Subcortical Vascular Cognitive Impairment Research Articles

Label-guided low-rank Approximation for functional brain network learning in identifying subcortical vascular cognitive impairment

Background and ObjectiveFunctional brain network (FBN) has played a pivotal role in unraveling the inherent mechanism of cognition/behavior and investigating neuropsychological disorders. Particularly, growing evidence suggests that FBNs have shown great potential in classifying brain disorders such as subcortical vascular cognitive impairment (SVCI). However, learning a high-quality FBN is still challenging since there is no ground truth. Most traditional methods tend to focus on learning FBNs independently of the downstream task. This practice neglects the valuable label information crucial for accurate classification. Besides, the methodology of constructing brain networks in an isolated, individualistic manner sidesteps the common information among individuals. MethodsTo address these issues, we developed a new FBN joint learning strategy named Label-Guided Low-rank Approximation (LGLA). LGLA integrates label information from training subjects and uses unlabeled testing subjects for auxiliary training, enhancing the discriminative power of FBN features tailored to testing subjects. By enforcing class-specific similarities and differences, and applying a low-rank constraint to capture shared information, LGLA presents an optimization framework that can be effectively solved. ResultsExperimental results demonstrate the effectiveness of our proposed FBN learning method for identifying SVCI. The proposed method achieved an accuracy of 75.70% and an area under the receiver operating characteristic curve (AUC) of 0.8233 in the task of identifying patients with amnestic mild cognitive impairment (aMCI). For identifying patients with non-amnestic mild cognitive impairment (naMCI), it achieved an accuracy of 63.64% and an AUC of 0.7857, while the task of identifying patients with no cognitive impairment (NCI), it achieved an accuracy of 63.64% and an AUC of 0.7917. Additionally, we further explored the brain network features and discovered potential biomarkers for personalized diagnosis. ConclusionThe LGLA method enhances FBN construction and classification accuracy for SVCI diagnosis by effectively integrating the label information and shared structure among subjects.

Physical reserve and its underpinning functional neural networks moderate the relationship between white matter hyperintensity and postural balance in older adults with subcortical ischemic vascular cognitive impairment

White matter hyperintensities (WMH) are markers of subcortical ischemic vascular cognitive impairment (SIVCI) associated with impaired postural balance. Physical reserve (PR) is a recently established construct that reflects one’s capacity to maintain physical function despite brain pathology. This cross-sectional study aims to map functional networks associated with PR, and examining the relationship between PR, WMH, and postural balance. PR was defined in 22 community-dwelling older adults with SIVCI. Functional networks of PR were computed using general linear model. Subsequent analyses examined whether PR and relevant networks moderated the relationship between WMH and postural balance under two conditions—eyes open while standing on foam (EOF) or on floor (EONF). We found that PR and the relevant networks—frontoparietal network (FPN) and default mode network (DMN)—significantly moderated the association between WMH and postural balance. For individuals with high PR, postural balance remained stable regardless of the extent of WMH load; whereas for those with low PR, postural balance worsened as WMH load increased. These results suggest the attenuated effects of WMH on postural stability due to PR may be underpinned by functional neural network reorganization in the FPN and DMN as a part of compensatory processes.

Achieving multi-modal brain disease diagnosis performance using only single-modal images through generative AI

Brain disease diagnosis using multiple imaging modalities has shown superior performance compared to using single modality, yet multi-modal data is not easily available in clinical routine due to cost or radiation risk. Here we propose a synthesis-empowered uncertainty-aware classification framework for brain disease diagnosis. To synthesize disease-relevant features effectively, a two-stage framework is proposed including multi-modal feature representation learning and representation transfer based on hierarchical similarity matching. Besides, the synthesized and acquired modality features are integrated based on evidential learning, which provides diagnosis decision and also diagnosis uncertainty. Our framework is extensively evaluated on five datasets containing 3758 subjects for three brain diseases including Alzheimer’s disease (AD), subcortical vascular mild cognitive impairment (MCI), and O[6]-methylguanine-DNA methyltransferase promoter methylation status for glioblastoma, achieving 0.950 and 0.806 in area under the ROC curve on ADNI dataset for discriminating AD patients from normal controls and progressive MCI from static MCI, respectively. Our framework not only achieves quasi-multimodal performance although using single-modal input, but also provides reliable diagnosis uncertainty.

Prediction of Amyloid Positivity in Patients with Subcortical Vascular Cognitive Impairment.

Amyloid-β (Aβ) commonly coexists and impacts prognosis in subcortical vascular cognitive impairment (SVCI). This study aimed to examine the differences in clinical and neuroimaging variables between Aβ-positive and Aβ-negative SVCI and to propose a prediction model for Aβ positivity in clinically diagnosed SVCI patients. A total of 130 patients with SVCI were included in model development, and a separate cohort of 70 SVCI patients was used in external validation. The variables for the prediction model were selected by comparing the characteristics of the Aβ-negative and Aβ-positive SVCI groups. The final model was determined using a stepwise method. The model performance was evaluated using the receiver operating characteristic (ROC) curve and a calibration curve. A nomogram was used for visualization. Among 130 SVCI patients, 70 (53.8%) were Aβ-positive. The Aβ-positive SVCI group was characterized by older age, tendency to be in the dementia stage, a higher prevalence of APOEɛ4, a lower prevalence of lacune, and more severe medial temporal atrophy (MTA). The final prediction model, which excluded MTA grade following the stepwise method for variable selection, demonstrated good accuracy in distinguishing between Aβ-positive and Aβ-negative SVCI, with an area under the curve (AUC) of 0.80. The external validation demonstrated an AUC of 0.71. The findings suggest that older age, dementia stage, APOEɛ4 carrier, and absence of lacunes may be predictive of Aβ positivity in clinically diagnosed SVCI patients.

Selective vulnerability of hippocampal sub-regions in patients with subcortical vascular mild cognitive impairment

Early diagnosis of subcortical vascular mild cognitive impairment (svMCI) is clinically essential because it is the most reversible subtype of all cognitive impairments. Since structural alterations of hippocampal sub-regions have been well studied in neurodegenerative diseases with pathophysiological cognitive impairments, we were eager to determine whether there is a selective vulnerability of hippocampal sub-fields in patients with svMCI. Our study included 34 svMCI patients and 34 normal controls (NCs), with analysis of T1 images and Montreal Cognitive Assessment (MoCA) scores. Gray matter volume (GMV) of hippocampal sub-regions was quantified and compared between the groups, adjusting for age, sex, and education. Additionally, we explored correlations between altered GMV in hippocampal sub-fields and MoCA scores in svMCI patients. Patients with svMCI exhibited selectively reduced GMV in several left hippocampal sub-regions, such as the hippocampal tail, hippocampal fissure, CA1 head, ML-HP head, CA4 head, and CA3 head, as well as decreased GMV in the right hippocampal tail. Specifically, GMV in the left CA3 head was inversely correlated with MoCA scores in svMCI patients. Our findings indicate that the atrophy pattern of patients with svMCI was predominantly located in the left hippocampal sub-regions. The left CA3 might be a crucial area underlying the distinct pathophysiological mechanisms of cognitive impairments with subcortical vascular origins.

Distinct spatiotemporal patterns of cortical thinning in Alzheimer’s disease-type cognitive impairment and subcortical vascular cognitive impairment

Previous studies on Alzheimer’s disease-type cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI) has rarely explored spatiotemporal heterogeneity. This study aims to identify distinct spatiotemporal cortical atrophy patterns in ADCI and SVCI. 1,338 participants (713 ADCI, 208 SVCI, and 417 cognitively unimpaired elders) underwent brain magnetic resonance imaging (MRI), amyloid positron emission tomography, and neuropsychological tests. Using MRI, this study measures cortical thickness in five brain regions (medial temporal, inferior temporal, posterior medial parietal, lateral parietal, and frontal areas) and utilizes the Subtype and Stage Inference (SuStaIn) model to predict the most probable subtype and stage for each participant. SuStaIn identifies two distinct cortical thinning patterns in ADCI (medial temporal: 65.8%, diffuse: 34.2%) and SVCI (frontotemporal: 47.1%, parietal: 52.9%) patients. The medial temporal subtype of ADCI shows a faster decline in attention, visuospatial, visual memory, and frontal/executive domains than the diffuse subtype (p-value < 0.01). However, there are no significant differences in longitudinal cognitive outcomes between the two subtypes of SVCI. Our study provides valuable insights into the distinct spatiotemporal patterns of cortical thinning in patients with ADCI and SVCI, suggesting the potential for individualized therapeutic and preventive strategies to improve clinical outcomes.

Hope for vascular cognitive impairment: Ac-YVAD-cmk as a novel treatment against white matter rarefaction.

Vascular cognitive impairment (VCI) is the second leading cause of dementia with limited treatment options, characterised by cerebral hypoperfusion-induced white matter rarefaction (WMR). Subcortical VCI is the most common form of VCI, but the underlying reasons for region susceptibility remain elusive. Recent studies employing the bilateral cortical artery stenosis (BCAS) method demonstrate that various inflammasomes regulate white matter injury and blood-brain barrier dysfunction but whether caspase-1 inhibition will be beneficial remains unclear. To address this, we performed BCAS on C57/BL6 mice to study the effects of Ac-YVAD-cmk, a caspase-1 inhibitor, on the subcortical and cortical regions. Cerebral blood flow (CBF), WMR, neuroinflammation and the expression of tight junction-related proteins associated with blood-brain barrier integrity were assessed 15 days post BCAS. We observed that Ac-YVAD-cmk restored CBF, attenuated BCAS-induced WMR and restored subcortical myelin expression. Within the subcortical region, BCAS activated the NLRP3/caspase-1/interleukin-1beta axis only within the subcortical region, which was attenuated by Ac-YVAD-cmk. Although we observed that BCAS induced significant increases in VCAM-1 expression in both brain regions that were attenuated with Ac-YVAD-cmk, only ZO-1 and occludin were observed to be significantly altered in the subcortical region. Here we show that caspase-1 may contribute to subcortical regional susceptibility in a mouse model of VCI. In addition, our results support further investigations into the potential of Ac-YVAD-cmk as a novel treatment strategy against subcortical VCI and other conditions exhibiting cerebral hypoperfusion-induced WMR.

Can exercise benefit cerebral white matter myelin? Findings from a 12‐month randomized controlled trial in older adults with vascular cognitive impairment

AbstractBackgroundCerebral small vessel disease is a major underlying cause of subcortical ischemic vascular cognitive impairment (SIVCI). Myelin loss is a feature of cerebral small vessel disease, which may underly cognitive and functional decline in older adults living with SIVCI. Resistance training (RT) is a form of exercise associated with slower progression of white matter lesions, a cerebral small vessel disease marker. However, it remains to be determined whether RT can counteract myelin loss in individuals living with SIVCI. Thus, we examined the impact of a 12‐month, twice‐weekly progressive RT program on myelin content in those with SIVCI.MethodThis was a sub‐study of a 12‐month single‐blinded, randomized controlled trial. Participants (n = 91) were randomized to RT or an active control group (balance and tone exercises [BAT]). Study eligibility included: 1) age 55 years and older; 2) magnetic resonance imaging (MRI) evidence of cerebral small vessel disease; 3) mild cognitive impairment; and 4) the absence of dementia. Myelin was measured using a multi‐echo gradient and spin echo T2 relaxation MRI sequence, indexed as myelin water fraction (MWF). Differences between groups at 12 months were assessed via analysis of covariance adjusting for baseline MWF and estimated intracranial volume. MWF data from fifteen white matter tracts were analyzed. Post‐hoc regressions were conducted to determine if changes in MWF were associated with changes in mobility measured with the Short Physical Performance Battery (SPPB).ResultSeventy‐three participants (RT = 36) aged 74.1 (SD = 5.7), 64% females with high‐quality MRI data were included in the analyses. At 12 months, RT showed lower MWF levels compared with BAT in the genu of the corpus callosum (estimated mean difference [RT – BAT]: ‐0.610, 95% CI: ‐1.041 to ‐0.178, p = 0.006), fornix (‐0.883, 95% CI: ‐1.570 to ‐0.197, p = 0.012), and combined white matter tracts (‐0.326, 95% CI: ‐0.643 to ‐0.009, p = 0.044). Changes in MWF in the combined white matter tracs were positively associated with changes in SPPB (Unstandardized B = 0.124, SE = 0.061, p = 0.047).ConclusionContrary to our expectations, 12 months of balance and tone exercises, but not RT, showed positive changes in myelin. These improvements may result in better mobility in older adults with SIVCI.

Method of differential diagnosis of mild cognitive impairment of various origins: cross sectional study

INTRODUCTION:The differential diagnosis of mild cognitive impairment (MCI), due to the high prevalence in the population and the rapid increase in incidence, is an urgent task. The most common causes leading to the development of cognitive impairment are Alzheimer’s disease (AD), cerebrovascular pathology, and their combination. AD usually manifests as an amnestic type of mild cognitive impairment (aMCI) at the pre-dementia stage. Subcortical vascular mild cognitive impairment (svMCI) is considered as the prodromal stage of subcortical vascular dementia. According to the results of pathomorphological studies, it was found that subfields of the hippocampal formation are selective vulnerability to AD, ischemia/hypoxia, and aging.Currently, using the FreeSurfer 6.0 software, it is possible to obtain quantitative indicators of the hippocampal formation subfieldsin vivo.The current trend in medicine is the development and implementation of new diagnostic solutions based on artificial intelligence and machine learning. One of the machine learning algorithms is binary logistic regression, which we used in the course of the study for the differential diagnosis of MCI of various origins.OBJECTIVE:To develop a method for the differential diagnosis of mil cognitive impairment of various origins.MATERIALS AND METHODS:The study included patients with the syndrome of mild cognitive impairment who were examined in the department of geriatric psychiatry of the V.M.Bekhterev National Medical Research Center for Psychiatry and Neurology, from which two groups were formed: group 1 — patients with aMCI, group 2 — patients with svMCI. Conditionally healthy volunteers, comparable in age, sex and level of education, made up the 3rdgroup (control). MRI examination was performed using a Excelart Vantage Atlas XGV magnetic resonance imaging system (Toshiba, Japan) with a magnetic field strength of 1.5 T, followed by MR morphometry of the subfields of the hippocampal formation.Statistics:Statistical analysis was carried out using data that was converted from a database in Microsoft Excel to the statistical package IBM SPSS 21. To develop a differential diagnosis method, based on the data obtained, the binary regression method and ROC analysis were used.RESULTS:Based on the obtained MR-morphometry data, a method was developed using the binary logistic regression equation. The value of p≥0.5 makes it possible to classify the patient to the aMCI group, and the value of p&lt;0.5 — to the svMCI. The sensitivity of the method is 90%, the specificity is 80%, and the accuracy is 85%.DISCUSSION:Using binary logistic regression, the selection of variants of sets of variables (quantitative indicators) was carried out, for which ROC curves were constructed. The selection criterion was the area under the ROC curve — the AUC criterion (Area Under the Curve). The largest area under the curve (AUC=0.824) in the differential diagnosis of aMCI from svMCI was determined for the combination of the volume of the left subiculum and the thickness of the right entorhinal cortex.Since patients in the aMCI group have a significantly lower number of vascular foci than in the svMCI group (p&lt;0.05), at the next stage, one more variable, the volume fraction, was added to the selected combination of two variables (volume of the left subiculum and thickness of the right entorhinal cortex) hypointense foci. When conducting an ROC analysis with a combination of three variables, an increase in AUC to 0.892 was noted. Further, using a combination of three variables and a binary logistic regression equation, a method for differential diagnosis of aMCI from svMCI was developed.CONCLUSION:The method of differential diagnosis based on binary logistic regression using MR morphometry data allows to distinguish patients with aMCI from patients with svMCI with high sensitivity and specificity.

Examining temporal features of BOLD-based cerebrovascular reactivity in clinical populations.

Conventional cerebrovascular reactivity (CVR) estimation has demonstrated that many brain diseases and/or conditions are associated with altered CVR. Despite the clinical potential of CVR, characterization of temporal features of a CVR challenge remains uncommon. This work is motivated by the need to develop CVR parameters that characterize individual temporal features of a CVR challenge. Data were collected from 54 adults and recruited based on these criteria: (1) Alzheimer's disease diagnosis or subcortical Vascular Cognitive Impairment, (2) sleep apnea, and (3) subjective cognitive impairment concerns. We investigated signal changes in blood oxygenation level dependent (BOLD) contrast images with respect to hypercapnic and normocapnic CVR transition periods during a gas manipulation paradigm. We developed a model-free, non-parametric CVR metric after considering a range of responses through simulations to characterize BOLD signal changes that occur when transitioning from normocapnia to hypercapnia. The non-parametric CVR measure was used to examine regional differences across the insula, hippocampus, thalamus, and centrum semiovale. We also examined the BOLD signal transition from hypercapnia back to normocapnia. We found a linear association between isolated temporal features of successive CO2 challenges. Our study concluded that the transition rate from hypercapnia to normocapnia was significantly associated with the second CVR response across all regions of interest (p < 0.001), and this association was highest in the hippocampus (R2 = 0.57, p < 0.0125). This study demonstrates that it is feasible to examine individual responses associated with normocapnic and hypercapnic transition periods of a BOLD-based CVR experiment. Studying these features can provide insight on between-subject differences in CVR.

CaMKIIα signaling is required for the neuroprotective effects of Dl‐3‐n‐butylphthalide in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is the most common form of neurodegenerative disease and most anti‐AD drugs have failed in clinical trials, hence it is urgent to find effective potential drugs against AD. DL‐3‐n‐Butylphthalide (NBP) is a compound extracted from celery seed and is a multiple‐target drug, and we have demonstrated NBP was effective for improving cognitive and global functioning in patients with subcortical vascular cognitive impairment without dementia and exhibited good safety. Even though there are several studies that have demonstrated the neuroprotective effects of NBP on cognitive impairment, and the mechanisms of NBP remains relatively unexplored.MethodCell viabilities was observed by MTT. Apoptosis and the level of intracellular Ca2+ were examined by flow cytometry. The activation of CaMKIIα signaling was detected by western blotting and immunofluorescence.ResultIn this study, we found that NBP could alleviated the increase of intracellular Ca2+ and reverse down‐regulation of Ca2+/calmodulin‐dependent protein kinase alpha (CaMKIIα) signaling, and rescue neuronal apoptosis in SH‐SY5Y cells treated by Aβ oligomers. Further, we found that these neuroprotection of NBP on neuronal damage and CaMKIIα signaling were abolished when CaMKIIα expression was knock‐downed or its activity was inhibited.ConclusionThus, our findings suggested that CaMKIIα signaling was required for the neuroprotective effects of NBP in AD, and provide an improved basis for elucidation of the mechanism and treatment of NBP in AD.

Clinical outcomes of amyloid and tau markers according to vascular markers

AbstractBackgroundAlzheimer’s disease (AD) is characterized by amyloid beta (Aβ) aggregation [A] and tau aggregation reflecting neurofibrillary tangles [T]. These AD markers lead to neurodegeneration [N] and cognitive impairments. Recently, the ATN research framework of was presented by National Institute on Aging and Alzheimer’s Association. Cerebral small vessel disease (CSVD, [V]), which is one of most important cause of cognitive impairments, has an additive or synergistic effect on cognitive impairments with AD markers. In the present study, we investigated the frequency of ATV abnormalities in participants with varying degree of AD and CSVD markers. We also determined whether CSVD might synergistically affect cognitive decline with AD markers.MethodWe consecutively recruited 195 subjects (105 AD‐related cognitive impairment subjects, 86 subcortical vascular cognitive impairment subjects) from Samsung Medical Center. [A] and [T] positivities were determined by cut‐off values of Aβ and tau uptakes on PET using iterative outlier methods. [V] was assessed by the presence of severe white matter hyperintensity. All subjects underwent neuropsychological tests including Mini‐Mental State Exam (MMSE) and clinical dementia rating‐sum of boxes (CDR‐SOB). A linear mixed effect model was used to compare cognitive changes over time.ResultThe number of subjects of A‐T‐, A+T‐, and A+T+ groups were 16 (15.1%), 29 (27.4%), and 56 (52.8%) in the V‐ group; and 46 (51.7%), 33 (37.1%), and 8 (9.0%) in the V+ group. The linear mixed effects model analysis showed that A+/T+ were associated with worse cognitive decline, and its impact is higher in the V+ group than in the V‐ group (Figure).ConclusionOur findings suggested that there were interactive effects of AD markers and CSVD on cognitive decline. These findings demonstrate the importance of vascular factor management in patients with cognitive impairment and suggest that the ATV framework is useful in predicting cognitive decline in clinical practice.

Identifying genetic variants for amyloid β in subcortical vascular cognitive impairment.

The genetic basis of amyloid β (Aβ) deposition in subcortical vascular cognitive impairment (SVCI) is still unknown. Here, we investigated genetic variants involved in Aβ deposition in patients with SVCI. We recruited a total of 110 patients with SVCI and 424 patients with Alzheimer's disease-related cognitive impairment (ADCI), who underwent Aβ positron emission tomography and genetic testing. Using candidate AD-associated single nucleotide polymorphisms (SNPs) that were previously identified, we investigated Aβ-associated SNPs that were shared or distinct between patients with SVCI and those with ADCI. Replication analyses were performed using the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Rush Memory and Aging Project cohorts (ROS/MAP). We identified a novel SNP, rs4732728, which showed distinct associations with Aβ positivity in patients with SVCI (P interaction = 1.49 × 10-5); rs4732728 was associated with increased Aβ positivity in SVCI but decreased Aβ positivity in ADCI. This pattern was also observed in ADNI and ROS/MAP cohorts. Prediction performance for Aβ positivity in patients with SVCI increased (area under the receiver operating characteristic curve = 0.780; 95% confidence interval = 0.757-0.803) when rs4732728 was included. Cis-expression quantitative trait loci analysis demonstrated that rs4732728 was associated with EPHX2 expression in the brain (normalized effect size = -0.182, P = 0.005). The novel genetic variants associated with EPHX2 showed a distinct effect on Aβ deposition between SVCI and ADCI. This finding may provide a potential pre-screening marker for Aβ positivity and a candidate therapeutic target for SVCI.

Aerobic exercise improves executive functions in females, but not males, without the BDNF Val66Met polymorphism

BackgroundAerobic exercise promotes cognitive function in older adults; however, variability exists in the degree of benefit. The brain-derived neurotropic factor (BDNF) Val66Met polymorphism and biological sex are biological factors that have been proposed as important modifiers of exercise efficacy. Therefore, we assessed whether the effect of aerobic exercise on executive functions was dependent on the BDNFval66met genotype and biological sex.MethodsWe used data from a single-blind randomized controlled trial in older adults with subcortical ischemic vascular cognitive impairment (NCT01027858). Fifty-eight older adults were randomly assigned to either the 6 months, three times per week progressive aerobic training (AT) group or the usual care plus education control (CON) group. The secondary aim of the parent study included executive functions which were assessed with the Trail Making Test (B–A) and the Digit Symbol Substitution Test at baseline and trial completion at 6 months.ResultsAnalysis of covariance, controlling for baseline global cognition and baseline executive functions performance (Trail Making Test or Digit Symbol Substitution Test), tested the three-way interaction between experimental group (AT, CON), BDNFval66met genotype (Val/Val carrier, Met carrier), and biological sex (female, male). Significant three-way interactions were found for the Trail Making Test (F(1,48) = 4.412, p < 0.04) and Digit Symbol Substitution Test (F(1,47) = 10.833, p < 0.002). Posthoc analyses showed female Val/Val carriers benefited the most from 6 months of AT compared with CON for Trail Making Test and Digit Symbol Substitution Test performance. Compared with CON, AT did not improve Trail Making Test performance in male Val/Val carriers or Digit Symbol Substitution Test performance in female Met carriers.ConclusionsThese results suggest that future randomized controlled trials should take into consideration BDNF genotype and biological sex to better understand the beneficial effects of AT on cognitive function in vascular cognitive impairment to maximize the beneficial effects of exercise and help establish exercise as medicine for cognitive health.

Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease.

It is challenging to predict which patients who meet criteria for subcortical ischemic vascular disease (SIVD) will ultimately progress to subcortical vascular cognitive impairment (SVCI). We collected clinical information, neuropsychological assessments, T1 imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging from 83 patients with SVCI and 53 age-matched patients with SIVD without cognitive impairment. We built an unsupervised machine learning model to isolate patients with SVCI. The model was validated using multimodal data from an external cohort comprising 45 patients with SVCI and 32 patients with SIVD without cognitive impairment. The accuracy, sensitivity, and specificity of the unsupervised machine learning model were 86.03%, 79.52%, and 96.23% and 80.52%, 71.11%, and 93.75% for internal and external cohort, respectively. We developed an accurate and accessible clinical tool which requires only data from routine imaging to predict patients at risk of progressing from SIVD to SVCI. Our unsupervised machine learning model provides an accurate and accessible clinical tool to predict patients at risk of progressing from subcortical ischemic vascular disease (SIVD) to subcortical vascular cognitive impairment (SVCI) and requires only data from imaging routinely used during the diagnosis of suspected SVCI. The model yields good accuracy, sensitivity, and specificity and is portable to other cohorts and to clinical practice to distinguish patients with SIVD at risk for progressing to SVCI. The model combines assessment of diffusion tensor imaging and functional magnetic resonance imaging measures in patients with SVCI to analyze whether the "disconnection hypothesis" contributes to functional and structural changes and to the clinical presentation of SVCI.

Study of gray matter atrophy pattern with subcortical ischemic vascular disease-vascular cognitive impairment no dementia based on structural magnetic resonance imaging.

This study explored the structural imaging changes in patients with subcortical ischemic vascular disease (SIVD)-vascular cognitive impairment no dementia (VCIND) and the correlation between the changes in gray matter volume and the field of cognitive impairment to provide new targets for early diagnosis and treatment. Our study included 15 patients with SIVD-normal cognitive impairment (SIVD-NCI), 63 with SIVD-VCIND, 26 with SIVD-vascular dementia (SIVD-VD), and 14 normal controls (NC). T1-weighted images of all participants were collected, and DPABI and SPM12 software were used to process the gray matter of the four groups based on voxels. Fisher's exact test, one-way ANOVA and Kruskal-Wallis H test were used to evaluate all clinical and demographic data and compare the characteristics of diencephalic gray matter atrophy in each group. Finally, the region of interest (ROI) of the SIVD-VCIND was extracted, and Pearson correlation analysis was performed between the ROI and the results of the neuropsychological scale. Compared to the NC, changes in gray matter atrophy were observed in the bilateral orbitofrontal gyrus, right middle temporal gyrus, superior temporal gyrus, and precuneus in the SIVD-VCIND. Gray matter atrophy was observed in the left cerebellar region 6, cerebellar crural region 1, bilateral thalamus, right precuneus, and calcarine in the SIVD-VD. Compared with the SIVD-VCIND, gray matter atrophy changes were observed in the bilateral thalamus in the SIVD-VD (p < 0.05, family-wise error corrected). In the SIVD-VCIND, the total gray matter volume, bilateral medial orbital superior frontal gyrus, right superior temporal gyrus, middle temporal gyrus, and precuneus were positively correlated with Boston Naming Test score, whereas the total gray matter volume, right superior temporal gyrus, and middle temporal gyrus were positively correlated with overall cognition. Structural magnetic resonance imaging can detect extensive and subtle structural changes in the gray matter of patients with SIVD-VCIND and SIVD-VD, providing valuable evidences to explain the pathogenesis of subcortical vascular cognitive impairment and contributing to the early diagnosis of SIVD-VCIND and early warning of SIVD-VD.

Structural atrophy and functional dysconnectivity patterns in the cerebellum relate to cerebral networks in svMCI.

Subcortical vascular mild cognitive impairment (svMCI) is associated with structural and functional changes in the cerebral cortex affecting major brain networks. While recent studies have shown that the intrinsic cerebral connectivity networks can be mapped onto the cerebellum, and the cortex and cerebellum are interconnected via the cortico-basal ganglia-cerebellar circuit, structural and functional disruptions in cerebellum in svMCI are rarely studied. In this study, we conducted voxel-based morphometry analysis to investigate gray matter atrophy pattern across cerebellar regions in 40 svMCI patients, and explored alterations in functional connectivity between the basal ganglia and cerebellum. The results showed that the amount of cerebellar atrophy within the default mode, salience, and frontoparietal networks correlated with their counterpart in the cerebral cortex. Moreover, key regions of the cerebellum, including the lobule VI, VIIb, VIII, and Crus I, which are reported to have a role in cognitive function, showed both anatomical atrophy and decreased functional connectivity with the striatum. These atrophy and connectivity patterns in the cerebellum also correlated with memory performances. These findings demonstrate that there are coupled changes in cerebral and cerebellar circuits, reflecting that degeneration patterns in svMCI are not limited to the cerebral cortex but similarly extend to the cerebellum as well, and suggest the cortico-basal ganglia-cerebellar circuit may play an important role in the pathology of svMCI.

Progressive alteration of dynamic functional connectivity patterns in subcortical ischemic vascular cognitive impairment patients

Alterations in the temporal evolution of brain states in the process of cognitive impairment aggravation due to subcortical ischemic vascular disease (SIVD) is not understood. The dynamic functional connectivity was investigated to identify the abnormal temporal properties of brain states associated with cognitive impairment caused by SIVD. Eighteen patients with subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND), 19 dementia patients (SIVaD) and 26 normal controls were enrolled. We found that the occupancy rate and mean lifetime of brain states were associated with cognitive performance. SIVCIND had a higher occupancy rate and longer mean lifetime in weakly connected states than normal controls. SIVaD had similar but more extensive changes in the temporal properties of brain states. In addition, switching from weakly connected states to more strongly connected states was more difficult in SIVCIND and SIVaD patients than in normal controls, especially in SIVaD patients. The results revealed that not only the transition to but also maintenance in strongly connected states became increasingly difficult when SIVD-related cognitive impairment progressed into a more severe stage.

Interaction between Alzheimer's Disease and Cerebral Small Vessel Disease: A Review Focused on Neuroimaging Markers.

Alzheimer’s disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.

Lateralized brain activities in subcortical vascular mild cognitive impairment with differential Chinese medicine patterns: A resting-state functional magnetic resonance imaging study.

BackgroundSubcortical vascular mild cognitive impairment (svMCI) is one of the most treatable cognitive impairments, but could be hampered by the high clinical heterogeneities. Further classification by Chinese Medicine (CM) patterns has been proved to stratify its clinical heterogeneities. It remains largely unknown of the spontaneous brain activities regarding deficiency patterns (DPs) and excess patterns (EPs) of svMCI patients based on fMRI data.ObjectiveWe aim to provide neuroimaging evidence of altered resting-state brain activities associated with DPs and EPs in svMCI patients.MethodsThirty-seven svMCI patients (PAs) and 23 healthy controls (CNs) were consecutively enrolled. All patients were categorized into either the EP group (n = 16) and the DP group (n = 21) based on a quantitative CM scale. The fractional amplitude of low-frequency fluctuation (fALFF) value was used to make comparisons between different subgroups.ResultsThe DP group showed significant differences of fALFF values in the right middle frontal gyrus and the right cerebellum, while the EP group showed significant differences in the left orbitofrontal gyrus and the left cerebellum, when compared with the CN group. When compared with the EP group, the DP group had markedly increased fALFF values in the left superior temporal gyrus, right middle temporal gyrus and brainstem. The decreased fALFF values was shown in the right anterior cingulate and paracingulate gyri. Among the extensive areas of frontotemporal lobe, the Montreal Cognitive Assessment (MoCA) scores were significantly correlated with the reduced fALFF value of the right middle frontal gyrus and the left orbitofrontal gyrus.ConclusionOur results indicated that the DPs and EPs presented the lateralization pattern in the bilateral frontal gyrus, which will probably benefit the future investigation of the pathogenesis of svMCI patients.