Structural brain network measures are superior to vascular burden scores in predicting early cognitive impairment in post stroke patients with small vessel disease

Trade-offs among brain structural network characteristics across the cognitive decline process in cerebral small vessel disease

Objectives

To investigate the potential trade-offs among brain structural network characteristics across different stages of cognitive impairment in cerebral small vessel disease (CSVD) based on diffusion tensor imaging (DTI).

Methods

A total of 264 CSVD patients, including 95 patients with non-cognitive impairment (NCI), 142 with mild cognitive impairment (MCI), 27 with vascular dementia (VaD), and 30 healthy controls (HC) underwent cognitive test and brain diffusion magnetic resonance imaging (MRI). The brain structural network was constructed using connections between 90 cortical and subcortical regions. Network characteristics, including sparsity, redundancy, global efficiency (Eg), and local efficiency (Eloc), were calculated.

Results

Sparsity and redundancy significantly declined in the NCI group compared to the HC group. Eg was significantly reduced in the MCI group compared to the NCI group. All network characteristics declined in the VaD group compared to the MCI group. In the NCI group, both sparsity and redundancy were significantly positively correlated with Montreal Cognitive Assessment (MoCA). In the MCI group, there was significant positive correlation between Eg and MoCA. In the VaD group, there was significant negative correlation between Eloc and MoCA. When controlling for sparsity, Eloc exhibited a significant negative correlation with Eg in all three CSVD groups, while redundancy displayed a significant negative correlation with Eg specifically in MCI group.

Conclusion

Our study provides evidence for the heterogeneous alterations in brain structural network across different stages of cognitive impairment in CSVD. The disconnection of brain structural network at NCI stage is mainly the loss of redundant connections. The decline of Eg is the vital factor for cognitive impairment at MCI stage. The decline of all network characteristics is the prominent manifestation at VaD stage. Throughout the cognitive decline process in CSVD, there are trade-offs among the brain network wiring cost, integration, and segregation.

Diffusion tensor imaging in cerebral small vessel disease applications: opportunities and challenges

Cerebral small vessel disease (CSVD) is a syndrome of pathology, imaging, and clinical manifestations caused primarily by a variety of functional or structural lesions in the small blood vessels of the brain. CSVD contributes to approximately 45% of dementia and 25% of ischemic strokes worldwide and is one of the most important causes of disability. The disease progresses insidiously, and patients often have no typical symptoms in the early stages, but have an increased risk of stroke, death, and poor long-term prognosis. Therefore, early diagnosis of CSVD is particularly important. Neuroimaging is the most important diagnostic tool used for CSVD. Therefore, it is important to explore the imaging mechanisms of CSVD for its early diagnosis and precise treatment. In this article, we review the principles and analysis methods of DTI, analyze the latest DTI studies on CSVD, clarify the disease-lesion mapping relationships between cerebral white matter (WM) microstructural damage and CSVD, explore the pathogenic mechanisms and preclinical imaging features of CSVD, and summarize the latest research directions of CSVD and research methods to provide a comprehensive and objective imaging basis for the diagnosis and treatment of CSVD.

Predicting white-matter hyperintensity progression and cognitive decline in patients with cerebral small-vessel disease: a magnetic resonance-based habitat analysis

Background

White-matter hyperintensity (WMH) is the key magnetic resonance imaging (MRI) marker of cerebral small-vessel disease (CSVD). This study aimed to investigate whether habitat analysis based on physiologic MRI parameters can predict the progression of WMH and cognitive decline in CSVD.

Methods

Diffusion- and perfusion-weighted imaging data were obtained from 69 patients with CSVD at baseline and at 1-year of follow-up. The white-matter region was classified into constant WMH, growing WMH, shrinking WMH, and normal-appearing white matter (NAWM) according to the T2-fluid-attenuated inversion recovery (FLAIR) sequences images at the baseline and follow-up. We employed k-means clustering on a voxel-wise basis to delineate WMH habitats, integrating multiple diffusion metrics and cerebral blood flow (CBF) values derived from perfusion data. The WMH at the baseline and the predicted WMH from the habitat analysis were used as regions of avoidance (ROAs). The decreased rate of global efficiency for the whole brain structural connectivity was calculated after removal of the ROA. The association between the decreased rate of global efficiency and Montreal Cognitive Assessment (MoCA) and mini-mental state examination (MMSE) scores was evaluated using Pearson correlation coefficients.

Results

We found that the physiologic MRI habitats with lower fractional anisotropy and CBF values and higher mean diffusivity, axial diffusivity, and radial diffusivity values overlapped considerably with the new WMH (growing WMH of baseline) after a 1-year follow-up; the accuracy of distinguishing growing WMH from NAWM was 88.9%±12.7% at baseline. Similar results were also found for the prediction of shrinking WMH. Moreover, after the removal of the predicted WMH, a decreased rate of global efficiency had a significantly negative correlation with the MoCA and MMSE scores at follow-up.

Conclusions

This study revealed that a habitat analysis combining perfusion with diffusion parameters could predict the progression of WMH and related cognitive decline in patients with CSVD.

Analysis of radiological features in patients with post-stroke depression and cognitive impairment

Post-stroke depression (PSD) and post-stroke cognitive impairment (PSCI) are common complications following a stroke, significantly impacting the quality of life and survival time of survivors. Currently, the comorbidity of PSCI and PSD is receiving increasing attention, as they share some common clinical characteristics, mechanisms, risk factors, radiological features, and treatment strategies. They influence each other, with the clinical prevalence of PSD comorbid with PSCI reaching as high as 26.15 %. The prevention, screening, diagnosis, and treatment of PSD and PSCI require collaboration across clinical, radiological, and neuropsychological evaluations. This paper aims to summarize the common radiological features of both conditions from a radiological perspective, which may aid in identifying early screening and predictive imaging biomarkers.

Aberrant baseline brain activity and disrupted functional connectivity in patients with vascular cognitive impairment due to cerebral small vessel disease

Objective

This study aims to examine the alterations in aberrant brain activity and network connectivity between individuals with mild and major vascular cognitive impairment (VCI).

Materials and methods

A total of 114 patients with cerebral small vessel disease (CSVD) were included in this study, comprising 61 individuals with mild VCI (mean age, 55.7 ± 6.9 years; male, 42.6%) and 53 cases with major VCI (mean age, 57.6 ± 5.5 years; male, 58.5%). Additionally, 53 age-, gender-, and education-matched healthy subjects were recruited as normal controls (NC) (mean age, 54.9 ± 7.9 years; male, 52.9%). All participants underwent neuropsychological assessments and magnetic resonance imaging scans. One-way analysis of variance was used to compare fractional amplitude of low-frequency fluctuation (fALFF) values among the three groups. Two-sample t-tests were conducted to assess functional connectivity matrices between different groups for each connection. Moreover, mediation analyses were performed to explore the mediating effect of aberrant brain activity on the relationship between cognitive impairment and CSVD total burden.

Results

VCI patients exhibited aberrant brain activity in regions such as the right thalamus (THA_R), right cuneus (CUN_R), left postcentral gyrus (PoCG_L), right postcentral gyrus (PoCG_R), right median cingulate, paracingulate gyri (PCG_R), and left precuneus (PCUN_L). Reduced positive functional connectivity was predominantly observed among nodes including PCUN_L, CUN_R, PoCG_L, PoCG_R, right posterior cingulate (PCG_R), and left occipital gyrus (IOG_L) in VCI patients. The aberrant baseline brain activity and disrupted brain network were more pronounced with worsening cognitive function. Increased fALFF values in THA_R, CUN_R, and PoCG_L mediated cognitive impairment in CSVD patients.

Conclusion

Abnormal brain activities in THA_R, CUN_R, and PoCG_L, along with their associated abnormal functional connections, play a significant role in VCI. The study revealed a progressive increase in aberrant brain activity and network connectivity with advancing stages of VCI.

Linear brain measurement: a new screening method for cognitive impairment in elderly patients with cerebral small vessel disease

Background

The old adults have high incidence of cognitive impairment, especially in patients with cerebral small vessel disease (CSVD). Cognitive impairment is not easy to be detected in such populations. We aimed to develop clinical prediction models for different degrees of cognitive impairments in elderly CSVD patients based on conventional imaging and clinical data to determine the better indicators for assessing cognitive function in the CSVD elderly.

Methods

210 CSVD patients were screened out by the evaluation of Magnetic Resonance Imaging (MRI). Then, participants were divided into the following three groups according to the cognitive assessment results: control, mild cognitive impairment (MCI), and dementia groups. Clinical data were collected from all patients, including demographic data, biochemical indicators, carotid ultrasound, transcranial Doppler (TCD) indicators, and linear measurement parameters based on MRI.

Results

Our results showed that the brain atrophy and vascular lesions developed progressive worsening with increased degree of cognitive impairment. Crouse score and Interuncal distance/Bitemporal distance (IUD/BTD) were independent risk factors for MCI in CSVD patients, and independent risk factors for dementia in CSVD were Crouse Score, the pulsatility index of the middle cerebral artery (MCAPI), IUD/BTD, and Sylvian fissure ratio (SFR). Overall, the parameters with high performance were the IUD/BTD (OR 2.28; 95% CI 1.26-4.10) and SFR (OR 3.28; 95% CI 1.54-6.91), and the AUC (area under the curve) in distinguishing between CSVD older adults with MCI and with dementia was 0.675 and 0.724, respectively. Linear brain measurement parameters had larger observed effect than other indexes to identify cognitive impairments in CSVD patients.

Conclusion

This study shows that IUD/BTD and SFR are good predictors of cognitive impairments in CSVD elderly. Linear brain measurement showed a good predictive power for identifying MCI and dementia in elderly subjects with CSVD. Linear brain measurement could be a more suitable and novel method for screening cognitive impairment in aged CSVD patients in primary healthcare facilities, and worth further promotion among the rural population.

Incidence and risk factors of post-stroke cognitive impairment in convalescent elderly patients with first-episode acute ischemic stroke

A total of 350 first-time AIS elderly patients (aged ≥60 years) were collected and analyzed. Multivariate Logistic regression analysis showed that the lesion site, frontal temporal, cerebral white matter degeneration, age ≥ 75 years, BMI ≥ 28, onset in autumn/winter, hospitalization expenses > 20,000 yuan/month, high DBPV, high NIHSS score, and high HAMD score were risk factors for PSCI. Higher education level was a protective factor. In conclusion, the incidence of PSCI in elderly AIS patients was relatively high and related to the several factors, which indicated that more attention should be paid for such patients to prevent PSCI.

Leukoaraiosis as a Predictor of Depression and Cognitive Impairment among Stroke Survivors: A Systematic Review

Stroke survivors are at increased risk of developing depression and cognitive decline. Thus, it is crucial for both clinicians and stroke survivors to be provided with timely and accurate prognostication of post-stroke depression (PSD) and post-stroke dementia (PSDem). Several biomarkers regarding stroke patients' propensity to develop PSD and PSDem have been implemented so far, leukoaraiosis (LA) being among them. The purpose of the present study was to review all available work published within the last decade dealing with pre-existing LA as a predictor of depression (PSD) and cognitive dysfunction (cognitive impairment or PSDem) in stroke patients. A literature search of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of preexisting LA as a prognostic indicator of PSD and PSDem/cognitive impairment. Only full-text articles published in the English language were included. Thirty-four articles were traced and are included in the present review. LA burden, serving as a surrogate marker of "brain frailty" among stroke patients, appears to be able to offer significant information about the possibility of developing PSD or cognitive dysfunction. Determining the extent of pre-existing white matter abnormalities can properly guide decision making in acute stroke settings, as a greater degree of such lesioning is usually coupled with neuropsychiatric aftermaths, such as PSD and PSDem.

Deep medullary veins: a promising neuroimaging marker for mild cognitive impairment in outpatients

BACKGROUND AND PURPOSE

Mild cognitive impairment is an age-dependent pre-dementia state caused by varied reasons. Early detection of MCI helps handle dementia. Vascular factors are vital for the occurrence of MCI. This study investigates the correlation between deep medullary veins and multi-dimensional cognitive outcomes.

MATERIALS AND METHODS

A total of 73 participants with MCI and 32 controls were enrolled. Minimum Mental State Examination and Montreal Cognitive Assessment were used to examine the global cognitive function, and different cognitive domains were measured by specific neuropsychological tests. MRI was used to assess the visibility of the DMV and other neuroimage markers.

RESULTS

DMV score was statistically significantly higher in the MCI group compared with the control group (P = 0.009) and independently related to MCI (P = 0.007). Linear regression analysis verified that DMV score was linearly related to global cognition, memory, attention, and executive function after adjusting for cerebrovascular risk factors.

CONCLUSION

DMV score was independently related to the onset of MCI, and correlates with overall cognition, memory, attention, and executive function in outpatients.

Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance

Post-stroke cognitive impairment is related to the effects of the acute stroke and pre-stroke brain health. We tested whether diffusion tensor imaging (DTI) can detect acute, global effects of stroke and predict post-stroke cognitive performance. Patients with stroke or TIA enrolled in a prospective cohort study were included if they had 1) at least one DTI acquisition at acute presentation, 24 hours, 5 days, or 30 days, and 2) follow-up testing with the telephone Montreal Cognitive Assessment (T-MoCA) at 30 and/or 90 days. A whole brain, white-matter skeleton excluding the infarct was used to derive mean global DTI measures for mean diffusivity (MD), fractional anisotropy (FA), free water (FW), FW-corrected MD (MD_tissue), and FW-corrected FA (FA_tissue). In 74 patients with ischemic stroke or TIA, there was a transient 4.2% increase in mean global FW between acute presentation and 24 hours (p = 0.024) that returned to initial values by 30 days (p = 0.03). Each acute global DTI measure was associated with 30-day T-MoCA score (n = 61, p = 0.0011-0.0076). Acute global FW, MD, FA and FA_tissue were also associated with 90-day T-MoCA (n = 56, p = 0.0034-0.049). Transient global FW elevation likely reflects stroke-related interstitial edema, whereas other global DTI measures are more representative of pre-stroke brain health.

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.

Structural brain network measures in elderly patients with cerebral small vessel disease and depressive symptoms

Objectives

To investigate the relationship between diffusion tensor imaging (DTI) indicators and cerebral small vessel disease (CSVD) with depressive states, and to explore the underlying mechanisms of white matter damage in CSVD with depression.

Method

A total of 115 elderly subjects were consecutively recruited from the neurology clinic, including 36 CSVD patients with depressive state (CSVD+D), 34 CSVD patients without depressive state (CSVD-D), and 45 controls. A detailed neuropsychological assessment and multimodal magnetic resonance imaging (MRI) were performed. Based on tract-based spatial statistics (TBSS) analysis and structural network analysis, differences between groups were compared, including white matter fiber indicators (fractional anisotropy and mean diffusivity) and structural brain network indicators (global efficiency, local efficiency and network strength), in order to explore the differences and correlations of DTI parameters among the three groups.

Results

There were no significant differences in terms of CSVD burden scores and conventional imaging findings between the CSVD-D and CSVD+D groups. Group differences were found in DTI indicators (p <  0.05), after adjusting for age, gender, education level, and vascular risk factors (VRF), there were significant correlations between TBSS analysis indicators and depression, including: fractional anisotropy (FA) (r = − 0.291, p <  0.05), mean diffusivity (MD) (r = 0.297, p < 0.05), at the same time, between structural network indicators and depression also show significant correlations, including: local efficiency (E_Local) (r = − 0.278, p < 0.01) and network strength (r = − 0.403, p < 0.001).

Conclusions

Changes in FA, MD values and structural network indicators in DTI parameters can predict the depressive state of CSVD to a certain extent, providing a more direct structural basis for the hypothesis of abnormal neural circuits in the pathogenesis of vascular-related depression. In addition, abnormal white matter alterations in subcortical neural circuits probably affect the microstructural function of brain connections, which may be a mechanism for the concomitant depressive symptoms in CSVD patients.

Effect of Early Cognitive Training Combined with Aerobic Exercise on Quality of Life and Cognitive Function Recovery of Patients with Poststroke Cognitive Impairment

Objective

To explore the effect of early cognitive training combined with aerobic exercise on quality of life (QOL) and cognitive function recovery of patients with poststroke cognitive impairment (PSCI).

Methods

Ninety PSCI patients treated in our hospital from April 2019 to April 2020 were selected as the subjects and were divided into the experimental group (EG) and control group (CG) according to the admission order, with 45 cases each. Patients in CG received conventional health education combined with rehabilitation training, and those in EG accepted early cognitive training combined with aerobic exercise so as to evaluate the clinical effect of different intervention modes on PSCI patients.

Results

Compared with CG after intervention, EG obtained an obviously higher Stroke Specific Quality of Life scale (SS-QOL) score, Montreal Cognitive Assessment (MoCA) score, Barthel Index (MBI) (BI) score and Functional Independence Measure (FIM) score (P < 0.001), and obviously shorter time for completing TMT-A and TMT-B (P < 0.001).

Conclusion

Performing early cognitive training combined with aerobic exercise for PSCI patients can effectively improve their QOL and promote the recovery of cognitive function. Compared with conventional health education combined with rehabilitation training, this mode presents a higher application value. Further study will be conducive to establishing a better solution for patients.

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.

Individual-specific networks for prediction modelling – A scoping review of methods

Background

Recent advances in biotechnology enable the acquisition of high-dimensional data on individuals, posing challenges for prediction models which traditionally use covariates such as clinical patient characteristics. Alternative forms of covariate representations for the features derived from these modern data modalities should be considered that can utilize their intrinsic interconnection. The connectivity information between these features can be represented as an individual-specific network defined by a set of nodes and edges, the strength of which can vary from individual to individual. Global or local graph-theoretical features describing the network may constitute potential prognostic biomarkers instead of or in addition to traditional covariates and may replace the often unsuccessful search for individual biomarkers in a high-dimensional predictor space.

Methods

We conducted a scoping review to identify, collate and critically appraise the state-of-art in the use of individual-specific networks for prediction modelling in medicine and applied health research, published during 2000–2020 in the electronic databases PubMed, Scopus and Embase.

Results

Our scoping review revealed the main application areas namely neurology and pathopsychology, followed by cancer research, cardiology and pathology (N = 148). Network construction was mainly based on Pearson correlation coefficients of repeated measurements, but also alternative approaches (e.g. partial correlation, visibility graphs) were found. For covariates measured only once per individual, network construction was mostly based on quantifying an individual’s contribution to the overall group-level structure. Despite the multitude of identified methodological approaches for individual-specific network inference, the number of studies that were intended to enable the prediction of clinical outcomes for future individuals was quite limited, and most of the models served as proof of concept that network characteristics can in principle be useful for prediction.

Conclusion

The current body of research clearly demonstrates the value of individual-specific network analysis for prediction modelling, but it has not yet been considered as a general tool outside the current areas of application. More methodological research is still needed on well-founded strategies for network inference, especially on adequate network sparsification and outcome-guided graph-theoretical feature extraction and selection, and on how networks can be exploited efficiently for prediction modelling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01544-6.

Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study

Cognitive deficits are central attendant symptoms of major depressive disorder (MDD) with a crucial impact in patients' everyday life. Thus, it is of particular clinical importance to understand their pathophysiology. The aim of this study was to investigate a possible relationship between brain structure and cognitive performance in MDD patients in a well-characterized sample. N = 1007 participants (N_MDD = 482, healthy controls (HC): N_HC = 525) were selected from the FOR2107 cohort for this diffusion-tensor imaging study employing tract-based spatial statistics. We conducted a principal component analysis (PCA) to reduce neuropsychological test results, and to discover underlying factors of cognitive performance in MDD patients. We tested the association between fractional anisotropy (FA) and diagnosis (MDD vs. HC) and cognitive performance factors. The PCA yielded a single general cognitive performance factor that differed significantly between MDD patients and HC (P < 0.001). We found a significant main effect of the general cognitive performance factor in FA (P_tfce-FWE = 0.002) in a large bilateral cluster consisting of widespread frontotemporal-association fibers. In MDD patients this effect was independent of medication intake, the presence of comorbid diagnoses, the number of previous hospitalizations, and depressive symptomatology. This study provides robust evidence that white matter disturbances and cognitive performance seem to be associated. This association was independent of diagnosis, though MDD patients show more pronounced deficits and lower FA values in the global white matter fiber structure. This suggests a more general, rather than the depression-specific neurological basis for cognitive deficits.

Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain

The connectome of the brain has a great impact on the function of the brain as the structure of the connectome affects the speed and efficiency of information transfer. As a highly energy-consuming organ, an efficient network structure is essential. A previous study has shown consistent overall brain connectivity across a large variety of species. This connectivity conservation was explained by a balance between interhemispheric and intrahemispheric connections; that is, spices with highly connected hemispheres appear to have weaker interhemisphere connections. This study examines this connectivity trade-off in the human brain using diffusion-based tractography and network analysis in the Human Connectome Project (970 subjects, 527 female). We explore the biological origins of this phenomenon, heritability, and the effect on cognitive measures.The proportion of commissural fibers in the brain had a negative correlation to hemispheric efficiency, pointing to a trade-off between inner hemispheric and interhemispheric connectivity. Network hubs including anterior and middle cingulate cortex, superior frontal areas, medial occipital areas, the parahippocampal gyrus, post- and precentral gyri, and the precuneus had the strongest contribution to this phenomenon. Other results show a high heritability as well as a strong connection to crystalized intelligence. This work presents cohort-based network analysis research, spanning a large variety of samples and exploring the overall architecture of the human connectome. Our results show a connectivity conservation phenomenon at the base of the overall brain network architecture. This network structure may explain much of the functional, behavioral, and cognitive variability among different brains.SIGNIFICANCE STATEMENT The network structure of the brain is at the basis of every brain function as it dictates the characteristics of information transfer. Understanding the patterns and mechanisms that guide the connectome structure is crucial to understanding the brain itself. Here we unravel the mechanism at the base of the connectivity conservation phenomenon by exploring the interaction between hemispheric and commissural connectivity in a large-scale cohort-based connectivity study. We describe the trade-off between the two components and examine the origins of the trade-off and observe the effect on cognitive abilities and behavior.

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.

Grip training improves handgrip strength, cognition, and brain white matter in minor acute ischemic stroke patients

OBJECTIVE

A large proportion of stroke patients experience cognitive impairment. Previous studies found that handgrip training can improve cognitive dysfunction after stroke through an unknown mechanism. In this study, we aimed to examine the influence of handgrip training on the cognition of patients with acute mild ischemic stroke and explore the mechanism using an advanced post-processing method for magnetic resonance imaging.

METHODS

Seventy-six patients with acute mild ischemic stroke were recruited for this study and randomly divided into a grip training group (n = 37) and a control group (n = 39). Both groups of patients also received standardized treatment for stroke in the acute phase and for secondary prevention, as well as conventional physical therapy after stroke. Grip strength, global cognitive function, and the local and global efficiencies of white matter networks derived from diffusion tensor images were measured before and after the 12-week training period.

RESULTS

In the within-group comparisons, grip training significantly improved the grip strength (3.52 [3.09-3.96], p = 0.02), Montreal Cognitive Assessment (MoCA) (2.27 [1.68-2.86], p = 0.05), and local, but not global, efficiency of the brain white matter network (0.03 [0.02-0.03], p = 0.02) in the experimental group. In contrast, these parameters were not statistically different over the same period in the control group. In the between-groups comparisons, the improvement of grip strength (2.71 [2.20-3.21], p = 0.01), MoCA (1.17 [0.39-1.95], p = 0.05), and local efficiency (0.02 [0.01-0.03], p = 0.01) showed statistically significant differences after the intervention, but not the absolute value of them, neither at the base line nor after the intervention.

CONCLUSIONS

Our results indicate that grip training can improve cognitive function by increasing the local efficiency of brain white matter connectivity. This suggests that white matter remodeling is a potential physiological mechanism connecting grip training and cognition improvement.

Multi-Dimensional Diffusion Tensor Imaging Biomarkers for Cognitive Decline From the Preclinical Stage: A Study of Post-stroke Small Vessel Disease

Objectives: We aim to investigate whether multi-dimensional diffusion tensor imaging (DTI) measures can sensitively identify different cognitive status of cerebral small vessel disease (CSVD) and to explore the underlying pattern of white matter disruption in CSVD.

Methods: Two hundred and two participants were recruited, composed of 99 CSVD patients with mild cognitive impairment (VaMCI) and 60 with no cognitive impairment (NCI) and 43 healthy subjects as normal controls (NC). Full domain neuropsychological tests and diffusion-weighted imaging were performed on each subject. DTI metrics such as fractional anisotropy (FA), mean diffusivity (MD), the skeletonized mean diffusivity (PSMD), and structural brain network measures including network strength, global efficiency (E_Global), and local efficiency (E_Local) were calculated. Region of interest (ROI) analysis of 42 white matter tracts was performed to examine the regional anatomical white matter disruption for each group.

Results: Significant differences of multiple cognitive test scores across all cognitive domains especially processing and executive function existed among the three groups. DTI measures (FA, MD, and PSMD) showed significant group difference with the cognitive status changing. FA and E_Global showed significant correlation with processing speed, executive function, and memory. ROI analysis found that white matter integrity impairment occurred from the preclinical stage of vascular cognitive impairment (VCI) due to CSVD. These lesions in the NCI group mainly involved some longitudinal fibers such as right superior longitudinal fasciculus (SLF-R), right superior fronto-occipital fasciculus (SFO-R), and right uncinate fasciculus (UNC-R), which might be more vulnerable to the cerebrovascular aging and disease process.

Conclusions: DTI measures are sensitive neuroimaging markers in detecting the early cognitive impairment and able to differentiate the different cognitive status due to CSVD. Subtle changes of some vulnerable white matter tracts may be observed from the preclinical stage of VCI and have a local to general spreading pattern during the disease progression.

Higher Total Cerebral Small Vessel Disease Burden Was Associated With Mild Cognitive Impairment and Overall Cognitive Dysfunction: A Propensity Score-Matched Case-Control Study

Background and Objective

The combination of neuroimaging and cognition characteristics may provide complementary information for early identification of mild cognitive impairment (MCI). This study aimed to establish the clinical relevance between cerebral small vessel disease (CSVD) burden and MCI and further explored the cognitive characteristics linked to CSVD applying a propensity score matching (PSM) approach.

Methods

The study was designed as a case–control study. All the subjects underwent the standard clinical assessments, neuropsychological testing battery (including global cognition, memory, executive function, and speed and motor control domains), and brain magnetic resonance imaging (MRI). A 1:2 nearest-neighbor matching approach without replacement was employed with a caliper of 0.15 in the PSM approach.

Results

A total of 84 MCI patients and 186 cognitively normal controls were included in this study. After PSM, 74 MCI patients and 129 controls were successfully matched, and the covariate imbalance was well eliminated. Compared with controls, the MCI group had more severe CSVD burden. In the binary logistic regression analysis, CSVD was associated with MCI after adjusting for all confounders. The results of multivariate linear regression analyses showed that higher total MRI CSVD burden was related to the deficit of cognitive performance in global cognition and three important cognitive domains after adjusting for all confounders.

Conclusion

Cerebral small vessel disease was an independent risk factor of MCI. Moreover, higher total MRI CSVD burden was associated with the overall cognitive impairment among middle-aged and elderly Chinese adults.

Difference in distribution functions: A new diffusion weighted imaging metric for estimating white matter integrity

Diffusion weighted imaging (DWI) is a widely recognized neuroimaging technique to evaluate the microstructure of brain white matter. The objective of this study is to establish an improved automated DWI marker for estimating white matter integrity and investigating ageing related cognitive decline. The concept of Wasserstein distance was introduced to help establish a new measure: difference in distribution functions (DDF), which captures the difference of reshaping one's mean diffusivity (MD) distribution to a reference MD distribution. This new DWI measure was developed using a population-based cohort (n=19,369) from the UK Biobank. Validation was conducted using the data drawn from two independent cohorts: the Sydney Memory and Ageing Study, a community-dwelling sample (n=402), and the Renji Cerebral Small Vessel Disease Cohort Study (RCCS), which consisted of cerebral small vessel disease (CSVD) patients (n=171) and cognitively normal controls (NC) (n=43). DDF was associated with age across all three samples and better explained the variance of changes than other established DWI measures, such as fractional anisotropy, mean diffusivity and peak width of skeletonized mean diffusivity (PSMD). Significant correlations between DDF and cognition were found in the UK Biobank cohort and the MAS cohort. Binary logistic analysis and receiver operator characteristic curve analysis of RCCS demonstrated that DDF had higher sensitivity in distinguishing CSVD patients from NC than the other DWI measures. To demonstrate the flexibility of DDF, we calculated regional DDF which also showed significant correlation with age and cognition. DDF can be used as a marker for monitoring the white matter microstructural changes and ageing related cognitive decline in the elderly.

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.

Cognitive impact of cerebral microbleeds in patients with symptomatic small vessel disease

BACKGROUND AND AIM

Whether cerebral microbleeds cause cognitive impairment remains uncertain. We analyzed whether cerebral microbleeds are associated with cognitive dysfunction in patients with symptomatic cerebral small vessel disease, and whether this association is independent of other neuroimaging markers of cerebral small vessel disease.

METHODS

We analyzed consecutive patients with MRI-confirmed lacunar stroke included in DNA-Lacunar-2 multicenter study. Cerebral microbleeds were graded using the Brain Observer Microbleed Rating Scale (BOMBS). Neuropsychological assessment was performed using the Brief Memory and Executive Test (BMET). We analyzed the association between cerebral microbleeds, BMET, and the following subdomains: executive function/processing speed and orientation/memory. We also searched for an independent association between cerebral microbleeds and vascular cognitive impairment, defined as BMET ≤ 13.

RESULTS

Out of 688 included patients, cerebral microbleeds were detected in 192 (27.9%). After adjusting for white matter hyperintensities severity, lacune count, and other confounders, both the presence and the number of cerebral microbleeds were significantly associated with impaired cognitive performance [β = -13.0; 95% CI = (-25.3, -0.6) and β = -13.1; 95% CI = (-19.8, -6.4), respectively]. On analysis of specific cognitive domains, associations were present for executive function/processing speed [β = -5.8; 95% CI = (-9.3, -2.2) and β = -4.3; 95% CI = (-6.2, -2.4), respectively] but not for orientation/memory [β = -0.4; 95% CI = (-4.0, 3.2) and β = -2.1; 95% CI = (-4.0, 0.1), respectively]. We also found an independent association between the presence and the number of cerebral microbleeds and vascular cognitive impairment [adjusted OR = 1.48; 95% CI = (1.01, 2.18) and OR = 1.43; 95% CI = (1.15, 1.79), respectively].

CONCLUSION

In a large cohort of symptomatic cerebral small vessel disease patients, after controlling for other neuroimaging markers of cerebral small vessel disease severity, cerebral microbleeds were associated with cognitive dysfunction. Executive function and processing speed were predominantly impaired. This might suggest a causal role of cerebral microbleeds in determining vascular cognitive impairment.

Cerebral small vessel disease and vascular cognitive impairment: from diagnosis to management

PURPOSE OF REVIEW

We present recent developments in the field of small vessel disease (SVD)-related vascular cognitive impairment, including pathological mechanisms, updated diagnostic criteria, cognitive profile, neuroimaging markers and risk factors. We further address available management and therapeutic strategies.

RECENT FINDINGS

Vascular and neurodegenerative pathologies often co-occur and share similar risk factors. The updated consensus criteria aim to standardize vascular cognitive impairment (VCI) diagnosis, relying strongly on cognitive profile and MRI findings. Aggressive blood pressure control and multidomain lifestyle interventions are associated with decreased risk of cognitive impairment, but disease-modifying treatments are still lacking. Recent research has led to a better understanding of mechanisms leading to SVD-related cognitive decline, such as blood-brain barrier dysfunction, reduced cerebrovascular reactivity and impaired perivascular clearance.

SUMMARY

SVD is the leading cause of VCI and is associated with substantial morbidity. Tackling cardiovascular risk factors is currently the most effective approach to prevent cognitive decline in the elderly. Advanced imaging techniques provide tools for early diagnosis and may play an important role as surrogate markers for cognitive endpoints in clinical trials. Designing and testing disease-modifying interventions for VCI remains a key priority in healthcare.

Cognitive Impairment in Patients with Stroke

Despite substantial advances in stroke care, vascular cognitive impairment remains a prominent source of disability. Unlike sensorimotor impairments, cognition often continues to decline after stroke. An aging population will increase the prevalence of vascular cognitive impairment, with stroke playing an important role. Ten percent of patients presenting with stroke have pre-stroke dementia; an additional 10% will develop incident dementia with a first stroke, and 30% with a recurrent stroke. While stroke increases the risk of cognitive impairment, the presence of cognitive impairment also impacts acute stroke treatment and increases risk of poor outcome by nearly twofold. There is substantial overlap in the clinical and pathological aspects of vascular and degenerative dementias in many patients. How they relate to one another is controversial. The treatment of vascular cognitive impairment remains supportive, focusing on treating vascular risk factors. Cognitive rehabilitation after stroke is an area of active research, and existing pharmacologic treatments have limited benefit. Heightened awareness of cognitive impairment in the setting of stroke is imperative for prognostication and management, impetus for research and, ultimately, the discovery of efficacious treatments.

Altered Brain Structural Networks in Patients with Brain Arteriovenous Malformations Located in Broca's Area

Focal brain lesions, such as stroke and tumors, can lead to remote structural alterations across the whole-brain networks. Brain arteriovenous malformations (AVMs), usually presumed to be congenital, often result in tissue degeneration and functional displacement of the perifocal areas, but it remains unclear whether AVMs may produce long-range effects upon the whole-brain white matter organization. In this study, we used diffusion tensor imaging and graph theory methods to investigate the alterations of brain structural networks in 14 patients with AVMs in the presumed Broca's area, compared to 27 normal controls. Weighted brain structural networks were constructed based on deterministic tractography. We compared the topological properties and network connectivity between patients and normal controls. Functional magnetic resonance imaging revealed contralateral reorganization of Broca's area in five (35.7%) patients. Compared to normal controls, the patients exhibited preserved small-worldness of brain structural networks. However, AVM patients exhibited significantly decreased global efficiency (p = 0.004) and clustering coefficient (p = 0.014), along with decreased corresponding nodal properties in some remote brain regions (p < 0.05, family-wise error corrected). Furthermore, structural connectivity was reduced in the right perisylvian regions but enhanced in the perifocal areas (p < 0.05). The vulnerability of the left supramarginal gyrus was significantly increased (p = 0.039, corrected), and the bilateral putamina were added as hubs in the AVM patients. These alterations provide evidence for the long-range effects of AVMs on brain white matter networks. Our preliminary findings contribute extra insights into the understanding of brain plasticity and pathological state in patients with AVMs.

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 of white matter integrity associated with cognitive deficits in patients with glioma

OBJECTIVE

This study aimed to investigate the characteristic of brain structural connections in glioma patients and further evaluate the relationship between changes in the white matter tracts and cognitive decline.

METHODS

This retrospective study included a total of 35 subjects with glioma and 14 demographically matched healthy controls, who underwent diffusion tensor imaging scans and formal neuropsychological assessment tests. Fractional anisotropy (FA) values of white matter tracts were derived from atlas-based analysis to compare group differences. Furthermore, subgroup-level analysis was performed to differentiate the effects of tumor location on white matter tracts. Partial correlation analysis was used to examine the associations between neurocognitive assessments and the integrity of tracts. Region of interest-based network analysis was performed to validate the alteration of structural brain network in subjects with glioma.

RESULTS

Compared with controls, subjects with glioma exhibited reduced FA values in the right uncinate fasciculus. Besides, subjects with glioma exhibited worse performance in several cognitive assessments. Partial correlation analysis indicated that the FA value in the right superior longitudinal fasciculus temporal part was significantly positively correlated with scores of visual-spatial abilities in subjects with glioma in the right temporal lobe (r = .932, p = .002). Region of interest-based network analysis revealed that subjects with glioma exhibited reduced FA, fiber length (FL), and fiber number (FN) between specific brain regions compared with controls.

CONCLUSION

The present study demonstrated the reduced integrity of white matter tracts and altered structural connectivity in brain networks in patients with glioma. Notably, white matter tracts in the right hemisphere might be vulnerable to the effects of a frontal or temporal lesion and might be associated with deficient cognitive function.

Structural changes in the lobar regions of brain in cerebral small-vessel disease patients with and without cognitive impairment: An MRI-based study with automated brain volumetry

PURPOSE

This study aims to investigate the alterations of brain volumetry and associated structural covariance at lobar level in cerebral small-vessel disease (CSVD) with and without cognitive impairment.

METHOD

Twenty-seven CSVD patients with mild cognitive impairment (CSVD-MCI), 37 CSVD patients with normal cognition (CSVD-NC), and 35 controls, underwent T1-weighted imaging of magnetic resonance. Volume of gray matter (GM) and white matter (WM) and a lobar atrophy index that measures the ratio of cerebrospinal fluid to brain parenchyma were quantified for each lobe. One-way ANOVA with multiple comparison corrections was performed to compare these volumetric measures. Volumetric structural covariance analyses were performed with lobar atrophy indexes to investigate the alterations of anatomical covariance within each pair of lobar regions in CSVD-NC and CSVD-MCI subjects compared with controls.

RESULTS

CSVD-NC subjects presented no significant volumetric differences with controls in any of the lobar regions. Compared with controls, CSVD-MCI patients presented significantly smaller volume of GM in bilateral frontal and parietal lobes, significantly smaller volume of WM in right cingulate lobe, and significantly larger lobar atrophy indexes of bilateral temporal, insular lobes and left cingulate lobe (P < 0.05). Both CSVD-NC group and CSVD-MCI group showed significant differences of structural covariance as measured by lobar atrophy index compared with controls. In particular, CSVD-MCI group showed even more extensive alterations of structural covariance, especially in bilateral cingulate and temporal lobes.

CONCLUSIONS

There are alterations of brain volumetry and associated structural covariance within lobar regions in CSVD, which indicates the potential brain structural reorganization in CSVD.

Impacts of Aerobic Exercise on Depression-Like Behaviors in Chronic Unpredictable Mild Stress Mice and Related Factors in the AMPK/PGC-1α Pathway

This study was to study the impact of aerobic exercises on the chronic unpredictable mild stress (CUMS) in mice, and to discuss the possible mechanism from the skeletal muscle AMPK/PGC-1α energy metabolism signaling pathway. The healthy male mice were randomly divided into Control Group (CG), Model Group (MG), and Model Exercise Group (ME).Twelve stress methods were adopted for four weeks (28 days) to establish the depression model. ME was subject to aerobic training plan after the model was established. The weight of the mice was recorded weekly. After the experimental intervention, the three groups of mice were subjected to behavioral assessment tests. Western blotting, RT-PCR, and ELISA were performed to test AMPK, p-AMPK, PGC-1α, and ATP in skeletal muscle. There were no significant difference in body weight between the three groups. CUMS leaded to significant decline in behavioral scores. and the p-AMPK and PGC-1α decreased significantly. But boosted ATP content. Aerobic exercise enhanced the expressions of p-AMPK and PGC-1α, increased the ratio of p-AMPK/AMPK, boosted ATP content. And improved behavioral scores significantly. Chronic stress-induced depression-like behavior was improved significantly by Aerobic exercise. The mechanism of aerobic exercise for improving depressive symptoms in mice with chronic stress depression may be related to influence AMPK/PGC-1α pathway.

Disrupted Brain Structural Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment With No Dementia

The alteration of the functional topological organization in subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) patients has been illuminated by previous neuroimaging studies. However, in regard to the changes in the structural connectivity of brain networks, little has been reported. In this study, a total of 27 subjects, consisting of 13 SIVCIND patients, and 14 normal controls, were recruited. Each of the structural connectivity networks was constructed by diffusion tensor tractography. Subsequently, graph theory, and network-based statistics (NBS) were employed to analyze the whole-brain mean factional anisotropy matrix. After removing the factor of age, gender, and duration of formal education, the clustering coefficients (C_p) and global efficiency (E_glob) were significantly decreased and the mean path length (L_p) was significantly increased in SIVCIND patients compared with normal controls. Using the combination of four network topological parameters as the classification feature, a classification accuracy of 78% was obtained by leave-one-out cross-validation for all subjects with a sensitivity of 69% and a specificity of 86%. Moreover, we also found decreased structural connections in the SIVCIND patients, which mainly concerned fronto-occipital, fronto-subcortical, and tempo-occipital connections (NBS corrected, p < 0.01). Additionally, significantly altered nodal centralities were found in several brain regions of the SIVCIND patients, mainly located in the prefrontal, subcortical, and temporal cortices. These results suggest that cognitive impairment in SIVCIND patients is associated with disrupted topological organization and provide structural evidence for developing reliable biomarkers related to cognitive decline in SIVCIND.

Differential Influence of Location-Specific White-Matter Hyperintensities on Attention Subdomains Measured Using the Attention Network Test

BACKGROUND Elderly people with white-matter hyperintensities (WMHs) typically show cognitive impairment. Attention, consisting of 3 independent component processes (alerting, orienting, and executive control), is crucial for cognitive functioning. Little is known about how WMHs interfere with these attention subdomains. In the present study, we sought to describe characteristics of attention deficits in patients with age-related WMHs and to assess whether the severity and location of lesions differentially affect specific attention subdomains using the attention network test (ANT), which is a computer-based paradigm tailored to accurately provide behavioral measures of the aforementioned subdomains. MATERIAL AND METHODS A total of 39 WMH patients and 39 age-, sex-, and education-matched controls underwent comprehensive neuropsychological and ANT evaluation. Brain magnetic resonance imaging (MRI) was performed to visualize severity of total and location-specific WMH lesions. Multiple linear regression analyses adjusted for possible confounders were performed. RESULTS Compared with controls, WMH patients showed pronounced deficits in orienting and executive control efficiencies (P<0.050), but not alerting efficiency (P=0.642). As total WMH severity increased, efficiencies in the impaired subdomains significantly declined (P<0.050). In terms of lesion location, fronto-parietal type of periventricular WMH (PWMH) and deep WMH (DWMH) in the parietal lobe affected orienting efficiency, while all PWMH types and DWMH in the frontal, parietal, and temporal lobes affected executive control efficiency (P<0.050). Additional adjustment for other MRI lesions significantly changed the impact on orienting, but not on executive control efficiency. CONCLUSIONS Our results reveal specific attention deficits in patients with age-related WMH and may help clarify how the location of lesions influences their effects on attention subdomains.

Disruption of white matter connectivity in chronic obstructive pulmonary disease

Background

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

Methods

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

Results

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

Conclusion

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

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

Supplemental Digital Content is available in the text.

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

Alterations in Brain Structural Connectivity After Unilateral Upper-Limb Amputation

Previous studies have indicated that amputation induces reorganization of functional brain network. However, the influence of amputation on structural brain network remains unclear. In this study, using diffusion tensor imaging (DTI), we aimed to investigate the alterations in fractional anisotropy (FA) network after unilateral upper-limb amputation. We acquired DTI from twenty-two upper-limb amputees (15 dominant-side and 7 nondominant-side amputees) as well as fifteen healthy controls. Using DTI tractography and graph theoretical approaches, we examined the topological changes in FA network of amputees. Compared with healthy controls, dominant-side amputees showed reduced global mean strength, increased characteristic path length, and decreased nodal strength in the contralateral sensorimotor system and visual areas. In particular, the nodal strength of the contralateral postcentral gyrus was negatively correlated with residual limb usage, representing a use-dependent reorganization. In addition, the nodal strength of the contralateral middle temporal gyrus was positively correlated with the magnitude of phantom limb sensation. Our results suggested a degeneration of FA network after dominant-side upper-limb amputation.

Neuroimaging studies on cognitive impairment due to cerebral small vessel disease

Vascular cognitive impairment (VCI) is a major contributor to age-related dementing illnesses which imposes a tremendous burden on families and society. It is a heterogeneous group of brain disorders. However, cerebral small vessel disease (CSVD) accounts for about 50%-70% of VCI, which represented a more homogeneous subtype of VCI. Advanced multimodal neuroimaging techniques like brain network connectome analyses are currently applied to explore the underlying mechanism of VCI. Some progress in the field of structural and functional brain network researches on a poststroke longitudinal CSVD cohort (Renji CSVD Cohort Study) was reported. Global and regional brain network characters were compared between patients with CSVD and healthy control. It suggested that distributed brain structural network disruption may play a pivot role in the cognitive decline. The results showed that brain structural network characters have distinctive differentiating capacity on the cognition of patients with CSVD.