Disruption of rich club organisation in cerebral small vessel disease

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

BACKGROUND

White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes.

METHODS

40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test.

RESULTS

Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data.

CONCLUSION

WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.

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.

Altered morphological connectivity mediated white matter hyperintensity-related cognitive impairment

White matter hyperintensities (WMH) are widely observed in older adults and are closely associated with cognitive impairment. However, the underlying neuroimaging mechanisms of WMH-related cognitive dysfunction remain unknown. This study recruited 61 WMH individuals with mild cognitive impairment (WMH-MCI, n = 61), 48 WMH individuals with normal cognition (WMH-NC, n = 48) and 57 healthy control (HC, n = 57) in the final analyses. We constructed morphological networks by applying the Kullback-Leibler divergence to estimate interregional similarity in the distributions of regional gray matter volume. Based on morphological networks, graph theory was applied to explore topological properties, and their relationship to WMH-related cognitive impairment was assessed. There were no differences in small-worldness, global efficiency and local efficiency. The nodal local efficiency, degree centrality and betweenness centrality were altered mainly in the limbic network (LN) and default mode network (DMN). The rich-club analysis revealed that WMH-MCI subjects showed lower average strength of the feeder and local connections than HC (feeder connections: P = 0.034; local connections: P = 0.042). Altered morphological connectivity mediated the relationship between WMH and cognition, including language (total indirect effect: -0.010; 95 % CI: -0.024, -0.002) and executive (total indirect effect: -0.010; 95 % CI: -0.028, -0.002) function. The altered topological organization of morphological networks was mainly located in the DMN and LN and was associated with WMH-related cognitive impairment. The rich-club connection was relatively preserved, while the feeder and local connections declined. The results suggest that single-subject morphological networks may capture neurological dysfunction due to WMH and could be applied to the early imaging diagnostic protocol for WMH-related cognitive impairment.

New horizons in cognitive and functional impairment as a consequence of cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a frequent finding in imaging of the brain in older adults, especially in the concomitance of cardiovascular disease risk factors. Despite the well-established link between cSVD and (vascular) cognitive impairment (VCI), it remains uncertain how and when these vascular alterations lead to cognitive decline. The extent of acknowledged markers of cSVD is at best modestly associated with the severity of clinical symptoms, but technological advances increasingly allow to identify and quantify the extent and perhaps also the functional impact of cSVD more accurately. This will facilitate a more accurate diagnosis of VCI, against the backdrop of concomitant other neurodegenerative pathology, and help to identify persons with the greatest risk of cognitive and functional deterioration. In this study, we discuss how better assessment of cSVD using refined neuropsychological and comprehensive geriatric assessment as well as modern image analysis techniques may improve diagnosis and possibly the prognosis of VCI. Finally, we discuss new avenues in the treatment of cSVD and outline how these contemporary insights into cSVD can contribute to optimise screening and treatment strategies in older adults with cognitive impairment and multimorbidity.

Advanced MRI in cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. This review summarizes recent developments in advanced neuroimaging of cSVD with a focus on clinical and research applications. In the first section, we highlight how advanced structural imaging techniques, including diffusion magnetic resonance imaging (MRI), enable improved detection of tissue damage, including characterization of tissue appearing normal on conventional MRI. These techniques enable progression to be monitored and may be useful as surrogate endpoint in clinical trials. Quantitative MRI, including iron and myelin imaging, provides insights into tissue composition on the molecular level. In the second section, we cover how advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, which could be targeted in mechanistic research and early-stage intervention trials. Such techniques include the use of dynamic contrast enhanced MRI to measure blood-brain barrier permeability, and MRI methods to assess cerebrovascular reactivity. In the third section, we discuss how the increased spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of perforating arteries, and flow velocity and pulsatility within them. The advanced MRI techniques we describe are providing novel pathophysiological insights in cSVD and allow improved quantification of disease burden and progression. They have application in clinical trials, both in assessing novel therapeutic mechanisms, and as a sensitive endpoint to assess efficacy of interventions on parenchymal tissue damage. We also discuss challenges of these advanced techniques and suggest future directions for research.

Impact of White Matter Hyperintensity and Age on Gait Parameters in Patients With Cerebral Small Vessel Disease

OBJECTIVES

This study aimed to investigate the effect of white matter hyperintensity (WMH), a common cerebral small vessel disease (CSVD) imaging marker, and age on gait parameters in middle-aged and geriatric populations.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

A total of 1076 participants (62.9% female; age 61.0 ± 9.3 years), who visited the neurology clinic or obtained a physical check-up from the Affiliated Hospital of Guizhou Medical University. In total, 883 patients with WMH and 193 healthy controls were included in this study.

METHODS

The Fazekas scores of patients with CSVD were used to assess the burden of WMH. Based on the Fazekas scores, all participants were divided into 4 groups: 553 patients with Fazekas I, 257 patients with Fazekas II, 73 patients with Fazekas III, and 193 controls. Gait parameters, including step speed, frequency, length, width, stance time, and swing time, were quantitatively assessed using a vision-based artificial intelligence gait analyzer (SAIL system). The relationships among the Fazekas scores, age, and gait parameters were analyzed.

RESULTS

Step speed, step length, step width, stance time, and swing time were significantly different among the 4 groups. Furthermore, Fazekas scores and age were both associated with gait parameters, including step speed, step length, stance time, and swing time. The Fazekas scores were associated with step width, whereas age was not. Age was associated with step frequency, whereas Fazekas scores were not.

CONCLUSIONS AND IMPLICATIONS

Fazekas score and age are useful for evaluating gait parameters in patients with CSVD. Emerging WMH (such as Fazekas Ⅰ) could be a clinical warning sign of gait disturbance in a geriatric population.

Improved sensitivity and precision in multicentre diffusion MRI network analysis using thresholding and harmonization

PURPOSE

To investigate if network thresholding and raw data harmonization improve consistency of diffusion MRI (dMRI)-based brain networks while also increasing precision and sensitivity to detect disease effects in multicentre datasets.

METHODS

Brain networks were reconstructed from dMRI of five samples with cerebral small vessel disease (SVD; 629 patients, 166 controls), as a clinically relevant exemplar condition for studies on network integrity. We evaluated consistency of network architecture in age-matched controls, by calculating cross-site differences in connection probability and fractional anisotropy (FA). Subsequently we evaluated precision and sensitivity to disease effects by identifying connections with low FA in sporadic SVD patients relative to controls, using more severely affected patients with a pure form of genetically defined SVD as reference.

RESULTS

In controls, thresholding and harmonization improved consistency of network architecture, minimizing cross-site differences in connection probability and FA. In patients relative to controls, thresholding improved precision to detect disrupted connections by removing false positive connections (precision, before: 0.09-0.19; after: 0.38-0.70). Before harmonization, sensitivity was low within individual sites, with few connections surviving multiple testing correction (k = 0-25 connections). Harmonization and pooling improved sensitivity (k = 38), while also achieving higher precision when combined with thresholding (0.97).

CONCLUSION

We demonstrated that network consistency, precision and sensitivity to detect disease effects in SVD are improved by thresholding and harmonization. We recommend introducing these techniques to leverage large existing multicentre datasets to better understand the impact of disease on brain networks.

Total Burden of Cerebral Small Vessel Disease on MRI May Predict Cognitive Impairment in Parkinson’s Disease

(1) Objective: to investigate the association between the total burden of cerebral small vessel disease (CSVD) and cognitive function in Parkinson’s disease (PD). (2) Methods: this retrospective study compared clinical and neuroimaging characteristics of 122 PD patients to determine the association between cognitive decline and total burden of CSVD in PD. All patients underwent brain MRI examinations, and their total CSVD burden scores were evaluated by silent lacunar infarction (SLI), cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS). The cognitive function was assessed by administering Mini-Mental State Examination (MMSE). Receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC) were performed to quantify the accuracy of the total burden of CSVD and PVH in discriminating PD patients with or without cognitive impairment. (3) Results: the PD patients with cognitive impairment had a significantly higher SLI, CMB, periventricular hyperintensities (PVH), deep white matter hyperintensities (DWMH), enlarged perivascular spaces of basal ganglia (BG-EPVS), and the total CSVD score compared with no cognitive impairment. Total CSVD score and MMSE had a significant negative correlation (r = −0. 483). Furthermore, total burden of CSVD and PVH were the independent risk factors of cognitive impairment in PD, and their good accuracy in discriminating PD patients with cognitive impairment from those with no cognitive impairment was confirmed by the results of ROC curves. (4) Conclusions: total burden of CSVD tightly linked to cognitive impairment in PD patients. The total burden of CSVD or PVH may predict the cognitive impairment in PD.

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.

Iron deposition in the precuneus is correlated with mild cognitive impairment in patients with cerebral microbleeds: A quantitative susceptibility mapping study

Purpose

The purpose of this study was to define whether mild cognitive impairment (MCI) is associated with iron deposition in rich-club nodes distant from cerebral microbleeds (CMBs) in patients with cerebral small vessel disease (CSVD).

Methods

A total of 64 participants underwent magnetic resonance imaging (MRI) scanning and were separated into three groups, namely, CMB(+), CMB(–), and healthy controls (HCs). We compared their characteristics and susceptibility values of rich-club nodes [e.g., superior frontal gyrus (SFG), precuneus, superior occipital gyrus (SOG), thalamus, and putamen]. We then divided the CMB(+) and CMB(–) groups into subgroups of patients with or without MCI. Then, we analyzed the relationship between iron deposition and MCI by comparing the susceptibility values of rich-club nodes. We assessed cognitive functions using the Montreal Cognitive Assessment (MoCA) and quantified iron content using quantitative susceptibility mapping (QSM).

Results

In the putamen, the CMB(+) and CMB(–) groups had significantly different susceptibility values. Compared with the HCs, the CMB(+) and CMB(–) groups had significantly different susceptibility values for the SFG and SOG. In addition, we found significant differences in the putamen susceptibility values of the CMB(+)MCI(+) group and the two CMB(–) groups. The CMB(+)MCI(+) and CMB(+)MCI(–) groups had significantly different precuneus susceptibility values. The binary logistic regression analysis revealed that only higher susceptibility values of precuneus were associated with a cognitive decline in patients with CMBs, and it indicated statistical significance.

Conclusion

Iron deposition in the precuneus is an independent risk factor for MCI in patients with CMBs. CMBs might influence iron content in remote rich-club nodes and be relevant to MCI.

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.

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.

Telomere length and brain aging: A systematic review and meta-analysis

The current evidence on the association of leukocyte telomere length (LTL) with age-related structural and cognitive changes in the brain is mixed. Herein conforming to PRISMA 2020 guidelines, we performed a systematic review and meta-analysis using data from 27 observational studies in non-demented individuals. We used effect size and p-value based meta-analysis methods considering marked heterogeneity among studies. We found that the longer LTL was associated with higher brain volume (β = 0.43, 95%CI: 0.36-0.50%, p = 0.008, N = 1102) and with higher global cognition (β = 0.01; 95%CI: 0.00-0.02, p = 0.03, N = 19609) by effect size based meta-analysis and with brain volume, hippocampal volume, global cognition, cognitive domains of attention/speed as well as executive functions by p-value based meta-analysis. No significant association of LTL with brain white matter hyperintensities was detected. Furthermore, the evidence strongly suggests a subgroup-specific canonical effect of telomeres, notably in older individuals and females. In conclusion, we provide meta-analytic evidence on the beneficial effect of telomeres on brain structure as well as cognition and advocate for a beneficial subgroup-specific effect that warrants further attention.

Systematic validation of structural brain networks in cerebral small vessel disease

Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability.Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.

Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy

White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. Two hundred and fifty‐four participants from the Coronary Artery Risk Development in Young Adults study were selected and stratified by WMH burden into Lo‐WMH (mean age = 50 ± 3.5 years) and Hi‐WMH (mean age = 51 ± 3.7 years) groups of equal size. We constructed group‐level covariance networks based on cerebral blood flow (CBF) and gray matter volume (GMV) maps across 74 gray matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo‐ and Hi‐WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no between‐group differences in either CBF or GMV covariance networks. In contrast, we found between‐group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence that WMH‐related network alterations are present at midlife.

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.

Aberrant rich club organization in patients with obsessive-compulsive disorder and their unaffected first-degree relatives

Recent studies suggested that the rich club organization promoting global brain communication and integration of information, may be abnormally increased in obsessive-compulsive disorder (OCD). However, the structural and functional basis of this organization is still not very clear. Given the heritability of OCD, as suggested by previous family-based studies, we hypothesize that aberrant rich club organization may be a trait marker for OCD. In the present study, 32 patients with OCD, 30 unaffected first-degree relatives (FDR) and 32 healthy controls (HC) underwent diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI). We examined the structural rich club organization and its interrelationship with functional coupling. Our results showed that rich club and peripheral connection strength in patients with OCD was lower than in HC, while it was intermediate in FDR. Finally, the coupling between structural and functional connections of the rich club, was decreased in FDR but not in OCD relative to HC, which suggests a buffering mechanism of brain functions in FDR. Overall, our findings suggest that alteration of the rich club organization may reflect a vulnerability biomarker for OCD, possibly buffered by structural and functional coupling of the rich club.

Rich-Club Analysis of the Structural Brain Network in Cases with Cerebral Small Vessel Disease and Depression Symptoms

BACKGROUND

Altered white matter brain networks have been extensively studied in cerebral small vessel disease (SVD). However, there exists currently a deficiency of comprehending the performance of changes within the structural networks of the brain in cases with cerebral SVD and depression symptoms. The main aim of the present research is to study the network topology behaviors and features of rich-club organization in SVD patients using graph theory and diffusion tensor imaging (DTI) to characterize changes in the microstructure of the brain.

METHODS

DTI datasets were acquired from 26 SVD patients with symptoms of depression (SVD + D) and 26 SVD patients without symptoms of depression (SVD - D), and a series of neuropsychological assessments were completed. A structural network was created using a deterministic fiber tracking method. The analysis of rich-club was performed in company with analysis of the global network features of the network to characterize the topological properties of all subjects.

RESULTS

DTI data were obtained from SVD patients who manifested symptoms of depression (SVD + D) and from control SVD patients (SVD - D). In comparison with SVD - D patients, SVD + D cases demonstrated a diminished coefficient of clustering along with lower global efficiencies and longer path length characteristics. Rich-club analysis showed SVD + D patients had decreased feeder connectivity and local connectivity strengths compared to SVD - D patients. Our data also showed that the feeder connections in the brain correlated significantly with the severity of depression in SVD + D patients.

CONCLUSIONS

Our study revealed that SVD patients with depressive symptoms have disrupted white matter networks that characteristically have reduced network efficiency compared to the networks in other SVD patients. Disrupted information interactions among the regions of nonrich-club and rich-club in SVD cases are related to the severity of depression. Our data suggest that DTI may be utilized as an appropriate biomarker for the diagnosis of depression in comorbid SVD patients.

Associations among vascular risk factors, neuroimaging biomarkers, and cognition: Preliminary analyses from the Multi-Ethnic Study of Atherosclerosis (MESA)

INTRODUCTION

Little is known about how antecedent vascular risk factor (VRF) profiles impact late-life brain health.

METHODS

We examined baseline VRFs, and cognitive testing and neuroimaging measures (β-amyloid [Aβ] PET, MRI) in a diverse longitudinal cohort (N = 159; 50% African-American, 50% White) from Wake Forest's Multi-Ethnic Study of Atherosclerosis Core.

RESULTS

African-Americans exhibited greater baseline Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE), Framingham stroke risk profile (FSRP), and atherosclerotic cardiovascular disease risk estimate (ASCVD) scores than Whites. We observed no significant racial differences in Aβ positivity, cortical thickness, or white matter hyperintensity (WMH) volume. Higher baseline VRF scores were associated with lower cortical thickness and greater WMH volume, and FSRP and CAIDE were associated with Aβ. Aβ was cross-sectionally associated with cognition, and all imaging biomarkers were associated with greater 6-year cognitive decline.

DISCUSSION

Results suggest the convergence of multiple vascular and Alzheimer's processes underlying neurodegeneration and cognitive decline.

Predicted disconnectome associated with progressive periventricular white matter ischemia

We used a virtual lesion DTI fiber tracking approach with healthy subject DTI data and simulated periventricular white matter (PVWM) lesion masks to predict the sequence of connectivity changes associated with progressive PVWM ischemia. We found that the optic radiations, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, corpus callosum, temporopontine tract and fornix were affected in early simulated ischemic injury, and that the connectivity of subcortical, cerebellar, and visual regions were significantly disrupted with increasing simulated lesion severity. The results of this study provide insights into the spatial-temporal changes of the brain structural connectome under progressive PVWM ischemia. The virtual lesion approach provides a meaningful proxy to the spatial-temporal changes of the brain's structural connectome and can be used to further characterize the cognitive sequelae of progressive PVWM ischemia in both normal aging and dementia.

Disrupted Structural Brain Connectome Is Related to Cognitive Impairment in Patients With Ischemic Leukoaraiosis

Ischemic leukoaraiosis (ILA) is related to cognitive impairment and vascular dementia in the elderly. One possible mechanism could be the disruption of white matter (WM) tracts and network function that connect distributed brain regions involved in cognition. The purpose of this study was to investigate the relationship between structural connectome and cognitive functions in ILA patients. A total of 89 patients with ILA (Fazekas score ≥ 3) and 90 healthy controls (HCs) underwent comprehensive neuropsychological examinations and diffusion tensor imaging scans. The tract-based spatial statistics approach was employed to investigate the WM integrity. Graph theoretical analysis was further applied to construct the topological architecture of the structural connectome in ILA patients. Partial correlation analysis was used to investigate the relationships between network measures and cognitive performances in the ILA group. Compared with HCs, the ILA patients showed widespread WM integrity disruptions. The ILA group displayed increased characteristic path length (L _p) and decreased global network efficiency at the level of the whole brain relative to HCs, and reduced nodal efficiencies, predominantly in the frontal-subcortical and limbic system regions. Furthermore, these structural connectomic alterations were associated with cognitive impairment in ILA patients. The association between WM changes (i.e., fractional anisotropy and mean diffusivity measures) and cognitive function was mediated by the structural connectivity measures (i.e., local network efficiency and L _p). In conclusion, cognitive impairment in ILA patients is related to microstructural disruption of multiple WM fibers and topological disorganization of structural networks, which have implications in understanding the relationship between ILA and the possible attendant cognitive impairment.

Altered white matter structural networks in drug-naïve patients with obsessive-compulsive disorder

White matter (WM) alteration is considered to be a vital neurological mechanism of obsessive-compulsive disorder (OCD). However, little is known regarding the changes in topological organization of WM structural network in OCD. We acquired diffusion tensor imaging (DTI) datasets from 28 drug-naïve OCD patients and 28 well-matched healthy controls (HC). A deterministic fiber tracking approach was used to construct the whole-brain structural connectome. Group differences in global and nodal topological properties as well as rich-club organizations were compared by using graph theory analysis. The relationship between the altered network metrics and the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was calculated. Compared with controls, OCD patients exhibited a significantly decreased small-worldness (σ), normalized clustering coefficient (γ) and shortest path length (L_p), as well as an increased global efficiency (E_glob). The nodal efficiency (E_nodal) was found to be reduced in the left middle frontal gyrus, and increased in the right parahippocampal gyrus and bilateral putamen in OCD patients. Besides, OCD patients showed increased rich-club, feeder and local connection strength, and the connection strength of the rich-club was positively correlated with the total Y-BOCS score. Our findings emphasized a central role for the complicatedly changed topological architecture of brain structural networks in the pathological mechanism underlying OCD.

Cognition mediates the relation between structural network efficiency and gait in small vessel disease

Cerebral small vessel disease (SVD), including white matter hyperintensities (WMH), microbleeds, lacunes, was related to gait disturbances, while the underlying mechanism is unclear. Here, we investigated the relation between structural network efficiency, cognition and gait performance in 272 elderly subjects with SVD. All participants underwent 1.5 T MRI, gait and neuropsychological assessment. Conventional MRI markers for SVD, i.e. WMH volume, number of lacunes and microbleeds, were assessed. Diffusion tensor imaging-based tractography was used to reconstruct the brain network for each individual, followed by graph-theoretical analyses to compute the well-established network measure, global efficiency. We found that lower global efficiency was associated with worse gait performance, including slower gait speed and shorter stride length, independent of conventional MRI markers for SVD. This association was partly mediated via cognitive function. We identified subnetworks of white matter connections associated with gait and cognition, characterized by dominant involvement of frontal tracts. Our findings suggest that network disruption is associated with gait disturbances through cognitive dysfunction in elderly with SVD. Gait is a highly cognitive process and the crucial role of cognition should be considered when investigating gait disturbances in the elderly with SVD.

Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy

Previous neuroimaging studies revealed radiation-induced brain injury in patients with nasopharyngeal carcinoma (NPC) in the years after radiotherapy (RT). These injuries may be associated with structural and functional alterations. However, differences in the brain structural connectivity of NPC patients at different times after RT, especially in the early-delayed period, remain unclear. We acquired diffusion tensor imaging (DTI) data from three groups of NPC patients, 25 in the pre-RT (before RT) group, 22 in the early-delayed (1-6 months) period (post-RT-ED) group, and 33 in the late-delayed (>6 months) period (post-RT-LD) group. Then, we constructed brain white matter (WM) structural networks and used graph theory to compare their between-group differences. The NPC patients in the post-RT-ED group showed decreased global properties when compared with the pre-RT group. We also detected the nodes with between-group differences in nodal parameters. The nodes that differed between the post-RT-ED and pre-RT groups were mainly located in the default mode (DMN) and central executive networks (CEN); those that differed between the post-RT-LD and pre-RT groups were located in the limbic system; and those that differed between the post-RT-LD and post-RT-ED groups were mainly in the DMN. These findings may indicate that radiation-induced brain injury begins in the early-delayed period and that a reorganization strategy begins in the late-delayed period. Our findings may provide new insight into the pathogenesis of radiation-induced brain injury in normal-appearing brain tissue from the network perspective.

White Matter Alterations Between Brain Network Hubs Underlie Processing Speed Impairment in Patients With Schizophrenia

Processing speed (PS) impairment is one of the most severe and common cognitive deficits in schizophrenia. Previous studies have reported correlations between PS and white matter diffusion properties, including fractional anisotropy (FA), in several fiber bundles in schizophrenia, suggesting that white matter alterations could underpin decreased PS. In schizophrenia, white matter alterations are most prevalent within inter-hub connections of the rich club. However, the spatial and topological characteristics of this association between PS and FA have not been investigated in patients. In this context, we tested whether structural connections comprising the rich club network would underlie PS impairment in 298 patients with schizophrenia or schizoaffective disorder and 190 healthy controls from the Australian Schizophrenia Research Bank. PS, measured using the digit symbol coding task, was largely (Cohen’s d = 1.33) and significantly (P < .001) reduced in the patient group when compared with healthy controls. Significant associations between PS and FA were widespread in the patient group, involving all cerebral lobes. FA was not associated with other cognitive measures of phonological fluency and verbal working memory in patients, suggesting specificity to PS. A topological analysis revealed that despite being spatially widespread, associations between PS and FA were over-represented among connections forming the rich club network. These findings highlight the need to consider brain network topology when investigating high-order cognitive functions that may be spatially distributed among several brain regions. They also reinforce the evidence that brain hubs and their interconnections may be particularly vulnerable parts of the brain in schizophrenia.

Abnormal Degree Centrality in White Matter Hyperintensities: A Resting-State Functional Magnetic Resonance Imaging Study

Background: White matter hyperintensities (WMHs) are a common occurrence with aging and are associated with cognitive impairment. However, the neurobiological mechanisms of WMHs remain poorly understood. Functional magnetic resonance imaging (fMRI) is a prominent tool that helps in non-invasive examinations and is increasingly used to diagnose neuropsychiatric diseases. Degree centrality (DC) is a common and reliable index in fMRI, which counts the number of direct connections for a given voxel in a network and reflects the functional connectivity within brain networks. We explored the underlying mechanism of cognitive impairment in WMHs from the perspective of DC. Methods: A total of 104 patients with WMHs and 37 matched healthy controls (HCs) were enrolled in the current study. All participants underwent individual and overall cognitive function tests and resting-state fMRI (rs-fMRI). WMHs were divided into three groups (39 mild WMHs, 37 moderate WMHs, and 28 severe WMHs) according to their Fazekas scores, and the abnormal DC values in the WMHs and HCs groups were analyzed. Results: There was a significant difference in the right inferior frontal orbital gyrus and left superior parietal gyrus between the WMHs and HCs groups. The functional connectivity between the right inferior frontal orbital gyrus and left inferior temporal gyrus, left superior parietal gyrus, and left parietal inferior gyrus was also different in the WMHs group. Conclusion: The change in DC value may be one of the underlying mechanisms of cognitive impairment in individuals with WMHs, which provides us with a new approach to delaying cognitive impairment in WMHs.

Structural Brain Network Disruption at Preclinical Stage of Cognitive Impairment Due to Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is a common disease among elderly individuals and recognized as a major cause of vascular cognitive impairment. Recent studies demonstrated that CSVD is a disconnection syndrome. However, due to the covert neurological symptoms and subtle changes in clinical performance, the connection alterations during the stage of preclinical cognitive impairment (PCI) and mild cognitive impairment (MCI) are usually neglected and still largely unknown. Using diffusion tensor imaging (DTI), we investigated the early structural network changes in PCI and MCI patients. The PCI group demonstrated well preserved rich-club organization, less nodal strength loss, and disruption of connections centered in the feeder and local connections. Nevertheless, the MCI group manifested a disruption in the rich-club organization, a worse nodal strength loss especially in hub nodes, and an overall disturbance in rich-club, feeder and local connections. Moreover, in all CSVD patients, the strength of the rich-club, feeder and local connections was significantly correlated with multiple cognitive scores, especially in attention, executive, and memory domains; while in MCI patients, only the strength of the rich-club connections was significantly correlated with cognition. Furthermore, based on the network-based statistic analysis, we also identified distinct network component disruption pattern between the PCI group and the MCI group, validating the results described above. These results suggest a disruption pattern from peripheral to central connections with the change of cognitive status, shedding light on the early identification and the underlying disruption of CSVD.

Functional Disorganization of Small-World Brain Networks in Patients With Ischemic Leukoaraiosis

Cognitive impairment is a key clinical feature of ischemic leukoaraiosis (ILA); however, the underlying neurobiological mechanism is still unclear. ILA has been associated with widespread gray and white matter (WM) damage mainly located in cortical-cortical and cortico-subcortical pathways. A total of 36 patients with ILA (Fazekas rating score ≥2) and 31 healthy controls (HCs) underwent comprehensive neuropsychological assessments (covering four cognitive domains, i.e., information processing speed, episodic memory, executive and visuospatial function) and resting-state functional MRI scans. Graph theory-based analyses were employed to explore the topological organization of the brain connectome in ILA patients, and we further sought to explore the associations of connectome-based metrics and neuropsychological performances. An efficient small-world architecture in the functional brain connectome was observed in the ILA and control groups. Moreover, compared with the HCs, the ILA patients showed increased path length and decreased network efficiency (i.e., global and local efficiency) in their functional brain networks. Further network-based statistic (NBS) analysis revealed a functional-disconnected network in ILA, which is comprised of functional connections linking different brain modules (i.e., default mode, frontoparietal, ventral attention and limbic systems) and connections within single modules (i.e., ventral attention and limbic systems). Intriguingly, the abnormal network metrics correlated with cognitive deficits in ILA patients. Therefore, our findings provide further evidence to support the concept that ILA pathologies could disrupt brain connections, impairing network functioning, and cognition via a “disconnection syndrome.”

Alterations and test-retest reliability of functional connectivity network measures in cerebral small vessel disease

While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test-retest reliability of functional network measures in sporadic SVD patients participating in a high-frequency (monthly) serial imaging study (RUN DMC-InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto-parietal task control network, FPCN; visual network, VN; hand somatosensory-motor network, HSMN) were constructed based on resting-state multi-band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = -.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = -.20, p = .047; direct path: std. beta = -.19, p = .25; total effect: std. beta = -.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high-frequency serial MRI dataset of the sporadic SVD patients revealed poor test-retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD-related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age-related comorbidities, impedes the analysis in elderly SVD patients.

Rich-club in the brain's macrostructure: Insights from graph theoretical analysis

The brain is a complex network. Growing evidence supports the critical roles of a set of brain regions within the brain network, known as the brain’s cores or hubs. These regions require high energy cost but possess highly efficient neural information transfer in the brain’s network and are termed the rich-club. The rich-club of the brain network is essential as it directly regulates functional integration across multiple segregated regions and helps to optimize cognitive processes. Here, we review the recent advances in rich-club organization to address the fundamental roles of the rich-club in the brain and discuss how these core brain regions affect brain development and disorders. We describe the concepts of the rich-club behind network construction in the brain using graph theoretical analysis. We also highlight novel insights based on animal studies related to the rich-club and illustrate how human studies using neuroimaging techniques for brain development and psychiatric/neurological disorders may be relevant to the rich-club phenomenon in the brain network.

Structural network efficiency predicts cognitive decline in cerebral small vessel disease

Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment. Earlier studies showed that a higher degree of white matter network damage, indicated by lower global efficiency (a graph-theory measure assessing efficiency of network information transfer), was associated with lower scores on cognitive performance independent of MRI markers for SVD. However, it is unknown whether this global efficiency index is the strongest predictor for cognitive impairment, as there is a wide range of network measures. Here, we investigate which network measure is the most informative in explaining baseline cognitive performance and decline over a period of 8.7 years in SVD. We used data from the Radboud University Nijmegen Diffusion tensor and MRI Cohort (RUN DMC), which included 436 participants without dementia (65.2 ± 8.8 years) but with evidence of SVD on neuroimaging. Binarized and weighted structural brain networks were reconstructed using diffusion tensor imaging and deterministic streamlining. Using graph-theory, we calculated 21 global network measures and performed linear regression analyses, elastic net analysis and linear mixed effect models to compare these measures. All analyses were adjusted for potential confounders (age, sex, educational level, depressive symptoms and conventional SVD MRI-markers (e.g. white matter hyperintensities (WMH), lacunes of presumed vascular origin and microbleeds). The elastic net analyses showed that, at baseline, global efficiency had the strongest association with cognitive index (CI), while characteristic path length showed the strongest association with psychomotor speed (PMS) and memory. Binary local efficiency showed the strongest association with attention & executive function (A&EF). In addition, linear mixed-effect models demonstrated that baseline global efficiency predicts decline in CI (χ2(1) = 8.18, p = 0.004),PMS (χ2(1) = 7.75, p = 0.005), memory (χ2(1) = 27.28, p = 0.000) over time and that binary local efficiency predicts decline in A&EF (χ2(1) = 8.66, p = 0.003) over time. Our results suggest that among all network measures, network efficiency measures, i.e. global efficiency and local efficiency, are the strongest predictors for cognitive functions at cross-sectional level and also predict faster cognitive decline in SVD, which is in line with earlier findings. These findings suggests that in our study sample network efficiency measures are the most suitable surrogate markers for cognitive performance in patients with cerebral SVD among all network measures and MRI markers, and play a key role in the genesis of cognitive decline in SVD.

Network Localisation of White Matter Damage in Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is a widespread condition associated to stroke, dementia and depression. To shed light on its opaque pathophysiology, we conducted a neuroimaging study aiming to assess the location of CSVD-induced damage in the human brain network. Structural connectomes of 930 subjects of the Hamburg City Health Study were reconstructed from diffusion weighted imaging. The connectome edges were partitioned into groups according to specific schemes: (1) connection to grey matter regions, (2) course and length of underlying streamlines. Peak-width of skeletonised mean diffusivity (PSMD) - a surrogate marker for CSVD - was related to each edge group's connectivity in a linear regression analysis allowing localisation of CSVD-induced effects. PSMD was associated with statistically significant decreases in connectivity of most investigated edge groups except those involved in connecting limbic, insular, temporal or cerebellar regions. Connectivity of interhemispheric and long intrahemispheric edges as well as edges connecting subcortical and frontal brain regions decreased most severely with increasing PSMD. In conclusion, MRI findings of CSVD are associated with widespread impairment of structural brain network connectivity, which supports the understanding of CSVD as a global brain disease. The pattern of regional preference might provide a link to clinical phenotypes of CSVD.

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.

Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease

A popular solution to control for edge density variability in structural brain network analysis is to threshold the networks to a fixed density across all subjects. However, it remains unclear how this type of thresholding affects the basic network architecture in terms of edge weights, hub location, and hub connectivity and, especially, how it affects the sensitivity to detect disease-related abnormalities. We investigated these two questions in a cohort of patients with cerebral small vessel disease and age-matched controls. Brain networks were reconstructed from diffusion magnetic resonance imaging data using deterministic fiber tractography. Networks were thresholded to a fixed density by removing edges with the lowest number of streamlines. We compared edge length (mm), fractional anisotropy (FA), proportion of hub connections, and hub location between the unthresholded and the thresholded networks of each subject. Moreover, we compared weighted graph measures of global and local connectivity obtained from the (un)thresholded networks between patients and controls. We performed these analyses over a range of densities (2-20%). Results indicate that fixed-density thresholding disproportionally removes edges composed of long streamlines, but is independent of FA. The edges removed were not preferentially connected to hub or nonhub nodes. Over half of the original hubs were reproducible when networks were thresholded to a density ≥10%. Furthermore, the between-group differences in graph measures observed in the unthresholded network remained present after thresholding, irrespective of the chosen density. We therefore conclude that moderate fixed-density thresholds can successfully be applied to control for the effects of density in structural brain network analysis.

Fiber Connectivity Density in Cerebral Small-Vessel Disease Patients With Mild Cognitive Impairment and Cerebral Small-Vessel Disease Patients With Normal Cognition

Abnormal structural connectivity of cerebral small-vessel disease (CSVD) is associated with cognitive impairment. But the different characteristics of structural connectivity have not been elucidated in early CSVD patients. The current study aimed to investigate the potential differences of structural connectivity in CSVD patients with mild cognitive impairment (MCI) and CSVD patients with normal cognition. Twenty-two CSVD patients with MCI, 34 CSVD patients with normal cognition, and 35 controls, who were age, sex, and education matched underwent diffusion tensor imaging and high resolution T1-weighted imaging. Clinical characteristics, lacunar infarct volume, white matter hyperintensity (WMH) volume, and global atrophy were quantitatively evaluated. Maps of fiber connectivity density (FiCD) were constructed and compared across groups in vertex levels. Pearson correlation was used to estimate the imaging–clinical relationships with control of general characteristics. CSVD patients with MCI had higher lesion load of WMH and lacunar infarcts, and correspondingly lower global FiCD value than CSVD patients with normal cognition (P < 0.01). Lacunar infarct (r = −0.318, P < 0.01) and WMH (r = −0.400, P < 0.01), but not global atrophy, age, or sex, were significantly correlated with the global FiCD value. CSVD patients with normal cognition showed decreased FiCD value mainly in the prefrontal areas (P < 0.01 with Monte Carlo correction). Compared with CSVD patients with normal cognition, CSVD patients with MCI showed significantly decreased FiCD value in enlarged frontal and parietal areas (P < 0.01 with Monte Carlo correction). Inter-group comparisons showed regional enhanced impairment of connectivity density in CSVD patients with MCI in the left superior frontal gyrus, the left precuneus, and the orbital part of the right inferior frontal gyrus (P < 0.01 with Monte Carlo correction). Regional FiCD value of frontal and parietal areas was associated with the cognitive function (P < 0.01). In conclusion, cognitively normal CSVD patients already have disruptions of structural connectivity. The extent and intensity of connectivity disruptions in frontal and parietal areas may underlie the mechanism of cognitive impairment in CSVD. Fiber connectivity density measurements may be helpful for quantitative description of structural cortical connectivity.

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.

Cardiovascular Risk Factors and Brain Health: Impact on Long-Range Cortical Connections and Cognitive Performance

Background Cardiovascular risk factor burden in the absence of clinical or radiological "events" is associated with mild cognitive impairment. Magnetic resonance imaging techniques exploring the integrity of neuronal fiber connectivity within white matter networks supporting cognitive processing could be used to measure the impact of cardiovascular disease on brain health and be used beyond bedside neuropsychological tests to detect subclinical changes and select or stratify participants for entry into clinical trials. Methods and Results We assessed the relationship between verbal IQ and brain network integrity and the effect of cardiovascular risk factors on network integrity by constructing whole-brain structural connectomes from magnetic resonance imaging diffusion images (N=60) from people with various degrees of cardiovascular risk factor burden. We measured axonal integrity by calculating network density and determined the effect of fiber loss on network topology and efficiency, using graph theory. Multivariate analyses were used to evaluate the relationship between cardiovascular risk factor burden, physical activity, age, education, white matter integrity, and verbal IQ . Reduced network density, resulting from a disproportionate loss of long-range white matter fibers, was associated with white matter network fragmentation ( r=-0.52, P<10^-4), lower global efficiency ( r=0.91, P<10^-20), and decreased verbal IQ (adjusted R²=0.23, P<10^-4). Conclusions Cardiovascular risk factors may mediate negative effects on brain health via loss of energy-dependent long-range white matter fibers, which in turn leads to disruption of the topological organization of the white matter networks, lowered efficiency, and reduced cognitive function.

Longitudinal changes in rich club organization and cognition in cerebral small vessel disease

Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of cognitive impairment and dementia. There is increasing awareness that SVD exerts its clinical effects by disrupting white matter connections, predominantly disrupting connections between rich club nodes, a set of highly connected and interconnected regions. Here we examined the progression of disturbances in rich club organization in older adults with SVD and their associations with conventional SVD markers and cognitive decline. We additionally investigated associations of baseline network measures with dementia. In 270 participants of the RUN DMC study, we performed diffusion tensor imaging (DTI) and cognitive assessments longitudinally. Rich club organization was examined in structural networks derived from DTI followed by deterministic tractography. Global efficiency (p<0.05) and strength of rich club connections (p<0.001) declined during follow-up. Decline in strength of peripheral connections was associated with a decline in overall cognition (β=0.164; p<0.01), psychomotor speed (β=0.151; p<0.05) and executive function (β=0.117; p<0.05). Baseline network measures were reduced in participants with dementia, and the association between WMH and dementia was causally mediated by global efficiency (p = =0.037) and peripheral connection strength (p = =0.040). SVD-related disturbances in rich club organization progressed over time, predominantly in participants with severe SVD. In this study, we found no specific role of rich club connectivity disruption in causing cognitive decline or dementia. The effect of WMH on dementia was mediated by global network efficiency and the strength of peripheral connections, suggesting an important role for network disruption in causing cognitive decline and dementia in older adults with SVD.

Cerebral small vessel disease: from a focal to a global perspective

Cerebral small vessel disease (SVD) is commonly observed on neuroimaging among elderly individuals and is recognized as a major vascular contributor to dementia, cognitive decline, gait impairment, mood disturbance and stroke. However, clinical symptoms are often highly inconsistent in nature and severity among patients with similar degrees of SVD on brain imaging. Here, we provide a new framework based on new advances in structural and functional neuroimaging that aims to explain the remarkable clinical variation in SVD. First, we discuss the heterogeneous pathology present in SVD lesions despite an identical appearance on imaging and the perilesional and remote effects of these lesions. We review effects of SVD on structural and functional connectivity in the brain, and we discuss how network disruption by SVD can lead to clinical deficits. We address reserve and compensatory mechanisms in SVD and discuss the part played by other age-related pathologies. Finally, we conclude that SVD should be considered a global rather than a focal disease, as the classically recognized focal lesions affect remote brain structures and structural and functional network connections. The large variability in clinical symptoms among patients with SVD can probably be understood by taking into account the heterogeneity of SVD lesions, the effects of SVD beyond the focal lesions, the contribution of neurodegenerative pathologies other than SVD, and the interaction with reserve mechanisms and compensatory mechanisms.

The efficiency of the brain connectome is associated with cerebrovascular reactivity in persons with white matter hyperintensities

The purpose of this study was to determine the relationship between the organization of the brain connectome and cerebrovascular reactivity (CVR) in persons with white matter hyperintensities. Diffusion tensor and CVR mapping 3T MRI scans were acquired in 31 participants with white matter hyperintensities. In each participant, the connectome was assessed by reconstructing all white matter tracts with tractography and segmenting the whole brain into multiple regions. Graph theory analysis was performed to quantify how effectively tracts connected brain regions by measuring the global and local efficiency of the connectome. CVR in white matter and gray matter was correlated with the global and local efficiency of the connectome, while adjusting for age, gender, and gray matter volume. For comparison, white matter hyperintensity volume was also correlated with global and local efficiency. White matter CVR was positively correlated with the global efficiency (coefficient: 23.3, p = .005) and local efficiency (coefficient: 2850, p = .004) of the connectome. Gray matter CVR was positively correlated with the global efficiency (coefficient: 21.3, p < .001) and local efficiency (coefficient: 2670, p < .001) of the connectome. White matter hyperintensity volume was negatively correlated with global efficiency (coefficient: -0.0002, p = .003) and local efficiency (coefficient: -0.024, p = .003) of the connectome. The association between CVR and the brain connectome suggests that impaired cerebrovascular function may be part of the pathophysiology of the disruption of the brain connectome in persons with white matter hyperintensities.

The Altered Reconfiguration Pattern of Brain Modular Architecture Regulates Cognitive Function in Cerebral Small Vessel Disease

Background: Cerebral small vessel disease (SVD) is a common cause of cognitive dysfunction. However, little is known whether the altered reconfiguration pattern of brain modular architecture regulates cognitive dysfunction in SVD.

Methods: We recruited 25 cases of SVD without cognitive impairment (SVD-NCI) and 24 cases of SVD with mild cognitive impairment (SVD-MCI). According to the Framingham Stroke Risk Profile, healthy controls (HC) were divided into 17 subjects (HC-low risk) and 19 subjects (HC-high risk). All individuals underwent resting-state functional magnetic resonance imaging and cognitive assessments. Graph-theoretical analysis was used to explore alterations in the modular organization of functional brain networks. Multiple regression and mediation analyses were performed to investigate the relationship between MRI markers, network metrics and cognitive performance.

Results: We identified four modules corresponding to the default mode network (DMN), executive control network (ECN), sensorimotor network and visual network. With increasing vascular risk factors, the inter- and intranetwork compensation of the ECN and a relatively reserved DMN itself were observed in individuals at high risk for SVD. With declining cognitive ability, SVD-MCI showed a disrupted ECN intranetwork and increased DMN connection. Furthermore, the intermodule connectivity of the right inferior frontal gyrus of the ECN mediated the relationship between periventricular white matter hyperintensities and visuospatial processing in SVD-MCI.

Conclusions: The reconfiguration pattern of the modular architecture within/between the DMN and ECN advances our understanding of the neural underpinning in response to vascular risk and SVD burden. These observations may provide novel insight into the underlying neural mechanism of SVD-related cognitive impairment and may serve as a potential non-invasive biomarker to predict and monitor disease progression.

Disrupted rich club organization and structural brain connectome in unmedicated bipolar disorder

BACKGROUND

Bipolar disorder (BD) has been associated with altered brain structural and functional connectivity. However, little is known regarding alterations of the structural brain connectome in BD. The present study aimed to use diffusion-tensor imaging (DTI) and graph theory approaches to investigate the rich club organization and white matter structural connectome in BD.

METHODS

Forty-two patients with unmedicated BD depression and 59 age-, sex- and handedness-matched healthy control participants underwent DTI. The whole-brain structural connectome was constructed by a deterministic fiber tracking approach. Graph theory analysis was used to examine the group-specific global and nodal topological properties, and rich club organizations, and then nonparametric permutation tests were used for group comparisons of network parameters.

RESULTS

Compared with healthy control participants, the patients with BD showed abnormal global properties, including increased characteristic path length, and decreased global efficiency and local efficiency. Locally, the patients with BD showed abnormal nodal parameters (nodal strength, nodal efficiency, and nodal betweenness) predominantly in the parietal, orbitofrontal, occipital, and cerebellar regions. Moreover, the patients with BD showed decreased rich club and feeder connectivity density.

CONCLUSIONS

Our results may reflect the disrupted white matter topological organization in the whole-brain, and abnormal regional connectivity supporting cognitive and affective functioning in depressed BD, which, in part, be due to impaired rich club connectivity.

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.

Neuroimaging of Small Vessel Disease in Late-Life Depression

Cerebral small vessel disease is associated with late-life depression, cognitive impairment, executive dysfunction, distress, and loss of life for older adults. Late-life depression is becoming a substantial public health burden, and a considerable number of older adults presenting to primary care have significant clinical depression. Even though white matter hyperintensities are linked with small vessel disease, white matter hyperintensities are nonspecific to small vessel disease and can co-occur with other brain diseases. Advanced neuroimaging techniques at the ultrahigh field magnetic resonance imaging are enabling improved characterization, identification of cerebral small vessel disease and are elucidating some of the mechanisms that associate small vessel disease with late-life depression.

Cerebral small vessel disease: neuroimaging markers and clinical implication

Cerebral small vessel disease (CSVD) is a broad category of cerebrovascular diseases which primarily affect the perforating arterioles, capillaries and venules with multiple distinct etiologies. In spite of distinctive pathogenesis, CSVD shares similar neuroimaging markers, including recent small subcortical infarct, lacune of presumed vascular origin, white matter hyperintensity of presumed vascular origin, perivascular space and cerebral microbleeds. The radiological features of neuroimaging markers are indicative for etiological analysis. Furthermore, in sporadic arteriosclerotic pathogenesis associated CSVD, the total CSVD burden is a significant predictor for stroke events, global cognitive impairment, psychiatric disorders and later life quality. This review aims to summarize the radiological characteristics as well as the clinical implication of CSVD markers and neuroimaging interpretation for CSVD symptomatology.

New insights into cerebral small vessel disease and vascular cognitive impairment from MRI

PURPOSE OF REVIEW

We review recent MRI research that addresses two important challenges in cerebral small vessel disease (SVD) research: early diagnosis, and linking SVD with cognitive impairment. First, we review studies of MRI measurements of blood flow and blood-brain barrier integrity. Second, we review MRI studies identifying neuroimaging correlates of SVD-related cognitive dysfunction, focusing on brain connectivity and white matter microarchitecture. This research is placed in context through discussion of recent recommendations for management of incidentally discovered SVD, and neuroimaging biomarker use in clinical trials.

RECENT FINDINGS

Cerebral perfusion, cerebrovascular reactivity (CVR), blood-brain barrier permeability, and white matter microarchitecture are measurable using MRI, and are altered in SVD. Lower cerebral blood flow predicts a higher future risk for dementia, whereas decreased CVR occurs at early stages of SVD and is associated with future white matter hyperintensity growth. Two new approaches to analyzing diffusion tensor imaging (DTI) data in SVD patients have emerged: graph theory-based analysis of networks of DTI connectivity between cortical nodes, and analysis of histograms of mean diffusivity of the hemispheric white matter.

SUMMARY

New, advanced quantitative neuroimaging techniques are not ready for routine radiological practice but are already being employed as monitoring biomarkers in the newest generation of trials for SVD.