Patterns of cortical degeneration in an elderly cohort with cerebral small vessel disease

Cortical microstructural involvement in cerebral small vessel disease

Background

In cerebral small vessel disease (CSVD), cortical atrophy occurs at a later stage compared to microstructural abnormalities and therefore cannot be used for monitoring short-term disease progression. We aimed to investigate whether cortical diffusion tensor imaging (DTI) and quantitative (q) magnetic resonance imaging (MRI) are able to detect early microstructural involvement of the cerebral cortex in CSVD.

Materials and Methods

33 CSVD patients without significant cortical or whole-brain atrophy and 16 healthy control subjects were included and underwent structural MRI, DTI and high-resolution qMRI with T2, T2* and T2' mapping at 3 T as well as comprehensive cognitive assessment. After tissue segmentation and reconstruction of the cortical boundaries with the Freesurfer software, DTI and qMRI parameters were saved as surface datasets and averaged across all vertices.

Results

Cortical diffusivity and quantitative T2 values were significantly increased in patients compared to controls (p < 0.05). T2 values correlated significantly positively with white matter hyperintensity (WMH) volume (p < 0.01). Both cortical diffusivity and T2 showed significant negative associations with axonal damage to the white matter fiber tracts (p < 0.05).

Conclusions

Cortical diffusivity and quantitative T2 mapping are suitable to detect microstructural involvement of the cerebral cortex in CSVD and represent promising imaging biomarkers for monitoring disease progression and effects of therapeutical interventions in clinical studies.

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia

PURPOSE

To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features.

METHODS

Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses.

RESULTS

Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability.

CONCLUSION

The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

Tract-specific statistics based on diffusion-weighted probabilistic tractography

Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the “default mode” and “what-where” networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions.

Andrew Reid et al. use publicly available data to present a method for deriving tract-specific statistics based on diffusion-weighted MRI, based upon arbitrarily-defined regions of interest. Their approach enables them to report both negative and positive associations between age and tract-specific anisotropy along with more moderate sex differences and age-by-sex interactions.

Association between white matter hyperintensity load and grey matter atrophy in mild cognitive impairment is not unidirectional

Neuroimaging measures of Alzheimer's disease (AD) include grey matter volume (GMV) alterations in the Default Mode Network (DMN) and Executive Control Network (ECN). Small-vessel cerebrovascular disease, often visualised as white matter hyperintensities (WMH) on MRI, is often seen in AD. However, the relationship between WMH load and GMV needs further examination. We examined the load-dependent influence of WMH on GMV and cognition in 183 subjects. T1-MRI data from 93 Mild Cognitive Impairment (MCI) and 90 cognitively normal subjects were studied and WMH load was categorized into low, medium and high terciles. We examined how differing loads of WMH related to whole-brain voxel-wise and regional DMN and ECN GMV. We further investigated how regional GMV moderated the relationship between WMH and cognition. We found differential load-dependent effects of WMH burden on voxel-wise and regional atrophy in only MCI. At high load, as expected WMH negatively related to both ECN and DMN GMV, however at low load, WMH positively related to ECN GMV. Additionally, negative associations between WMH and memory and executive function were moderated by regional GMV. Our results demonstrate non-unidirectional relationships between WMH load, GMV and cognition in MCI.

Small vessel disease lesion type and brain atrophy: The role of co-occurring amyloid

INTRODUCTION

It is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co-occurring Alzheimer's disease pathology affects this relation.

METHODS

In 725 memory clinic patients with SVD (mean age 67 ± 8 years, 48% female) we compared brain volumes of those with moderate/severe white matter hyperintensities (WMHs; n = 326), lacunes (n = 132) and cerebral microbleeds (n = 321) to a reference group with mild WMHs (n = 197), also considering cerebrospinal fluid (CSF) amyloid status in a subset of patients (n = 488).

RESULTS

WMHs and lacunes, but not cerebral microbleeds, were associated with smaller gray matter (GM) volumes. In analyses stratified by CSF amyloid status, WMHs and lacunes were associated with smaller total brain and GM volumes only in amyloid-negative patients. SVD-related atrophy was most evident in frontal (cortical) GM, again predominantly in amyloid-negative patients.

DISCUSSION

Amyloid status modifies the differential relation between SVD lesion type and brain atrophy in memory clinic patients.

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44-77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

Modular Development of Cortical Gray Matter Across Childhood and Adolescence

Brain maturation across childhood and adolescence is characterized by cortical thickness (CT) and volume contraction, and early expansion of surface area (SA). These processes occur asynchronously across the cortical surface, with functional, topographic, and network-based organizing principles proposed to account for developmental patterns. Characterizing regions undergoing synchronized development can help determine whether "maturational networks" overlap with well-described functional networks, and whether they are targeted by neurodevelopmental and psychiatric disorders. In the present study, we modeled changes with age in CT, SA, and volume from 335 typically developing subjects in the NIH MRI study of normal brain development, with 262 followed longitudinally for a total of 724 scans. Vertices showing similar maturation between 5 and 22 years were grouped together using data-driven clustering. Patterns of CT development distinguished sensory and motor regions from association regions, and were vastly different from SA patterns, which separated anterior from posterior regions. Developmental modules showed little similarity to networks derived from resting-state functional connectivity. Our findings present a novel perspective on maturational changes across the cortex, showing that several proposed organizing principles of cortical development co-exist, albeit in different structural parameters, and enable visualization of developmental trends occurring in parallel at remote cortical sites.

Differential associations of metabolic risk factors on cortical thickness in metabolic syndrome

Objective

Metabolic syndrome (MetS) refers to a cluster of risk factors for cardiovascular disease, including obesity, hypertension, dyslipidemia, and hyperglycemia. While sizable prior literature has examined associations between individual risk factors and quantitative measures of cortical thickness (CT), only very limited research has investigated such measures in MetS. Furthermore, the relative contributions of these risk factors to MetS-related effects on brain morphology have not yet been studied. The primary goal of this investigation was to examine how MetS may affect CT. A secondary goal was to explore the relative contributions of individual risk factors to regional alterations in CT, with the potential to identify risk factor combinations that may underlie structural changes.

Methods

Eighteen participants with MetS (mean age = 59.78 years) were age-matched with 18 healthy control participants (mean age = 60.50 years). CT measures were generated from T1-weighted images and groups were contrasted using whole-brain general linear modeling. A follow-up multivariate partial least squares correlation (PLS) analysis, including the full study sample with complete risk factor measurements (N = 53), was employed to examine which risk factors account for variance in group structural differences.

Results

Participants with MetS demonstrated significantly reduced CT in left hemisphere inferior parietal, rostral middle frontal, and lateral occipital clusters and in a right hemisphere precentral cluster. The PLS analysis revealed that waist circumference, high-density lipoprotein cholesterol (HDL-C), triglycerides, and glucose were significant contributors to reduced CT in these clusters. In contrast, diastolic blood pressure showed a significantly positive association with CT while systolic blood pressure did not emerge as a significant contributor. Age was not associated with CT.

Conclusion

These results indicate that MetS can be associated with regionally specific reductions in CT. Importantly, a novel link between a risk factor profile comprising indices of obesity, hyperglycemia, dyslipidemia and diastolic BP and localized alterations in CT emerged. While the pathophysiological mechanisms underlying these associations remain incompletely understood, these findings may be relevant for future investigations of MetS and might have implications for treatment approaches that focus on specific risk factor profiles with the aim to reduce negative consequences on the structural integrity of the brain.

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Cortical thickness is reduced bilaterally in metabolic syndrome.

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Five out of six risk factor components contribute to altered cortical thickness.

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Particular risk factor combination may be an important target for intervention.

Suspected non-Alzheimer's pathology - Is it non-Alzheimer's or non-amyloid?

Neurodegeneration, the progressive loss of neurons, is a major process involved in dementia and age-related cognitive impairment. It can be detected clinically using currently available biomarker tests. Suspected Non-Alzheimer Pathology (SNAP) is a biomarker-based concept that encompasses a group of individuals with neurodegeneration, but no evidence of amyloid deposition (thereby distinguishing it from Alzheimer's disease (AD)). These individuals may often have a clinical diagnosis of AD, but their clinical features, genetic susceptibility and progression can differ significantly, carrying crucial implications for precise diagnostics, clinical management, and efficacy of clinical drug trials. SNAP has caused wide interest in the dementia research community, because it is still unclear whether it represents distinct pathology separate from AD, or whether in some individuals, it could represent the earliest stage of AD. This debate has raised pertinent questions about the pathways to AD, the need for biomarkers, and the sensitivity of current biomarker tests. In this review, we discuss the biomarker and imaging trials that first recognized SNAP. We describe the pathological correlates of SNAP and comment on the different causes of neurodegeneration. Finally, we discuss the debate around the concept of SNAP, and further unanswered questions that are emerging.

Relationship between white matter connectivity loss and cortical thinning in cerebral amyloid angiopathy

Patients with cerebral amyloid angiopathy (CAA) show loss of white matter connectivity and cortical thinning on MRI, primarily in posterior brain regions. Here we examined whether a potential causal relationship exists between these markers of subcortical and cortical brain injury by examining whether changes in cortical thickness progress in tandem with changes in their underlying connections. Thirty-one patients with probable CAA with brain MRI at two time points were included (follow-up time: 1.3 ± 0.4 years). Brain networks were reconstructed using diffusion MRI-based fiber tractography. Of each network node, we calculated the change in fractional anisotropy-weighted connectivity strength over time and the change in cortical thickness. The association between change in connectivity strength and cortical thickness was assessed with (hierarchical) linear regression models. Our results showed that decline in posterior network connectivity over time was strongly related to thinning of the occipital cortex (β = 0.65 (0.35-0.94), P < 0.001), but not to thinning of the other posterior or frontal cortices. However, at the level of individual network nodes, we found no association between connectivity strength and cortical thinning of the corresponding node (β = 0.009 ± 0.04, P = 0.80). Associations were independent of age, sex, and other brain MRI markers of CAA. To conclude, CAA patients with greater progressive loss of posterior white matter connectivity also have greater progression of occipital cortical thinning, but our results do not support a direct causal relationship between them. The association can be better explained by a shared underlying mechanism, which may form a potential target for future treatments. Hum Brain Mapp 38:3723-3731, 2017. © 2017 Wiley Periodicals, Inc.

A seed-based cross-modal comparison of brain connectivity measures

Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about "functional connectivity." Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function.

Alterations of the cerebral cortex in sporadic small vessel disease: A systematic review of in vivo MRI data

Cerebral small vessel diseases of the brain are a major determinant of cognitive impairment in the elderly. In small vessel diseases, the most easily identifiable lesions, both at post-mortem evaluation and magnetic resonance imaging, lie in subcortical areas. However, recent results obtained post-mortem, particularly in severe cases, have highlighted the burden of cortex lesions such as microinfarcts and diffuse neuronal loss. The recent development of image post-processing methods allows now assessing in vivo multiple aspects of the cerebral cortex. This systematic review aimed to analyze in vivo magnetic resonance imaging studies evaluating cortex alterations at different stages of small vessel diseases. Studies assessing the relationships between small vessel disease magnetic resonance imaging markers obtained at the subcortical level and cortex estimates were reviewed both in community-dwelling elderly and in patients with symptomatic small vessel diseases. Thereafter, studies analyzing cortex estimates in small vessel disease patients compared with healthy subjects were evaluated. The results support that important cortex alterations develop along the course of small vessel diseases independently of concomitant neurodegenerative processes. Easy detection and quantification of cortex changes in small vessel diseases as well as understanding their underlying mechanisms are challenging tasks for better understanding cognitive decline in small vessel diseases.

Albuminuria, Cerebrovascular Disease and Cortical Atrophy: among Cognitively Normal Elderly Individuals

We tested the hypothesis that decreased glomerular filtration rate and albuminuria have different roles in brain structure alterations. We enrolled 1,215 cognitively normal individuals, all of whom underwent high-resolution T1-weighted volumetric magnetic resonance imaging scans. The cerebral small vessel disease burdens were assessed with white matter hyperintensities (WMH), lacunes, and microbleeds. Subjects were considered to have an abnormally elevated urine albumin creatinine ratio if the value was ≥17 mg/g for men and ≥25 mg/g for women. Albuminuria, but not estimated glomerular filtration rate (eGFR), was associated with increased WMH burdens (p = 0.002). The data was analyzed after adjusting for age, sex, education, history of hypertension, diabetes mellitus, hyperlipidemia, ischemic heart disease, stroke, total cholesterol level, body mass index, status of smoking and alcohol drinking, and intracranial volume. Albuminuria was also associated with cortical thinning, predominantly in the frontal and occipital regions (both p < 0.01) in multiple linear regression analysis. However, eGFR was not associated with cortical thickness. Furthermore, path analysis for cortical thickness showed that albuminuria was associated with frontal thinning partially mediated by WMH burdens. The assessment of albuminuria is needed to improve our ability to identify individuals with high risk for cognitive impairments, and further institute appropriate preventive measures.

Characterising the grey matter correlates of leukoaraiosis in cerebral small vessel disease

Cerebral small vessel disease (SVD) is a heterogeneous group of pathological disorders that affect the small vessels of the brain and are an important cause of cognitive impairment. The ischaemic consequences of this disease can be detected using MRI, and include white matter hyperintensities (WMH), lacunar infarcts and microhaemorrhages. The relationship between SVD disease severity, as defined by WMH volume, in sporadic age-related SVD and cortical thickness has not been well defined. However, regional cortical thickness change would be expected due to associated phenomena such as underlying ischaemic white matter damage, and the observation that widespread cortical thinning is observed in the related genetic condition CADASIL (Righart et al., 2013). Using MRI data, we have developed a semi-automated processing pipeline for the anatomical analysis of individuals with cerebral small vessel disease and applied it cross-sectionally to 121 subjects diagnosed with this condition. Using a novel combined automated white matter lesion segmentation algorithm and lesion repair step, highly accurate warping to a group average template was achieved. The volume of white matter affected by WMH was calculated, and used as a covariate of interest in a voxel-based morphometry and voxel-based cortical thickness analysis. Additionally, Gaussian Process Regression (GPR) was used to assess if the severity of SVD, measured by WMH volume, could be predicted from the morphometry and cortical thickness measures. We found significant (Family Wise Error corrected p < 0.05) volumetric decline with increasing lesion load predominately in the parietal lobes, anterior insula and caudate nuclei bilaterally. Widespread significant cortical thinning was found bilaterally in the dorsolateral prefrontal, parietal and posterio-superior temporal cortices. These represent distinctive patterns of cortical thinning and volumetric reduction compared to ageing effects in the same cohort, which exhibited greater changes in the occipital and sensorimotor cortices. Using GPR, the absolute WMH volume could be significantly estimated from the grey matter density and cortical thickness maps (Pearson's coefficients 0.80 and 0.75 respectively). We demonstrate that SVD severity is associated with regional cortical thinning. Furthermore a quantitative measure of SVD severity (WMH volume) can be predicted from grey matter measures, supporting an association between white and grey matter damage. The pattern of cortical thinning and volumetric decline is distinctive for SVD severity compared to ageing. These results, taken together, suggest that there is a phenotypic pattern of atrophy associated with SVD severity.

Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence

The human brain develops with a nonlinear contraction of gray matter across late childhood and adolescence with a concomitant increase in white matter volume. Across the adult population, properties of cortical gray matter covary within networks that may represent organizational units for development and degeneration. Although gray matter covariance may be strongest within structurally connected networks, the relationship to volume changes in white matter remains poorly characterized. In the present study we examined age-related trends in white and gray matter volume using T1-weighted MR images from 360 human participants from the NIH MRI study of Normal Brain Development. Images were processed through a voxel-based morphometry pipeline. Linear effects of age on white and gray matter volume were modeled within four age bins, spanning 4-18 years, each including 90 participants (45 male). White and gray matter age-slope maps were separately entered into k-means clustering to identify regions with similar age-related variability across the four age bins. Four white matter clusters were identified, each with a dominant direction of underlying fibers: anterior-posterior, left-right, and two clusters with superior-inferior directions. Corresponding, spatially proximal, gray matter clusters encompassed largely cerebellar, fronto-insular, posterior, and sensorimotor regions, respectively. Pairs of gray and white matter clusters followed parallel slope trajectories, with white matter changes generally positive from 8 years onward (indicating volume increases) and gray matter negative (decreases). As developmental disorders likely target networks rather than individual regions, characterizing typical coordination of white and gray matter development can provide a normative benchmark for understanding atypical development.

Relationship between white matter hyperintensities, cortical thickness, and cognition

BACKGROUND AND PURPOSE

White matter hyperintensities (WMH) are associated with clinically heterogeneous symptoms that cannot be explained by these lesions alone. It is hypothesized that these lesions are associated with distant cortical atrophy and cortical thickness network measures, which can result in an additional cognitive impairment. Here, we investigated the relationships between WMH, cortical thickness, and cognition in subjects with cerebral small vessel disease.

METHODS

A total of 426 subjects with cerebral small vessel disease were included, aged between 50 and 85 years, without dementia, and underwent MRI scanning. Cortical thickness analysis was performed, and WMH were manually segmented. Graph theory was applied to examine the relationship between network measures and WMH, and structural covariance matrices were constructed using inter-regional cortical thickness correlations.

RESULTS

Higher WMH load was related to lower cortical thickness in frontotemporal regions, whereas in paracentral regions, this was related to higher cortical thickness. Network analyses revealed that measures of network disruption were associated with WMH and cognitive performance. Furthermore, WMH in specific white matter tracts were related to regional-specific cortical thickness and network measures. Cognitive performances were related to cortical thickness in frontotemporal regions and network measures, and not to WMH, while controlling for cortical thickness.

CONCLUSIONS

These cross-sectional results suggest that cortical changes (regional-specific damage and network breakdown), mediated (in)directly by WMH (tract-specific damage) and other factors (eg, vascular risk factors), might lead to cognitive decline. These findings have implications in understanding the relationship between WMH, cortical morphology, and the possible attendant cognitive decline and eventually dementia.

Brain cortical thickness in the general elderly population: the Rotterdam Scan Study

Cortical thickness is considered a potentially relevant marker for neurodegenerative diseases. However, the relationship of demographic and vascular risk factors with cortical thickness remains unclear. In a population-based sample of 1022 non-demented elderly persons (mean age 68.4±7.3 years), we examined aging effects on global and lobar cortical thickness and the relationship with demographic variables and cardiovascular risk factors. We used a validated model-based approach to calculate mean cortical thickness (μm) in brain MR-images. We found that women had a significant thicker cortex than men (p<0.01). Further, with increasing age, cortical thickness decreased (approximately 0.2% per year), with the largest age effects for the occipital and temporal lobes, and the decrease in the frontal lobe being more apparent in men than in women (p-interaction<0.001). Additionally, higher education, higher diastolic blood pressure and larger intra-cranial volume were related to a larger cortical thickness, whilst diabetes mellitus and higher HDL cholesterol levels were related to a thinner cortex.

Impact of regional cortical and subcortical changes on processing speed in cerebral small vessel disease

Slowed processing speed is common in elderly subjects and frequently related to cerebral small vessel disease. Previous studies have demonstrated associations between processing speed and subcortical ischemic lesions as well as cortical alterations but the precise functional–anatomical relationships remain poorly understood. Here we assessed the impact of both cortical and subcortical changes on processing speed by measuring regional cortical thickness and regional lesion volumes within distinct white-matter tracts. To limit confounding effects from age-related pathologies we studied patients with CADASIL, a genetic small vessel disease. General linear model analysis revealed significant associations between cortical thickness in the medial frontal and occipito-temporal cortex and processing speed. Bayesian network analysis showed a robust conditional dependency between the volume of lacunar lesions in the left anterior thalamic radiation and cortical thickness of the left medial frontal cortex, and between thickness of the left medial frontal cortex and processing speed, whereas there was no direct dependency between lesion volumes in the left anterior thalamic radiation and processing speed. Our results suggest that the medial frontal cortex has an intermediate position between lacunar lesions in the anterior thalamic radiation and deficits in processing speed. In contrast, we did not observe such a relationship for the occipito-temporal region. These findings reinforce the key role of frontal–subcortical circuits in cognitive impairment resulting from cerebral small vessel disease.

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Slowed processing speed is a key feature of cerebral small vessel disease.

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Processing speed correlates with cortical thickness in frontal and occipital areas.

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Effects of ischemic lesions on processing speed are mediated by cortical changes.

Networks of anatomical covariance

Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.

Severe brain atrophy in the elderly as a risk factor for lower respiratory tract infection

BACKGROUND

The purpose of this study is to determine whether elderly subjects with severe brain atrophy, which is associated with neurodegeneration and difficulty swallowing (dysphagia), are more susceptible to lower respiratory tract infections (LRTI), including pneumonia.

METHODS

The severity of brain atrophy was assessed by computed tomography in 51 nursing home residents aged 60-96 years. The incidence of LRTI, defined by body temperature ≥ 38.0°C, presence of two or more respiratory symptoms, and use of antibiotics, was determined over 4 years. The incidence of LRTI was compared according to the severity and type of brain atrophy.

RESULTS

The incidence rate ratio of LRTI was significantly higher (odds ratio 4.60, 95% confidence interval 1.18-17.93, fully adjusted P = 0.028) and the time to the first episode of LRTI was significantly shorter (log-rank test, P = 0.019) in subjects with severe brain atrophy in any lobe. Frontal and parietal lobe atrophy was associated with a significantly increased risk of LRTI, while temporal lobe atrophy, ventricular dilatation, and diffuse white matter lesions did not influence the risk of LRTI.

CONCLUSION

Elderly subjects with severe brain atrophy are more susceptible to LRTI, possibly as a result of neurodegeneration causing dysphagia and silent aspiration. Assessing the severity of brain atrophy might be useful to identify subjects at increased risk of respiratory infections in a prospective manner.

Cortical thickness is associated with gait disturbances in cerebral small vessel disease

Although gait disturbances are present in a substantial portion of patients with cerebral small vessel disease (SVD), their pathogenesis has not been clarified as they are not entirely explained by the white matter lesions (WMLs) and lacunar infarcts. The role of cortical thickness in these patients remains largely unknown. We aimed to assess the regions of cortical thickness associated with distinct gait parameters in patients with SVD, and whether these associations were dependent on WMLs and lacunar infarcts. MRI data were obtained from 415 subjects with SVD, aged between 50 and 85 years. We assessed cortical thickness using surface-based cortical thickness analysis, and gait performance using the GAITRite system. Cortical thickness of predominantly the orbitofrontal and ventrolateral prefrontal cortex, the inferior parietal lobe, cingulate areas and visual association cortices was positively related to stride length. Thickness of the primary and supplementary motor cortices and the cingulate cortex was positively related to cadence, while thickness of the orbitofrontal and ventrolateral prefrontal cortex, anterior cingulate cortex and especially the inferior parietal lobe and superior temporal gyrus was negatively related to stride width. The associations with stride length and width were partially explained by the subcortical WMLs and lacunar infarcts. Cortical thickness may therefore be important in gait disturbances in individuals with SVD, with different cortical patterns for specific gait parameters. We suggest that cortical atrophy is part of the disease processes in patients with SVD.