Changes of white matter integrity and structural network connectivity in nondemented cerebral small‐vessel disease

Cerebral microbleeds linked to structural network disruption and cognitive impairment in white matter hyperintensities

OBJECTIVE

This study aims to explore the relationship between the cerebral microbleeds (CMBs) and white matter structural network in patients with white matter hyperintensities (WMHs), and the correlation with the cognitive impairment.

METHOD

One hundred and fifty-eight participants with WMHs underwent 3.0 T magnetic resonance imaging scans and neuropsychological assessment. The grouping method included count grading with categories: non-CMBs (n-CMBs), CMBs < 5, and CMBs ≥ 5. Additionally, the distribution of CMBs was considered, distinguishing between strictly lobar CMBs (SL-CMBs) and deep or infratentorial CMBs (DI-CMBs). Diffusion tensor imaging was employed to construct the white matter structural network for each participant. Subsequently, we analyzed the correlations between the topological parameters of network and cognitive performance in individuals with CMBs.

RESULTS

Compared with n-CMBs group, both CMBs ≥ 5 and DI-CMBs participants exhibited a significant decreased in global efficiency and increased in characteristic path length. Moreover, in the nodal network metrics, the CMBs ≥ 5 showed the left middle occipital gyrus (MOG.L) of nodal efficiency and nodal shortest path correlated with SCWT-A and MMSE, while in the DI-CMBs groups, the left cuneus (CUN.L) of nodal shortest path correlated with SCWT-A. However, there were no significant neuropsychological correlations observed in the SL-CMBs and CMBs < 5 groups.

CONCLUSION

In this study, patients with a high count (≥5) of CMBs or DI-CMBs are associated with disruptions in the microstructure of the white matter structural network, partially impacting the visual network of occipital lobe and affecting the cognitive function of information processing speed and attention.

Blood-brain barrier breakdown in brain ischemia: Insights from MRI perfusion imaging

Brain ischemia is a major cause of neurological dysfunction and mortality worldwide. It occurs not only acutely, such as in acute ischemic stroke (AIS), but also in chronic conditions like cerebral small vessel disease (cSVD). Any other conditions resulting in brain hypoperfusion can also lead to ischemia. Ischemic events can cause blood-brain barrier (BBB) disruption and, ultimately, white matter alterations, contributing to neurological deficits and long-term functional impairments. Hence, understanding the mechanisms of BBB breakdown and white matter injury across various ischemic conditions is critical for developing effective interventions and improving patient outcomes. This review discusses the proposed mechanisms of ischemia-related BBB breakdown. Moreover, magnetic resonance imaging (MRI) based perfusion-weighted imaging (PWI) techniques sensitive to BBB permeability changes are described, including dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI), two perfusion-weighted imaging (PWI). These PWI techniques provide valuable insights that improve our understanding of the complex early pathophysiology of brain ischemia, which can lead to better assessment and management. Finally, in this review, we explore the implications of the mentioned neuroimaging findings, which emphasize the potential of neuroimaging biomarkers to guide personalized treatment and inform novel neuroprotective strategies. This review highlights the importance of investigating BBB changes in brain ischemia and the critical role of advanced neuroimaging in improving patient care and advancing stroke research.

Characterizing the role of the microbiota-gut-brain axis in cerebral small vessel disease: An integrative multi‑omics study

BACKGROUND

Prior efforts have revealed changes in gut microbiome, circulating metabolome, and multimodal neuroimaging features in cerebral small vessel disease (CSVD). However, there is a paucity of research integrating the multi-omic information to characterize the role of the microbiota-gut-brain axis in CSVD.

METHODS

We collected gut microbiome, fecal and blood metabolome, multimodal magnetic resonance imaging data from 37 CSVD patients with white matter hyperintensities and 46 healthy controls. Between-group comparison was performed to identify the differential gut microbial taxa, followed by performance of multi-stage microbiome-metabolome-neuroimaging-neuropsychology correlation analyses in CSVD patients.

RESULTS

Our data showed both depleted and enriched gut microbes in CSVD patients. Among the differential microbes, Haemophilus and Akkermansia were associated with a range of metabolites enriched for Aminoacyl-tRNA biosynthesis pathway. Furthermore, the affected metabolites were associated with neuroimaging measures involving gray matter morphology, spontaneous intrinsic brain activity, white matter integrity, and global structural network topology, which were in turn related to cognition and emotion in CSVD patients.

CONCLUSION

Our findings provide an integrative framework to understand the pathophysiological mechanisms underlying the interplay between gut microbiota dysbiosis and CSVD, highlighting the potential of targeting the microbiota-gut-brain axis as a therapeutic strategy in CSVD patients.

Aberrant brain structural-functional connectivity coupling associated with cognitive dysfunction in different cerebral small vessel disease burdens

AIMS

Emerging evidence suggests that cerebral small vessel disease (CSVD) pathology changes brain structural connectivity (SC) and functional connectivity (FC) networks. Although network-level SC and FC are closely coupled in the healthy population, how SC-FC coupling correlates with neurocognitive outcomes in patients with different CSVD burdens remains largely unknown.

METHODS

Using multimodal MRI, we reconstructed whole-brain SC and FC networks for 54 patients with severe CSVD burden (CSVD-s), 106 patients with mild CSVD burden (CSVD-m), and 79 healthy controls. We then investigated the aberrant SC-FC coupling and functional network topology in CSVD and their correlations with cognitive dysfunction.

RESULTS

Compared with controls, the CSVD-m patients showed no significant change in any SC-FC coupling, but the CSVD-s patients exhibited significantly decreased whole-brain (p = 0.014), auditory/motor (p = 0.033), and limbic modular (p = 0.011) SC-FC coupling. For functional network topology, despite no change in global efficiency, CSVD-s patients exhibited significantly reduced nodal efficiency of the bilateral amygdala (p = 0.024 and 0.035) and heschl gyrus (p = 0.001 and 0.005). Notably, for the CSVD-s patients, whole-brain SC-FC coupling showed a significantly positive correlation with MoCA (r = 0.327, p = 0.020) and SDMT (r = 0.373, p = 0.008) scores, limbic/subcortical modular SC-FC coupling showed a negative correlation (r = -0.316, p = 0.025) with SCWT score, and global/local efficiency (r = 0.367, p = 0.009 and r = 0.353, p = 0.012) showed a positive correlation with AVLT score. For the CSVD-m group, whole-brain and auditory/motor modular SC-FC couplings showed significantly positive correlations with SCWT (r = 0.217, p = 0.028 and r = 0.219, p = 0.027) and TMT (r = 0.324, p = 0.001 and r = 0.245, p = 0.013) scores, and global/local efficiency showed positive correlations with AVLT (r = 0.230, p = 0.020 and r = 0.248, p = 0.012) and SDMT (r = 0.263, p = 0.008 and r = 0.263, p = 0.007) scores.

CONCLUSION

Our findings demonstrated that decreased whole-brain and module-dependent SC-FC coupling associated with reduced functional efficiency might underlie more severe burden and worse cognitive decline in CSVD. SC-FC coupling might serve as a more sensitive neuroimaging biomarker of CSVD burden and provided new insights into the pathophysiologic mechanisms of clinical development of CSVD.

Alterations in structural integrity of superior longitudinal fasciculus III associated with cognitive performance in cerebral small vessel disease

BACKGROUND

This study aimed to investigate the alterations in structural integrity of superior longitudinal fasciculus subcomponents with increasing white matter hyperintensity severity as well as the relationship to cognitive performance in cerebral small vessel disease.

METHODS

110 cerebral small vessel disease study participants with white matter hyperintensities were recruited. According to Fazekas grade scale, white matter hyperintensities of each subject were graded. All subjects were divided into two groups. The probabilistic fiber tracking method was used for analyzing microstructure characteristics of superior longitudinal fasciculus subcomponents.

RESULTS

Probabilistic fiber tracking results showed that mean diffusion, radial diffusion, and axial diffusion values of the left arcuate fasciculus as well as the mean diffusion value of the right arcuate fasciculus and left superior longitudinal fasciculus III in high white matter hyperintensities rating group were significantly higher than those in low white matter hyperintensities rating group (p < 0.05). The mean diffusion value of the left superior longitudinal fasciculus III was negatively related to the Montreal Cognitive Assessment score of study participants (p < 0.05).

CONCLUSIONS

The structural integrity injury of bilateral arcuate fasciculus and left superior longitudinal fasciculus III is more severe with the aggravation of white matter hyperintensities. The structural integrity injury of the left superior longitudinal fasciculus III correlates to cognitive impairment in cerebral small vessel disease.

Microvascular Dysfunction and Whole-Brain White Matter Connectivity: The Maastricht Study

BACKGROUND

Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity.

METHODS AND RESULTS

Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (β per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures.

CONCLUSIONS

These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

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.

Disrupted white matter structural networks in individuals with alcohol dependence

Previous diffusion tensor imaging (DTI) studies have demonstrated widespread white matter microstructure damage in individuals with alcoholism. However, very little is known about the alterations in the topological architecture of white matter structural networks in alcohol dependence (AD). This study included 67 AD patients and 69 controls. The graph theoretical analysis method was applied to examine the topological organization of the white matter structural networks, and network-based statistics (NBS) were employed to detect structural connectivity alterations. Compared to controls, AD patients exhibited abnormal global network properties characterized by increased small-worldness, normalized clustering coefficient, clustering coefficient, and shortest path length; and decreased global efficiency and local efficiency. Further analyses revealed decreased nodal efficiency and degree centrality in AD patients mainly located in the default mode network (DMN), including the precuneus, anterior cingulate and paracingulate gyrus, median cingulate and paracingulate gyrus, posterior cingulate gyrus, and medial part of the superior frontal gyrus. Furthermore, based on NBS approaches, patients displayed weaker subnetwork connectivity mainly located in the region of the DMN. Additionally, altered network metrics were correlated with intelligence quotient (IQ) scores and global assessment function (GAF) scores. Our results may reveal the disruption of whole-brain white matter structural networks in AD individuals, which may contribute to our comprehension of the underlying pathophysiological mechanisms of alcohol addiction at the level of white matter structural networks.

Amide proton transfer could be a surrogate imaging marker for predicting vascular cognitive impairment

BACKGROUD

Emerging evidence suggests an overlap in the underlying pathways contributing to both cerebral small vessel disease (CSVD) and the neurodegenerative disease. Studies investigating the progression of CSVD should incorporate markers that reflect neurodegenerative lesions.

OBJECTIVE

We aim to investigate whether Amide proton transfer (APT) can serve as a potential marker for reflecting vascular cognitive impairment (VCI).

METHOD

Participants were categorized into one of three groups based on their Montreal Cognitive Assessment (MoCA) scores: normal control group (age,54.9 ± 7.9; male, 52.9%), mild cognitive impairment (MCI) group (age,55.7 ± 6.9; male, 42.6%), or vascular dementia (VaD) group (age,57.6 ± 5.5, male, 58.5%). One way analysis of variance was performed to compare the demographic and APT variables between groups. Multiple logistic regression analysis wwas constructed to examine the relationship between APT values and VCI grouping. A hierarchical linear regression model was employed to examine the associations between patients' demographic factors, imaging markers, APT values, and MoCA.

RESULTS

The APT values of frontal white matter, hippocampus, amygdala, and thalamus were significantly different among different groups (p < 0.05). The APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on MCI grouping. the APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on VaD grouping. The demographic data, CSVD imaging markers and APT values can account for 5.1%, 20.1% and 27.7% of the variation in MoCA, respectively.

CONCLUSION

APT imaging can partially identifying and predicting the occurrence of VCI.

Superficial white matter microstructure affects processing speed in cerebral small vessel disease

White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.

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.

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 magnetic resonance imaging on cerebral small vessel disease - Part 2: Diffusion tensor imaging and functional magnetic resonance imaging

Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.

Topologic Efficiency Abnormalities of the Connectome in Asymptomatic Patients with Leukoaraiosis

Leukoaraiosis (LA) is commonly found in aging healthy people but its pathophysiological mechanism is not entirely known. Furthermore, there is still a lack of effective pathological biomarkers that can be used to identify the early stage of LA. Our aim was to investigate the white matter structural network in asymptomatic patients with the early stage of LA. Tractography data of 35 asymptomatic patients and 20 matched healthy controls (HCs) based on diffusion kurtosis imaging (DKI) were analysed by using graph theory approaches and tract-based spatial statistics (TBSS). Diffusion parameters measured within the ALAs and HCs were compared. Decreased clustering coefficient and local efficiency values of the overall topological white matter network were observed in the ALAs compared with those of the HCs. Participants in the asymptomatic group also had lower nodal efficiency in the left triangular part of the inferior frontal gyrus, left parahippocampal gyrus, right calcarine fissure and surrounding cortex, right temporal pole of the superior temporal gyrus and left middle temporal gyrus compared to the ALAs. Moreover, similar hub distributions were found within participants in the two groups. In this study, our data demonstrated a topologic efficiency abnormalities of the structural network in asymptomatic patients with leukoaraiosis. The structural connectome provides potential connectome-based measures that may be helpful for detecting leukoaraiosis before clinical symptoms evolve.

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.

Regional cerebral perfusion in patients with amnestic mild cognitive impairment: effect of cerebral small vessel disease

OBJECTIVE

To explore the effort of cerebral small vessel disease (CSVD) on regional cerebral perfusion in patients with mild cognitive impairment (MCI) using NeuroGam™ software and evaluate the capability of brain perfusion single photon emission computed tomography (SPECT) in distinguishing MCI with and without CSVD.

METHODS

34 amnestic MCI subjects entered this study, conducting neuropsychological tests, MRI and 99mTechnetium ethyl cystine dimer brain perfusion SPECT imaging. All subjects were divided into those with CSVD and those without CSVD. Perfusion value was measured with Brodmann area (BA) mapping in these two groups. Automated software (NeuroGam™) was used for semi-quantitative analyses of perfusion value and comparison with normal database.

RESULTS

Compared with normal database, perfusion levels in BAs 23-left, 28 and 36-left of MCI without CSVD group had great deviations, while perfusion levels in BAs 21, 23, 24, 25, 28, 36, 38 and 47-left of MCI with CSVD group had great deviations. Furthermore, compared with CSVD group, there was significantly lower perfusion value in BA 7-left (P < 0.001) in MCI without CSVD group.

CONCLUSIONS

CSVD could interact with pathological changes related to AD, exacerbating hypoperfusion in BAs 21, 23, 28, 36, 38 while compensating for cerebral blood perfusion disorder in BA 7-left in MCI patients. Meanwhile, MCI patients with CSVD shared similar hypoperfusion with vascular cognitive impairment (VCI) in BAs 24, 25 and 47L. Brain perfusion SPECT may help improve our ability to differentiate MCI with and without CSVD.

Abnormal Cerebral Blood Flow and Functional Connectivity Strength in Subjects With White Matter Hyperintensities

White matter hyperintensities (WMHs) are common neuroimaging findings in the aging population and are associated with various clinical symptoms, especially cognitive impairment. Abnormal global cerebral blood flow (CBF) and specific functional connections have been reported in subjects with higher WMH loads. Nevertheless, the comprehensive functional mechanisms underlying WMH are yet to be established. In this study, by combining resting-state functional magnetic resonance imaging and arterial spin labeling, we investigated the neurovascular dysfunction in subjects with WMH in CBF, functional connectivity strength (FCS), and CBF–FCS coupling. The whole-brain alterations of all these measures were explored among non-dementia subjects with different WMH loads using a fine-grained Human Brainnetome Atlas. In addition, exploratory mediation analyses were conducted to further determine the relationships between these neuroimaging indicators, WMH load, and cognition. The results showed that subjects with higher WMH loads displayed decreased CBF and FCS mainly in regions involving the cognitive- and emotional-related brain networks, including the default mode network, salience network, and central executive network. Notably, subjects with higher WMH loads also showed an abnormal regional CBF–FCS coupling in several regions of the thalamus, posterior cingulate cortex, and parahippocampal gyrus involving the default mode network. Furthermore, regional CBF in the right inferior temporal gyrus and right dorsal caudate may mediate the relationship between WMH load and cognition in WMH subjects. These findings indicated characteristic changes in cerebral blood supply, brain activity, and neurovascular coupling in regions involving specific brain networks with the development of WMH, providing further information on pathophysiology underpinnings of the WMH and related 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.

Leukoaraiosis and acute ischemic stroke

Ischaemic stroke is characterized by high morbidity, high disability rate, high mortality and high recurrence rate, which can have a grave impact on the quality of life of the patients and consequently becomes an economic burden on their families and society. With the developments in imaging technology in recent years, patients with acute cerebral infarction are predominantly more likely to be diagnosed with leukoaraiosis (LA). LA is a common degenerative disease of the nervous system, which is related to cognitive decline, depression, abnormal gait, ischaemic stroke and atherosclerosis. The aetiology of LA is not clear and there is no gold standard for imaging assessment. Related studies have shown that LA has an adverse effect on the prognosis of cerebral infarction, but some experts have contrary beliefs. Hence, we undertook the present review of the literature on the mechanism and the effect of LA on the prognosis of patients with acute ischaemic stroke.

A Systematic Review of WNT Signaling in Endothelial Cell Oligodendrocyte Interactions: Potential Relevance to Cerebral Small Vessel Disease

Key pathological features of cerebral small vessel disease (cSVD) include impairment of the blood brain barrier (BBB) and the progression of white matter lesions (WMLs) amongst other structural lesions, leading to the clinical manifestations of cSVD. The function of endothelial cells (ECs) is of major importance to maintain a proper BBB. ECs interact with several cell types to provide structural and functional support to the brain. Oligodendrocytes (OLs) myelinate axons in the central nervous system and are crucial in sustaining the integrity of white matter. The interplay between ECs and OLs and their precursor cells (OPCs) has received limited attention yet seems of relevance for the study of BBB dysfunction and white matter injury in cSVD. Emerging evidence shows a crosstalk between ECs and OPCs/OLs, mediated by signaling through the Wingless and Int-1 (WNT)/β-catenin pathway. As the latter is involved in EC function (e.g., angiogenesis) and oligodendrogenesis, we reviewed the role of WNT/β-catenin signaling for both cell types and performed a systematic search to identify studies describing a WNT-mediated interplay between ECs and OPCs/OLs. Dysregulation of this interaction may limit remyelination of WMLs and render the BBB leaky, thereby initiating a vicious neuroinflammatory cycle. A better understanding of the role of this signaling pathway in EC-OL crosstalk is essential in understanding cSVD development.