White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype

The time-course augmentation of perivascular space enlargement in the basal ganglia among a community-dwelling elder population

PURPOSE

We examined whether time-course augmentation of perivascular space enlargement in the basal ganglia (BG-PVS) reflected cerebral small vessel disease (CSVD) severity by considering white matter hyperintensity lesion (WMHL) as an indicator for CSVD.

MATERIALS AND METHODS

This study population included 416 older participants from a community-based cohort. They participated in magnetic resonance imaging (MRI) studies more than once during the study period. The grades for BG-PVS and WMHL were evaluated by visual rating scales; BG-PVS time-course augmentation in 4-9 years was also evaluated. At baseline, the participants were asked about their smoking and drinking history, and medical history. They also underwent a blood examination and their office blood pressure (BP) examination. In addition, 24-h ambulatory BP monitoring was also performed within the study period.

RESULTS

Of the 416 participants, 48 participants (11.5%) had BG-PVS time-course augmentation. The participants with BG-PVS augmentation had significantly lower LDL levels, hyper-nighttime BP, and lower nighttime BP fall in univariate analysis (p = 0.03, p = 0.03, p = 0.003, respectively). In multivariate analysis, lower nighttime BP fall and male sex showed significance (p = 0.02, 0.03, respectively). Additionally, BG-PVS time-course augmentation was significantly associated with subsequent WMHL severity in univariate analysis (p < 0.001), which remained significant in multivariate analysis adjusted by imaging and demographic factors (p = 0.03). In multivariate analysis, additionally adjusted by the clinical factors, the significance disappeared (p = 0.07).

CONCLUSION

This study revealed that the lower nighttime BP fall in ambulatory blood pressure monitoring was a factor significantly associated with BG-PVS augmentation. Moreover, the BG-PVS time-course augmentation would be a notable finding that was associated with the subsequent WMHL.

Differential risk factor profile and neuroimaging markers of small vessel disease between lacunar ischemic stroke and deep intracerebral hemorrhage

Background

Lacunar ischemic stroke (LIS) and deep intracerebral hemorrhage (dICH) are two stroke phenotypes of deep perforator arteriopathy. It is unclear what factors predispose individuals with deep perforator arteriopathy to either ischemic or hemorrhagic events.

Objectives

We aimed to investigate risk factors and neuroimaging features of small vessel disease (SVD) associated with LIS versus dICH in a cross-sectional study.

Methods

We included patients with clinically presenting, magnetic resonance imaging-confirmed LIS or dICH from two tertiary hospitals between 2010 and 2021. We recorded vascular risk factors and SVD markers, including lacunes, white matter hyperintensities (WMH), perivascular spaces (PVS), and cerebral microbleeds (CMB). Logistic regression modeling was used to determine the association between vascular risk factors, SVD markers, and stroke phenotype. We further created WMH probability maps to compare WMH distribution between LIS and dICH.

Results

A total of 834 patients with LIS (mean age 61.7 ± 12.1 years) and 405 with dICH (57.7 ± 13.2 years) were included. Hypertension was equally frequent between LIS and dICH (72.3% versus 74.8%, p = 0.349). Diabetes mellitus, hyperlipidemia, smoking, and prior ischemic stroke were more associated with LIS [odds ratio (OR) (95% confidence interval (CI)), 0.35 (0.25-0.48), 0.32 (0.22-0.44), 0.31 (0.22-0.44), and 0.38 (0.18-0.75)]. Alcohol intake and prior ICH were more associated with dICH [OR (95% CI), 2.34 (1.68-3.28), 2.53 (1.31-4.92)]. Lacunes were more prevalent in LIS [OR (95% CI) 0.23 (0.11-0.43)], while moderate-to-severe basal-ganglia PVS and CMB were more prevalent in dICH [OR (95% CI) 2.63 (1.35-5.27), 4.95 (2.71-9.42)]. WMH burden and spatial distribution did not differ between groups.

Conclusion

The microangiopathy underlying LIS and dICH reflects distinct risk profiles and SVD features, hence possibly SVD subtype susceptibility. Prospective studies with careful phenotyping and genetics are needed to clarify the mechanisms underlying this difference.

Effect of pre-stroke antiplatelet use on stroke outcomes in acute small vessel occlusion stroke with moderate to severe white matter burden

BACKGROUND

Cerebral small vessel disease is characterized by white matter hyperintensities (WMH) and acute small vessel occlusion (SVO) stroke. We investigated the effect of prior antiplatelet use (APU) on stroke outcome in 1151 patients with acute SVO stroke patients and moderate to severe WMH.

METHODS

Using a multicenter database, this retrospective study used quantitative WMH volume measurements and propensity score matching (PSM) for comparisons between patients with prior APU and without APU. Primary outcomes were stroke progression and poor functional outcome (modified Rankin Scale>2) at 3 months. Logistic regression analyses assessed associations between prior APU, WMH burden, and stroke outcomes.

RESULTS

Stroke progression was lower in the prior APU group in both the total cohort (14.8% vs. 6.9%, p < 0.001) and the PSM cohort (16.3% vs. 6.9%, p < 0.001). The proportion of poor functional outcomes at 3 months was not significantly different in the total cohort, but the PSM cohort showed a lower proportion in the prior APU group (30.8% vs. 20.2%, p = 0.002). Logistic regression analysis confirmed that prior APU was associated with a reduced risk of stroke progression (OR, 0.39; 95% CI, 0.22-0.70; p = 0.001) and poor functional outcome at 3 months (OR, 0.37; 95% CI, 0.23-0.59; p < 0.001).

CONCLUSION

Prior APU is associated with reduced stroke progression and improved functional outcome at 3 months in acute SVO stroke patients with moderate to severe WMH. Early treatment of WMH and acute SVO stroke may have potential benefits in improving stroke outcomes.

Correlation between body composition and white matter hyperintensity in patients with acute ischemic stroke

White matter hyperintensity (WMH) burden is associated with a higher risk of ischemic stroke. The relationship between WMH and obesity is somewhat controversial which might be interfered by different body composition such as skeletal muscle, fat and bone density. However, few researchers have evaluated the relationship between WMH burden and disaggregated body constituents in acute ischemic stroke (AIS) patients systematically. A total of 352 AIS patients were enrolled in this study. The subcutaneous adipose tissue, erector spinae muscle area and bone density were evaluated on the computed tomography scanning. The burden of WMH was evaluated using the Fazekas scale based on the fluid-attenuated inversion recovery sequence. The severity of overall WMH was defined as none-mild WMH (total Fazekas score 0-2) or moderate-severe WMH (total Fazekas score 3-6). Based on the severity of periventricular WMH (P-WMH) and deep WMH, patients were categorized into either a none-mild (Fazekas score 0-1) group or a moderate-severe (Fazekas score 2-3) group. We found that patients with moderate-severe WMH showed lower bone density and smaller erector spinae muscle area and subcutaneous adipose tissue than none-mild. The logistic regression analysis showed that the bone density was independently associated with moderate-severe overall WMH (odds radio = 0.98, 95% confidence interval, 0.972-0.992, P < .001) and similar results were found in the analyses according to P-WMH (odds radio = 0.98, 95% confidence interval, 0.972-0.992, P < .001). These findings suggest that among the AIS body composition, the bone density is independently associated with the severity of overall WMH and P-WMH.

White matter hyperintensities combined with serum NLRP3 in diagnosis of cognitive impairment in patients with cerebral small vessel disease

Background: White matter hyperintensities (WMH) are widely used for the diagnosis of cerebral small vessel disease (CSVD). However, whether NLRP3 is correlated with cognitive impairment after CSVD is still not clear.Objective: This study aimed to investigate the diagnostic value of WMHs combined with NLRP3 for cognitive impairment after CSVD.Methods: This prospective observational study enrolled a total of 188 CSVD patients from September 2019 to May 2022. All patients received brain MRI assessment and WMH Fazekas score, as well as WMH volume, was recorded. Serum NLRP3 level was measured by ELISA. Patients' cognitive function was measured by MoCA after 6 months of diagnosis of CSVD. The serum levels of C reactive protein (CRP), interleukin (IL)-6, total cholesterol (TC), triglyceride (TG), high-density leptin cholesterol (HDL) and low-density leptin cholesterol (LDL) were recordedResults: CSVD patients with cognitive impairment had significantly higher Fazekas scores, WMH volumes, serum NLRP3 and IL-6 levels compared to patients without cognitive impairment. A positive correlation was found among Fazekas scores, WMH volumes and NLRP3 levels. The combination of WMH volume and NLRP3 could achieve a better specificity for the diagnosis of cognitive impairment. Coronary syndrome history, WMH volume and NLRP3 were found as independent risk factors for cognitive impairment after CSVD.Conclusion: Fazekas scores, WMH volume and serum NLRP3 levels are associated with cognitive impairment after CSVD and have the potential to be used as diagnostic biomarkers.

Optimal systolic and diastolic blood pressure threshold that associated with lower risk of white matter hyperintensity progression

Background

The optimal control thresholds for systolic blood pressure (SBP) and diastolic blood pressure (DBP) in patients with white matter hyperintensity (WMH) are still unclear.

Method

A longitudinal retrospective study of patients with brain magnetic resonance imaging (MRI) scans with intervals of more than 3  years was conducted. Blood pressure records during hospitalization and from outpatient visits between baseline and the last MRI scan were collected. The outcome was the change in total WMH from baseline to the final visit.

Results

Among the 965 patients with MRI scans, 457 patients with detailed longitudinal blood pressure records were ultimately included and classified into the WMH absent group (n = 121), mild WMH group (n = 126), and moderate to severe WMH group (n = 210). Both baseline and longitudinal mean SBP, DBP, and SBP SD were significantly associated with WMH severity (p < 0.05). An average SBP of 130-140 mmHg [vs. <130 mmHg, aOR, 1.80, (95% CI, 1.05-3.07), p = 0.03] was associated with a higher risk of WMH progression. DBP ≥ 90 mmHg [vs. <80 mmHg, OR, 1.81, (95% CI, 0.88-3.74), p = 0.02, aOR, 1.54, (95% CI, 0.66-3.53), p = 0.32] was associated with a higher risk of WMH progression, but was not after adjusted for other covariates. Longitudinal BP variability was not significantly associated with WMH progression.

Conclusion

Both SBP and DBP had a stronger relationship with the severity of WMH. A target mean SBP of <130 mmHg and mean DBP of <80 mmHg was associated with a lower risk of WMH progression.

White Matter Cerebrovascular Reactivity: Effects of Microangiopathy and Proximal Occlusions on the Dynamic BOLD Response

Introduction

Cerebral microangiopathy often manifests as white matter hyperintensities (WMH) on T2-weighted MR images and is associated with elevated stroke risk. Large vessel steno-occlusive disease (SOD) is also independently associated with stroke risk, however, the interaction of microangiopathy and SOD is not well understood. Cerebrovascular reactivity (CVR) describes the capacity of cerebral circulation to adapt to changes in perfusion pressure and neurovascular demand, and its impairment portends future infarctions. CVR can be measured with blood oxygen level dependent (BOLD) imaging following acetazolamide stimulus (ACZ-BOLD). We studied CVR differences between WMH and normal-appearing white matter (NAWM) in patients with chronic SOD, hypothesizing additive influences upon CVR measured by novel, fully dynamic CVR maxima ( CVR _max ).

Methods

A cross sectional study was conducted to measure per-voxel, per-TR maximal CVR ( CVR _max ) using a custom computational pipeline in 23 subjects with angiographically-proven unilateral SOD. WMH and NAWM masks were applied to CVR _max maps. White matter was subclassified with respect to the SOD-affected hemisphere, including: i. contralateral NAWM; ii. contralateral WMH iii. ipsilateral NAWM; iv. ipsilateral WMH. CVR _max was compared between these groups with a Kruskal-Wallis test followed by a Dunn-Sidak post-hoc test for multiple comparisons.

Results

19 subjects (age 50±12 years, 53% female) undergoing 25 examinations met criteria. WMH volume was asymmetric in 16/19 subjects with 13/16 exhibiting higher volumes ipsilateral to SOD. Pairwise comparisons of CVR _max between groups was significant with ipsilateral WMH CVR _max lower than contralateral NAWM (p=0.015) and contralateral WMH (p=0.003) when comparing in-subject medians and lower than all groups when comparing pooled voxelwise values across all subjects (p<0.0001). No significant relationship between WMH lesion size and CVR _max was detected.

Conclusion

Our results suggest additive effects of microvascular and macrovascular disease upon white matter CVR, but with greater overall effects relating to macrovascular SOD than to apparent microangiopathy. Dynamic ACZ-BOLD presents a promising path towards a quantitative stroke risk imaging biomarker.

BACKGROUND

Cerebral white matter (WM) microangiopathy manifests as sporadic or sometimes confluent high intensity lesions in MR imaging with T2-weighting, and bears known associations with stroke, cognitive disability, depression and other neurological disorders ^1-5 . Deep white matter is particularly susceptible to ischemic injury owing to the deprivation of collateral flow between penetrating arterial territories, and hence deep white matter hyperintensities (WMH) may portend future infarctions ^6-8 . The pathophysiology of WMH is variable but commonly includes a cascade of microvascular lipohyalinosis and atherosclerosis together with impaired vascular endothelial and neurogliovascular integrity, leading to blood brain barrier dysfunction, interstitial fluid accumulation, and eventually tissue damage ^9-14 . Independent of the microcirculation, cervical and intracranial large vessel steno-occlusive disease (SOD) often results from atheromatous disease and is associated with increased risk of stroke owing to thromboembolic phenomena, hypoperfusion, or combinations thereof ^15-17 . White matter disease is more common in the affected hemisphere of patients with asymmetric or unilateral SOD, producing both macroscopic WMH detectable by routine structural MRI, as well as microstructural changes and altered structural connectivity detected by advanced diffusion microstructural imaging ^{18, 19} . An improved understanding of the interaction of microvascular disease (i.e., WMH) and macrovascular steno-occlusion could better inform stroke risk stratification and guide treatment strategies when coexistent. Cerebrovascular reactivity (CVR) is an autoregulatory adaptation characterized by the capacity of the cerebral circulation to respond to physiological or pharmacological vasodilatory stimuli ^20-22 . CVR may be heterogeneous and varies across tissue type and pathological states ^{1, 16} . Alterations in CVR are associated with elevated stroke risk in SOD patients, although white matter CVR, and in particular the CVR profiles of WMH, are only sparsely studied and not fully understood ^{1, 23-26} . We have previously employed blood oxygen level dependent (BOLD) imaging following a hemodynamic stimulus with acetazolamide (ACZ) in order to measure CVR (i.e. ACZ-BOLD) ^{21, 27, 28} . Despite the emergence of ACZ-BOLD as a technique for clinical and experimental use, poor signal-to-noise characteristics of the BOLD effect have generally limited its interpretation to coarse, time-averaged assessment of the terminal ACZ response at arbitrarily prescribed delays following ACZ administration (e.g. 10-20 minutes) ²⁹ . More recently, we have introduced a dedicated computational pipeline to overcome historically intractable signal-to-noise ratio (SNR) limitations of BOLD, enabling fully dynamic characterization of the cerebrovascular response, including identification of previously unreported, unsustained or transient CVR maxima ( CVR _max ) following hemodynamic provocation ^{27, 30} . In this study, we compared such dynamic interrogation of true CVR maxima between WMH and normal appearing white matter (NAWM) among patients with chronic, unilateral SOD in order to quantify their interaction and to assess the hypothesized additive effects of angiographically-evident macrovascular stenoses when intersecting microangiopathic WMH.

Spatial patterns of white matter hyperintensities: a systematic review

Background

White matter hyperintensities are an important marker of cerebral small vessel disease. This disease burden is commonly described as hyperintense areas in the cerebral white matter, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging data. Studies have demonstrated associations with various cognitive impairments, neurological diseases, and neuropathologies, as well as clinical and risk factors, such as age, sex, and hypertension. Due to their heterogeneous appearance in location and size, studies have started to investigate spatial distributions and patterns, beyond summarizing this cerebrovascular disease burden in a single metric-its volume. Here, we review the evidence of association of white matter hyperintensity spatial patterns with its risk factors and clinical diagnoses.

Design/methods

We performed a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We used the standards for reporting vascular changes on neuroimaging criteria to construct a search string for literature search on PubMed. Studies written in English from the earliest records available until January 31st, 2023, were eligible for inclusion if they reported on spatial patterns of white matter hyperintensities of presumed vascular origin.

Results

A total of 380 studies were identified by the initial literature search, of which 41 studies satisfied the inclusion criteria. These studies included cohorts based on mild cognitive impairment (15/41), Alzheimer's disease (14/41), Dementia (5/41), Parkinson's disease (3/41), and subjective cognitive decline (2/41). Additionally, 6 of 41 studies investigated cognitively normal, older cohorts, two of which were population-based, or other clinical findings such as acute ischemic stroke or reduced cardiac output. Cohorts ranged from 32 to 882 patients/participants [median cohort size 191.5 and 51.6% female (range: 17.9-81.3%)]. The studies included in this review have identified spatial heterogeneity of WMHs with various impairments, diseases, and pathologies as well as with sex and (cerebro)vascular risk factors.

Conclusion

The results show that studying white matter hyperintensities on a more granular level might give a deeper understanding of the underlying neuropathology and their effects. This motivates further studies examining the spatial patterns of white matter hyperintensities.

Artificial Intelligence in Acute Ischemic Stroke Subtypes According to Toast Classification: A Comprehensive Narrative Review

The correct recognition of the etiology of ischemic stroke (IS) allows tempestive interventions in therapy with the aim of treating the cause and preventing a new cerebral ischemic event. Nevertheless, the identification of the cause is often challenging and is based on clinical features and data obtained by imaging techniques and other diagnostic exams. TOAST classification system describes the different etiologies of ischemic stroke and includes five subtypes: LAAS (large-artery atherosclerosis), CEI (cardio embolism), SVD (small vessel disease), ODE (stroke of other determined etiology), and UDE (stroke of undetermined etiology). AI models, providing computational methodologies for quantitative and objective evaluations, seem to increase the sensitivity of main IS causes, such as tomographic diagnosis of carotid stenosis, electrocardiographic recognition of atrial fibrillation, and identification of small vessel disease in magnetic resonance images. The aim of this review is to provide overall knowledge about the most effective AI models used in the differential diagnosis of ischemic stroke etiology according to the TOAST classification. According to our results, AI has proven to be a useful tool for identifying predictive factors capable of subtyping acute stroke patients in large heterogeneous populations and, in particular, clarifying the etiology of UDE IS especially detecting cardioembolic sources.

Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke

BACKGROUND AND OBJECTIVES

While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes.

METHODS

We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input.

RESULTS

We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes.

DISCUSSION

T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.

Serum YKL-40 Levels and White Matter Hyperintensities in Patients with Acute Ischemic Stroke

Background

White matter hyperintensity (WMH) is associated with risk of acute ischemic stroke (AIS) and poor outcomes after AIS. The purpose of this prospective study was to evaluate the association between serum YKL-40 levels and WMH burden in patients with AIS.

Methods

From February 2020 to March 2021, a total of 672 consecutive AIS patients with magnetic resonance imaging data were prospectively recruited form two centers. Serum YKL-40 levels were quantified using enzyme-linked immunosorbent assay. The burden of WMH was semiquantitatively measured by the Fazekas visual grading scale. According to severity of overall WMH, patients were dichotomized into none-mild WMH group (Fazekas score 0-2) or moderate-severe WMH group (Fazekas score 3-6). Besides, based on severity of periventricular WMH (PV-WMH) and deep WMH (D-WMH), patients were categorized as none-mild (Fazekas score 0-1) or moderate-severe (Fazekas score 2-3).

Results

Among the 672 patients, 335 (49.9%) participants were identified with moderate-severe overall WMH, 326 (48.5%) with moderate-severe PV-WMH and 262 (39.0%) with moderate-severe D-WMH. Compared with the first quartile of serum YKL-40, the adjusted odds ratio (OR) of the fourth quartile for moderate-severe PV-WMH was 2.473 (95% confidence interval [CI] 1.316-4.646; P=0.005). No significant association was observed between YKL-40 and overall WMH (OR 0.762; 95% CI 0.434-1.336; P=0.343) or D-WMH (OR 0.695; 95% CI 0.413-1.171; P=0.172).

Conclusion

Our results suggested that higher YKL-40 levels appeared to be associated with PV-WMH, but not with overall WMH or D-WMH in patients with AIS.

In Mild and Moderate Acute Ischemic Stroke, Increased Lipid Peroxidation and Lowered Antioxidant Defenses Are Strongly Associated with Disabilities and Final Stroke Core Volume

In acute ischemic stroke (AIS), there are no data on whether oxidative stress biomarkers have effects above and beyond known risk factors and measurements of stroke volume. This study was conducted in 122 mild-moderate AIS patients and 40 controls and assessed the modified ranking scale (mRS) at baseline, and 3 and 6 months later. We measured lipid hydroperoxides (LOOH), malondialdehyde (MDA), advanced oxidation protein products, paraoxonase 1 (PON1) activities and PON1 Q192R genotypes, high density lipoprotein cholesterol (HDL), sulfhydryl (-SH) groups), and diffusion-weighted imaging (DWI) stroke volume and fluid-attenuated inversion recovery (FLAIR) signal intensity. We found that (a) AIS is characterized by lower chloromethyl acetate CMPAase PON1 activity, HDL and -SH groups and increased LOOH and neurotoxicity (a composite of LOOH, inflammatory markers and glycated hemoglobin); (b) oxidative and antioxidant biomarkers strongly and independently predict mRS scores 3 and 6 months later, DWI stroke volume and FLAIR signal intensity; and (c) the PON1 Q192R variant has multiple effects on stroke outcomes that are mediated by its effects on antioxidant defenses and lipid peroxidation. Lipid peroxidation and lowered -SH and PON1-HDL activity are drug targets to prevent AIS and consequent neurodegenerative processes and increased oxidative reperfusion mediators due to ischemia-reperfusion injury.

Acute Infarcts on Brain MRI Following Aortic Arch Repair With Circulatory Arrest: Insights From the ACE CardioLink-3 Randomized Trial

BACKGROUND

to investigate the frequency and distribution of new ischemic brain lesions detected by diffusion-weighted imaging on brain magnetic resonance imaging after aortic arch surgery.

METHODS

This preplanned secondary analysis of the randomized, controlled ACE (Aortic Surgery Cerebral Protection Evaluation) CardioLink-3 trial compared the safety and efficacy of innominate versus axillary artery cannulation during elective proximal aortic arch surgery. Participants underwent pre and postoperative magnetic resonance imaging. New ischemic lesions were defined as lesions visible on postoperative, but not preoperative diffusion weighted imaging.

RESULTS

Of the 111 trial participants, 102 had complete magnetic resonance imaging data. A total of 391 new ischemic lesions were observed on diffusion-weighted imaging in 71 (70%) patients. The average number of lesions in patients with ischemic lesion were 5.5±4.9 with comparable numbers in the right (2.9±2.0) and left (3.0±2.3) hemispheres (P=0.49). Half the new lesions were in the middle cerebral artery territory; 63% of the cohort had ischemic lesions in the anterior circulation, 49% in the posterior circulation, 42% in both, and 20% in watershed areas. A probability mask of all diffusion-weighted imaging lesions revealed that the cerebellum was commonly involved. More severe white matter hyperintensity on preoperative magnetic resonance imaging (odds ratio, 1.80 [95% CI, 1.10-2.95]; P=0.02) and lower nadir nasopharyngeal temperature during surgery (odds ratio per 1°C decrease, 1.15 [95% CI, 1.00-1.32]; P=0.05) were associated with the presentation of new ischemic lesion; older age (risk ratio per 1-year increase, 1.02 [95% CI, 1.00-1.04]; P=0.03) and lower nadir temperature (risk ratio per 1°C decrease, 1.06 [95% CI, 1.00-1.14]; P=0.06) were associated with greater number of lesions.

CONCLUSIONS

In patients who underwent elective proximal aortic arch surgery, new ischemic brain lesions were common, and predominantly involved the middle cerebral artery territory or cerebellum. Underlying small vessel disease, lower temperature nadir during surgery, and advanced age were risk factors for perioperative ischemic lesions.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT02554032.

Brain Metabolic Network Redistribution in Patients with White Matter Hyperintensities on MRI Analyzed with an Individualized Index Derived from 18F-FDG-PET/MRI

OBJECTIVE

Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs.

MATERIALS AND METHODS

This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent 18F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUVmean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association.

RESULTS

The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10-3 and (0.0967 ± 0.0545) × 10-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUVmean of the limbic network (p < 0.001).

CONCLUSION

The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome

BACKGROUND AND OBJECTIVES

To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.

METHODS

MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.

RESULTS

A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location.

DISCUSSION

Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood

Background

Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes.

Methods

Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and Bayesian colocalization analysis to prioritize genes that contribute to stroke and its subtypes risk via affecting their expression and protein abundance in brain and blood.

Results

Our integrative analysis revealed that ICA1L was associated with small-vessel stroke (SVS), according to robust evidence at both protein and transcriptional levels based on brain-derived data. We also identified NBEAL1 that was causally related to SVS via its cis-regulated brain expression level. In blood, we identified 5 genes (MMP12, SCARF1, ABO, F11, and CKAP2) that had causal relationships with stroke and stroke subtypes.

Conclusions

Together, via using an integrative analysis to deal with multidimensional data, we prioritized causal genes in the pathogenesis of SVS, which offered hints for future biological and therapeutic studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03377-9.

Application of Deep Learning to Ischemic and Hemorrhagic Stroke Computed Tomography and Magnetic Resonance Imaging

Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been applied not only to the "downstream" side such as lesion detection, treatment decision making, and outcome prediction, but also to the "upstream" side for generation and enhancement of stroke imaging. This paper aims to comprehensively overview the common applications of DL to stroke imaging. In the future, more standardized imaging datasets and more extensive studies are needed to establish and validate the role of DL in stroke imaging.

Role of Semaphorins in Ischemic Stroke

Ischemic stroke is one of the major causes of neurological morbidity and mortality in the world. Although the management of ischemic stroke has been improved significantly, it still imposes a huge burden on the health and property. The integrity of the neurovascular unit (NVU) is closely related with the prognosis of ischemic stroke. Growing evidence has shown that semaphorins, a family of axon guidance cues, play a pivotal role in multiple pathophysiological processes in NVU after ischemia, such as regulating the immune system, angiogenesis, and neuroprotection. Modulating the NVU function via semaphorin signaling has a potential to develop a novel therapeutic strategy for ischemic stroke. We, therefore, review recent progresses on the role of semphorin family members in neurons, glial cells and vasculature after ischemic stroke.

Gut-Derived Metabolite Phenylacetylglutamine and White Matter Hyperintensities in Patients With Acute Ischemic Stroke

Background: White matter hyperintensity (WMH) burden is associated with a higher risk of ischemic stroke. Phenylacetylglutamine (PAGln) is a gut microbiota-derived metabolite that may induce cardiovascular events by activating platelets and increasing the risk of thrombosis. The relationship between plasma PAGln and WMH burden in patients with ischemic stroke is unknown. This study was designed to investigate the association between plasma PAGln and WMH burden in patients with acute ischemic stroke.

Methods: A total of 595 patients with acute ischemic stroke were enrolled in this study within 14 days of symptom onset. The burden of WMH was evaluated using the Fazekas scale based on the fluid-attenuated inversion recovery sequence. The severity of overall WMH was defined as none–mild WMH (total Fazekas score 0–2) or moderate–severe WMH (total Fazekas score 3–6). Based on the severity of periventricular WMH (P-WMH) and deep WMH (D-WMH), patients were categorized into either a none–mild (Fazekas score 0–1) group or a moderate–severe (Fazekas score 2–3) group. Plasma PAGln levels were quantified using liquid chromatography–mass spectrometry.

Results: We found that patients with moderate–severe overall WMH showed higher plasma PAGln levels than patients with none–mild overall WMH, and similar results were found in the analyses according to P-WMH and D-WMH. The logistic regression analysis showed that the fourth PAGln quartile was independently associated with moderate–severe overall WMH (adjusted 95% CI 1.134–4.018) and P-WMH (adjusted 95% CI 1.174–4.226).

Conclusion: These findings suggest that higher plasma PAGln levels are associated with moderate–severe overall WMH and P-WMH in patients with acute ischemic stroke.

MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes

OBJECTIVE

Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes.

METHODS

We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA).

RESULTS

Radiomic features were predictive of WMH burden (R 2 = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-values CV 1 - 6 < 0.001, p-value CV 7 = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes.

CONCLUSION

Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients' brain health.

The Stroke Neuro-Imaging Phenotype Repository: An Open Data Science Platform for Stroke Research

Stroke is one of the leading causes of death and disability worldwide. Reducing this disease burden through drug discovery and evaluation of stroke patient outcomes requires broader characterization of stroke pathophysiology, yet the underlying biologic and genetic factors contributing to outcomes are largely unknown. Remedying this critical knowledge gap requires deeper phenotyping, including large-scale integration of demographic, clinical, genomic, and imaging features. Such big data approaches will be facilitated by developing and running processing pipelines to extract stroke-related phenotypes at large scale. Millions of stroke patients undergo routine brain imaging each year, capturing a rich set of data on stroke-related injury and outcomes. The Stroke Neuroimaging Phenotype Repository (SNIPR) was developed as a multi-center centralized imaging repository of clinical computed tomography (CT) and magnetic resonance imaging (MRI) scans from stroke patients worldwide, based on the open source XNAT imaging informatics platform. The aims of this repository are to: (i) store, manage, process, and facilitate sharing of high-value stroke imaging data sets, (ii) implement containerized automated computational methods to extract image characteristics and disease-specific features from contributed images, (iii) facilitate integration of imaging, genomic, and clinical data to perform large-scale analysis of complications after stroke; and (iv) develop SNIPR as a collaborative platform aimed at both data scientists and clinical investigators. Currently, SNIPR hosts research projects encompassing ischemic and hemorrhagic stroke, with data from 2,246 subjects, and 6,149 imaging sessions from Washington University's clinical image archive as well as contributions from collaborators in different countries, including Finland, Poland, and Spain. Moreover, we have extended the XNAT data model to include relevant clinical features, including subject demographics, stroke severity (NIH Stroke Scale), stroke subtype (using TOAST classification), and outcome [modified Rankin Scale (mRS)]. Image processing pipelines are deployed on SNIPR using containerized modules, which facilitate replicability at a large scale. The first such pipeline identifies axial brain CT scans from DICOM header data and image data using a meta deep learning scan classifier, registers serial scans to an atlas, segments tissue compartments, and calculates CSF volume. The resulting volume can be used to quantify the progression of cerebral edema after ischemic stroke. SNIPR thus enables the development and validation of pipelines to automatically extract imaging phenotypes and couple them with clinical data with the overarching aim of enabling a broad understanding of stroke progression and outcomes.

Risk factors analysis according to regional distribution of white matter hyperintensities in a stroke cohort

OBJECTIVES

The spectrum of distribution of white matter hyperintensities (WMH) may reflect different functional, histopathological, and etiological features. We examined the relationships between cerebrovascular risk factors (CVRF) and different patterns of WMH in MRI using a qualitative visual scale in ischemic stroke (IS) patients.

METHODS

We assembled clinical data and imaging findings from patients of two independent cohorts with recent IS. MRI scans were evaluated using a modified visual scale from Fazekas, Wahlund, and Van Swieten. WMH distributions were analyzed separately in periventricular (PV-WMH) and deep (D-WMH) white matter, basal ganglia (BG-WMH), and brainstem (B-WMH). Presence of confluence of PV-WMH and D-WMH and anterior-versus-posterior WMH predominance were also evaluated. Statistical analysis was performed with SPSS software.

RESULTS

We included 618 patients, with a mean age of 72 years (standard deviation [SD] 11 years). The most frequent WMH pattern was D-WMH (73%). In a multivariable analysis, hypertension was associated with PV-WMH (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.29-2.50, p = 0.001) and BG-WMH (OR 2.13, 95% CI 1.19-3.83, p = 0.012). Diabetes mellitus was significantly related to PV-WMH (OR 1.69, 95% CI 1.24-2.30, p = 0.001), D-WMH (OR 1.46, 95% CI 1.07-1.49, p = 0.017), and confluence patterns of D-WMH and PV-WMH (OR 1.62, 95% CI 1.07-2.47, p = 0.024). Hyperlipidemia was found to be independently related to brainstem distribution (OR 1.70, 95% CI 1.08-2.69, p = 0.022).

CONCLUSIONS

Different CVRF profiles were significantly related to specific WMH spatial distribution patterns in a large IS cohort.

KEY POINTS

• An observational study of WMH in a large IS cohort was assessed by a modified visual evaluation. • Different CVRF profiles were significantly related to specific WMH spatial distribution patterns. • Distinct WMH anatomical patterns could be related to different pathophysiological mechanisms.

Emerging Concepts in Vascular Dementia: A Review

OBJECTIVE

Vascular dementia (VaD) is the second most common cause of dementia and a major health concern worldwide. A comprehensive review on VaD is warranted for better understanding and guidance for the practitioner. We provide an updated overview of the epidemiology, pathophysiological mechanisms, neuroimaging patterns as well as current diagnostic and therapeutic approaches.

MATERIALS AND METHODS

A narrative review of current literature in VaD was performed based on publications from the database of PubMed, Scopus and Google Scholar up to January, 2021.

RESULTS

VaD can be the result of ischemic or hemorrhagic tissue injury in a particular region of the brain which translates into clinically significant cognitive impairment. For example, a cerebral infarct in the speech area of the dominant hemisphere would translate into clinically significant impairment as would involvement of projection pathways such as the arcuate fasciculus. Specific involvement of the angular gyrus of the dominant hemisphere, with resultant Gerstman's syndrome, could have a pronounced effect on functional ability despite being termed a "minor stroke". Small vessel cerebrovascular disease can have a cumulate effect on cognitive function over time. It is unfortunately well recognized that "good" functional recovery in acute ischemic or haemorrhagic stroke, including subarachnoid haemorrhage, does not necessarily translate into good cognitive recovery. The victim may often be left unable to have gainful employment, drive a car safely or handle their affairs independently.

CONCLUSIONS

This review should serve as a compendium of updated information on VaD and provide guidance in terms of newer diagnostic and potential therapeutic approaches.

Genetic Variants behind Cardiovascular Diseases and Dementia

Cardiovascular diseases (CVDs) and dementia are the leading causes of disability and mortality. Genetic connections between cardiovascular risk factors and dementia have not been elucidated. We conducted a scoping review and pathway analysis to reveal the genetic associations underlying both CVDs and dementia. In the PubMed database, literature was searched using keywords associated with diabetes mellitus, hypertension, dyslipidemia, white matter hyperintensities, cerebral microbleeds, and covert infarctions. Gene lists were extracted from these publications to identify shared genes and pathways for each group. This included high penetrance genes and single nucleotide polymorphisms (SNPs) identified through genome wide association studies. Most risk SNPs to both diabetes and dementia participate in the phospholipase C enzyme system and the downstream nositol 1,4,5-trisphosphate and diacylglycerol activities. Interestingly, AP-2 (TFAP2) transcription factor family and metabolism of vitamins and cofactors were associated with genetic variants that were shared by white matter hyperintensities and dementia, and by microbleeds and dementia. Variants shared by covert infarctions and dementia were related to VEGF ligand-receptor interactions and anti-inflammatory cytokine pathways. Our review sheds light on future investigations into the causative relationships behind CVDs and dementia, and can be a paradigm of the identification of dementia treatments.