Predicting cerebrovascular age and its clinical relevance: Modeling using 3D morphological features of brain vessels.

Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline. Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455). Our novel pipeline adapted an existing framework to compute generic vessel features for brain vessels, resulting in 126 morphological features. We further built various machine learning models to predict age using only clinical factors, only brain vessel features, and a combination of both. We further assessed deviation from healthy aging using the age gap and explored its clinical relevance by correlating the predicted age and age gap with various risk factors. The models constructed using only brain vessel features and those combining clinical factors with vessel features were better predictors of age than the clinical factor-only model (r = 0.37, 0.48, and 0.26, respectively). Predicted age was associated with many known clinical factors, and the associations were stronger for the age gap in the normal cohort. The age gap was also associated with important factors in the pooled cohort atherosclerotic cardiovascular disease risk score and white matter hyperintensity measurements. Cerebrovascular age, computed using the morphological features of brain vessels, could serve as a potential individualized marker for the early detection of various cerebrovascular diseases.

Comparing the safety and effectiveness of overlapping stents with flow diverters for unruptured vertebral artery dissecting aneurysms.

BACKGROUND: Endovascular treatment for vertebral artery dissecting aneurysms (VADAs) includes overlapping stents and flow diverters. This study compared the safety and effectiveness of overlapping stents and flow diverters for unruptured VADAs. METHODS: We retrospectively enrolled patients with unruptured VADAs who underwent overlapping stents or flow diverters at two tertiary hospitals in South Korea. The primary clinical outcome was the occurrence of stroke. The primary angiographic outcomes (>12 months) were categorized as regression, no decrease in size, recanalization, or stent occlusion, of which only regression was defined as a favorable angiographic outcomes. RESULTS: Of the 146 patients with VADAs, 25 (17.1%) had flow diverters and 121 (82.9%) had overlapping stents. For the primary angiographic outcomes over 12 months, the rate of favorable angiographic outcomes for flow diverters was 81.8% and for overlapping stents (triple stents) was 98.8% (P=0.006). In the multivariale analysis, after adjusting for partially thrombosed aneurysms, aneurysm shape, non-dominant vessel, posterior inferior cerebellar artery involvement, and procedure type, overlapping stents (triple stents) was not associated with favorable angiographic outcomes compared with flow diverters (OR 7.040, 95% CI 0.549 to 90.294; P=0.134), but partially thrombosed aneurysms was inversely associated with favorable angiographic outcomes (OR 0.056, 95% CI 0.005 to 0.589; P=0.016). The primary clinical outcome followed up to the last angiography did not occur in all patients. CONCLUSION: There was no difference in safety and effectiveness between overlapping stents and flow diverters in unruptured VADAs. Further endovascular treatment studies are needed regarding the association of partially thrombosed aneurysms with unfavorable angiographic outcomes.

Temporal Trends of Sex Differences in Acute Reperfusion Therapy and Early Outcomes of Acute Ischemic Stroke in South Korea: 10-Year Analysis of the Nationwide Stroke Registry.

BACKGROUND: Sex differences in stroke outcomes are notable, with women experiencing higher incidence rates, greater disability-adjusted life years, and poorer recovery compared to men, even after adjusting for age and comorbidities. Despite the disproportionate burden in women, studies have reported that women are less likely to receive appropriate stroke treatment than men. AIM: This study investigated temporal trends of sex differences in acute reperfusion therapy and early outcomes in patients with acute ischemic stroke over 10 years in South Korea. METHODS: A retrospective analysis of Korean Stroke Registry included patients with acute ischemic stroke from 2012 to 2021. The study outcomes were the temporal trends of acute reperfusion therapy and early outcomes over 10 years in men and women, respectively. Additionally, this study analyzed the temporal trends of sex differences in these parameters during the same period. Early outcomes include the proportions of favorable functional outcomes at discharge, discharge patterns, and in-hospital mortality. RESULTS: A total of 93,692 patients (68.4 years, 40.1% women) with acute ischemic stroke were finally enrolled. Women had a higher age at stroke onset, a higher prevalence of atrial fibrillation, and more severe strokes than men. Women had lower proportion of favorable functional outcomes at discharge and higher proportion of in-hospital mortality compared to men each year. The proportion of patients who received intravenous thrombolysis was lower or similar in women compared to men in most years, and the proportion of patients who received endovascular thrombectomy did not significantly differ between sexes annually. Sex differences in acute reperfusion therapy remained unchanged over 10 years. CONCLUSION: Women have received acute reperfusion therapy at similar or lower rates than men and experienced poorer outcomes, despite having more stroke risk factors and often more severe strokes.

Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.

Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (EV-miRNAs) to distinguish the following ischemic stroke subtypes: large artery atherosclerosis (LAA), cardioembolic stroke (CES), and small artery occlusion (SAO). Using next-generation sequencing (NGS) and machine-learning techniques, we identified differentially expressed miRNAs (DEMs) associated with each subtype. Through patient selection and diagnostic evaluation, a cohort of 70 patients with acute ischemic stroke was classified: 24 in the LAA group, 24 in the SAO group, and 22 in the CES group. Our findings revealed distinct EV-miRNA profiles among the groups, suggesting their potential as diagnostic markers. Machine-learning models, particularly logistic regression models, exhibited a high diagnostic accuracy of 92% for subtype discrimination. The collective influence of multiple miRNAs was more crucial than that of individual miRNAs. Additionally, bioinformatics analyses have elucidated the functional implications of DEMs in stroke pathophysiology, offering insights into the underlying mechanisms. Despite limitations like sample size constraints and retrospective design, our study underscores the promise of EV-miRNAs coupled with machine learning for ischemic stroke subtype classification. Further investigations are warranted to validate the clinical utility of the identified EV-miRNA biomarkers in stroke patients.

Global intracranial arterial tortuosity is associated with intracranial atherosclerotic burden.

The effect of arterial tortuosity on intracranial atherosclerosis (ICAS) is not well understood. This study aimed to evaluate the effect of global intracranial arterial tortuosity on intracranial atherosclerotic burden in patients with ischemic stroke. We included patients with acute ischemic stroke who underwent magnetic resonance angiography (MRA) and classified them into three groups according to the ICAS burden. Global tortuosity index (GTI) was defined as the standardized mean curvature of the entire intracranial arteries, measured by in-house vessel analysis software. Of the 516 patients included, 274 patients had no ICAS, 140 patients had a low ICAS burden, and 102 patients had a high ICAS burden. GTI increased with higher ICAS burden. After adjustment for age, sex, vascular risk factors, and standardized mean arterial area, GTI was independently associated with ICAS burden (adjusted odds ratio [adjusted OR] 1.33; 95% confidence interval [CI] 1.09-1.62). The degree of association increased when the arterial tortuosity was analyzed limited to the basal arteries (adjusted OR 1.48; 95% CI 1.22-1.81). We demonstrated that GTI is associated with ICAS burden in patients with ischemic stroke, suggesting a role for global arterial tortuosity in ICAS.

Developing a national surveillance system for stroke and acute myocardial infarction using claims data in the Republic of Korea: a retrospective study.

BACKGROUND: Limited information is available concerning the epidemiology of stroke and acute myocardial infarction (AMI) in the Republic of Korea. This study aimed to develop a national surveillance system to monitor the incidence of stroke and AMI using national claims data. METHODS: We developed and validated identification algorithms for stroke and AMI using claims data. This validation involved a 2-stage stratified sampling method with a review of medical records for sampled cases. The weighted positive predictive value (PPV) and negative predictive value (NPV) were calculated based on the sampling structure and the corresponding sampling rates. Incident cases and the incidence rates of stroke and AMI in the Republic of Korea were estimated by applying the algorithms and weighted PPV and NPV to the 2018 National Health Insurance Service claims data. RESULTS: In total, 2,200 cases (1,086 stroke cases and 1,114 AMI cases) were sampled from the 2018 claims database. The sensitivity and specificity of the algorithms were 94.3% and 88.6% for stroke and 97.9% and 90.1% for AMI, respectively. The estimated number of cases, including recurrent events, was 150,837 for stroke and 40,529 for AMI in 2018. The age- and sex-standardized incidence rate for stroke and AMI was 180.2 and 46.1 cases per 100,000 person-years, respectively, in 2018. CONCLUSION: This study demonstrates the feasibility of developing a national surveillance system based on claims data and identification algorithms for stroke and AMI to monitor their incidence rates.

Edoxaban for the treatment of hypercoagulability and cerebral thromboembolism associated with cancer: A randomized clinical trial of biomarker targets.

BACKGROUND: This study aimed compare efficacy of edoxaban and enoxaparin upon biomarkers of hypercoagulability in patients with cancer-related embolic stroke of undetermined source (ESUS). METHODS: In this open-label, randomized, pilot trial, patients with cancer-related ESUS within 30 days of diagnosis were randomly assigned (1:1) to receive edoxaban (60 mg once daily) or enoxaparin (1 mg/kg twice daily) for 90 days. The primary endpoint was interval change of serum D-dimer level between days 0 and 7. The secondary endpoints were microembolic signals detected by transcranial Doppler at 7 and 90 days, the modified Rankin scale score, and stroke recurrence during 90 days. Safety outcomes included major bleeding and all-cause death at 90 days. RESULTS: Of 303 patients with ischemic stroke and cancer, 40 fully met enrollment criteria and were randomized. Baseline D-dimer levels were numerically higher in the edoxaban group (22.9 ± 15.9 µg/mL vs 16.9 ± 16.9 µg/mL). D-dimer level change (%) between days 0 and 7 was similar in the two groups (53.2 ± 25.7 vs 52.2 ± 52.0; P = 0.11). Microembolic signals were detected in 41.1% and 43.8% at baseline, 41.2% and 42.9% at day 7, and 25.0% and 28.6% at day 90 in the edoxaban and enoxaparin groups, respectively. Non-significantly higher major bleeding (35.0% vs 10.0%, P = 0.06) and 90-day mortality (40.0% vs 25.0%, P = 0.31) were noted in the edoxaban group. CONCLUSION: Edoxaban and enoxaparin were comparable with respect to the biomarkers of hypercoagulability and cerebral thromboembolism. Larger trials are warranted to compare effects of edoxaban and enoxaparin upon recurrent stroke and major bleeding in patients with cancer-related ESUS. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT03570281 (https://clinicaltrials.gov/ct2/show/NCT03570281).

Effectiveness of endovascular treatment for in-hospital stroke vs. community-onset stroke: a propensity score-matched analysis.

BACKGROUND: The effectiveness of endovascular treatment for in-hospital stroke remains debatable. We aimed to compare the outcomes between patients with in-hospital stroke and community-onset stroke who received endovascular treatment. METHODS: This prospective registry-based cohort study included consecutive patients who underwent endovascular treatment from January 2013 to December 2022 and were registered in the Selection Criteria in Endovascular Thrombectomy and Thrombolytic Therapy study and Yonsei Stroke Cohort. Functional outcomes at day 90, radiological outcomes, and safety outcomes were compared between the in-hospital and community-onset groups using logistic regression and propensity score-matched analysis. RESULTS: Of 1,219 patients who underwent endovascular treatment, 117 (9.6%) had in-hospital stroke. Patients with in-hospital onset were more likely to have a pre-stroke disability and active cancer than those with community-onset. The interval from the last known well to puncture was shorter in the in-hospital group than in the community-onset group (155 vs. 355 min, p<0.001). No significant differences in successful recanalization or safety outcomes were observed between the groups; however, the in-hospital group exhibited worse functional outcomes and higher mortality at day 90 than the community-onset group (all p<0.05). After propensity score matching including baseline characteristics, functional outcomes after endovascular treatment did not differ between the groups (OR: 1.19, 95% CI 0.78-1.83, p=0.4). Safety outcomes did not significantly differ between the groups. CONCLUSION: Endovascular treatment is a safe and effective treatment for eligible patients with in-hospital stroke. Our results will help physicians in making decisions when planning treatment and counseling caregivers or patients.

Predicting short-term outcomes in atrial-fibrillation-related stroke using machine learning.

Background: Prognostic prediction and the identification of prognostic factors are critical during the early period of atrial-fibrillation (AF)-related strokes as AF is associated with poor outcomes in stroke patients. Methods: Two independent datasets, namely, the Korean Atrial Fibrillation Evaluation Registry in Ischemic Stroke Patients (K-ATTENTION) and the Korea University Stroke Registry (KUSR), were used for internal and external validation, respectively. These datasets include common variables such as demographic, laboratory, and imaging findings during early hospitalization. Outcomes were unfavorable functional status with modified Rankin scores of 3 or higher and mortality at 3 months. We developed two machine learning models, namely, a tree-based model and a multi-layer perceptron (MLP), along with a baseline logistic regression model. The area under the receiver operating characteristic curve (AUROC) was used as the outcome metric. The Shapley additive explanation (SHAP) method was used to evaluate the contributions of variables. Results: Machine learning models outperformed logistic regression in predicting both outcomes. For 3-month unfavorable outcomes, MLP exhibited significantly higher AUROC values of 0.890 and 0.859 in internal and external validation sets, respectively, than those of logistic regression. For 3-month mortality, both machine learning models exhibited significantly higher AUROC values than the logistic regression for internal validation but not for external validation. The most significant predictor for both outcomes was the initial National Institute of Health and Stroke Scale. Conclusion: The explainable machine learning model can reliably predict short-term outcomes and identify high-risk patients with AF-related strokes.

Incidence and risk of stroke in Korean patients with congenital heart disease.

OBJECTIVES: The incidence and risk of ischemic stroke (IS) and hemorrhagic stroke (HS) in Korean patients with CHD have not been reported, therefore, we aimed to investigate this. MATERIALS AND METHODS: Participants were selected from the Korean National Health Insurance Service benefit records from 2006-2017. Cases were extracted using diagnosis codes related to CHD. Controls without CHD were selected through age- and sex-matched random sampling at a 1:10 ratio. RESULTS: The case and control groups included 232,203 and 3,024,633 participants, respectively. The median (interquartile range) follow-up period was 7.28 (3.59-8.73) years. The incidence rates of IS and HS per 100,000 person-years were much higher in cases than in controls (IS: 135 vs. 47; HS: 41.7 vs. 24.9). After adjusting for confounders, CHD was a risk factor for IS and HS (subdistribution HR; 1.96 and 1.71, respectively). In patients with CHD, the following risk factors were identified: diabetes, heart failure, and atrial fibrillation for any stroke; hypertension, atrial septal defects, and use of antiplatelet agents for IS only; and coronary artery bypass graft surgery for HS only. CONCLUSIONS: Korean patients with CHD have a high risk of stroke. A personalized preventive approach is needed to reduce the incidence of stroke in this population.

Imaging and clinical predictors of acute constipation in patients with acute ischemic stroke.

Background: Constipation symptoms are highly prevalent in acute ischemic stroke, but the clinical and neuroimaging predictors are unknown. This study aimed to identify lesions and clinical features associated with acute constipation. Methods: Data from patients with acute ischemic stroke registered in a hospital-based stroke registry between January 2018 and December 2019 were analyzed. Clinical, laboratory, and imaging features were examined for associations with acute constipation. Using the topographic lesion on diffusion-weighted images, multivariate support vector regression-based lesion-symptom mapping (SVR-LSM) was conducted and compared between the non-constipation and acute constipation groups. Results: A total of 256 patients (mean age 67 years, men: 64%) were included. Acute constipation was noted in 81 patients (32%). Initial stroke severity, represented by initial National Institutes of Health and Stroke Scale (NIHSS) scores, was associated with acute constipation. Laboratory parameters, including fibrin degradation products (FDP), fibrinogen, D-dimer, lipoprotein (a), and free fatty acid levels, also showed statistically significant differences between the non-constipation and constipation groups. FDP, D-dimer, and free fatty acid levels were independently associated with acute constipation in the logistic regression model after adjusting for initial NIHSS scores and potassium levels. SVR-LSM revealed that bilateral lesions in the precentral gyrus, insula, opercular part of the inferior frontal gyrus, the inferior parietal lobule, and lesions in the right middle frontal gyrus were significantly associated with acute constipation. The results were consistent after controlling for the initial NIHSS scores and poststroke potassium levels. When cardioembolic stroke subjects were excluded, the right insular and prefrontal cortex lesions lost their association with acute constipation. Conclusion: Acute constipation symptoms after acute ischemic stroke are mainly related to bilateral lesions in the insula, precentral gyrus, postcentral gyrus, and inferior parietal lobule. Clinically important predictors of acute constipation include initial neurological severity and thromboembolic markers of stroke.

Proposed Protocols for Artificial Intelligence Imaging Database in Acute Stroke Imaging.

PURPOSE: To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models. MATERIALS AND METHODS: A nationwide survey on acute stroke imaging protocols was conducted using an electronic questionnaire sent to 43 registered tertiary hospitals between April and May 2021. Imaging protocols for endovascular thrombectomy (EVT) in the early and late time windows and during follow-up were assessed. Clinical applications of AI techniques in stroke imaging and required sequences for developing AI models were reviewed. Standardized and feasible imaging protocols for data curation in acute stroke were proposed. RESULTS: There was considerable heterogeneity in the imaging protocols for EVT candidates in the early and late time windows and posterior circulation stroke. Computed tomography (CT)-based protocols were adopted by 70% (30/43), and acquisition of noncontrast CT, CT angiography and CT perfusion in a single session was most commonly performed (47%, 14/30) with the preference of multiphase (70%, 21/30) over single phase CT angiography. More hospitals performed magnetic resonance imaging (MRI)-based protocols or additional MRI sequences in a late time window and posterior circulation stroke. Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) were most commonly performed MRI sequences with considerable variation in performing other MRI sequences. AI models for diagnostic purposes required noncontrast CT, CT angiography and DWI while FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI) were additionally required for prognostic AI models. CONCLUSION: Given considerable heterogeneity in acute stroke imaging protocols at tertiary hospitals in South Korea, standardized and feasible imaging protocols are required for constructing AI database in acute stroke. The essential sequences may be noncontrast CT, DWI, CT/MR angiography and CT/MR perfusion while FLAIR and T1WI may be additionally required.

D-dimer to fibrinogen ratio predicts early neurological deterioration in ischemic stroke with atrial fibrillation.

INTRODUCTION: The D-dimer to fibrinogen ratio (DFR) is a good indicator of clot-producing activity in thrombotic disease, but its clinical usefulness in stroke patients with nonvalvular atrial fibrillation (NVAF) has not been studied. We evaluated the association between the DFR and early neurological deterioration (END) in acute ischemic stroke (AIS) patients with NVAF. METHODS: We included consecutive AIS patients with NVAF between 2013 and 2015 from the registry of a real-world prospective cohort from 11 large centers in South Korea. END was defined as an increase ≥2 in the total NIHSS score or ≥ 1 in the motor NIHSS score within the first 72 h of admission. The DFR was calculated as follows: DFR = D-dimer (mg/L)/fibrinogen (mg/dL) x 100. RESULTS: A total of 1018 AIS patients with NVAF were evaluated. In multivariable logistic regression analysis, the highest DFR tertile was closely associated with END (adjusted odds ratio [aOR] = 2.14, 95 % confidence interval [CI]: 1.24-3.69). Hypertension (aOR = 1.71, 95 % CI: 1.09-2.70), initial NIHSS score (aOR = 1.05, 95 % CI: 1.02-1.07) and use of anticoagulants (aOR = 0.41, 95 % CI: 0.28-0.60) were also correlated with END. In addition to END, the DFR was correlated with discharge NIHSS and modified Rankin Scale (mRS) scores and the 3-month mRS score. CONCLUSIONS: High DFR values were associated with END in AIS patients with NVAF. As the DFR is an indicator directly related to the main pathological mechanism of NVAF patients (fibrinolysis and coagulation), it may be useful in predicting their prognosis.

Stroke-Specific Predictors of Major Bleeding in Anticoagulated Patients With Stroke and Atrial Fibrillation: A Nationwide Multicenter Registry-Based Study.

BACKGROUND AND PURPOSE: The congestive heart failure, hypertension, age, diabetes, previous stroke/transient ischemic attack (CHA2DS2-VASc) and hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/alcohol (HAS-BLED) scores have been validated in estimating the risks of ischemic stroke and major bleeding, respectively, in patients with atrial fibrillation (AF). This study investigated stroke-specific predictors of major bleeding in patients with stroke and AF who were taking oral anticoagulants (OACs). METHODS: Subjects were selected from patients enrolled in the Korean ATrial fibrillaTion EvaluatioN regisTry in Ischemic strOke patieNts (K-ATTENTION) nationwide multicenter registry between 2013 and 2015. Patients were excluded if they were not taking OACs, had no brain imaging data, or had intracranial bleeding directly related to the index stroke. Major bleeding was defined according to International Society of Thrombosis and Haemostasis criteria. Cox regression analyses were performed to assess the associations between clinical variables and major bleeding and Kaplan-Meier estimates were performed to analyze event-free survival. RESULTS: Of a total of 3,213 patients, 1,414 subjects (mean age of 72.6 years, 52.5% males) were enrolled in this study. Major bleeding was reported in 34 patients during the median follow-up period of 1.73 years. Multivariable analysis demonstrated that initial National Institutes of Health Stroke Scale scores (hazard ratio [HR] 1.07, p=0.006), hypertension (HR 3.18, p=0.030), persistent AF type (HR 2.51, p=0.016), and initial hemoglobin level (HR 0.74, p=0.001) were independently associated with major bleeding risk. Except for hypertension, these associations remained significant after adjusting for the HAS-BLED score. Intracranial atherosclerosis presented a trend of association without statistical significance (HR 2.21, p=0.050). CONCLUSIONS: This study found that major bleeding risk was independently associated with stroke-specific factors in anticoagulated patients with stroke and AF. This has the clinical implication that baseline characteristics of patients with stroke and AF should be considered in secondary prevention, which would bring the net clinical benefit of balancing recurrent stroke prevention with minimal bleeding complications.

Topographical Association Between Left Ventricular Strain and Brain Lesions in Patients With Acute Ischemic Stroke and Normal Cardiac Function.

Background Although it is well known that the disordered brain provokes cardiac autonomic dysfunction, the detailed location of brain lesions related to cardiac function warrants further investigation. We aimed to elucidate the brain lesions topographically associated with left ventricular (LV) systolic function measured by myocardial strain in patients with acute ischemic stroke without preexisting primary cardiac dysfunction by using support vector regression lesion-symptom mapping. Methods and Results Subjects were those with LV ejection fraction of 50% or more among patients with acute ischemic stroke registered in the Samsung Medical Center stroke registry between 2016 and 2017. To evaluate LV systolic performance and contractility, we measured LV ejection fraction and LV global and regional longitudinal strain using 2-dimensional speckle-tracking echocardiography. The association between stroke lesion location and cardiac strain was assessed using support vector regression lesion-symptom mapping. Of a total of 776 patients, 286 subjects (mean age of 67.0 years, 65.4% men) were finally enrolled in this study. The mean global longitudinal strain was -17.0±3.4%, and the mean LV ejection fraction was 64.7±5.7%. The support vector regression lesion-symptom mapping analysis revealed that the right insula and peri-insular regions and left parietal cortex were associated with impaired LV global longitudinal strain in patients with acute ischemic stroke. In addition, impaired regional longitudinal strain showed topographical associations with these regions. Conclusions This study suggests that brain lesions in the right insula and peri-insular regions and left parietal cortex are topographically associated with impaired LV strain in patients with acute ischemic stroke without preexisting cardiac dysfunction.

The effect of intensive statin therapy in non-symptomatic intracranial arteries: The STAMINA-MRI sub-study.

Background and aims: Pleiotropic effects of statins result in the stabilization of symptomatic intracranial arterial plaque. However, little is known about the effect of statins in non-symptomatic cerebral arteries. We hypothesized that intensive statin therapy could produce a change in the non-symptomatic cerebral arteries. Methods: This is a sub-study of a prospective observational study under the title of "Intensive Statin Treatment in Acute Ischemic Stroke Patients with Intracranial Atherosclerosis: a High-Resolution Magnetic Resonance Imaging (HR-MRI) study." Patients with statin-naive acute ischemic stroke who had symptomatic intracranial artery stenosis (above 50%) were recruited for this study. HR-MRI was performed to assess the patients' cerebral arterial status before and 6 months after the statin therapy. To demonstrate the effect of statins in the non-symptomatic segment of intracranial cerebral arteries, we excluded symptomatic segments from the data to be analyzed. We compared the morphological changes using cerebrovascular morphometry. Results: A total of 54 patients (mean age: 62.9 ± 14.4 years, 59.3% women) were included in this study. Intensive statin therapy produced significant morphological changes of overall cerebral arteries. Among the morphological features, the arterial luminal area showed the highest number of significant changes with a range from 5.7 and 6.7%. Systolic blood pressure (SBP) was an independent factor associated with relative changes in posterior circulation bed maximal diameter percentage change (beta -0.21, 95% confidence interval -0.36 to -0.07, p = 0.005). Conclusion: Intensive statin therapy produced a favorable morphological change in cerebral arteries of not only the target arterial segment but also non-symptomatic arterial segments. The change in cerebral arterial luminal diameter was influenced by the baseline SBP and was dependent on the topographic distribution of the cerebral arteries.Clinical Trial Registration: ClinicalTrials.gov, identifier NCT02458755.

Circulating Extracellular-Vesicle-Incorporated MicroRNAs as Potential Biomarkers for Ischemic Stroke in Patients With Cancer.

BACKGROUND AND PURPOSE: This study aimed to evaluate whether extracellular-vesicle-incorporated microRNAs (miRNAs) are potential biomarkers for cancer-related stroke. METHODS: This cohort study compared patients with active cancer who had embolic stroke of unknown sources (cancer-stroke group) with patients with only cancer, patients with only stroke, and healthy individuals (control groups). The expression profiles of miRNAs encapsulated in plasma exosomes and microvesicles were evaluated using microarray and validated using quantitative real-time polymerase chain reaction. The XENO-QTM miRNA assay technology was used to determine the absolute copy numbers of individual miRNAs in an external validation cohort. RESULTS: This study recruited 220 patients, of which 45 had cancer-stroke, 76 were healthy controls, 39 were cancer controls, and 60 were stroke controls. Three miRNAs (miR-205-5p, miR-645, and miR-646) were specifically incorporated into microvesicles in patients with cancer-related stroke, cancer controls, and stroke controls. The area under the receiver operating characteristic curves of these three miRNAs were 0.7692-0.8510 for the differentiation of patients with cancer-stroke from cancer-controls and 0.8077-0.8846 for the differentiation of patients with cancer-stroke from stroke controls. The levels of several miRNAs were elevated in the plasma exosomes of patients with cancer, but were lower than those in plasma microvesicles. An in vivo study showed that systemic injection of miR-205-5p promoted the development of arterial thrombosis and elevation of D-dimer levels. CONCLUSION: Stroke due to cancer-related coagulopathy was associated with deregulated expression of miRNAs, particularly microvesicle-incorporated miR-205-5p, miR-645, and miR-646. Further prospective studies of extracellular-vesicle-incorporated miRNAs are required to confirm the diagnostic role of miRNAs in patients with stroke and to screen the roles of miRNAs in patients with cancer.

Moderate-Intensity Rosuvastatin Plus Ezetimibe Versus High-Intensity Rosuvastatin for Target Low-Density Lipoprotein Cholesterol Goal Achievement in Patients With Recent Ischemic Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Moderate-intensity statin plus ezetimibe versus high-intensity statin alone may provide a greater low-density lipoprotein cholesterol (LDL-C) reduction in patients with recent ischemic stroke. METHODS: This randomized, open-label, controlled trial assigned patients with recent ischemic stroke <90 days to rosuvastatin/ezetimibe 10/10 mg once daily (ROS10/EZT10) or to rosuvastatin 20 mg once daily (ROS20). The primary endpoint was LDL-C reduction ≥50% from baseline at 90 days. Key secondary endpoints were LDL-C <70 mg/dL and multiple lipid goal achievement, and composite of major vascular events. RESULTS: Of 584 randomized, 530 were included in the modified intention-to-treat analysis. The baseline LDL-C level was 130.2±34.7 mg/dL in the ROS10/EZT10 group and 131.0±33.9 mg/dL in the ROS20 group. The primary endpoint was achieved in 198 patients (72.5%) in the ROS10/EZT10 group and 148 (57.6%) in the ROS20 group (odds ratio [95% confidence interval], 1.944 [1.352-2.795]; P= 0.0003). LDL-C level <70 mg/dL was achieved in 80.2% and 65.4% in the ROS10/EZT10 and ROS20 groups (P=0.0001). Multiple lipid goal achievement rate was 71.1% and 53.7% in the ROS10/EZT10 and ROS20 groups (P<0.0001). Major vascular events occurred in 1 patient in the ROS10/EZT10 group and 9 in the ROS20 group (P=0.0091). The adverse event rates did not differ between the two groups. CONCLUSION: Moderate-intensity rosuvastatin plus ezetimibe was superior to high-intensity rosuvastatin alone for intensive LDL-C reduction in patients with recent ischemic stroke. With the combination therapy, more than 70% of patients achieved LDL-C reduction ≥50% and 80% had an LDL-C <70 mg/dL at 90 days.

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used machine learning to examine the anatomical profile of the cerebral arterial tree. The method is less sensitive to inter-subject and cohort-wise anatomical variations and exhibits robust performance with an unprecedented in-depth vessel range. We applied machine learning algorithms to disease-free healthy control subjects (n = 42), patients with stroke with intracranial atherosclerosis (ICAS) (n = 46), and patients with stroke mixed with the existing controls (n = 69). We trained and tested 70% and 30% of each study cohort, respectively, incorporating spatial coordinates and geometric vessel feature vectors. Cerebral arterial images were analyzed based on the 'segmentation-stacking' method using magnetic resonance angiography. We precisely classified the cerebral arteries across the exhaustive scope of vessel components using advanced geometric characterization, redefinition of vessel unit conception, and post-processing algorithms. We verified that the neural network ensemble, with multiple joint models as the combined predictor, classified all vessel component types independent of inter-subject variations in cerebral arterial anatomy. The validity of the categorization performance of the model was tested, considering the control, ICAS, and control-blended stroke cohorts, using the area under the receiver operating characteristic (ROC) curve and precision-recall curve. The classification accuracy rarely fell outside each image's 90-99% scope, independent of cohort-dependent cerebrovascular structural variations. The classification ensemble was calibrated with high overall area rates under the ROC curve of 0.99-1.00 [0.97-1.00] in the test set across various study cohorts. Identifying an all-inclusive range of vessel components across controls, ICAS, and stroke patients, the accuracy rates of the prediction were: internal carotid arteries, 91-100%; middle cerebral arteries, 82-98%; anterior cerebral arteries, 88-100%; posterior cerebral arteries, 87-100%; and collections of superior, anterior inferior, and posterior inferior cerebellar arteries, 90-99% in the chunk-level classification. Using a voting algorithm on the queued classified vessel factors and anatomically post-processing the automatically classified results intensified quantitative prediction performance. We employed stochastic clustering and deep neural network ensembles. Ma-chine intelligence-assisted prediction of vessel structure allowed us to personalize quantitative predictions of various types of cerebral arterial structures, contributing to precise and efficient decisions regarding the cerebrovascular disease.