A comparison of functional and tractography based networks in cerebral small vessel disease

Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning-Derived Diffusion Scalar Maps From T1

BACKGROUND

Cerebral small vessel disease is the most common pathology underlying vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to white matter damage and better predicts dementia risk than conventional magnetic resonance imaging sequences, such as T1 and fluid attenuation inversion recovery, but diffusion tensor imaging takes longer to acquire and is not routinely available in clinical practice. As diffusion tensor imaging-derived scalar maps-fractional anisotropy (FA) and mean diffusivity (MD)-are frequently used in clinical settings, one solution is to synthesize FA/MD from T1 images.

METHODS

We developed a deep learning model to synthesize FA/MD from T1. The training data set consisted of 4998 participants with the highest white matter hyperintensity volumes in the UK Biobank. Four external validations data sets with small vessel disease were included: SCANS (St George's Cognition and Neuroimaging in Stroke; n=120), RUN DMC (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort; n=502), PRESERVE (Blood Pressure in Established Cerebral Small Vessel Disease; n=105), and NETWORKS (n=26), along with 1000 normal controls from the UK Biobank.

RESULTS

The synthetic maps resembled ground-truth maps (structural similarity index >0.89 for MD maps and >0.80 for FA maps across all external validation data sets except for SCANS). The prediction accuracy of dementia using whole-brain median MD from the synthetic maps is comparable to the ground truth (SCANS ground-truth c-index, 0.822 and synthetic, 0.821; RUN DMC ground truth, 0.816 and synthetic, 0.812) and better than white matter hyperintensity volume (SCANS, 0.534; RUN DMC, 0.710).

CONCLUSIONS

We have developed a fast and generalizable method to synthesize FA/MD maps from T1 to improve the prediction accuracy of dementia in small vessel disease when diffusion tensor imaging data have not been acquired.

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.

Pathophysiology of cerebral small vessel disease: a journey through recent discoveries

Cerebral small vessel disease (cSVD) encompasses a heterogeneous group of age-related small vessel pathologies that affect multiple regions. Disease manifestations range from lesions incidentally detected on neuroimaging (white matter hyperintensities, small deep infarcts, microbleeds, or enlarged perivascular spaces) to severe disability and cognitive impairment. cSVD accounts for approximately 25% of ischemic strokes and the vast majority of spontaneous intracerebral hemorrhage and is also the most important vascular contributor to dementia. Despite its high prevalence and potentially long therapeutic window, there are still no mechanism-based treatments. Here, we provide an overview of the recent advances in this field. We summarize recent data highlighting the remarkable continuum between monogenic and multifactorial cSVDs involving NOTCH3, HTRA1, and COL4A1/A2 genes. Taking a vessel-centric view, we discuss possible cause-and-effect relationships between risk factors, structural and functional vessel changes, and disease manifestations, underscoring some major knowledge gaps. Although endothelial dysfunction is rightly considered a central feature of cSVD, the contributions of smooth muscle cells, pericytes, and other perivascular cells warrant continued investigation.

MAPT rs17649553 T allele is associated with better verbal memory and higher small-world properties in Parkinson's disease

Currently, over 90 genetic loci have been found to be associated with Parkinson's disease (PD) in genome-wide association studies, nevertheless, the effects of these genetic variants on the clinical features and brain structure of PD patients are largely unknown. This study investigated the effects of microtubule-associated protein tau (MAPT) rs17649553 (C>T), a genetic variant associated with reduced PD risk, on the clinical manifestations and brain networks of PD patients. We found MAPT rs17649553 T allele was associated with better verbal memory in PD patients. In addition, MAPT rs17649553 significantly shaped the topology of gray matter covariance network and white matter network. Both the network metrics in gray matter covariance network and white matter network were correlated with verbal memory, however, the mediation analysis showed that it was the small-world properties in white matter network that mediated the effects of MAPT rs17649553 on verbal memory. These results suggest that MAPT rs17649553 T allele is associated with higher small-world properties in structural network and better verbal memory in PD.

Cortical Thickness and Brain Connectivity Mediate the Relation Between White Matter Hyperintensity and Information Processing Speed in Cerebral Small Vessel Disease

White matter hyperintensities of presumed vascular origin (WMH) are the most common imaging feature of cerebral small vessel disease (cSVD) and are associated with cognitive impairment, especially information processing speed (IPS) deficits. However, it is unclear how WMH can directly impact IPS or whether the cortical thickness and brain connectivity mediate such association. In this study, it was evaluated the possible mediating roles of cortical thickness and brain (structural and functional) connectivity on the relationship between WMH (also considering its topography distribution) and IPS in 389 patients with cSVD from the RUN-DMC (Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort) database. Significant (p < 0.05 after multiple comparisons correction) associations of WMH volume and topography with cortical thickness, brain connectivity, and IPS performance in cSVD individuals were found. Additionally, cortical thickness and brain structural and functional connectivity were shown to mediate the association of WMH volume and location with IPS scores. More specifically, frontal cortical thickness, functional sensorimotor network, and posterior thalamic radiation tract were the essential mediators of WMH and IPS in this clinical group. This study provided insight into the mechanisms underlying the clinical relevance of white matter hyperintensities in information processing speed deficits in cSVD through cortical thinning and network disruptions.

Reproducibility of regional structural and functional MRI networks in cerebral small vessel disease compared to age matched and stroke-free controls

Abnormalities in structural and functional MRI connectivity measures have been reported in cerebral small vessel disease (SVD). Previous research has shown that whole-brain structural connectivity was highly reproducible in SVD patients, while whole-brain functional connectivity showed low reproducibility. It remains unclear whether the lower reproducibility of functional networks reported in SVD is due to selective disruption of reproducibility in specific networks or is generalised in patients with SVD. In this case-control study 15 SVD and 10 age-matched control participants were imaged twice with diffusion tensor imaging and resting state fMRI. Structural and functional connectivity matrices were constructed from this data and the default mode, fronto-parietal, limbic, salience, somatomotor and visual networks were extracted and the average connectivity between connections calculated and used to determine their reproducibility. Regional structural networks were more reproducible than functional networks, all structural networks showed ICC values ≥0.64 (except the salience network in SVD). The functional networks showed greater reproducibility in the controls compared to SVD with ICC values >0.7 for control participants and <=0.5 for the SVD group. The default mode network showed the greatest reproducibility for both control and SVD groups. Reproducibility of functional networks was affected by disease status with lower reproducibility in SVD compared with controls.

Network structure-function coupling and neurocognition in cerebral small vessel disease

BACKGROUND

Cerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural-functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients.

METHODS

Participants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural-functional network coupling for each participant.

RESULTS

Lower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network.

CONCLUSIONS

Our work demonstrates the influence of structural-functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.

Age and sex differentially shape brain networks in Parkinson's disease

AIMS

Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients.

METHODS

Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated.

RESULTS

Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients.

CONCLUSION

Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.

Functional connectivity in older adults-the effect of cerebral small vessel disease

Ageing is associated with functional reorganization that is mainly characterized by declining functional connectivity due to general neurodegeneration and increasing incidence of disease. Functional connectivity has been studied across the lifespan; however, there is a paucity of research within the older groups (≥75 years) where neurodegeneration and disease prevalence are at its highest. In this cross-sectional study, we investigated associations between age and functional connectivity and the influence of cerebral small vessel disease (CSVD)-a common age-related morbidity-in 167 community-dwelling older adults aged 75-91 years (mean = 80.3 ± 3.8). Resting-state functional MRI was used to determine functional connectivity within ten standard networks and calculate the whole-brain graph theoretical measures global efficiency and clustering coefficient. CSVD features included white matter hyperintensities, lacunar infarcts, cerebral microbleeds, and atrophy that were assessed in each individual and a composite score was calculated. Both main and interaction effects (age*CSVD features) on functional connectivity were studied. We found stable levels of functional connectivity across the age range. CSVD was not associated with functional connectivity measures. To conclude, our data show that the functional architecture of the brain is relatively unchanged after 75 years of age and not differentially affected by individual levels of vascular pathology.

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.

Structural and functional alterations in cerebral small vessel disease: an ALE-based meta-analysis

 

Cerebral small vessel disease (CSVD) is one of the most important causes of stroke and dementia. Although increasing studies have reported alterations of brain structural or neuronal functional activity exhibited in patients with CSVD, it is still unclear which alterations are reliable. Here, we performed a meta-analysis to establish which brain structural or neuronal functional activity changes in those studies were consistent. Activation likelihood estimation revealed that changes in neuronal functional activity in the left angular gyrus, bilateral anterior cingulate cortex/left medial prefrontal cortex, right rolandic operculum, and alterations of gray structure in the left insular cortex/superior temporal gyrus/claustrum were reliable in sporadic CSVD. Decreased neuronal functional activity in the caudate head, anterior cingulate cortex, and reduced gray matter volume in the insular cortex/superior temporal gyrus/claustrum were associated with CSVD-related cognitive impairment. Furthermore, unlike sporadic CSVD, the reliable alterations of neuronal functional activity in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy were concentrated in the left parahippocampal gyrus. The current study presents stable brain structural and neuronal functional abnormalities within the brain, which can help further understand the pathogenesis of CSVD and CSVD-cognitive impairment and provide an index to evaluate the effectiveness of treatment protocols.

Highlights

• Default mode network and salience network are reliable networks affected in sporadic CSVD in resting-state.

• Altered corticostriatal circuitry is associated with cognitive decline.

• Decreased gray matter volume in the insular cortex is stable “remote effects” of sporadic CSVD.

• The parahippocampal gyrus may be a reliable affected brain region in CADASIL.

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.

The Clustering Analysis of Time Properties in Patients With Cerebral Small Vessel Disease: A Dynamic Connectivity Study

Purpose

This study aimed to investigate the dynamic functional connectivity (DFC) pattern in cerebral small vessel disease (CSVD) and explore the relationships between DFC temporal properties and cognitive impairment in CSVD.

Methods

Functional data were collected from 67 CSVD patients, including 35 patients with subcortical vascular cognitive impairment (SVCI) and 32 cognitively unimpaired (CU) patients, as well as 35 healthy controls (HCs). The DFC properties were estimated by k-means clustering analysis. DFC strength analysis was used to explore the regional functional alterations between CSVD patients and HCs. Correlation analysis was used for DFC properties with cognition and SVD scores, respectively.

Results

The DFC analysis showed three distinct connectivity states (state I: sparsely connected, state II: strongly connected, state III: intermediate pattern). Compared to HCs, CSVD patients exhibited an increased proportion in state I and decreased proportion in state II. Besides, CSVD patients dwelled longer in state I while dwelled shorter in state II. CSVD subgroup analyses showed that state I frequently occurred and dwelled longer in SVCI compared with CSVD-CU. Also, the internetwork (frontal-parietal lobe, frontal-occipital lobe) and intranetwork (frontal lobe, occipital lobe) functional activities were obviously decreased in CSVD. Furthermore, the fractional windows and mean dwell time (MDT) in state I were negatively correlated with cognition in CSVD but opposite to cognition in state II.

Conclusion

Patients with CSVD accounted for a higher proportion and dwelled longer mean time in the sparsely connected state, while presented lower proportion and shorter mean dwell time in the strongly connected state, which was more prominent in SVCI. The changes in the DFC are associated with altered cognition in CSVD. This study provides a better explanation of the potential mechanism of CSVD patients with cognitive impairment from the perspective of DFC.

Brain metabolic connectivity reconfiguration in the semantic variant of primary progressive aphasia

Functional network-level alterations in the semantic variant of Primary Progressive Aphasia (sv-PPA) are relevant to understanding the clinical features and the neural spreading of the pathology. We assessed the effect of neurodegeneration on brain systems reorganization in early sv-PPA, using advanced brain metabolic connectivity approaches. Forty-four subjects with sv-PPA and forty-four age-matched healthy controls (HC) were included. We applied two multivariate approaches to [18F]FDG-PET data - i.e., sparse inverse covariance estimation and seed-based interregional correlation analysis - to assess the integrity of (i) the whole-brain metabolic connectivity and (ii) the connectivity of brain regions relevant for cognitive and behavioral functions. Whole-brain analysis revealed a global-scale connectivity reconfiguration in sv-PPA, with widespread changes in metabolic connections of frontal, temporal, and parietal regions. In comparison to HC, the seed-based analysis revealed a) functional isolation of the left anterior temporal lobe (ATL), b) decreases in temporo-occipital connections and contralateral homologous regions, c) connectivity increases to the dorsal parietal cortex from the spared posterior temporal cortex, d) a disruption of the large-scale limbic brain networks. In sv-PPA, the severe functional derangement of the left ATL may lead to an extensive connectivity reconfiguration, encompassing several brain regions, including those not yet affected by neurodegeneration. These findings support the hypothesis that in sv-PPA the focal vulnerability of the core region (i.e., ATL) can potentially drive the widespread cerebral connectivity changes, already present in the early phase.

The Hyperintense study: Assessing the effects of induced blood pressure increase and decrease on MRI markers of cerebral small vessel disease: Study rationale and protocol

Background:

Neuroimaging markers of cerebral small vessel disease (SVD) are common in older individuals, but the pathophysiological mechanisms causing these lesions remain poorly understood. Although hypertension is a major risk factor for SVD, the direct causal effects of increased blood pressure are unknown. The Hyperintense study is designed to examine cerebrovascular and structural abnormalities, possibly preceding SVD, in young adults with hypertension. These patients undergo a diagnostic work-up that requires patients to temporarily discontinue their antihypertensive agents, often leading to an increase in blood pressure followed by a decrease once effective medication is restarted. This allows examination of the effects of blood pressure increase and decrease on the cerebral small vessels.

Methods:

Hyperintense is a prospective observational cohort study in 50 hypertensive adults (18–55 years) who will temporarily discontinue antihypertensive medication for diagnostic purposes. MRI and clinical data is collected at four timepoints: before medication withdrawal (baseline), once antihypertensives are largely or completely withdrawn (T = 1), when patients have restarted medication (T = 2) and reached target blood pressure and 1 year later (T = 3). The 3T MRI protocol includes conventional structural sequences and advanced techniques to assess various aspects of microvascular integrity, including blood-brain barrier function using Dynamic Contrast Enhanced MRI, white matter integrity, and microperfusion. Clinical assessments include motor and cognitive examinations and blood sampling.

Discussion:

The Hyperintense study will improve the understanding of the pathophysiological mechanisms following hypertension that may cause SVD. This knowledge can ultimately help to identify new targets for treatment of SVD, aimed at prevention or limiting disease progression.

Central obesity is selectively associated with cerebral gray matter atrophy in 15,634 subjects in the UK Biobank

BACKGROUND

Obesity is a risk factor for both cardiovascular disease and dementia, but the mechanisms underlying this association are not fully understood. We examined associations between obesity, including estimates of central obesity using different modalities, with brain gray matter (GM) volume in the UK Biobank, a large population-based cohort study.

METHODS

To determine relationships between obesity and the brain we used brain MRI, abdominal MRI, dual-energy X-ray absorptiometry (DXA), and bioelectric whole-body impedance. We determined whether obesity was associated with any change in brain gray matter (GM) and white matter (WM) volumes, and brain network efficiency derived from the structural connectome (wiring of the brain) as determined from diffusion-tensor MRI tractography. Using Waist-Hip Ratio (WHR), abdominal MRI and DXA we determined whether any associations were primarily with central rather than peripheral obesity, and whether associations were mediated by known cardiovascular risk factors. We analyzed brain MRI data from 15,634.

RESULTS

We found that central obesity, was associated with decreased GM volume (anthropometric data: p = 6.7 × 10-16, DXA: p = 8.3 × 10-81, abdominal MRI: p = 0.0006). Regional associations were found between central obesity and with specific GM subcortical nuclei (thalamus, caudate, pallidum, nucleus accumbens). In contrast, no associations were found with WM volume or structure, or brain network efficiency. The effects of central obesity on GM volume were not mediated by C-reactive protein or blood pressure, glucose, lipids.

CONCLUSIONS

Central body-fat distribution rather than the overall body-fat percentage is associated with gray matter changes in people with obesity. Further work is required to identify the factors that mediate the association between central obesity and GM atrophy.

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.

Neural Substrates of Poststroke Depression: Current Opinions and Methodology Trends

Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients’ functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.

The influence of white matter hyperintensities severity on functional brain activity in cerebral small vessel disease: An rs-fMRI study

OBJECTIVE

To investigate relationships between the severity of white matter hyperintensities (WMH), functional brain activity, and cognition in cerebral small vessel disease (CSVD) based on resting-state functional magnetic resonance imaging (rs-fMRI) data.

METHODS

A total of 103 subjects with CSVD were included. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), functional connectivity (FC) and their graph properties were applied to explore the influence of WMH burden on functional brain activity. We also investigated whether there are correlations between different functional brain characteristics and cognitive assessments. Finally, we selected disease-related rs-fMRI features in combination with ensemble learning to classify CSVD patients with low WMH load and with high WMH load.

RESULTS

The high WMH load group demonstrated significantly abnormal functional brain activity based on rs-MRI data, relative to the low WMH load group. ALFF and graph properties in specific brain regions were significantly correlated with patients' cognitive assessments in CSVD. Moreover, altered rs-fMRI signal can help predict the severity of WMH in CSVD patients with an overall accuracy of 92.23%.

CONCLUSIONS

This study provided a comprehensive analysis and evidence for a pattern of altered functional brain activity under different WMH load in CSVD based on rs-fMRI data, enabling accurately individual prediction of status of WMH.

Longitudinal relation between structural network efficiency, cognition, and gait in cerebral small vessel disease

Background

To investigate changes in gait performance over time and how these changes are associated with the decline in structural network efficiency and cognition in older patients with cerebral small vessel disease (SVD).

Methods

In a prospective, single-center cohort with 217 older participants with SVD, we performed 1.5T MRI scans, cognitive tests, and gait assessments evaluated by Timed UP and Go (TUG) test twice over 4 years. We reconstructed the white matter network for each subject based on diffusion tensor imaging tractography, followed by graph-theoretical analyses to compute the global efficiency. Conventional MRI markers for SVD, that is, white matter hyperintensity (WMH) volume, number of lacunes, and microbleeds, were assessed.

Results

Baseline global efficiency was not related to changes in gait performance, while decline in global efficiency over time was significantly associated with gait decline (ie, increase in TUG time), independent of conventional MRI markers for SVD. Neither baseline cognitive performance nor cognitive decline was associated with gait decline.

Conclusions

We found that disruption of the white matter structural network was associated with gait decline over time, while the effect of cognitive decline was not. This suggests that structural network disruption has an important role in explaining the pathophysiology of gait decline in older patients with SVD, independent of cognitive decline.

Functional connectivity changes in cerebral small vessel disease - a systematic review of the resting-state MRI literature

BACKGROUND

Cerebral small vessel disease (CSVD) is a common neurological disease present in the ageing population that is associated with an increased risk of dementia and stroke. Damage to white matter tracts compromises the substrate for interneuronal connectivity. Analysing resting-state functional magnetic resonance imaging (fMRI) can reveal dysfunctional patterns of brain connectivity and contribute to explaining the pathophysiology of clinical phenotypes in CSVD.

MATERIALS AND METHODS

This systematic review provides an overview of methods and results of recent resting-state functional MRI studies in patients with CSVD. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, a systematic search of the literature was performed.

RESULTS

Of 493 studies that were screened, 44 reports were identified that investigated resting-state fMRI connectivity in the context of cerebral small vessel disease. The risk of bias and heterogeneity of results were moderate to high. Patterns associated with CSVD included disturbed connectivity within and between intrinsic brain networks, in particular the default mode, dorsal attention, frontoparietal control, and salience networks; decoupling of neuronal activity along an anterior-posterior axis; and increases in functional connectivity in the early stage of the disease.

CONCLUSION

The recent literature provides further evidence for a functional disconnection model of cognitive impairment in CSVD. We suggest that the salience network might play a hitherto underappreciated role in this model. Low quality of evidence and the lack of preregistered multi-centre studies remain challenges to be overcome in the future.

Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury

Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function.

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.

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.

Integrity of Neurocognitive Networks in Dementing Disorders as Measured with Simultaneous PET/Functional MRI

Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with ¹⁸F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous resting-state fMRI and ¹⁸F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and ¹⁸F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.

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.

Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease

In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.

Apathy is associated with large-scale white matter network disruption in small vessel disease

OBJECTIVE

To investigate whether white matter network disruption underlies the pathogenesis of apathy, but not depression, in cerebral small vessel disease (SVD).

METHODS

Three hundred thirty-one patients with SVD from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study completed measures of apathy and depression and underwent structural MRI. Streamlines reflecting underlying white matter fibers were reconstructed with diffusion tensor tractography. First, path analysis was used to determine whether network measures mediated associations between apathy and radiologic markers of SVD. Next, we examined differences in whole-brain network measures between participants with only apathy, only depression, and comorbid apathy and depression and a control group free of neuropsychiatric symptoms. Finally, we examined regional network differences associated with apathy.

RESULTS

Path analysis demonstrated that network disruption mediated the relationship between apathy and SVD markers. Patients with apathy, compared to all other groups, were impaired on whole-brain measures of network density and efficiency. Regional network analyses in both the apathy subgroup and the entire sample revealed that apathy was associated with impaired connectivity in premotor and cingulate regions.

CONCLUSIONS

Our results suggest that apathy, but not depression, is associated with white matter tract disconnection in SVD. The subnetworks delineated suggest that apathy may be driven by damage to white matter networks underlying action initiation and effort-based decision making.

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.

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.