White matter hyperintensities and normal-appearing white matter integrity in the aging brain

Blood-Brain Barrier Permeability Is Associated With Cognitive Functioning in Normal Aging and Neurodegenerative Diseases

BACKGROUND

The purpose of this study was to investigate the relationship between blood-brain barrier (BBB) permeability and cognitive functioning in healthy older adults and individuals with neurodegenerative diseases.

METHODS AND RESULTS

A total of 124 participants with Alzheimer disease, cerebrovascular disease, or a mix Alzheimer's and cerebrovascular diseases and 55 controlparticipants underwent magnetic resonance imaging and neuropsychological testing. BBB permeability was measured with dynamic contrast-enhanced magnetic resonance imaging and white matter injury was measured using a quantitative diffusion-tensor imaging marker of white matter injury. Structural equation modeling was used to examine the relationships between BBB permeability, vascular risk burden, white matter injury, and cognitive functioning. Vascular risk burden predicted BBB permeability (r=0.24, P<0.05) and white matter injury (r=0.38, P<0.001). BBB permeability predicted increased white matter injury (r=0.34, P<0.001) and increased white matter injury predicted lower cognitive functioning (r=-0.51, P<0.001).

CONCLUSIONS

The study provides empirical support for a vascular contribution to white matter injury and cognitive impairment, directly or indirectly via BBB permeability. This highlights the importance of targeting modifiable vascular risk factors to help mitigate future cognitive decline.

Heme Oxygenase-1 Gene (GT)n Polymorphism Linked to Deep White Matter Hyperintensities, Not Periventricular Hyperintensities

BACKGROUND

Oxidative stress plays a principal role in the pathogenesis of white matter hyperintensities (WMHs). The induction of heme oxygenase-1 (HO-1) gene in the brain represents 1 of the pivotal mechanisms to counteract the noxious effects of reactive oxygen species, and the transcriptional modulation of HO-1 induction depends on the length of a GT-repeat (GT)n in the promoter region. We investigated whether the HO-1 gene (GT)n polymorphism is associated with the risk of WMHs.

METHODS AND RESULTS

A total of 849 subjects from the memory clinic were consecutively enrolled, and the HO-1 (GT)n genotype was determined. WMHs were assessed with the Fazekas scale and further divided into periventricular WMHs and deep WMHs (DWMHs). Allelic HO-1 (GT)n polymorphisms were classified as short (≤24 (GT)n), median (25≤[GT]n<31), or long (31≤[GT]n). Multivariate logistic regression analysis was used to evaluate the effect of the HO-1 (GT)n variants on WMHs. The number of repetitions of the HO-1 gene (GT)n ranged from 15 to 39 with a bimodal distribution at lengths 23 and 30. The proportion of S/S genotypes was higher for moderate/severe DWMHs than none/mild DWMHs (22.22% versus 12.44%; P=0.001), but the association for periventricular WMHs was not statistically significant. Logistic regression suggested that the S/S genotype was significantly associated with moderate/severe DWMHs (S/S versus non-S/S: odds ratio, 2.001 [95% CI, 1.323-3.027]; P<0.001). The HO-1 gene (GT)n S/S genotype and aging synergistically contributed to the progression of DWMHs (relative excess risk attributable to interaction, 6.032 [95% CI, 0.149-11.915]).

CONCLUSIONS

Short (GT)n variants in the HO-1 gene may confer susceptibility to rather than protection from DWMHs, but not periventricular WMHs.

REGISTRATION

URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100045869.

Imaging Biomarkers of VCI: A Focused Update

Vascular cognitive impairment is common after stroke, in memory clinics, medicine for the elderly services, and undiagnosed in the community. Vascular disease is said to be the second most common cause of dementia after Alzheimer disease, yet vascular dysfunction is now known to predate cognitive decline in Alzheimer disease, and most dementias at older ages are mixed. Neuroimaging has a major role in identifying the proportion of vascular versus other likely pathologies in patients with cognitive impairment. Here, we aim to provide a pragmatic but evidence-based summary of the current state of potential imaging biomarkers, focusing on magnetic resonance imaging and computed tomography, which are relevant to diagnosing, estimating prognosis, monitoring vascular cognitive impairment, and incorporating our own experiences. We focus on markers that are well-established, with a known profile of association with cognitive measures, but also consider more recently described, including quantitative tissue markers of vascular injury. We highlight the gaps in accessibility and translation to more routine clinical practice.

Subtle white matter intensity changes on fluid-attenuated inversion recovery imaging in patients with ischaemic stroke

Leukoaraiosis is a neuroimaging marker of small-vessel disease that is characterized by high signal intensity on fluid-attenuated inversion recovery MRI. There is increasing evidence from pathology and neuroimaging suggesting that the structural abnormalities that characterize leukoaraiosis are actually present within regions of normal-appearing white matter, and that the underlying pathophysiology of white matter damage related to small-vessel disease involves blood-brain barrier damage. In this study, we aim to verify whether leukoaraiosis is associated with elevated signal intensity on fluid-attenuated inversion recovery imaging, a marker of brain tissue free-water accumulation, in normal-appearing white matter. We performed a cross-sectional study of adult patients admitted to our hospital with a diagnosis of acute ischaemic stroke or transient ischaemic attack. Leukoaraiosis was segmented using a semi-automated method involving manual outlining and signal thresholding. White matter regions were segmented based on the probabilistic tissue maps from the International Consortium for Brain Mapping 152 atlas. Also, normal-appearing white matter was further segmented based on voxel distance from leukoaraiosis borders, resulting in five normal-appearing white matter strata at increasing voxel distances from leukoaraiosis. The relationship between mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter and leukoaraiosis volume was studied in a multivariable statistical analysis using linear mixed modelling, having normal-appearing white matter strata as a clustering variable. One hundred consecutive patients meeting inclusion and exclusion criteria were selected for analysis (53% female, mean age 68 years). Mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was higher in the vicinity of leukoaraiosis and progressively lower at increasing distances from leukoaraiosis. In a multivariable analysis, the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was positively associated with leukoaraiosis volume and age (B = 0.025 for each leukoaraiosis quartile increase; 95% confidence interval 0.019-0.030). This association was found similarly across normal-appearing white matter strata. Voxel maps of the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter showed an increase in signal intensity that was not adjacent to leukoaraiosis regions. Our results show that normal-appearing white matter exhibits subtle signal intensity changes on fluid-attenuated inversion recovery imaging that are related to leukoaraiosis burden. These results suggest that diffuse free-water accumulation is likely related to the aetiopathogenic processes underlying the development of white matter damage related to small-vessel disease.

Magnetic Resonance Imaging Tissue Signatures Associated With White Matter Changes Due to Sporadic Cerebral Small Vessel Disease Indicate That White Matter Hyperintensities Can Regress

BACKGROUND

White matter hyperintensities (WMHs) might regress and progress contemporaneously, but we know little about underlying mechanisms. We examined WMH change and underlying quantitative magnetic resonance imaging tissue measures over 1 year in patients with minor ischemic stroke with sporadic cerebral small vessel disease.

METHODS AND RESULTS

We defined areas of stable normal-appearing white matter, stable WMHs, progressing and regressing WMHs based on baseline and 1-year brain magnetic resonance imaging. In these areas we assessed tissue characteristics with quantitative T1, fractional anisotropy (FA), mean diffusivity (MD), and neurite orientation dispersion and density imaging (baseline only). We compared tissue signatures cross-sectionally between areas, and longitudinally within each area. WMH change masks were available for N=197. Participants' mean age was 65.61 years (SD, 11.10), 59% had a lacunar infarct, and 68% were men. FA and MD were available for N=195, quantitative T1 for N=182, and neurite orientation dispersion and density imaging for N=174. Cross-sectionally, all 4 tissue classes differed for FA, MD, T1, and Neurite Density Index. Longitudinally, in regressing WMHs, FA increased with little change in MD and T1 (difference estimate, 0.011 [95% CI, 0.006-0.017]; -0.002 [95% CI, -0.008 to 0.003] and -0.003 [95% CI, -0.009 to 0.004]); in progressing and stable WMHs, FA decreased (-0.022 [95% CI, -0.027 to -0.017] and -0.009 [95% CI, -0.011 to -0.006]), whereas MD and T1 increased (progressing WMHs, 0.057 [95% CI, 0.050-0.063], 0.058 [95% CI, 0.050 -0.066]; stable WMHs, 0.054 [95% CI, 0.045-0.063], 0.049 [95% CI, 0.039-0.058]); and in stable normal-appearing white matter, MD increased (0.004 [95% CI, 0.003-0.005]), whereas FA and T1 slightly decreased and increased (-0.002 [95% CI, -0.004 to -0.000] and 0.005 [95% CI, 0.001-0.009]).

CONCLUSIONS

Quantitative magnetic resonance imaging shows that WMHs that regress have less abnormal microstructure at baseline than stable WMHs and follow trajectories indicating tissue improvement compared with stable and progressing WMHs.

Vascular risk, gait, behavioral, and plasma indicators of VCID

INTRODUCTION

Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age.

METHODS

In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles.

RESULTS

VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata.

DISCUSSION

Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID.

HIGHLIGHTS

Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.

Bidirectional associations of high-level cognitive domains with hand motor function and gait speed in high-functioning older adults: A 7-year study

BACKGROUND

Whether age-related decline in the musculoskeletal system may contribute to a decline in cognitive performance or vice versa is unclear. Understanding the direction of their associations and the extent to which upper and lower extremities similarly predict subtle changes in high-level cognitive performance will help elucidate their mechanisms, especially that of the hand dexterity.

METHODS

We evaluated the bidirectional associations of motor performance and high-level cognitive domains in 165 highly cognitively and physically healthy older adults. Motor performance tests consisted of handgrip strength, hand dexterity, assessed with the Purdue Pegboard Test (PPT), and usual and maximum gait speeds. High-level cognitive measures included executive function and information processing speed. The Trail Making Test (TMT)B and the letter and category fluency tests (LFT and CFT) evaluated executive function, while the TMTA and Digit Symbol assessed processing speed. Measurements were taken at baseline and at 2-, 5- and 7-year follow-up.

RESULTS

Generalized linear mixed-effect models showed that baseline hand dexterity and its trajectory predicted changes in TMTB, CFT, TMTA, and Digit Symbol over time, and vice versa. Baseline maximum gait speed was associated with LFT over time and vice versa. No associations were found for handgrip and usual gait speed.

CONCLUSION

The positive bidirectional association observed both in hand dexterity and maximum gait speed with executive function performance and that of hand dexterity with processing speed over time highlights a reciprocal relationship where each factor affects the other and both factors are dependent on each other, suggesting commonality in their neural basis.

Sex Differences in the Association of Age at Hypertension Diagnosis With Brain Structure

BACKGROUND

Sex differences exist in the likelihood of cognitive decline. The age at hypertension diagnosis is a unique contributor to brain structural changes associated with cerebral small vessel disease. However, whether this relationship differs between sexes remains unclear. Therefore, our objective was to evaluate sex differences in the association between the age at hypertension diagnosis and cerebral small vessel disease-related brain structural changes.

METHODS

We used data from the UK Biobank to select participants with a known age at hypertension diagnosis and brain magnetic resonance imaging (n=9430) and stratified them by sex and age at hypertension diagnosis. Control participants with magnetic resonance imaging scans but no hypertension were chosen at random matched by using propensity score matching. For morphological brain structural changes, generalized linear models were used while adjusting for other vascular risk factors. For the assessment of white matter microstructure, principal component analysis led to a reduction in the number of fractional anisotropy variables, followed by regression analysis with major principal components as outcomes.

RESULTS

Males but not females with a younger age at hypertension diagnosis exhibited lower brain gray and white matter volume compared with normotensive controls. The volume of white matter hyperintensities was greater in both males and females with hypertension than normotensive controls, significantly higher in older females with hypertension. Compared with normotensive controls, white matter microstructural integrity was lower in individuals with hypertension, which became more prominent with increasing age.

CONCLUSIONS

Our study demonstrates that the effect of hypertension on cerebral small vessel disease-related brain structure differs by sex and by age at hypertension diagnosis.

Association of Vascular Risk Factors and CSF and Imaging Biomarkers With White Matter Hyperintensities in Former American Football Players

BACKGROUND AND OBJECTIVES

Recent data link exposure to repetitive head impacts (RHIs) from American football with increased white matter hyperintensity (WMH) burden. WMH might have unique characteristics in the context of RHI beyond vascular risk and normal aging processes. We evaluated biological correlates of WMH in former American football players, including markers of amyloid, tau, inflammation, axonal injury, neurodegeneration, and vascular health.

METHODS

Participants underwent clinical interviews, MRI, and lumbar puncture as part of the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of Chronic Traumatic Encephalopathy Research Project. Structural equation modeling tested direct and indirect effects between log-transformed total fluid-attenuated inversion recovery (FLAIR) lesion volumes (TLV) and the revised Framingham stroke risk profile (rFSRP), MRI-derived global metrics of cortical thickness and fractional anisotropy (FA), and CSF levels of amyloid β1-42, p-tau181, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and neurofilament light. Covariates included age, race, education, body mass index, APOE ε4 carrier status, and evaluation site. Models were performed separately for former football players and a control group of asymptomatic men unexposed to RHI.

RESULTS

In 180 former football players (mean age = 57.2, 36% Black), higher log(TLV) had direct associations with the following: higher rFSRP score (B = 0.26, 95% CI 0.07-0.40), higher p-tau181 (B = 0.17, 95% CI 0.01-0.43), lower FA (B = -0.28, 95% CI -0.42 to -0.13), and reduced cortical thickness (B = -0.25, 95% CI -0.45 to -0.08). In 60 asymptomatic unexposed men (mean age = 59.3, 40% Black), there were no direct effects on log(TLV) (rFSRP: B = -0.03, 95% CI -0.48 to 0.57; p-tau181: B = -0.30, 95% CI -1.14 to 0.37; FA: B = -0.07, 95% CI -0.48 to 0.42; or cortical thickness: B = -0.28, 95% CI -0.64 to 0.10). The former football players showed stronger associations between log(TLV) and rFSRP (1,069% difference in estimates), p-tau181 (158%), and FA (287%) than the unexposed men.

DISCUSSION

Risk factors and biological correlates of WMH differed between former American football players and asymptomatic unexposed men. In addition to vascular health, p-tau181 and diffusion tensor imaging indices of white matter integrity showed stronger associations with WMH in the former football players. FLAIR WMH may have specific risk factors and pathologic underpinnings in RHI-exposed individuals.

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data

BACKGROUND

White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain.

METHODS

We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis.

RESULTS

The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score.

CONCLUSION

Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.

Early detection of white matter hyperintensities using SHIVA-WMH detector

White matter hyperintensities (WMHs) are well-established markers of cerebral small vessel disease, and are associated with an increased risk of stroke, dementia, and mortality. Although their prevalence increases with age, small and punctate WMHs have been reported with surprisingly high frequency even in young, neurologically asymptomatic adults. However, most automated methods to segment WMH published to date are not optimized for detecting small and sparse WMH. Here we present the SHIVA-WMH tool, a deep-learning (DL)-based automatic WMH segmentation tool that has been trained with manual segmentations of WMH in a wide range of WMH severity. We show that it is able to detect WMH with high efficiency in subjects with only small punctate WMH as well as in subjects with large WMHs (i.e., with confluency) in evaluation datasets from three distinct databases: magnetic resonance imaging-Share consisting of young university students, MICCAI 2017 WMH challenge dataset consisting of older patients from memory clinics, and UK Biobank with community-dwelling middle-aged and older adults. Across these three cohorts with a wide-ranging WMH load, our tool achieved voxel-level and individual lesion cluster-level Dice scores of 0.66 and 0.71, respectively, which were higher than for three reference tools tested: the lesion prediction algorithm implemented in the lesion segmentation toolbox (LPA: Schmidt), PGS tool, a DL-based algorithm and the current winner of the MICCAI 2017 WMH challenge (Park et al.), and HyperMapper tool (Mojiri Forooshani et al.), another DL-based method with high reported performance in subjects with mild WMH burden. Our tool is publicly and openly available to the research community to facilitate investigations of WMH across a wide range of severity in other cohorts, and to contribute to our understanding of the emergence and progression of WMH.

Hybrid model of CT-fractional flow reserve, pericoronary fat attenuation index and radiomics for predicting the progression of WMH: a dual-center pilot study

Objective

To develop and validate a hybrid model incorporating CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics signatures for predicting progression of white matter hyperintensity (WMH).

Methods

A total of 226 patients who received coronary computer tomography angiography (CCTA) and brain magnetic resonance imaging from two hospitals were divided into a training set (n = 116), an internal validation set (n = 30), and an external validation set (n = 80). Patients who experienced progression of WMH were identified from subsequent MRI results. We calculated CT-FFR and pFAI from CCTA images using semi-automated software, and segmented the pericoronary adipose tissue (PCAT) and myocardial ROI. A total of 1,073 features were extracted from each ROI, and were then refined by Elastic Net Regression. Firstly, different machine learning algorithms (Logistic Regression [LR], Support Vector Machine [SVM], Random Forest [RF], k-nearest neighbor [KNN] and eXtreme Gradient Gradient Boosting Machine [XGBoost]) were used to evaluate the effectiveness of radiomics signatures for predicting WMH progression. Then, the optimal machine learning algorithm was used to compare the predictive performance of individual and hybrid models based on independent risk factors of WMH progression. Receiver operating characteristic (ROC) curve analysis, calibration and decision curve analysis were used to evaluate predictive performance and clinical value of the different models.

Results

CT-FFR, pFAI, and radiomics signatures were independent predictors of WMH progression. Based on the machine learning algorithms, the PCAT signatures led to slightly better predictions than the myocardial signatures and showed the highest AUC value in the XGBoost algorithm for predicting WMH progression (AUC: 0.731 [95% CI: 0.603-0.838] vs.0.711 [95% CI: 0.584-0.822]). In addition, pFAI provided better predictions than CT-FFR (AUC: 0.762 [95% CI: 0.651-0.863] vs. 0.682 [95% CI: 0.547-0.799]). A hybrid model that combined CT-FFR, pFAI, and two radiomics signatures provided the best predictions of WMH progression [AUC: 0.893 (95%CI: 0.815-0.956)].

Conclusion

pFAI was more effective than CT-FFR, and PCAT signatures were more effective than myocardial signatures in predicting WMH progression. A hybrid model that combines pFAI, CT-FFR, and two radiomics signatures has potential use for identifying WMH progression.

A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging

Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm2/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.

Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging

White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.

Characterizing the penumbras of white matter hyperintensities in patients with cerebral small vessel disease

PURPOSE

The white matter hyperintensity penumbra (WMH-P) is the subtly changed normal-appearing white matter (NAWM) that surrounds white matter hyperintensities (WMHs). The goal of this study was to define WMH-P in cerebral small vessel disease (CSVD) by arterial spin labeling (ASL) and diffusion tensor imaging (DTI)/diffusion kurtosis imaging (DKI).

MATERIALS AND METHODS

We prospectively analyzed 42 patients with CSVD. To determine the range of cerebral blood flow (CBF) and DTI/DKI penumbras around white matter hyperintensities, we generated NAWM layer masks from periventricular WMHs (PVWMHs) and deep WMHs (DWMHs). Mean values of CBF, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis, and radial kurtosis within the WMHs and their corresponding NAWM layer masks were analyzed. Paired sample t tests were used for analysis, and differences were considered statistically significant if the associated p value was ≤ 0.05.

RESULTS

For DWMHs, the CBF penumbras were 13 mm, and the DTI/DKI penumbras were 8 mm. For PVWMHs, the CBF penumbras were 14 mm, and the DTI/DKI penumbras were 14 mm.

CONCLUSIONS

Our findings revealed that DTI/DKI and ASL can show structural and blood flow changes in brain tissue surrounding WMHs. In DWMHs, the blood flow penumbra was larger than the structural penumbra, while in PVWMHs, the blood flow penumbra was almost the same as the structural penumbra.

Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds

We investigate associations between normal-appearing white matter microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 birth cohort) underwent PET-MRI around age 70. Mean standardized normal-appearing white matter integrity metrics (fractional anisotropy, mean diffusivity, neurite density index and orientation dispersion index) were derived from diffusion MRI. Linear regression was used to test associations between normal-appearing white matter metrics and (i) concurrent measures, including whole brain volume, white matter hyperintensity volume, PET amyloid and cognition; (ii) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socio-economic position and genetic risk for Alzheimer's disease (APOE-ɛ4); (iii) systolic and diastolic blood pressure and cardiovascular health (Framingham Heart Study Cardiovascular Risk Score) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). Three hundred and sixty-two participants met inclusion criteria (mean age 70, 49% female). Higher white matter hyperintensity volume was associated with lower fractional anisotropy [b = -0.09 (95% confidence interval: -0.11, -0.06), P < 0.01], neurite density index [b = -0.17 (-0.22, -0.12), P < 0.01] and higher mean diffusivity [b = 0.14 (-0.10, -0.17), P < 0.01]; amyloid (in men) was associated with lower fractional anisotropy [b = -0.04 (-0.08, -0.01), P = 0.03)] and higher mean diffusivity [b = 0.06 (0.01, 0.11), P = 0.02]. Framingham Heart Study Cardiovascular Risk Score in later-life (age 69) was associated with normal-appearing white matter {lower fractional anisotropy [b = -0.06 (-0.09, -0.02) P < 0.01], neurite density index [b = -0.10 (-0.17, -0.03), P < 0.01] and higher mean diffusivity [b = 0.09 (0.04, 0.14), P < 0.01]}. Significant sex interactions (P < 0.05) emerged for midlife cardiovascular health (age 53) and normal-appearing white matter at 70: marginal effect plots demonstrated, in women only, normal-appearing white matter was associated with higher midlife Framingham Heart Study Cardiovascular Risk Score (lower fractional anisotropy and neurite density index), midlife systolic (lower fractional anisotropy, neurite density index and higher mean diffusivity) and diastolic (lower fractional anisotropy and neurite density index) blood pressure and greater blood pressure change between 43 and 53 years (lower fractional anisotropy and neurite density index), independently of white matter hyperintensity volume. In summary, poorer normal-appearing white matter microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how normal-appearing white matter can provide additional information to overt white matter disease. Our findings further show that greater 'midlife' cardiovascular risk and higher blood pressure were associated with poorer normal-appearing white matter microstructural integrity in females only, suggesting that women's brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health.

The association of diffusion tensor MRI measures of normal appearing white matter and cognition

Objective

Median and peak height of fractional anisotropy (FA) and mean diffusivity (MD) are diffusion tensor imaging (DTI) markers used to quantify white matter microstructure changes. We examine the association of DTI histogram-derived measures in global normal appearing white matter (NAWM) and cognitive decline in patients with normal cognition and cognitive impairment no dementia from a memory clinic in Singapore.

Methods

A total of 252 patients (mean age: 71.1 ± 7.6 years, 53.2% women) were included. All patients underwent clinical assessments, a brain MRI scan at baseline, and neuropsychological assessments annually for 2 years. DTI scans were processed to obtain MD and FA histogram-derived measures. The National Institute of Neurological Disorders and Stroke and the Canadian Stroke Network harmonization neuropsychological battery were used to assess cognitive function. Linear regression models with generalised estimating equation (GEE) and logistic regression models were used to examine the association between DTI histogram measures and cognitive decline.

Results

When compared to baseline, MD and FA measures at Year 2 were associated with an accelerated worsening in global cognition (all p for interaction <0.001; Year 0 vs 2, MD median: -0.29 (95%CI: -0.49, -0.09) vs -0.45 (95%CI: -0.65,-0.25); MD peak height: 0.22 (95%CI: 0.07, 0.37) vs 0.37 (95%CI: 0.21, 0.53); FA median: 0.11 (95%CI: -0.05, 0.26) vs 0.22 (95%CI: 0.07, 0.37); FA peak height: -0.14 (95%CI: -0.28, 0.00) vs -0.24 (95%CI: -0.38, -0.10);). Similar findings were observed for executive function and visuomotor speed while only MD measures predicted worsening in memory domain.

Interpretation

This study shows that DTI histogram measures are associated with accelerated cognitive decline suggesting the utility of DTI as a pre-clinical marker in predicting the worsening of cognition in clinical trials.

Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration

Progressive white matter degeneration in periventricular and deep white matter regions appears as white matter hyperintensities (WMH) on MRI scans. To date, periventricular WMHs are often associated with vascular dysfunction. Here, we demonstrate that ventricular inflation resulting from cerebral atrophy and hemodynamic pulsation with every heartbeat leads to a mechanical loading state of periventricular tissues that significantly affects the ventricular wall. Specifically, we present a physics-based modeling approach that provides a rationale for ependymal cell involvement in periventricular WMH formation. Building on eight previously created 2D finite element brain models, we introduce novel mechanomarkers for ependymal cell loading and geometric measures that characterize lateral ventricular shape. We show that our novel mechanomarkers, such as maximum ependymal cell deformations and maximum curvature of the ventricular wall, spatially overlap with periventricular WMH locations and are sensitive predictors for WMH formation. We also explore the role of the septum pellucidum in mitigating mechanical loading of the ventricular wall by constraining the radial expansion of the lateral ventricles during loading. Our models consistently show that ependymal cells are stretched thin only in the horns of the ventricles irrespective of ventricular shape. We therefore pose that periventricular WMH etiology is strongly linked to the deterioration of the over-stretched ventricular wall resulting in CSF leakage into periventricular white matter. Subsequent secondary damage mechanisms, including vascular degeneration, exacerbate lesion formation and lead to progressive growth into deep white matter regions.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Transient receptor potential Ankyrin-1 (TRPA1) agonists suppress myelination and induce demyelination in organotypic cortical slices

Oligodendrocytes are highly specialized glial cells characterized by their production of multilayer myelin sheaths that wrap axons to speed up action potential propagation. It is due to their specific role in supporting axons that impairment of myelin structure and function leads to debilitating symptoms in a wide range of degenerative diseases, including Multiple Sclerosis and Leukodystrophies. It is known that myelin damage can be receptor-mediated and recently oligodendrocytes have been shown to express Ca2+ -permeable Transient Receptor Potential Ankyrin-1 (TRPA1) channels, whose activation can result in myelin damage in ischemia. Here, we show, using organotypic cortical slice cultures, that TRPA1 activation, by TRPA1 agonists JT010 and Carvacrol for varying lengths of time, induces myelin damage. Although TRPA1 activation does not appear to affect oligodendrocyte progenitor cell number or proliferation, it prevents myelin formation and after myelination causes internodal shrinking and significant myelin degradation. This does not occur when the TRPA1 antagonist, A967079, is also applied. Of note is that when TRPA1 agonists are applied for either 24 h, 3 days or 7 days, axon integrity appears to be preserved while mature myelinated oligodendrocytes remain but with significantly shortened internodes. These results provide further evidence that TRPA1 inhibition could be protective in demyelination diseases and a promising therapy to prevent demyelination and promote remyelination.

Evidence against a temporal association between cerebrovascular disease and Alzheimer's disease imaging biomarkers

Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.

Assessment of the clinical feasibility of detecting subtle blood-brain barrier leakage in cerebral small vessel disease using dynamic susceptibility contrast MRI

PURPOSE

Cerebral small vessel disease (cSVD) involves several pathologies affecting the small vessels, including blood-brain barrier (BBB) impairment. Dynamic susceptibility contrast (DSC) MRI is sensitive to both blood perfusion and BBB leakage, and correction methods may be crucial for obtaining reliable perfusion measures. These methods might also be applicable to detect BBB leakage itself. This study investigated to what extent DSC-MRI can measure subtle BBB leakage in a clinical feasibility setting.

METHODS

In vivo DCE and DSC data were collected from fifteen cSVD patients (71 (±10) years, 6F/9M) and twelve elderly controls (71 (±10) years, 4F/8M). DSC-derived leakage fractions were obtained using the Boxerman-Schmainda-Weisskoff method (K2). K2 was compared with the DCE-derived leakage rate K_i, obtained from Patlak analysis. Subsequently, differences were assessed between white matter hyperintensities (WMH), cortical gray matter (CGM), and normal-appearing white matter (NAWM). Additionally, computer simulations were performed to assess the sensitivity of DSC-MRI to BBB leakage.

RESULTS

K2 showed significant differences between tissue regions (P < 0.001 for CGM-NAWM and CGM-WMH, and P = 0.001 for NAWM-WMH). Conversely, according to the computer simulations the DSC sensitivity was insufficient to measure subtle BBB leakage, as the K2 values were below the derived limit of quantification (4∙10^-3 min^-1). As expected, K_i was elevated in the WMH compared to CGM and NAWM (P < 0.001).

CONCLUSIONS

Although clinical DSC-MRI seems capable to detect subtle BBB leakage differences between WMH and normal-appearing brain tissue it is not recommended. K2 as a direct measure for subtle BBB leakage remains ambiguous as its signal effects are due to mixed T₁- and T₂^∗-weighting. Further research is warranted to better disentangle perfusion from leakage effects.

Diffusion Tensor Imaging as a Tool to Evaluate the Cognitive Function of Patients With Vascular Dementia: A Meta-Analysis

BACKGROUND

Vascular dementia (VaD) is the most common type of dementia secondary to Alzheimer's disease. The pathologic mechanism of VaD is complex, and VaD still lacks a more objective diagnosis and evaluation method. Diffusion tensor imaging (DTI) can better detect the organizational structure and functional characteristics compared with any other diagnosis methods. Therefore, DTI has broad application in evaluating the severity and prognosis of VaD. This study aimed to assess the value of DTI in evaluating the cognitive function of patients with VaD.

METHODS

Authors searched Pubmed, Embase, and Cochrane Library, using the search terms, such as "diffusion tensor imaging," "DTI," "Vascular Dementia," "Arteriosclerotic Dementia," "Cognition," and "Cognitive." A voxel-based meta-analysis combined with quality statistics was performed, using the anisotropic effect-size version of the signed differential mapping method.

RESULTS

A total of 8 case-control studies were included in this meta-analysis. The sample size of patients ranged from 35 to 60, including 166 patients in the VaD group and 177 healthy individuals. The DTI imaging of the brain tissue of VaD patients was significantly different from that of healthy individuals.

CONCLUSIONS

DTI imaging of the brain tissue of VaD patients was clearly different from that of healthy controls. Therefore it may be feasible to use DTI imaging as a diagnostic method for VaD.

Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.

The Future of Ischemic Stroke Diagnosis and a Review of Underrecognized Ischemic Stroke Etiologies

Accurate ischemic stroke etiologic determination and diagnosis form the foundation of excellent cerebrovascular care as from it stems initiation of the appropriate secondary prevention strategy as well as appropriate patient education regarding specific risk factors for that subtype. Recurrent stroke rates are highest among those patients who receive an incorrect initial stroke diagnosis. Patient distrust and patient reported depression are also higher. The cause of the ischemic stroke also informs predicted patient outcomes and the anticipated recovery trajectory. Finally, determining the accurate cause of the ischemic stroke provides the patient the opportunity to enroll in appropriate research studies studying mechanism, or targeting treatment approaches for that particular disease process. Advances in ischemic stroke research, imaging techniques, biomarkers, and the ability to rapidly perform genetic sequencing over the past decade have shown that classifying patients into large etiologic buckets may not always be appropriate and may represent one reason why some patients are labeled as cryptogenic, or for whom an underlying etiology is never found. Aside from the more traditional stroke mechanisms, there is new research emerging regarding clinical findings that are not normative, but the contributions to ischemic stroke are unclear. In this article, we first review the essential steps to accurate ischemic stroke etiologic classification and then transition to a discussion of embolic stroke of undetermined source (ESUS) and other new entities that have been postulated as causal in ischemic stroke (i.e., genetics and subclinical atherosclerosis). We also discuss the limitations that are inherent in the current ischemic stroke diagnostic algorithms and finally review the most recent studies regarding more uncommon diagnoses and the future of stroke diagnostics and classification.

Peak Width of Skeletonized Mean Diffusivity: A Neuroimaging Marker for White Matter Injury

A leading cause of white matter (WM) injury in older individuals is cerebral small vessel disease (SVD). Cerebral SVD is the most prevalent vascular contributor to cognitive impairment and dementia. Therapeutic progress for cerebral SVD and other WM disorders depends on the development and validation of neuroimaging markers suitable as outcome measures in future interventional trials. Diffusion-tensor imaging (DTI) is one of the best-suited MRI techniques for assessing the extent of WM damage in the brain. But the optimal method to analyze individual DTI data remains hindered by labor-intensive and time-consuming processes. Peak width of skeletonized mean diffusivity (PSMD), a recently developed fast, fully automated DTI marker, was designed to quantify the WM damage secondary to cerebral SVD and reflect related cognitive impairment. Despite its promising results, knowledge about PSMD is still limited in the radiologic community. This focused review provides an overview of the technical details of PSMD while synthesizing the available data on its clinical and neuroimaging associations. From a critical expert viewpoint, the authors discuss the limitations of PSMD and its current validation status as a neuroimaging marker for vascular cognitive impairment. Finally, they point out the gaps to be addressed to further advance the field.

Associations of Life's Simple 7 with cerebral white matter hyperintensities and microstructural integrity: UK Biobank cohort study

BACKGROUND AND PURPOSE

The American Heart Association Life's Simple 7 (LS7) metric was used to define optimal cardiovascular and brain health, but the associations with macrostructural hyperintensities and microstructural white matter damage are unclear. The objective was to determine the association of LS7 ideal cardiovascular health factors with macrostructural and microstructural integrity.

METHOD

A total of 37,140 participants with available LS7 and imaging data from UK Biobank were included in this study. Linear associations were implemented to examine the associations of LS7 score and subscores with white matter hyperintensity load (WMH) (WMH volume normalized by total white matter volume and logit-transformed) and diffusion imaging indices (fractional anisotropy [FA], mean diffusivity, orientation dispersion index [OD], intracellular volume fraction, isotropic volume fraction [ISOVF]).

RESULTS

In individuals (mean age 54.76 years; 19,697 females, 52.4%), higher LS7 score and subscores were strongly associated with lower WMH and microstructural white matter injury, including OD, ISOVF, FA. Both interaction analyses and stratified analyses of LS7 score and subscores with age and sex showed a strong association with microstructural damage markers, with remarkable age and sex differences. The association of OD was pronounced in females and populations younger than 50 years and FA, mean diffusivity and ISOVF were pronounced in males and populations older than 50 years.

CONCLUSION

These findings suggest that healthier LS7 profiles are associated with better profiles of both macrostructural and microstructural markers of brain health, and indicate that ideal cardiovascular health is associated with improved brain health.

Circulating cardiac biomarkers, structural brain changes, and dementia: Emerging insights and perspectives

Diseases of the heart and brain are strongly linked to each other, and cardiac dysfunction is associated with cognitive decline and dementia. This link between cardiovascular disease and dementia offers opportunities for dementia prevention through prevention and treatment of cardiovascular risk factors and heart disease. Increasing evidence suggests the clinical utility of cardiac biomarkers as risk markers for structural brain changes and cognitive impairment. We propose the hypothesis that structural brain changes are the link between impaired cardiac function, as captured by blood-based cardiac biomarkers, and cognitive impairment. This review provides an overview of the literature and illustrates emerging insights into the association of markers of hemodynamic stress (natriuretic peptides) and markers of myocardial injury (cardiac troponins) with imaging findings of brain damage and cognitive impairment or dementia. Based on these findings, we discuss potential pathophysiological mechanisms underlying the association of cardiac biomarkers with structural brain changes and dementia. We suggest testable hypotheses and a research plan to close the gaps in understanding the mechanisms linking vascular damage and neurodegeneration, and to pave the way for targeted effective interventions for dementia prevention. From a clinical perspective, cardiac biomarkers open the window for early identification of patients at risk of dementia, who represent a target population for preventive interventions targeting modifiable cardiovascular risk factors to avert cognitive decline and dementia.

Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease

Cerebral small vessel disease (SVD) is a cause of stroke and dementia. Retinal capillary microvessels revealed by optical coherence tomography angiography (OCTA) are developmentally related to brain microvessels. We quantified retinal vessel density (VD) and branching complexity, investigating relationships with SVD lesions, white matter integrity on diffusion tensor imaging (DTI) and cerebrovascular reactivity (CVR) to CO2 in patients with minor stroke. We enrolled 123 patients (mean age 68.1 ± SD 9.9 years), 115 contributed retinal data. Right (R) and left (L) eyes are reported. After adjusting for age, eye disease, diabetes, blood pressure and image quality, lower VD remained associated with higher mean diffusivity (MD) (standardized β; R -0.16 [95%CI -0.32 to -0.01]) and lower CVR (L 0.17 [0.03 to 0.31] and R 0.19 [0.02 to 0.36]) in normal appearing white matter (NAWM). Sparser branching remained associated with sub-visible white matter damage shown by higher MD (R -0.24 [-0.08 to -0.40]), lower fractional anisotropy (FA) (L 0.17 [0.01 to 0.33]), and lower CVR (R 0.20 [0.02 to 0.38]) in NAWM. OCTA-derived metrics provide evidence of microvessel abnormalities that may underpin SVD lesions in the brain.

Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease

White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.

Multimodal imaging of the aging brain: Baseline findings of the LoCARPoN study

We quantified and investigated multimodal brain MRI measures in the LoCARPoN Study due to lack of normative data among Indians. A total of 401 participants (aged 50-88 years) without stroke or dementia completed MRI investigation. We assessed 31 brain measures in total using four brain MRI modalities, including macrostructural (global & lobar volumes, white matter hyperintensities [WMHs]), microstructural (global and tract-specific white matter fractional anisotropy [WM-FA] and mean diffusivity [MD]) and perfusion measures (global and lobar cerebral blood flow [CBF]). The absolute brain volumes of males were significantly larger than those of females, but such differences were relatively small (<1.2% of intracranial volume). With increasing age, lower macrostructural brain volumes, lower WM-FA, greater WMHs, higher WM-MD were found (P = 0.00018, Bonferroni threshold). Perfusion measures did not show significant differences with increasing age. Hippocampal volume showed the greatest association with age, with a reduction of approximately 0.48%/year. This preliminary study augments and provides insight into multimodal brain measures during the nascent stages of aging among the Indian population (South Asian ethnicity). Our findings establish the groundwork for future hypothetical testing studies.

Neuropathologic scales of cerebrovascular disease associated with diffusion changes on MRI

Summarizing the multiplicity and heterogeneity of cerebrovascular disease (CVD) features into a single measure has been difficult in both neuropathology and imaging studies. The objective of this work was to evaluate the association between neuroimaging surrogates of CVD and two available neuropathologic CVD scales in those with both antemortem imaging CVD measures and postmortem CVD evaluation. Individuals in the Mayo Clinic Study of Aging with MRI scans within 5 years of death (N = 51) were included. Antemortem CVD measures were computed from diffusion MRI (dMRI), FLAIR, and T2* GRE imaging modalities and compared with postmortem neuropathologic findings using Kalaria and Strozyk Scales. Of all the neuroimaging measures, both regional and global dMRI measures were associated with Kalaria and Strozyk Scales (p < 0.05) and modestly correlated with global cognitive performance. The major conclusions from this study were: (i) microstructural white matter injury measurements using dMRI may be meaningful surrogates of neuropathologic CVD scales, because they aid in capturing diffuse (and early) changes to white matter and secondary neurodegeneration due to lesions; (ii) vacuolation in the corpus callosum may be associated with white matter changes measured on antemortem dMRI imaging; (iii) Alzheimer's disease neuropathologic change did not associate with neuropathologic CVD scales; and (iv) future work should be focused on developing better quantitative measures utilizing dMRI to optimally assess CVD-related neuropathologic changes.

Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity

Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function.

3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations

Aging-related periventricular white matter hyperintensities (pvWMHs) are a common observation in medical images of the aging brain. The underlying tissue damage is part of the complex pathophysiology associated with age-related microstructural changes and cognitive decline. PvWMH formation is linked to blood-brain barrier dysfunction from cerebral small vessel disease as well as the accumulation of cerebrospinal fluid in periventricular tissue due to progressive denudation of the ventricular wall. In need of a unifying theory for pvWMH etiology, image-based finite-element modeling is used to demonstrate that ventricular expansion from age-related cerebral atrophy and hemodynamic loading leads to maximum mechanical loading of the ventricular wall in the same locations that show pvWMHs. Ventricular inflation, induced via pressurization of the ventricular wall, creates significant ventricular wall stretch and stress on the ependymal cells lining the wall, that are linked to cerebrospinal fluid leaking from the lateral ventricles into periventricular white matter tissue. Eight anatomically accurate 3D brain models of cognitively healthy subjects with a wide range of ventricular shapes are created. For all models, our simulations show that mechanomarkers of mechanical wall loading are consistently highest in pvWMHs locations (p < 0.05). Maximum principal strain, the ependymal cell thinning ratio, and wall curvature are on average 14%, 8%, and 24% higher in pvWMH regions compared to the remaining ventricular wall, respectively. Computational modeling provides a powerful framework to systematically study pvWMH formation and growth with the goal to develop pharmacological interventions in the future.

Characterization of white matter over 1–2 years in small vessel disease using MR-based quantitative susceptibility mapping and free-water mapping

Purpose

The aim of this study was to investigate alterations in white matter lesions (WMLs) and normal-appearing white matter (NAWM) with small vessel disease (SVD) over 1–2 years using quantitative susceptibility mapping (QSM) and free-water (FW) mapping.

Methods

Fifty-one SVD patients underwent MRI brain scans and neuropsychological testing both at baseline and follow-up. The main approach for treating these patients is the management of risk factors. Quantitative susceptibility (QS), fractional anisotropy (FA), mean diffusivity (MD), FW, FW-corrected FA (FAT), and FW-corrected MD (MDT) maps within WMLs and NAWM were generated. Furthermore, the JHU-ICBM-DTI label atlas was used as an anatomic guide, and the measurements of the segmented NAWMs were calculated. The average regional values were extracted, and a paired t-test was used to analyze the longitudinal change. Partial correlations were used to assess the relationship between the MRI indices changes (e.g., ΔQSfollowup − baseline/QSbaseline) and the cognitive function changes (e.g., ΔMoCAfollowup − baseline/MoCAbaseline).

Results

After SVD risk factor control, no gradual cognitive decline occurred during 1–2 years. However, we still found that the QS values (index of demyelination) increased in the NAWM at follow-up, especially in the NAWM part of the left superior frontal blade (SF), left occipital blade, right uncinate fasciculus, and right corticospinal tract (CST). FW (index of neuroinflammation/edema) analysis revealed that the follow-up group differed from the baseline group in the NAWM part of the right CST and inferior frontal blade (IF). Decreased FAT (index of axonal loss) was observed in the NAWM part of the right SF and IF at follow-up. In addition, the FAT changes in the NAWM part of the right IF were associated with overall cognitive performance changes. In contrast, no significant differences were found in the WMLs.

Conclusion

The NAWM was still in the progressive injury process over time, while WMLs remained relatively stable, which supports the notion that SVD is a chronic progressive disease. The process of axonal loss in the NAWM part of the prefrontal lobe might be a biomarker of cognitive changes in the evolution of SVD.

Free-water diffusion MRI detects structural alterations surrounding white matter hyperintensities in the early stage of cerebral small vessel disease

In cerebral small vessel disease (CSVD), both white matter hyperintensities (WMH) of presumed vascular origin and the normal-appearing white matter (NAWM) contain microstructural brain alterations on diffusion-weighted MRI (DWI). Contamination of DWI-derived metrics by extracellular free-water can be corrected with free-water (FW) imaging. We investigated the alterations in FW and FW-corrected fractional anisotropy (FA-t) in WMH and surrounding tissue and their association with cerebrovascular risk factors. We analysed 1,000 MRI datasets from the Hamburg City Health Study. DWI was used to generate FW and FA-t maps. WMH masks were segmented on FLAIR and T1-weighted MRI and dilated repeatedly to create 8 NAWM masks representing increasing distance from WMH. Linear models were applied to compare FW and FA-t across WMH and NAWM masks and in association with cerebrovascular risk. Median age was 64 ± 14 years. FW and FA-t were altered 8 mm and 12 mm beyond WMH, respectively. Smoking was significantly associated with FW in NAWM (p = 0.008) and FA-t in WMH (p = 0.008) and in NAWM (p = 0.003) while diabetes and hypertension were not. Further research is necessary to examine whether FW and FA-t alterations in NAWM are predictors for developing WMH.

Neuroimaging correlates of persistent fatigue in older adults: A secondary analysis from the Multidomain Alzheimer Preventive Trial (MAPT) trial

OBJECTIVES

Fatigue has been suggested as a marker of biological aging. It seems plausible that this symptom might be associated with changes in brain health. The objective of this study was to examine the associations between persistent fatigue and neuroimaging correlates in a non-disease-specific population of community-dwelling older adults.

METHODS

We performed a cross-sectional analysis using data from The Multidomain Alzheimer Preventive Trial (MAPT). We included 458 subjects. Persistent fatigue was defined as meeting exhaustion criterion of Fried frailty phenotype in two consecutive clinical visits six months apart between study baseline and one year. Brain imaging correlates, assessed by magnetic resonance imaging (MRI), were the outcomes. The associations between persistent fatigue and brain correlates were explored using mixed model linear regressions with random effect at the center level.

RESULTS

The mean age of the participants was 74.8 ± 4 years old, and 63% of the subjects were women. Forty-seven participants (10%) exhibited a persistent fatigue profile. People with persistent fatigue were older compared to subjects without persistent fatigue (76.2 years ± 4.3 vs.74.7 ± 3.9 p = 0.009). Persistent fatigue was associated with higher white matter hyperintensity volume in the fully adjusted analysis. We did not find any cross-sectional association between persistent fatigue and sub-cortical volumes and global and regional cortical thickness.

CONCLUSION

Persistent fatigue was cross-sectionnally associated with higher white matter hyperintensity volume in older adults. Further longitudinal studies, using an assessment tool specifically designed and validated for measuring fatigue, are needed to confirm our findings.

Regional Disruption of White Matter Integrity and Network Connectivity Are Related to Cognition

BACKGROUND

Cognitive impairment is common in the elderly population. Exploring patterns of white matter damage at the microstructural level would give important indications for the underlying mechanisms.

OBJECTIVE

To investigate the spatial patterns of white matter microstructure and structural network alternations in relation to different cognition domainsMethods:Participants from the community-based Shunyi Study were included to investigate the association between white matter measurements and cognition cross-sectionally, via both global and local analysis. Cognitive functions were assessed using digit span, trail making test (TMT)-A/B, Fuld object Memory, and 12-Word Philadelphia Verbal Learning Test (PVLT). White matter measurements including fractional anisotropy (FA), mean diffusivity (MD), and structural network parameters were calculated based on diffusion tensor imaging.

RESULTS

Of the 943 participants included, the mean (SD) age was 55.8 (9.1) years, and the mean (SD) education level was 6.7 (3.2) years. We found the whole set of cognitive measurements was related to diffused white matter microstructural integrity damage and lower global efficiency. Poor executive functions (TMTA/B complete time) were related to lower FA and higher MD predominantly on the anterior white matter skeleton, while verbal memory loss (PVLT test scores) was related to sub-network dysconnectivity in the midline and the right temporal lobe.

CONCLUSION

The anterior brain is dominantly involved in executive dysfunction, while midline and right temporal brain disconnection are more prominent in verbal memory loss. Global and regional disruption of white matter integrity and network connectivity is the anatomical basis of the cognitive impairment in the aging population.

Horizons in Human Aging Neuroscience: From Normal Neural Aging to Mental (Fr)Agility

While aging is an important risk factor for neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease, age-related cognitive decline can also manifest without apparent neurodegenerative changes. In this review, we discuss molecular, cellular, and network changes that occur during normal aging in the absence of neurodegenerative disease. Emerging findings reveal that these changes include metabolic alterations, oxidative stress, DNA damage, inflammation, calcium dyshomeostasis, and several other hallmarks of age-related neural changes that do not act on their own, but are often interconnected and together may underlie age-related alterations in brain plasticity and cognitive function. Importantly, age-related cognitive decline may not be reduced to a single neurobiological cause, but should instead be considered in terms of a densely connected system that underlies age-related cognitive alterations. We speculate that a decline in one hallmark of neural aging may trigger a decline in other, otherwise thus far stable subsystems, thereby triggering a cascade that may at some point also incur a decline of cognitive functions and mental well-being. Beyond studying the effects of these factors in isolation, considerable insight may be gained by studying the larger picture that entails a representative collection of such factors and their interactions, ranging from molecules to neural networks. Finally, we discuss some potential interventions that may help to prevent these alterations, thereby reducing cognitive decline and mental fragility, and enhancing mental well-being, and healthy aging.

Microglial Priming in Infections and Its Risk to Neurodegenerative Diseases

Infectious diseases of different etiologies have been associated with acute and long-term neurological consequences. The primary cause of these consequences appears to be an inflammatory process characterized primarily by a pro-inflammatory microglial state. Microglial cells, the local effectors' cells of innate immunity, once faced by a stimulus, alter their morphology, and become a primary source of inflammatory cytokines that increase the inflammatory process of the brain. This inflammatory scenario exerts a critical role in the pathogenesis of neurodegenerative diseases. In recent years, several studies have shown the involvement of the microglial inflammatory response caused by infections in the development of neurodegenerative diseases. This has been associated with a transitory microglial state subsequent to an inflammatory response, known as microglial priming, in which these cells are more responsive to stimuli. Thus, systemic inflammation and infections induce a transitory state in microglia that may lead to changes in their state and function, making priming them for subsequent immune challenges. However, considering that microglia are long-lived cells and are repeatedly exposed to infections during a lifetime, microglial priming may not be beneficial. In this review, we discuss the relationship between infections and neurodegenerative diseases and how this may rely on microglial priming.

Causal structure discovery identifies risk factors and early brain markers related to evolution of white matter hyperintensities

Our goal was to understand the complex relationship between age, sex, midlife risk factors, and early white matter changes measured by diffusion tensor imaging (DTI) and their role in the evolution of longitudinal white matter hyperintensities (WMH). We identified 1564 participants (1396 cognitively unimpaired, 151 mild cognitive impairment and 17 dementia participants) with age ranges of 30-90 years from the population-based sample of Mayo Clinic Study of Aging. We used computational causal structure discovery and regression analyses to evaluate the predictors of WMH and DTI, and to ascertain the mediating effect of DTI on WMH. We further derived causal graphs to understand the complex interrelationships between midlife protective factors, vascular risk factors, diffusion changes, and WMH. Older age, female sex, and hypertension were associated with higher baseline and progression of WMH as well as DTI measures (P ≤ 0.003). The effects of hypertension and sex on WMH were partially mediated by microstructural changes measured on DTI. Higher midlife physical activity was predictive of lower WMH through a direct impact on better white matter tract integrity as well as an indirect effect through reducing the risk of hypertension by lowering BMI. This study identified key risks factors, early brain changes, and pathways that may lead to the evolution of WMH.

Effects of Vascular Comorbidity on Cognition in Multiple Sclerosis Are Partially Mediated by Changes in Brain Structure

Objective

Vascular comorbidities are associated with reduced cognitive performance and with changes in brain structure in people with multiple sclerosis (MS). Understanding causal pathways is necessary to support the design of interventions to mitigate the impacts of comorbidities, and to monitor their effectiveness. We assessed the inter-relationships among vascular comorbidity, cognition and brain structure in people with MS.

Methods

Adults with neurologist-confirmed MS reported comorbidities, and underwent assessment of their blood pressure, HbA1c, and cognitive functioning (i.e., Symbol Digit Modalities Test, California Verbal Learning Test, Brief Visuospatial Memory Test-Revised, and verbal fluency). Test scores were converted to age-, sex-, and education-adjusted z-scores. Whole brain magnetic resonance imaging (MRI) was completed, from which measures of thalamic and hippocampal volumes, and mean diffusivity of gray matter and normal-appearing white matter were converted to age and sex-adjusted z-scores. Canonical correlation analysis was used to identify linear combinations of cognitive measures (cognitive variate) and MRI measures (MRI variate) that accounted for the most correlation between the cognitive and MRI measures. Regression analyses were used to test whether MRI measures mediated the relationships between the number of vascular comorbidities and cognition measures.

Results

Of 105 participants, most were women (84.8%) with a mean (SD) age of 51.8 (12.8) years and age of symptom onset of 29.4 (10.5) years. Vascular comorbidity was common, with 35.2% of participants reporting one, 15.2% reporting two, and 8.6% reporting three or more. Canonical correlation analysis of the cognitive and MRI variables identified one pair of variates (Pillai's trace = 0.45, p = 0.0035). The biggest contributors to the cognitive variate were the SDMT and CVLT-II, and to the MRI variate were gray matter MD and thalamic volume. The correlation between cognitive and MRI variates was 0.50; these variates were used in regression analyses. On regression analysis, vascular comorbidity was associated with the MRI variate, and with the cognitive variate. After adjusting for the MRI variate, vascular comorbidity was not associated with the cognitive variate.

Conclusion

Vascular comorbidity is associated with lower cognitive function in people with MS and this association is partially mediated via changes in brain macrostructure and microstructure.

Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up

BACKGROUND

The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD.

METHODS

Five hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers.

RESULTS

A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up.

CONCLUSIONS

SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.

White matter damage due to pulsatile versus steady blood pressure differs by vascular territory: A cross-sectional analysis of the UK Biobank cohort study

Small vessel disease is associated with age, mean blood pressure (MAP) and blood pressure pulsatility (PP). We used data from the UK Biobank cohort study to determine the relative importance of MAP versus PP driving white matter injury within individual white matter tracts, particularly in the anterior and posterior vascular territory. The associations between blood pressure and diffusion indices in 27 major tracts were analysed using unadjusted and fully-adjusted general linear models and mixed-effect linear models. Blood pressure and neuroimaging data were available for 37,041 participants (mean age 64+/-7.5 years, 53% female). In unadjusted analyses, MAP and PP were similarly associated with diffusion indices in the anterior circulation. In the posterior circulation, the associations were weaker, particularly for MAP. In fully-adjusted analyses, MAP remained associated with all diffusion indices in the anterior circulation, independently of age. In the posterior circulation, the effect of MAP became protective. PP remained associated with greater mean diffusivity and extracellular free water diffusion in the anterior circulation and all diffusion indices in the posterior circulation. There was a significant interaction between PP and age. This implies discordant mechanisms for chronic white matter injury in different brain regions and potentially in the associated stroke risks.

Impact of White Matter Hyperintensity Burden on Outcome in Large-Vessel Occlusion Stroke

Background White matter hyperintensity (WMH) has been linked to poor clinical outcomes after acute ischemic stroke. Purpose To assess whether the WMH burden on pretreatment MRI scans is associated with an increased risk for symptomatic intracranial hemorrhage (sICH) or poor functional outcome in patients with acute ischemic stroke treated with endovascular thrombectomy (EVT). Materials and Methods In this retrospective study, consecutive patients treated with EVT for anterior circulation acute ischemic stroke at a comprehensive stroke center (where MRI was the first-line pretreatment imaging strategy; January 2015 to December 2017) were included and analyzed. WMH volumes were assessed with semiautomated volumetric analysis at fluid-attenuated inversion recovery MRI by readers who were blinded to clinical data. The associations of WMH burden with sICH and 3-month functional outcome (modified Rankin Scale [mRS] score) were assessed. Results A total of 366 patients were included (mean age, 69 years ± 19 [SD]; 188 women [51%]). Median total WMH volume was 3.61 cm³ (IQR, 1.10-10.83 cm³). Patients demonstrated higher mRS scores with increasing WMH volumes (odds ratio [OR], 1.020 [95% CI: 1.003, 1.037] per 1.0-cm³ increase for each mRS point increase; P = .018) after adjustment for patient and clinical variables. There were no significant associations between WMH severity and 90-day mortality (OR, 1.007 [95% CI: 0.990, 1.024]; P = .40) or the occurrence of sICH (OR, 1.001 [95% CI: 0.978, 1.024]; P = .94). Conclusion Higher white matter hyperintensity burden was associated with increased risk for poor 3-month functional outcome after endovascular thrombectomy for large-vessel occlusive stroke. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mossa-Basha and Zhu in this issue.

Cortical Short-Range Fiber Connectivity and Its Association With Deep Brain White Matter Hyperintensities in Older Diabetic People With Low Serum Vitamin B12

Although previous studies have indicated that older people with diabetes mellitus (DM) had an approximately two times larger white matter hyperintensity (WMH) load than those without DM, the influence of WMHs on cognition is uncertain and inconsistent in the literature. It is unclear whether the short-range fibers in the juxtacortical region, traditionally considered to be spared from WMH pathology, are enhanced as an adaptive response to deep WM degeneration in older diabetic people with normal cognition. Moreover, the specific effect of vitamin B₁₂ deficiency, commonly accompanied by DM, remains to be investigated. This study implemented a specialized analysis of the superficial cortical short-range fiber connectivity density (SFiCD) based on a data-driven framework in 70 older individuals with DM and low serum vitamin B₁₂. Moreover, the effects of time and vitamin B₁₂ supplementation were assessed based on a randomized placebo-controlled trial in 59 individuals. The results demonstrated a higher SFiCD in diabetic individuals with a higher deep WMH load. Additionally, a significant interaction between DWMH load and homocysteine on SFiCD was found. During the 27-month follow-up period, a longitudinal increase in the SFiCD was observed in the bilateral frontal cortices. However, the observed longitudinal SFiCD change was not dependent on vitamin B₁₂ supplementation; thus, the specific reason for the longitudinal cortical short fiber densification may need further study. Overall, these findings may help us better understand the neurobiology of brain plasticity in older patients with DM, as well as the interplay among DM, WMH, and vitamin B₁₂ deficiency.

Epidermal Growth Factor Pathway in the Age-Related Decline of Oligodendrocyte Regeneration

Oligodendrocytes (OLs) are specialized glial cells that myelinate CNS axons. OLs are generated throughout life from oligodendrocyte progenitor cells (OPCs) via a series of tightly controlled differentiation steps. Life-long myelination is essential for learning and to replace myelin lost in age-related pathologies such as Alzheimer's disease (AD) as well as white matter pathologies such as multiple sclerosis (MS). Notably, there is considerable myelin loss in the aging brain, which is accelerated in AD and underpins the failure of remyelination in secondary progressive MS. An important factor in age-related myelin loss is a marked decrease in the regenerative capacity of OPCs. In this review, we will contextualize recent advances in the key role of Epidermal Growth Factor (EGF) signaling in regulating multiple biological pathways in oligodendroglia that are dysregulated in aging.

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.

Tract Specific White Matter Lesion Load Affects White Matter Microstructure and Their Relationships With Functional Connectivity and Cognitive Decline

White matter hyperintensities (WMHs) are associated with cognitive decline. Assessing the effect of WMH on WM microstructural changes and its relationships with structural and functional connectivity to multiple cognitive domains are helpful to better understand the pathophysiological processes of cognitive impairment. 65 participants (49 normal and 16 MCI subjects, age: 67.4 ± 8.3 years, 44 females) were studied at 3T. The WMHs and fifty fiber tracts were automatically segmented from the T1/T2-weighted images and diffusion-weighted images, respectively. Tract-profiles of WMH were compared with those of apparent fiber density (AFD). The relationship between AFD and tract connectivity (TC) was assessed. Functional connectivity (FC) between tract ends obtained from resting-state functional MRI was examined in relation to TC. Tract-specific relationships of WMH, TC and FC with a multi-domain neuropsychological test battery and Montreal Cognitive Assessment (MoCA) were also separately assessed by lasso linear regression. Indirect pathways of TC and FC between WMH and multiple cognitive measures were tested using the mediation analysis. Higher WMH loads in WM tracts were locally matched with the reduced AFD, which was related to decrease in TC. However, no direct relationship was found between TC and FC. Tract-specific changes on WMH, TC and FC for each cognitive performance may explain that macro- and microstructural and functional changes are associated differently with each cognitive domain in a fiber specific manner. In these identified tracts, the differences between normal and MCI for WMH and TC were increased, and the relationships of WMH, TC and FC with cognitive outcomes were more significant, compared to the results from all tracts. Indirect pathways of two-step (TC-FC) between WMH and all cognitive domains were significant (p < 0.0083 with Bonferroni correction), while the separated indirect pathways through TC and through FC were different depending on cognitive domain. Deterioration in specific cognitive domains may be affected by alterations in a set of different tracts that are differently associated with macrostructural, microstructural, and function changes. Thus, assessments of WMH and its associated changes on specific tracts help for better understanding of the interrelationships of multiple changes in cognitive impairment.