Association of White Matter Hyperintensity Markers on MRI and Long-term Risk of Mortality and Ischemic Stroke: The SMART-MR Study

Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study

BACKGROUND

Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aβ (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration.

METHODS AND RESULTS

Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010).

CONCLUSIONS

Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.

White matter hyperintensity shape is associated with long-term dementia risk

INTRODUCTION

We aimed to investigate the association between white matter hyperintensity (WMH) shape and volume and the long-term dementia risk in community-dwelling older adults.

METHODS

Three thousand seventy-seven participants (mean age: 75.6 ± 5.2 years) of the Age Gene/Environment Susceptibility (AGES)-Reykjavik study underwent baseline 1.5T brain magnetic resonance imaging and were followed up for dementia (mean follow-up: 9.9 ± 2.6 years).

RESULTS

More irregular shape of periventricular/confluent WMH (lower solidity (hazard ratio (95% confidence interval) 1.34 (1.17 to 1.52), p < .001) and convexity 1.38 (1.28 to 1.49), p < .001); higher concavity index 1.43 (1.32 to 1.54), p < .001) and fractal dimension 1.45 (1.32 to 1.58), p < .001)), higher total WMH volume (1.68 (1.54 to 1.87), p < .001), higher periventricular/confluent WMH volume (1.71 (1.55 to 1.89), p < .001), and higher deep WMH volume (1.17 (1.08 to 1.27), p < .001) were associated with an increased long-term dementia risk.

DISCUSSION

WMH shape markers may in the future be useful in determining patient prognosis and may aid in patient selection for future preventive treatments in community-dwelling older adults.

Incidence, characteristics and outcome of post-stroke recrudescence in the Chinese population: a single-centre observational study

OBJECTIVES

The aim of our observational study was to investigate the incidence, clinical characteristics and outcome of post-stroke recrudescence (PSR) in the Chinese population.

DESIGN AND SETTING

Single-centre prospective observational study in China.

PARTICIPANTS

A total of 1114 patients who had a suspected stroke were prospectively screened from October 2020 to February 2022.

OUTCOME MEASURES

The primary outcome was the proportion of patients with functional independence defined as a score of 0-2 on the modified Rankin Scale (mRS) at 3 months. Secondary outcomes were: early neurological improvement (ENI), defined as a National Institutes of Health Stroke Scale (NIHSS) score of 0 or an improvement of ≥2 points from admission at 24 hours; mortality within 3 months; stroke recurrence within 3 months and length of stay in hospital.

RESULTS

A total of 959 patients with cerebral infarction and 30 patients without an available magnetic resonance imaging (MRI) scan were excluded. Among the 125 included patients, 27 cases of PSR (2.4%), 50 cases of transient ischaemic attack (TIA) (4.5%) and 48 cases of stroke mimics (SMs) (4.3%) were identified. A higher frequency of infection at admission (22.2% vs 2%, p=0.007) was observed in patients with PSR compared with patients with TIA, and a lower proportion of functional independence at 3 months (80% vs 98%, p=0.015) was seen. Patients with TIA had a higher frequency of ENI compared with patients with PSR and SMs (98% vs 59.3%, p<0.001; 98% vs 52.1%, p<0.001). Patients with PSR exhibited a higher frequency of grade 2 Fazekas deep white matter hyperintensity compared with those with SMs (33.3% vs 8.3%, p=0.010).

CONCLUSIONS

PSR is not uncommon in patients presenting with stroke symptoms and can be distinguished from TIA and SMs based on a combination of clinical features and trigger in the Chinese population. The neurological deficits of patients with PSR often resolve within several days following the resolution of the trigger.

Association of the coexistence of intracranial atherosclerotic disease and cerebral small vessel disease with acute ischemic stroke

PURPOSE

Whether the coexistence of intracranial atherosclerotic disease (ICAD) and cerebral small vessel disease (CSVD) is an effective indicator for acute ischemic stroke (AIS) is unclear. This study aimed to investigate the association of coexistence of ICAD and CSVD with AIS.

METHODS

Patients with symptomatic ICAD were recruited from a multicenter study. All patients underwent intracranial artery vessel wall and brain magnetic resonance (MR) imaging at 3.0 T. The characteristics of T1 hyperintensity, plaque enhancement, and surface irregularity of the ICAD were assessed. The types of CSVD including enlarged perivascular space, white matter hyperintensity and lacune, and AIS were also analyzed. Logistic regressions were used to evaluate the associations of coexistence of ICAD and CSVD with AIS.

RESULTS

Of 122 recruited patients (mean age: 56.69 ± 11.07 years; 70 males), 69 (56.56%) had AIS. Coexistence of ICAD and CSVD was more likely found in patients with AIS compared to those without AIS (all P < 0.05). After full adjustment, coexistences of surface irregularity and EPVS (odds ratio [OR], 12.770; 95% confidence interval [CI], 2.163-75.380; P = 0.005), surface irregularity and lacune (OR, 8.450; 95% CI, 2.028-35.213; P = 0.003), enhancement and lacune (OR, 13.888; 95% CI, 2.888-66.786; P = 0.001), surface irregularity and WMH (OR, 3.692; 95% CI, 1.264-10.786; P = 0.017), and enhancement and WMH (OR, 7.899; 95% CI, 2.357-26.475; P = 0.001) were significantly associated with AIS.

CONCLUSION

Coexistence of intracranial atherosclerosis and cerebral small vessel disease might be a stronger indicator for acute ischemic stroke than each alone.

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.

CarveMix: A simple data augmentation method for brain lesion segmentation

Brain lesion segmentation provides a valuable tool for clinical diagnosis and research, and convolutional neural networks (CNNs) have achieved unprecedented success in the segmentation task. Data augmentation is a widely used strategy to improve the training of CNNs. In particular, data augmentation approaches that mix pairs of annotated training images have been developed. These methods are easy to implement and have achieved promising results in various image processing tasks. However, existing data augmentation approaches based on image mixing are not designed for brain lesions and may not perform well for brain lesion segmentation. Thus, the design of this type of simple data augmentation method for brain lesion segmentation is still an open problem. In this work, we propose a simple yet effective data augmentation approach, dubbed as CarveMix, for CNN-based brain lesion segmentation. Like other mixing-based methods, CarveMix stochastically combines two existing annotated images (annotated for brain lesions only) to obtain new labeled samples. To make our method more suitable for brain lesion segmentation, CarveMix is lesion-aware, where the image combination is performed with a focus on the lesions and preserves the lesion information. Specifically, from one annotated image we carve a region of interest (ROI) according to the lesion location and geometry with a variable ROI size. The carved ROI then replaces the corresponding voxels in a second annotated image to synthesize new labeled images for network training, and additional harmonization steps are applied for heterogeneous data where the two annotated images can originate from different sources. Besides, we further propose to model the mass effect that is unique to whole brain tumor segmentation during image mixing. To evaluate the proposed method, experiments were performed on multiple publicly available or private datasets, and the results show that our method improves the accuracy of brain lesion segmentation. The code of the proposed method is available at https://github.com/ZhangxinruBIT/CarveMix.git.

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.

Impact of total cerebral small vessel disease score on ophthalmic artery morphologies and hemodynamics

BACKGROUND

Cerebral small vessel disease (CSVD) is a systemic disease, affecting not only the brain, but also eyes and other organs. The total CSVD score is a tool for comprehensive evaluation of brain lesions in patients with CSVD. The ophthalmic artery (OA) is a direct response to ocular blood flow. However, little is known about the correlation between CSVD and characteristics of OA. We investigated the OA morphologies and hemodynamics in patients with CSVD and the correlation between these changes and the total CSVD score.

METHODS

This cross-sectional observational study included 34 eyes from 22 patients with CSVD and 10 eyes from 5 healthy controls. The total CSVD score was rated according to the CSVD signs on magnetic resonance imaging. OA morphological characteristics were measured on the basis of 3D OA model reconstruction. OA hemodynamic information was calculated using computational fluid dynamics simulations.

RESULTS

The total CSVD score negatively correlated with the OA diameter, blood flow velocity, and mass flow ratio (all P < 0.05). After adjusting for potential confounding factors, the total CSVD score was still independently correlated with the OA blood velocity (β = - 0.202, P = 0.005). The total CSVD score was not correlated with OA angle (P > 0.05). The presence of cerebral microbleeds and enlarged perivascular spaces was correlated with the OA diameter (both P < 0.01), while the lacunar infarcts and white matter hyperintensities were correlated with the OA blood velocity (both P < 0.001).

CONCLUSIONS

The decrease of the blood velocity in the OA was associated with the increase in the total CSVD score. The changes of the OA diameter and velocity were associated with the presence of various CSVD signs. The findings suggest that more studies are needed in the future to evaluate CSVD by observing the morphologies and hemodynamics of OA.

Classification of white matter lesions and characteristics of small vessel disease markers

OBJECTIVES

Radiological markers for cerebral small vessel disease (SVD) may have different biological underpinnings in their development. We attempted to categorize SVD burden by integrating white matter signal abnormalities (WMSA) features and secondary presence of lacunes, microbleeds, and enlarged perivascular spaces.

METHODS

Data were acquired from 610 older adults (aged > 40 years) who underwent brain magnetic resonance imaging exam as part of a health checkup. The WMSA were classified individually by the number and size of non-contiguous lesions, distribution, and contrast. Age-detrended lacunes, microbleeds, and enlarged perivascular space were quantified to further categorize individuals. Clinical and laboratory values were compared across the individual classes.

RESULTS

Class I was characterized by multiple, small, deep WMSA but a low burden of lacunes and microbleeds; class II had large periventricular WMSA and a high burden of lacunes and microbleeds; and class III had limited juxtaventricular WMSA and lacked lacunes and microbleeds. Class II was associated with older age, diabetes, and a relatively higher neutrophil-to-lymphocyte ratio. Smoking and higher uric acid levels were associated with an increased risk of class I.

CONCLUSION

The heterogeneity of SVD was categorized into three classes with distinct clinical correlates. This categorization will improve our understanding of SVD pathophysiology, risk stratification, and outcome prediction.

KEY POINTS

• Classification of white matter signal abnormality (WMSA) features was associated with different characteristic of lacunes, microbleeds, and enlarged perivascular space and clinical variability. • Class I was characterized by multiple, small, deep WMSA but a low burden of lacunes and microbleeds. Class II had large periventricular WMSA and a high burden of lacunes and microbleeds. Class III had limited juxtaventricular WMSA and lacked lacunes and microbleeds. • Class II was associated with older age, diabetes, and higher neutrophil-to-lymphocyte ratio. Smoking and higher uric acid levels were associated with an increased risk of class I.

Low-grade carotid artery stenosis is associated with progression of brain atrophy and cognitive decline. The SMART-MR study

Asymptomatic low-grade carotid artery stenosis (LGCS) is a common finding in patients with manifest arterial disease, however its relationship with brain MRI changes and cognitive decline is unclear. We included 902 patients (58 ± 10 years; 81% male) enrolled in the Second Manifestations of Arterial Disease - Magnetic Resonance (SMART-MR) study without a history of cerebrovascular disease. LGCS was defined as 1-49% stenosis on baseline carotid ultrasound, whereas no LGCS (reference category) was defined as absence of carotid plaque. Brain and white matter hyperintensity (WMH) volumes and cognitive function were measured at baseline and after 4 (n = 480) and 12 years (n = 222) of follow-up. Using linear mixed-effects models, we investigated associations of LGCS with progression of brain atrophy, WMH, and cognitive decline. LGCS was associated with greater progression of global brain atrophy (estimate -0.03; 95%CI, -0.06 to -0.01; p = 0.002), and a greater decline in executive functioning (estimate -0.02; 95%CI, -0.031 to -0.01; p < 0.001) and memory (estimate -0.012; 95%CI, -0.02 to -0.001; p = 0.032), independent of demographics, cardiovascular risk factors, and incident brain infarcts on MRI. No association was observed between LGCS and progression of WMH. Our results indicate that LGCS may represent an early marker of greater future brain atrophy and cognitive decline.

Rehabilomics: A state-of-the-art review of framework, application, and future considerations

Rehabilomics is an important research framework that allows omics research built upon rehabilitation practice, especially in function evaluation, outcome prediction, and individualized rehabilitation. In the field of rehabilomics, biomarkers can serve as objectively measured indicators for body functioning, so as to complement the International Classification of Functioning, Disability, and Health (ICF) assessment. Studies on traumatic brain injury (TBI), stroke, and Parkinson's disease have shown that biomarkers (such as serum markers, MRI, and digital signals derived from sensors) are correlated with diagnosis, disease severity, and prognosis. Rehabilomics also examines a wide range of individual biological characteristics in order to develop personalized rehabilitation programs. Secondary prevention and rehabilitation of stroke have already adopted a rehabilomic approach to individualize treatment programs. Mechanisms of non-pharmacological therapies are expected to be unveiled in light of rehabilomics research. When formulating the research plan, learning from established databases is recommended and a multidisciplinary collaborative team is warranted. Although still in its infancy, the advancement and incorporation of rehabilomics has the potential to make a significant impact on public health.

Covert Brain Infarction as a Risk Factor for Stroke Recurrence in Patients With Atrial Fibrillation

BACKGROUND

We aimed to evaluate covert brain infarction (CBI), frequently encountered during the diagnostic work-up of acute ischemic stroke, as a risk factor for stroke recurrence in patients with atrial fibrillation (AF).

METHODS

For this prospective cohort study, from patients with acute ischemic stroke hospitalized at 14 centers between 2017 and 2019, we enrolled AF patients without history of stroke or transient ischemic attack and divided them into the CBI (+) and CBI (-) groups. The 2 groups were compared regarding the 1-year cumulative incidence of recurrent ischemic stroke and all-cause mortality using the Fine and Gray subdistribution hazard model with nonstroke death as a competing risk and the Cox frailty model, respectively. Each CBI lesion was also categorized into either embolic-appearing (EA) or non-EA pattern CBI. Adjusted hazard ratios and 95% CIs of any CBI, EA pattern CBI only, non-EA pattern CBI only, and both CBIs were estimated.

RESULTS

Among 1383 first-ever stroke patients with AF, 578 patients (41.8%) had CBI. Of these 578 with CBI, EA pattern CBI only, non-EA pattern CBI only, and both CBIs were 61.8% (n=357), 21.8% (n=126), and 16.4% (n=95), respectively. The estimated 1-year cumulative incidence of recurrent ischemic stroke was 5.2% and 1.9% in the CBI (+) and CBI (-) groups, respectively (P=0.001 by Gray test). CBI increased the risk of recurrent ischemic stroke (adjusted hazard ratio [95% CI], 2.91 [1.44-5.88]) but did not the risk of all-cause mortality (1.32 [0.97-1.80]). The EA pattern CBI only and both CBIs elevated the risk of recurrent ischemic stroke (2.76 [1.32-5.77] and 5.39 [2.25-12.91], respectively), while the non-EA pattern only did not (1.44 [0.40-5.16]).

CONCLUSIONS

Our study suggests that AF patients with CBI might have increased risk of recurrent stroke. CBI could be considered when estimating the stroke risk in patients with AF.

Tract-based white matter hyperintensity patterns in patients with systemic lupus erythematosus using an unsupervised machine learning approach

Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

Cerebrovascular damage in subjective cognitive decline: A systematic review and meta-analysis

BACKGROUND

Subjective cognitive decline (SCD) has been postulated as an early marker of Alzheimer's Disease (AD) but it can also be associated to other non-AD pathologies such as Vascular Dementia (VaD). Nevertheless, there is scarce data about SCD as a potential harbinger of cerebrovascular pathology. Thus, we conducted a systematic review and meta-analysis on the association between SCD and cerebrovascular damage measured by neuroimaging markers.

METHOD

This study was performed following the PRISMA guidelines. The search was conducted in 3 databases (PubMed, Scopus and Web of Science) from origin to December 8th, 2021. Primary studies including cognitively unimpaired adults with SCD and neuroimaging markers of cerebrovascular damage (i.e., white matter signal abnormalities, WMSA) were selected. Qualitative synthesis and meta-analysis of studies with a case-control design was performed.

RESULTS

Of 241 articles identified, 21 research articles were selected. Eight case-control studies were included for the meta-analysis. A significant overall effect-size was observed for the mean WMSA burden in SCD relative to controls, where the WMSA burden was higher in SCD.

CONCLUSION

Our findings show the potential usefulness of SCD as a harbinger of cerebrovascular disease in cognitively healthy individuals. Further research is needed in order to elucidate the role of SCD as a preclinical marker of vascular cognitive impairment.

MRI-Based Classification of Neuropsychiatric Systemic Lupus Erythematosus Patients With Self-Supervised Contrastive Learning

Introduction/Purpose

Systemic lupus erythematosus (SLE) is a chronic auto-immune disease with a broad spectrum of clinical presentations, including heterogeneous neuropsychiatric (NP) syndromes. Structural brain abnormalities are commonly found in SLE and NPSLE, but their role in diagnosis is limited, and their usefulness in distinguishing between NPSLE patients and patients in which the NP symptoms are not primarily attributed to SLE (non-NPSLE) is non-existent. Self-supervised contrastive learning algorithms proved to be useful in classification tasks in rare diseases with limited number of datasets. Our aim was to apply self-supervised contrastive learning on T1-weighted images acquired from a well-defined cohort of SLE patients, aiming to distinguish between NPSLE and non-NPSLE patients.

Subjects and Methods

We used 3T MRI T1-weighted images of 163 patients. The training set comprised 68 non-NPSLE and 34 NPSLE patients. We applied random geometric transformations between iterations to augment our data sets. The ML pipeline consisted of convolutional base encoder and linear projector. To test the classification task, the projector was removed and one linear layer was measured. Validation of the method consisted of 6 repeated random sub-samplings, each using a random selection of a small group of patients of both subtypes.

Results

In the 6 trials, between 79% and 83% of the patients were correctly classified as NPSLE or non-NPSLE. For a qualitative evaluation of spatial distribution of the common features found in both groups, Gradient-weighted Class Activation Maps (Grad-CAM) were examined. Thresholded Grad-CAM maps show areas of common features identified for the NPSLE cohort, while no such communality was found for the non-NPSLE group.

Discussion/Conclusion

The self-supervised contrastive learning model was effective in capturing common brain MRI features from a limited but well-defined cohort of SLE patients with NP symptoms. The interpretation of the Grad-CAM results is not straightforward, but indicates involvement of the lateral and third ventricles, periventricular white matter and basal cisterns. We believe that the common features found in the NPSLE population in this study indicate a combination of tissue loss, local atrophy and to some extent that of periventricular white matter lesions, which are commonly found in NPSLE patients and appear hypointense on T1-weighted images.

Motoric Cognitive Risk Syndrome: Symptoms, Pathology, Diagnosis, and Recovery

The motoric cognitive risk (MCR) syndrome is a pre-dementia condition, marked by the enhanced risk for Alzheimer's disease (AD) and vascular dementia, together with falls, disability, and abnormal movements. The research studies revealed the distinct neurological and non-neurological clinical gait irregularities during dementia and accelerated functional decline, such as postural and balance impairments, memory loss, cognitive failure, and metabolic dysfunctions. The disabling characteristics of MCR comprise altered afferent sensory and efferent motor responses, together with disrupted visual, vestibular, and proprioceptive components. The pathological basis of MCR relates with the frontal lacunar infarcts, white matter hyperintensity (WMH), gray matter atrophy in the pre-motor and pre-frontal cortex, abnormal cholinergic functioning, inflammatory responses, and genetic factors. Further, cerebrovascular lesions and cardiovascular disorders exacerbate the disease pathology. The diagnosis of MCR is carried out through neuropsychological tests, biomarker assays, imaging studies, questionnaire-based evaluation, and motor function tests, including walking speed, dual-task gait tests, and ambulation ability. Recovery from MCR may include cognitive, physical, and social activities, exercise, diet, nutritional supplements, symptomatic drug treatment, and lifestyle habits that restrict the disease progression. Psychotherapeutic counseling, anti-depressants, and vitamins may support motor and cognitive improvement, primarily through the restorative pathways. However, an in-depth understanding of the association of immobility, dementia, and cognitive stress with MCR requires additional clinical and pre-clinical studies. They may have a significant contribution in reducing MCR syndrome and the risk for dementia. Overall, the current review informs the vital connection between gait performance and cognition in MCR and highlights the usefulness of future research in the discernment and treatment of dementiating illness.

Chronic Covert Brain Infarctions and White Matter Hyperintensities in Patients With Stroke, Transient Ischemic Attack, and Stroke Mimic

Background

This study was conducted to compare frequencies of chronic brain infarctions (CBIs) and white matter hyperintensities (WMHs) as well as their associations with established early recurrence risk scores in patients with transient ischemic attack (TIA) and stroke mimics compared with ischemic stroke.

Methods and Results

Single‐center cohort study including consecutive patients with TIA, stroke mimics, and acute ischemic stroke, with available magnetic resonance imaging from January 2015 to December 2017. Blinded raters adjudicated WMH (age‐related white matter changes score) and CBI according to established definitions. A total of 2112 patients (median [Q1–Q3] age 71 [59–80] years, 43% women, National Institutes of Health Stroke Scale score of 2 [1–7], 80% ischemic stroke, 18% TIA, 2% stroke mimics) were included. While CBIs were present in only 10% of patients with stroke mimic, they were detected in 28% of TIAs and 38% of ischemic strokes (P<0.001). WMHs were less pronounced (0, 0–1) in patients with stroke mimic, but there was no difference between TIA (1, 1–2) and ischemic stroke (0, 1–2) patients. CBIs (adjusted odds ratio, 0.3; 95% CI, 0.1–0.9) were associated with a lower rate of stroke mimic as the final diagnosis, while WMHs were not (adjusted odds ratio per point, 1.3; 95% CI, 0.7–2.2). WMH (β per point, 0.4; 95% CI, 0.3–0.6) and presence of CBI (β, 0.6; 95% CI, 0.3–0.9) were associated with a higher cardiovascular risk profile according to the ABCD3‐I score. The accuracy of prediction was good for high‐risk TIA (cross‐validated area under the receiver operating characteristic curve, 0.89; 95% CI, 0.79–0.93) on the basis of brain imaging, age, and sex.

Conclusions

CBI and WMH differ between patients with stroke mimic and patients with TIA/ischemic stroke and are closely associated with established recurrence risk scores. Prospective studies need to clarify whether including brain frailty markers may contribute to the refinement of current management algorithms and risk stratifications.

Different cardiovascular risk factors are related to distinct white matter hyperintensity MRI phenotypes in older adults

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White matter hyperintensity (WMH) shape: a novel, advanced MRI marker.

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Hypertension correlates with a more irregular shape of periventricular/confluent WMH.

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Different cardiovascular/pathological mechanisms lead to distinct WMH MRI phenotypes.

The underlying mechanisms of the association between cardiovascular risk factors and a higher white matter hyperintensity (WMH) burden are unknown. We investigated the association between cardiovascular risk factors and advanced WMH markers in 155 non-demented older adults (mean age: 71 ± 5 years). The association between cardiovascular risk factors and quantitative MRI-based WMH shape and volume markers were examined using linear regression analysis. Presence of hypertension was associated with a more irregular shape of periventricular/confluent WMH (convexity (B (95 % CI)): −0.12 (−0.22–−0.03); concavity index: 0.06 (0.02–0.11)), but not with total WMH volume (0.22 (−0.15–0.59)). Presence of diabetes was associated with deep WMH volume (0.89 (0.15–1.63)). Body mass index or hyperlipidemia showed no association with WMH markers. In conclusion, different cardiovascular risk factors seem to be related to a distinct pattern of WMH shape markers in non-demented older adults. These findings may suggest that different underlying cardiovascular pathological mechanisms lead to different WMH MRI phenotypes, which may be valuable for early detection of individuals at risk for stroke and dementia.

Cumulative Concussion and Odds of Stroke in Former National Football League Players

BACKGROUND AND PURPOSE

Postmortem and experimental studies indicate a potential association between repeated concussions and stroke risk in older contact sport athletes. We examined the relationship between concussion and stroke history in former National Football League players aged ≥50 years.

METHODS

Former professional football players aged ≥50 years who played ≥1 year in the National Football League were enrolled in the cross-sectional study. Indirect standardization was used to calculate overall and decade-specific standardized prevalence ratios. Logistic regression using Firth's bias reduction method examined the association between lifetime concussion history 0 (n=119; 12.2%), 1 to 2 (n=152; 15.5%), 3 to 5 (n=242; 24.7%), 6 to 9 (201; 20.5%), and 10+(n=265; 27.1%) and stroke. Adjusted odds ratios for stroke were calculated for concussion history groups, age, and coronary artery disease and/or myocardial infarction.

RESULTS

The 979 participants who met inclusion criteria had a mean age of 65.0±9.0 years (range, 50-99). The prevalence of stroke was 3.4% (n=33), significantly lower than expected based on rates of stroke in US men aged 50 and over (standardized prevalence ratio=0.56, Z= -4.56, P<0.001). Greater odds of stroke history were associated with concussion history (10+ versus 0, adjusted odds ratio [95% CI]=5.51 [1.61-28.95]), cardiovascular disease (adjusted odds ratio [95% CI]=2.24 [1.01-4.77]), and age (1-year-increase adjusted odds ratio [95% CI]=1.07 [1.02-1.11]).

CONCLUSIONS

The prevalence of stroke among former National Football League players aged ≥50 years was lower than the general population, with significantly increased risk among those with 10 or more prior concussions. Findings add to the evidence suggesting that traumatic brain injuries are associated with increased risk of stroke. Clinically, management of cardio- and cerebrovascular health may be pertinent to those with a history of multiple prior concussions.

Sex Differences in Hemostatic Factors in Patients With Ischemic Stroke and the Relation With Migraine-A Systematic Review

Background: Women are more affected by stroke than men. This might, in part, be explained by sex differences in stroke pathophysiology. The hemostasis system is influenced by sex hormones and associated with female risk factors for stroke, such as migraine.

Aim: To systematically review possible sex differences in hemostatic related factors in patients with ischemic stroke in general, and the influence of migraine on these factors in women with ischemic stroke.

Results: We included 24 studies with data on sex differences of hemostatic factors in 7247 patients with ischemic stroke (mean age 57–72 years, 27–57% women) and 25 hemostatic related factors. Levels of several factors were higher in women compared with men; FVII:C (116% ± 30% vs. 104% ± 30%), FXI (0.14 UI/mL higher in women), PAI-1 (125.35 ± 49.37 vs. 96.67 ± 38.90 ng/mL), D-dimer (1.25 ± 0.31 vs. 0.95 ± 0.24 μg/mL), and aPS (18.7% vs. 12.0% positive). In contrast, protein-S (86.2% ± 23.0% vs. 104.7% ± 19.8% antigen) and P-selectin (48.9 ± 14.4 vs. 79.1 ± 66.7 pg/mL) were higher in men. Most factors were investigated in single studies, at different time points after stroke, and in different stroke subtypes. Only one small study reported data on migraine and hemostatic factors in women with ischemic stroke. No differences in fibrinogen, D-dimer, t-PA, and PAI-1 levels were found between women with and without migraine.

Conclusion: Our systematic review suggests that sex differences exist in the activation of the hemostatic system in ischemic stroke. Women seem to lean more toward increased levels of procoagulant factors whereas men exhibit increased levels of coagulation inhibitors. To obtain better insight in sex-related differences in hemostatic factors, additional studies are needed to confirm these findings with special attention for different stroke phases, stroke subtypes, and not in the least women specific risk factors, such as migraine.

Neuropsychiatric systemic lupus erythematosus is associated with a distinct type and shape of cerebral white matter hyperintensities

Objectives

Advanced white matter hyperintensity (WMH) markers on brain MRI may help reveal underlying mechanisms and aid in the diagnosis of different phenotypes of SLE patients experiencing neuropsychiatric (NP) manifestations.

Methods

In this prospective cohort study, we included a clinically well-defined cohort of 155 patients consisting of 38 patients with NPSLE (26 inflammatory and 12 ischaemic phenotype) and 117 non-NPSLE patients. Differences in 3 T MRI WMH markers (volume, type and shape) were compared between patients with NPSLE and non-NPSLE and between patients with inflammatory and ischaemic NPSLE by linear and logistic regression analyses corrected for age, sex and intracranial volume.

Results

Compared with non-NPSLE [92% female; mean age 42 (13) years], patients with NPSLE [87% female; mean age 40 (14) years] showed a higher total WMH volume [B (95%-CI)]: 0.46 (0.0 7 ↔ 0.86); P = 0.021], a higher periventricular/confluent WMH volume [0.46 (0.0 6 ↔ 0.86); P = 0.024], a higher occurrence of periventricular with deep WMH type [0.32 (0.1 3 ↔ 0.77); P = 0.011], a higher number of deep WMH lesions [3.06 (1.2 1 ↔ 4.90); P = 0.001] and a more complex WMH shape [convexity: ‒0.07 (‒0.12 ↔ ‒0.02); P = 0.011, concavity index: 0.05 (0.0 1 ↔ 0.08); P = 0.007]. WMH shape was more complex in inflammatory NPSLE patients [89% female; mean age 39 (15) years] compared with patients with the ischaemic phenotype [83% female; mean age 41 (11) years] [concavity index: 0.08 (0.0 1 ↔ 0.15); P = 0.034].

Conclusion

We demonstrated that patients with NPSLE showed a higher periventricular/confluent WMH volume and more complex shape of WMH compared with non-NPSLE patients. This finding was particularly significant in inflammatory NPLSE patients, suggesting different or more severe underlying pathophysiological abnormalities.