroke occurrence within 3 years in patients with CSVD.

RESULTS

MRI-derived parameters, including average WMH volume, perfusion deficit volume, ischemic core volume, microbleed count, and perivascular spaces, exhibited strong correlations with stroke occurrence (P < 0.001). MRI-derived parameters demonstrated high sensitivities (0.719 to 0.906), specificities (0.704 to 0.877), and AUC values (0.815 to 0.871). The combined model of machine learning algorithms and MRI parameters yielded an AUC value of 0.925, indicating significantly high predictive accuracy for identifying the risk of stroke within three years in CSVD patients.

CONCLUSION

The integrated risk stratification model, incorporating machine learning algorithms and MRI parameters, demonstrated strong predictive potential for stroke within three years in patients with CSVD. This model offered valuable insights for personalized interventions and clinical decision-making in the management of CSVD.

The Role of Changes in the Expression of Inflammation-Associated Genes in the Variants of Cerebral Small Vessel Disease

Age-dependent cerebral small vessel disease (CSVD) is a common disease with a high social burden characterized by heterogeneity of forms and frequent comorbidity with Alzheimer's disease (AD). Previously, we identified two MRI types of CSVD with specific clinical presentation and, probably, different mechanisms. The present study included 34 patients with CSVD and white matter hyperintensity (WMH) of stage Fazekas (F) 3 (mean age 61.7 ± 8.9) and 11 volunteers (mean age 57.3 ± 9.7). Total RNA was isolated from peripheral blood leukocytes. The expression of 58 protein-coding genes associated with CSVD and/or AD and 4 reference genes were assessed as part of the original panel for the NanoString nCounter analyzer. Testing results were validated by real-time PCR. There was a significant decrease in the expression levels of the ACOX1, CD33, CD2AP, TNFR1, and VEGFC genes in MRI type 2 relative to the control group as well as a decrease in the expression level of the CD33 gene in MRI type 2 compared to MRI type 1. Processes associated with inflammatory pathways with decreased expression of the identified genes are important in the development of MRI type 2 of CSVD. Given the direct connection of the established genes with AD, the importance of this form of CSVD in comorbidity with AD has been assumed.

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.

Imaging the neurovascular unit in health and neurodegeneration: a scoping review of interdependencies between MRI measures

The neurovascular unit (NVU) is a complex structure that facilitates nutrient delivery and metabolic waste clearance, forms the blood-brain barrier (BBB), and supports fluid homeostasis in the brain. The integrity of NVU subcomponents can be measured in vivo using magnetic resonance imaging (MRI), including quantification of enlarged perivascular spaces (ePVS), BBB permeability, cerebral perfusion and extracellular free water. The breakdown of NVU subparts is individually associated with aging, pathology, and cognition. However, how these subcomponents interact as a system, and how interdependencies are impacted by pathology remains unclear. This systematic scoping review identified 26 studies that investigated the inter-relationships between multiple subcomponents of the NVU in nonclinical and neurodegenerative populations using MRI. A further 112 studies investigated associations between the NVU and white matter hyperintensities (WMH). We identify two putative clusters of NVU interdependencies: a 'vascular' cluster comprising BBB permeability, perfusion and basal ganglia ePVS; and a 'fluid' cluster comprising ePVS, free water and WMH. Emerging evidence suggests that subcomponent coupling within these clusters may be differentially related to aging, neurovascular injury or neurodegenerative pathology.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology

PURPOSE

Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease.

METHODS

We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting.

RESULTS

Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected.

CONCLUSION

Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.

New insights in addressing cerebral small vessel disease: Associated with extracellular fluid in white matter

Objective

To explore the role of extracellular fluid, assessed by diffusion tensor imaging (DTI) metrics of free water (FW), in the white matter of patients with cerebral small vessel disease (CSVD).

Materials and methods

The baseline clinical and imaging data of 129 patients with CSVD were collected and reviewed. CSVD MR markers, including periventricular white matter hyperintensity (PWMH), deep white matter hyperintensity (DWMH), cerebral microbleed (CMB), enlarged perivascular space (PVS), and lacunar infarction (LI), were identified, and CSVD burden was calculated. According to total CSVD MR marker score, cases were classified as mild, moderate, or severe. The mean FW and fractional anisotropy (FA) values were calculated using DTI images.

Results

The mean white matter FW was associated with the CSVD MR markers, including PWMH, DWMH, LI and PVS (P < 0.05). Moreover, age, hypertension, diabetes mellitus, and FW value were associated with total CSVD MR marker score (P < 0.05). Ordinal logistic regression analysis revealed that FW and age were independently associated with CSVD burden (P < 0.05). Finally, FW in white matter was associated with FA (r = –0.334, P < 0.001).

Conclusion

Extracellular fluid changes, assessed by DTI metrics of FW in white matter, were associated with CSVD markers and burden. An increased extracellular fluid volume in the white matter was associated with lower FA.