Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter

PURPOSE

This study aimed to develop and validate a radiomics model based on whole-brain white matter and clinical features to predict the progression of Parkinson disease (PD).

METHODS

PD patient data from the Parkinson's Progress Markers Initiative (PPMI) database was evaluated. Seventy-two PD patients with disease progression, as measured by the Hoehn-Yahr Scale (HYS) (stage 1-5), and 72 PD patients with stable PD were matched by sex, age, and category of HYS and included in the current study. Each individual's T₁ -weighted MRI scans at the baseline timepoint were segmented to isolate whole-brain white matter for radiomics feature extraction. The total dataset was divided into a training and test set according to subject serial number. The size of the training dataset was reduced using the maximum relevance minimum redundancy (mRMR) algorithm to construct a radiomics signature using machine learning. Finally, a joint model was constructed by incorporating the radiomics signature and clinical progression scores. The test data were then used to validate the prediction models, which were evaluated based on discrimination, calibration, and clinical utility.

RESULTS

Based on the overall data, the areas under curve (AUCs) of the joint model, signature and Unified Parkinson Disease Rating Scale III PD rating score were 0.836, 0.795, and 0.550, respectively. Furthermore, the sensitivities were 0.805, 0.875, and 0.292, respectively, and the specificities were 0.722, 0.697, and 0.861, respectively. In addition, the predictive accuracy of the model was 0.827, the sensitivity was 0.829 and the specificity was 0.702 for stage-1 PD. For stage-2 PD, the predictive accuracy of the model was 0.854, the sensitivity was 0.960, and the specificity was 0.600.

CONCLUSION

Our results provide evidence that conventional structural MRI can predict the progression of PD. This work also supports the use of a simple radiomics signature built from whole-brain white matter features as a useful tool for the assessment and monitoring of PD progression.

Total Cerebral Small Vessel Disease Burden Is Related to Worse Performance on the Mini-Mental State Examination and Incident Dementia: A Prospective 5-Year Follow-Up

Individual cerebral small vessel disease (CSVD) may cause cognitive decline. However, the association between total burden of CSVD and cognitive deterioration in the general population remains unclear. We aimed to determine whether total CSVD score is associated with cognitive performance change and incident dementia in the general population. In the longitudinal population-based Taizhou Imaging Study, 556 participants free of neurological disorders underwent brain MRI and neuropsychological testing at baseline. A total of 456 participants were followed up for cognitive performance for a mean (standard deviation) of 4.6 (0.6) years. Total CSVD score (range 0-4) was calculated by assigning 1 point for the presence of each of the following markers: lacune, white matter hyperintensity, cerebral microbleed, and perivascular space. Beta regression was used to evaluate the association between total CSVD burden and MMSE score change. The association of prevalent CSVD with incident dementia was studied using Fisher's exact test. CSVDs were present in 262 individuals (47.1%). The total CSVD score was significantly associated with MMSE score decline (p = 0.001). Compared to those with no CSVD, participants with 4 CSVD markers had a steeper decline in MMSE score (β: -0.53, 95% CI: -0.86 to -0.21; p = 0.001). A total of 15 participants developed dementia during follow-up. The presence of more than three CSVD markers at baseline was associated with a significantly higher risk of dementia (p = 0.020). Total CSVD burden appears to be associated with MMSE score decline and incident dementia in a general population in China.

Pathophysiology, classification, and MRI parallels in microvascular disease of the heart and brain

Diagnostic imaging technology in vascular disease has long focused on large vessels and the pathologic processes that impact them. With improved diagnostic techniques, investigators are now able to uncover many underlying mechanisms and prognostic factors for microvascular disease. In the heart and brain, these pathologic entities include coronary microvascular disease and cerebral small vessel disease, both of which have significant impact on patients, causing angina, myocardial infarction, heart failure, stroke, and dementia. In the current paper, we will discuss parallels in pathophysiology, classification, and diagnostic modalities, with a focus on the role of magnetic resonance imaging in microvascular disease of the heart and brain. Novel approaches for streamlined imaging of the cardiac and central nervous systems including the use of intravascular contrast agents such as ferumoxytol are presented, and unmet research gaps in diagnostics are summarized.

Structural disconnectivity and the risk of dementia in the general population

Objective

The disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.

Methods

Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.

Results

During a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts.

Conclusions

Structural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population.

Genome-wide association study of MRI markers of cerebral small vessel disease in 42,310 participants

Cerebral small vessel disease is a major cause of stroke and dementia, but its genetic basis is incompletely understood. We perform a genetic study of three MRI markers of the disease in UK Biobank imaging data and other sources: white matter hyperintensities (N = 42,310), fractional anisotropy (N = 17,663) and mean diffusivity (N = 17,467). Our aim is to better understand the disease pathophysiology. Across the three traits, we identify 31 loci, of which 21 were previously unreported. We perform a transcriptome-wide association study to identify associations with gene expression in relevant tissues, identifying 66 associated genes across the three traits. This genetic study provides insights into the understanding of the biological mechanisms underlying small vessel disease.

Simple MRI score aids prediction of dementia in cerebral small vessel disease

Objective

To determine whether a simple small vessel disease (SVD) score, which uses information available on rapid visual assessment of clinical MRI scans, predicts risk of cognitive decline and dementia, above that provided by simple clinical measures.

Methods

Three prospective longitudinal cohort studies (SCANS [St George's Cognition and Neuroimaging in Stroke], RUN DMC [Radboud University Nijmegen Diffusion Imaging and Magnetic Resonance Imaging Cohort], and the ASPS [Austrian Stroke Prevention Study]), which covered a range of SVD severity from mild and asymptomatic to severe and symptomatic, were included. In all studies, MRI was performed at baseline, cognitive tests repeated during follow-up, and progression to dementia recorded prospectively. Outcome measures were cognitive decline and onset of dementia during follow-up. We determined whether the SVD score predicted risk of cognitive decline and future dementia. We also determined whether using the score to select a group of patients with more severe disease would reduce sample sizes for clinical intervention trials.

Results

In a pooled analysis of all 3 cohorts, the score improved prediction of dementia (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.81–0.89) compared with that from clinical risk factors alone (AUC, 0.76; 95% CI, 0.71–0.81). Predictive performance was higher in patients with more severe SVD. Power calculations showed selecting patients with a higher score reduced sample sizes required for hypothetical clinical trials by 40%–66% depending on the outcome measure used.

Conclusions

A simple SVD score, easily obtainable from clinical MRI scans and therefore applicable in routine clinical practice, aided prediction of future dementia risk.

Structural network changes in cerebral small vessel disease

OBJECTIVES

To investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD).

METHODS

A prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume.

RESULTS

The decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (β=0.18, p=0.03) and a trend with change in cognitive index (β=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76).

CONCLUSION

Disruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.

Prospects for Diminishing the Impact of Nonamyloid Small-Vessel Diseases of the Brain

Small-vessel diseases (SVDs) of the brain are involved in about one-fourth of ischemic strokes and a vast majority of intracerebral hemorrhages and are responsible for nearly half of dementia cases in the elderly. SVDs are a heavy burden for society, a burden that is expected to increase further in the absence of significant therapeutic advances, given the aging population. Here, we provide a critical appraisal of currently available therapeutic approaches for nonamyloid sporadic SVDs that are largely based on targeting modifiable risk factors. We review what is known about the pathogenic mechanisms of vascular risk factor-related SVDs and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most frequent hereditary SVD, and elaborate on two mechanism-based therapeutic approaches worth exploring in sporadic SVD and CADASIL. We conclude by discussing opportunities and challenges that need to be tackled if efforts to achieve significant therapeutic advances for these diseases are to be successful.

Proceedings from the Albert Charitable Trust Inaugural Workshop on white matter and cognition in aging

This third in a series of vascular cognitive impairment (VCI) workshops, supported by "The Leo and Anne Albert Charitable Trust," was held from February 8 to 12 at the Omni Resort in Carlsbad, CA. This workshop followed the information gathered from the earlier two workshops suggesting that we focus more specifically on brain white matter in age-related cognitive impairment. The Scientific Program Committee (Frank Barone, Shawn Whitehead, Eric Smith, and Rod Corriveau) assembled translational, clinical, and basic scientists with unique expertise in acute and chronic white matter injury at the intersection of cerebrovascular and neurodegenerative etiologies. As in previous Albert Trust workshops, invited participants addressed key topics related to mechanisms of white matter injury, biomarkers of white matter injury, and interventions to prevent white matter injury and age-related cognitive decline. This report provides a synopsis of the presentations and discussions by the participants, including the existing knowledge gaps and the delineation of the next steps towards advancing our understanding of white matter injury and age-related cognitive decline. Workshop discussions and consensus resulted in action by The Albert Trust to (1) increase support from biannual to annual "White Matter and Cognition" workshops; (2) provide funding for two collaborative, novel research grants annually submitted by meeting participants; and (3) coordinate the formation of the "Albert Research Institute for White Matter and Cognition." This institute will fill a gap in white matter science, providing white matter and cognition communications, including annual updates from workshops and the literature and interconnecting with other Albert Trust scientific endeavors in cognition and dementia, and providing support for newly established collaborations between seasoned investigators and to the development of talented young investigators in the VCI-dementia (VCID) and white matter cognition arena.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

INTRODUCTION

Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.

METHODS

Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.

RESULTS

A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.

CONCLUSIONS

The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Cerebral White Matter Hyperintensity as a Healthcare Quotient

To better understand the risk factors and optimal therapeutic strategies of cerebral white matter hyperintensity (WMH), we examined a large population of adults with and without various vascular risk factors (VRFs) or vascular risk conditions (VRCs), such as hypertension (HT), diabetes mellitus (DM), and dyslipidemia (DLP), including the comorbidities. We assessed two participant groups having no medical history of stroke or dementia that underwent brain checkup using magnetic resonance imaging (MRI): 5541 participants (2760 men, 2781 women) without VRCs and 1969 participants (1169 men, 800 women) who had received drug treatments for VRCs and the combination of comorbidities. For data analysis, we constructed WMH-brain healthcare quotient (WMH-BHQ) based on the percentile rank of WMH volume. This metric has an inverse relation to WMH. Multiple linear regression analysis of 5541 participants without VRCs revealed that age, systolic blood pressure (SBP), Brinkman index (BI), and female sex were significant factors lowering WMH-BHQ, whereas body mass index (BMI), male sex, fasting blood sugar, and triglyceride levels were increasing factors. The Kruskal–Wallis test and Dunn tests showed that WMH-BHQs significantly increased or decreased with BMI or SBP and with BI classification, respectively. Regarding the impact of impaired fasting glucose and abnormal lipid metabolism, there were almost no significant relationships. For 1969 participants who had HT, DM, and DLP, as well as their comorbidities, we found that DLP played a substantial role in increasing WMH-BHQ for some comorbidities, whereas the presence of HT and DM alone tended to decrease it. Cerebral WMH can be used as a healthcare quotient for quantitatively evaluating VRFs and VRCs and their comorbidities.

Peak width of skeletonized mean diffusivity and its association with age-related cognitive alterations and vascular risk factors

Introduction

Only two studies investigated the associations between peak width of skeletonized mean diffusivity (PSMD) and age-related cognitive alterations, whereas none of the studies investigated the association with vascular risk factors.

Methods

We evaluated 801 stroke- and dementia-free elderlies with baseline and 3-year follow-up assessments. Regression analyses were used to assess the association between age-related cognitive functions and PSMD. Simple mediation models were used to study the mediation effect of PSMD between vascular risk factors and age-related cognitive outcomes.

Results

PSMD was negatively associated with processing speed at baseline and negatively associated with processing and memory scores at 3-year follow-up. The association between vascular risk factors and age-related cognition was mediated by PSMD, as well as other diffusion tensor imaging markers.

Discussion

PSMD is preferred over other diffusion tensor imaging markers as it is sensitive to age-related cognitive alterations and calculation is fully automated. PSMD is proposed as a research tool to monitor age-related cognitive alterations.

Disruption of white matter connectivity in chronic obstructive pulmonary disease

Background

Mild cognitive impairment is a common systemic manifestation of chronic obstructive pulmonary disease (COPD). However, its pathophysiological origins are not understood. Since, cognitive function relies on efficient communication between distributed cortical and subcortical regions, we investigated whether people with COPD have disruption in white matter connectivity.

Methods

Structural networks were constructed for 30 COPD patients (aged 54–84 years, 57% male, FEV₁ 52.5% pred.) and 23 controls (aged 51–81 years, 48% Male). Networks comprised 90 grey matter regions (nodes) interconnected by white mater fibre tracts traced using deterministic tractography (edges). Edges were weighted by the number of streamlines adjusted for a) streamline length and b) end-node volume. White matter connectivity was quantified using global and nodal graph metrics which characterised the networks connection density, connection strength, segregation, integration, nodal influence and small-worldness. Between-group differences in white matter connectivity and within-group associations with cognitive function and disease severity were tested.

Results

COPD patients’ brain networks had significantly lower global connection strength (p = 0.03) and connection density (p = 0.04). There was a trend towards COPD patients having a reduction in nodal connection density and connection strength across the majority of network nodes but this only reached significance for connection density in the right superior temporal gyrus (p = 0.02) and did not survive correction for end-node volume. There were no other significant global or nodal network differences or within-group associations with disease severity or cognitive function.

Conclusion

COPD brain networks show evidence of damage compared to controls with a reduced number and strength of connections. This loss of connectivity was not sufficient to disrupt the overall efficiency of network organisation, suggesting that it has redundant capacity that makes it resilient to damage, which may explain why cognitive dysfunction is not severe. This might also explain why no direct relationships could be found with cognitive measures. Smoking and hypertension are known to have deleterious effects on the brain. These confounding effects could not be excluded.

Functional brain connectome and its relation to mild cognitive impairment in cerebral small vessel disease patients with thalamus lacunes: A cross-sectional study

To investigate the functional connectome alterations in cerebral small-vessel disease (CSVD) patients with thalamus lacunes and its relation to cognitive impairment.This case-control study was approved by the local research ethics committee, and all participants provided informed consent. There were 14 CSVD patients with thalamus lacunes (CSVDw.), 27 without (CSVDwo.), and 34 healthy controls (HC) recruited matched for age, sex, and education to undergo a 3T resting-state functional MR examination. The whole-brain functional connectome was constructed by thresholding the Pearson correlation matrices of 90 brain regions, and the topologic properties were analyzed by using graph theory approaches. Networks were compared between CSVD patients and HC, and associations between network measures and cognitive function were tested.Compared with HC, the functional connectome in CSVDw. patients showed abnormalities at the global level and at the nodal level (P < .05, false discovery rate corrected). The network-based statistics method identified a significantly altered network consisting 6 nodes and 13 connections. Among all the 13 connections, only two connections had significant correlation with episodic memory (EM) and processing speed (PS) respectively (P < .05). The CSVDwo. patients showed no significant network alterations relative to controls (P > .05).The configurations of brain functional connectome in CSVDw. patients were perturbed but not obvious for those without, and correlated with the mild cognitive impairment, especially for EM and PS. This study suggested that lacunes on thalamus played a vital role in mediating the neural functional changes of CSVD patients.

Predicting Dementia in Cerebral Small Vessel Disease Using an Automatic Diffusion Tensor Image Segmentation Technique

Supplemental Digital Content is available in the text.

Cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment, with a significant proportion of cases going on to develop dementia. We explore the extent to which diffusion tensor image segmentation technique (DSEG; which characterizes microstructural damage across the cerebrum) predicts both degree of cognitive decline and conversion to dementia, and hence may provide a useful prognostic procedure.

The Vascular Hypothesis of Alzheimer's Disease: A Key to Preclinical Prediction of Dementia Using Neuroimaging

The vascular hypothesis of Alzheimer's disease (VHAD) was proposed 24 years ago from observations made in our laboratory using aging rats subjected to chronic brain hypoperfusion. In recent years, VHAD has become a mother-lode to numerous neuroimaging studies targeting cerebral hemodynamic changes, particularly brain hypoperfusion in elderly patients at risk of developing Alzheimer's disease (AD). There is a growing consensus among neuroradiologists that brain hypoperfusion is likely involved in the pathogenesis of AD and that disturbed cerebral blood flow (CBF) can serve as a key biomarker for predicting conversion of mild cognitive impairment to AD. The use of cerebral hypoperfusion as a preclinical predictor of AD is becoming decisive in stratifying low and high risk patients that may develop cognitive decline and for assessing the effectiveness of therapeutic interventions. There is currently an international research drive from neuroimaging groups to seek new perspectives that can broaden our understanding of AD and improve lifestyle. Diverse neuroimaging methods are currently being used to monitor normal and dyscognitive brain activity. Some techniques are very powerful and can detect, diagnose, quantify, prognose, and predict cognitive decline before AD onset, even from a healthy cognitive state. Multimodal imaging offers new insights in the treatment and prevention of cognitive decline during advanced aging and better understanding of the functional and structural organization of the human brain. This review discusses the impact the VHAD and CBF are having on the neuroimaging technology that can usher practical strategies to help prevent AD.

Vascular Cognitive Impairment and Dementia: JACC Scientific Expert Panel

Cognitive impairment associated with aging has emerged as one of the major public health challenges of our time. Although Alzheimer's disease is the leading cause of clinically diagnosed dementia in Western countries, cognitive impairment of vascular etiology is the second most common cause and may be the predominant one in East Asia. Furthermore, alterations of the large and small cerebral vasculature, including those affecting the microcirculation of the subcortical white matter, are key contributors to the clinical expression of cognitive dysfunction caused by other pathologies, including Alzheimer's disease. This scientific expert panel provides a critical appraisal of the epidemiology, pathobiology, neuropathology, and neuroimaging of vascular cognitive impairment and dementia, and of current diagnostic and therapeutic approaches. Unresolved issues are also examined to shed light on new basic and clinical research avenues that may lead to mitigating one of the most devastating human conditions.

Development and Validation of a Dementia Risk Prediction Model in the General Population: An Analysis of Three Longitudinal Studies

OBJECTIVE

Identification of individuals at high risk of dementia is essential for development of prevention strategies, but reliable tools are lacking for risk stratification in the population. The authors developed and validated a prediction model to calculate the 10-year absolute risk of developing dementia in an aging population.

METHODS

In a large, prospective population-based cohort, data were collected on demographic, clinical, neuropsychological, genetic, and neuroimaging parameters from 2,710 nondemented individuals age 60 or older, examined between 1995 and 2011. A basic and an extended model were derived to predict 10-year risk of dementia while taking into account competing risks from death due to other causes. Model performance was assessed using optimism-corrected C-statistics and calibration plots, and the models were externally validated in the Dutch population-based Epidemiological Prevention Study of Zoetermeer and in the Alzheimer's Disease Neuroimaging Initiative cohort 1 (ADNI-1).

RESULTS

During a follow-up of 20,324 person-years, 181 participants developed dementia. A basic dementia risk model using age, history of stroke, subjective memory decline, and need for assistance with finances or medication yielded a C-statistic of 0.78 (95% CI=0.75, 0.81). Subsequently, an extended model incorporating the basic model and additional cognitive, genetic, and imaging predictors yielded a C-statistic of 0.86 (95% CI=0.83, 0.88). The models performed well in external validation cohorts from Europe and the United States.

CONCLUSIONS

In community-dwelling individuals, 10-year dementia risk can be accurately predicted by combining information on readily available predictors in the primary care setting. Dementia prediction can be further improved by using data on cognitive performance, genotyping, and brain imaging. These models can be used to identify individuals at high risk of dementia in the population and are able to inform trial design.

Cerebral white matter free water: A sensitive biomarker of cognition and function

OBJECTIVE

To determine whether free water (FW) content, initially developed to correct metrics derived from diffusion tensor imaging and recently found to be strongly associated with vascular risk factors, may constitute a sensitive biomarker of white matter (WM) microstructural differences associated with cognitive performance but remains unknown.

METHODS

Five hundred thirty-six cognitively diverse individuals, aged 77 ± 8 years, received yearly comprehensive clinical evaluations and a baseline MRI examination of whom 224 underwent follow-up MRI. WM microstructural measures, including FW, fractional anisotropy, and mean diffusivity corrected for FW and WM hyperintensity burden were computed within WM voxels of each individual. Baseline and change in MRI metrics were then used as independent variables to explain baseline and change in episodic memory (EM), executive function (EF), and Clinical Dementia Rating (CDR) scores using linear, logistic, and Cox proportional-hazards regressions.

RESULTS

Higher baseline FW and WM hyperintensity were associated with lower baseline EM and EF, higher baseline CDR, accelerated EF and EM decline, and higher probability to transition to a more severe CDR stage (p values <0.01). Annual change in FW was also found to be associated with concomitant change in cognitive and functional performance (p values <0.01).

CONCLUSIONS

This study finds cross-sectional and longitudinal associations between FW content and trajectory of cognitive and functional performance in a large sample of cognitively diverse individuals. It supports the need to investigate the pathophysiologic process that manifests increased FW, potentially leading to more severe WM territory injury and promoting cognitive and functional decline.

Altered functional connectivity in patients with subcortical ischemic vascular disease: A resting-state fMRI study

Patients with subcortical ischemic vascular disease (SIVD) may hold a high risk of cognitive impairment (CI) by affecting the functional connectivity (FC) of resting-state networks (RSNs). Current studies have mainly focused on the patients with CI but have ignored the prodromal stage when people suffered subcortical vascular damage, but without CI. Independent component analysis (ICA) of rs-fMRI could detect altered FC in RSNs at the early stage of the disease. 81 SIVD patients with CI (SVCI = 29) and without CI (pre-SVCI = 25), and 27 normal controls (NCs) were scanned with rs-fMRI, analyzed by ICA and assessed by neuropsychological examinations. We found significantly altered FC within the RSNs of sensorimotor network (SMN), posterior default mode networks (pDMN), right frontoparietal network (rFPN) and language network (LN) (P < 0.05, AlphaSim corrected). The pre-SVCI group showed significantly increased FC in brain regions of the multiple RSNs when compared with the other two groups. The mean values extracted from the right inferior frontal gyrus (IFG.R) and the left posterior cingulate gyrus (PCG.L) were significantly correlated with clock drawing test (CDT). The right precentral/postcentral gyrus (PreCG.R/PoCG.R) and the right supramarginal gyrus (SMG.R) were positively correlated with Stroop-1 Test. We concluded the FC in RSNs had already been changed at the early stage of the disease as the maladaptive response or compensatory reallocation of the cognitive resources. The ICA of rs-fMRI can be applied as a potential approach to identify the underlying mechanisms of SIVD.

Deep/mixed cerebral microbleeds are associated with cognitive dysfunction through thalamocortical connectivity disruption: The Taizhou Imaging Study

Background

Cerebral microbleeds (CMBs) are considered to be risk factors for cognitive dysfunction. The specific pathology and clinical manifestations of CMBs are different based on their locations. We investigated the association between CMBs at different locations and cognitive dysfunction and explored the potential underlying pathways in a rural Han Chinese population.

Methods

We used baseline data from 562 community-dwelling adults (55–65 years old) in the Taizhou Imaging Study between 2013 and 2015. All individuals underwent multimodal brain magnetic resonance imaging (MRI) and 444 subjects completed neuropsychological tests: the Mini-Mental Status Examination and the Montreal Cognitive Assessment. Multinomial logistic regression was used to estimate the association between CMBs and cognitive dysfunction. The volume of brain regions and white matter microstructure were analyzed using Freesurfer and tract-based spatial statistics, respectively.

Results

CMBs were detected in 104 individuals (18.5%) in our study. Multinomial logistic regression found deep/mixed CMBs were associated with global cognitive dysfunction (OR 3.52; 95% CI 1.21 to 10.26), whereas lobar CMBs (OR 1.76; 95% CI 0.56 to 5.53) were not. Quantification of multimodal brain MRI showed that deep/mixed CMBs were accompanied by decreased thalamic volume and loss of fractional anisotropy of bilateral anterior thalamic radiations.

Conclusion

Deep/mixed CMBs were associated with cognitive dysfunction in this Chinese cross-sectional study. Disruption of thalamocortical connectivity might be a potential pathway underlying this relationship.

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Cerebral microbleeds (CMBs) are found in 18.5% of middle-aged Chinese population.

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Deep/mixed CMBs, not lobar CMBs, are associated with cognitive dysfunction.

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Atrophy and fiber connectivity disruption might be the underlying neural pathways.

Review of diffusion MRI studies in chronic white matter diseases

Diffusion MRI studies characterizing the changes in white matter (WM) due to vascular cognitive impairment, which includes all forms of small vessel disease are reviewed. We reviewed the usefulness of diffusion methods in discriminating the affected WM regions and its relation to cognitive impairment. These studies were categorized based on the diffusion MRI techniques used. The most common method was the diffusion tensor imaging, whereas other methods included diffusion weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and studies based on diffusion tractography. The diffusion measures showed correlation with cognitive scores and disease progression, with mean diffusivity being the most robust parameter. Future studies should focus on incorporating multi-compartment and higher order diffusion models, which can handle the presence of multiple and crossing fibers inside a voxel.

Alterations of White Matter Integrity in Subcortical Ischemic Vascular Disease with and Without Cognitive Impairment: a TBSS Study

Patients with subcortical ischemic vascular disease (SIVD) may exhibit a high risk of cognitive impairment (CI) by disruption of white matter (WM) integrity. Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore whole brain WM alterations at an asymptomatic stage of the disease, which might be correlated with underlying cognitive disorders. We aim to investigate alterations in WM microstructures and evaluate the relationships between the mean values of diffusion metrics (FA, MD, AD, and RD) and cognitive assessments in SIVD patients. Fifty SIVD patients with (SVCI, N = 25) and without (pre-SVCI, N = 25) cognitive impairments and normal controls (NC, N = 23) underwent DTI and neuropsychological examinations. DTI data were analyzed via TBSS to detect significant changes in WM tracts. Spearman correlation analysis was performed to evaluate relationships between the mean values of diffusion indices and the cognitive assessments. In general, extensive symmetrically altered areas that involved approximately the entire cerebral WM were noted in the pre-SVCI group but were less distinct than that noted in the SVCI group compared with NCs. The genu of corpus callosum exhibited the most damaged WM fiber. Throughout WM, FA was decreased, whereas MD, AD, and RD were increased. Some specific WM tracts in patient groups were significantly correlated with the severity of white matter hyperintensity (WMH), cognitive assessments about executive functions and processing speed. WM integrity has already been damaged at the pre-SVCI stage, which would be associate with future cognitive dysfunction. DTI could potentially establish early biomarkers to detect underlying mechanisms of SIVD.

Laboratory and Neuroimaging Biomarkers in Neuropsychiatric Systemic Lupus Erythematosus: Where Do We Stand, Where To Go?

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by multi-systemic involvement. Nervous system involvement in SLE leads to a series of uncommon and heterogeneous neuropsychiatric (NP) manifestations. Current knowledge on the underlying pathogenic processes and their subsequent pathophysiological changes leading to NP-SLE manifestations is incomplete. Several putative laboratory biomarkers have been proposed as contributors to the genesis of SLE-related nervous system damage. Alongside the laboratory biomarkers, several neuroimaging tools have shown to reflect the nature of tissue microstructural damage associated with SLE, and thus were suggested to contribute to the understanding of the pathophysiological changes and subsequently help in clinical decision making. However, the number of useful biomarkers in NP-SLE in clinical practice is disconcertingly modest. In some cases it is not clear whether the biomarker is truly involved in pathogenesis, or the result of non-specific pathophysiological changes in the nervous system (e.g., neuroinflammation) or whether it is the consequence of a concomitant underlying abnormality related to SLE activity. In order to improve the diagnosis of NP-SLE and provide a better targeted care to these patients, there is still a need to develop and validate a range of biomarkers that reliably capture the different aspects of disease heterogeneity. This article critically reviews the current state of knowledge on laboratory and neuroimaging biomarkers in NP-SLE, discusses the factors that need to be addressed to make these biomarkers suitable for clinical application, and suggests potential future research paths to address important unmet needs in the NP-SLE field.

"Liquid Biopsy" of White Matter Hyperintensity in Functionally Normal Elders

Background and Objective: In the aging brain, increased blood-brain barrier (BBB) leakage and white matter hyperintensity (WMH) on MRI are frequently presumed secondary to cerebral small vessel disease (cSVD) or endotheliopathy. We investigate this association in vivo by quantifying protein cargo from endothelial-derived exosomes (EDE), and comparing levels between two groups of functionally normal elders with and without WMH. In addition, we study associations of EDE proteins with upstream and downstream factors, such as inflammation and neurodegenerative changes, respectively.

Methods: Twenty six neurologically normal older adults completed general health questionnaires, neuropsychological and physical examinations, and brain MRI. WMH was visually graded with modified Fazekas score of 2 or greater used to classify 11 subjects as cases, and 15 without WMH as controls. Plasma total exosomes were precipitated and EDEs enriched by sequential immuno-precipitations. In addition, we quantified three inflammatory cytokines from plasma and imaging variables on MRI. Group means were compared, the discriminant functions of biomarkers calculated, and the association of EDE biomarkers with plasma inflammatory markers, cognition, and imaging outcomes assessed via regression modeling.

Results: Plasma levels of EDE cargo proteins GLUT1, LAT1, P-GP, and NOSTRIN were significantly higher in subjects with WMH in comparison to those without. In contrast, EDE levels of the marker with low expression in brain (VCAM1) were equal between groups. The effect sizes for each of the brain-expressed cargo proteins (GLUT1, LAT1, and P-GP) were such that age-adjusted logistic regressions revealed areas under the curve (AUC) with range of 0.82–0.89, differentiating subjects with WMH from those without. VCAM1 poorly discriminated between groups (AUC:0.55). Higher levels of all brain-expressed EDE proteins were also associated with lower cognitive function, unrelated to burden of WMH. Levels of LAT1 and P-GP were significantly inversely associated with global gray matter volumes, and EDE GLUT1, LAT-1, and P-GP concentrations were significantly associated with systemic IL-6 levels.

Conclusion: In a case control study of clinically normal adults with and without WMH, concentrations of EDE proteins were significantly higher in subjects with WMH in comparison to controls. This work is a first step toward in vivo dissection of molecular changes in endothelia of functionally normal subjects with radiographic evidence of age-associated white matter disease.

Texture Analysis of T1-Weighted and Fluid-Attenuated Inversion Recovery Images Detects Abnormalities That Correlate With Cognitive Decline in Small Vessel Disease

Supplemental Digital Content is available in the text.

Background and Purpose—

Magnetic resonance imaging may be useful to assess disease severity in cerebral small vessel disease (SVD), identify those individuals who are most likely to progress to dementia, monitor disease progression, and act as surrogate markers to test new therapies. Texture analysis extracts information on the relationship between signal intensities of neighboring voxels. A potential advantage over techniques, such as diffusion tensor imaging, is that it can be used on clinically obtained magnetic resonance sequences. We determined whether texture parameters (TP) were abnormal in SVD, correlated with cognitive impairment, predicted cognitive decline, or conversion to dementia.

Methods—

In the prospective SCANS study (St George’s Cognition and Neuroimaging in Stroke), we assessed TP in 121 individuals with symptomatic SVD at baseline, 99 of whom attended annual cognitive testing for 5 years. Conversion to dementia was recorded for all subjects during the 5-year period. Texture analysis was performed on fluid-attenuated inversion recovery and T1-weighted images. The TP obtained from the SVD cohort were cross-sectionally compared with 54 age-matched controls scanned on the same magnetic resonance imaging system.

Results—

There were highly significant differences in several TP between SVD cases and controls. Within the SVD population, TP were highly correlated to other magnetic resonance imaging parameters (brain volume, white matter lesion volume, lacune count). TP correlated with executive function and global function at baseline and predicted conversion to dementia, after controlling for age, sex, premorbid intelligence quotient, and magnetic resonance parameters.

Conclusions—

TP, which can be obtained from routine clinical images, are abnormal in SVD, and the degree of abnormality correlates with executive dysfunction and global cognition at baseline and decline during 5 years. TP may be useful to assess disease severity in clinically collected data. This needs testing in data clinically acquired across multiple sites.