Correlation of perfusion- and diffusion-weighted MRI with NIHSS score in acute (<6.5 hour) ischemic stroke

Plasma brain-derived tau correlates with cerebral infarct volume

BACKGROUND

A blood-based biomarker that accurately reflects neuronal injury in acute ischemic stroke could be an easily accessible and cost-effective complement to clinical and radiological evaluation. Here, we investigate whether plasma levels of the novel biomarker brain-derived tau (BD-tau) reflect cerebral infarct volumes and whether BD-tau can improve clinical outcome prediction.

METHODS

The present study included 713 consecutive cases from two different hospital-based cohorts, the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS) and SAHLSIS phase 2 (SAHLSIS2). Acute stroke severity was determined by the Scandinavian Stroke Scale converted to the National Institutes of Health stroke scale (NIHSS) in SAHLSIS and by the NIHSS in SAHLSIS2. All participants were assessed for functional outcome 3 months after stroke by the modified Rankin Scale, and 254 participants in SAHLSIS had quantitative neuroimaging available.

FINDINGS

Plasma BD-tau concentrations and cerebral infarct volumes were highly correlated (ρ 0.72, p < 0.001). BD-tau improved the prognostic accuracy of suffering an unfavorable outcome over age and stroke severity in the whole cohort. However, the gain in predictive power was dependent on stroke severity and infarct location. The largest improvement was observed for mild ischemic strokes (NIHSS <5; area under the curve [AUC] = 0.73 for age + NIHSS versus AUC = 0.84 with addition of BD-tau; DeLong p 0.02), posterior circulation stroke (AUC = 0.75 vs. AUC = 0.84; DeLong p 0.06) and more specifically for infarcts in the brainstem/cerebellum (AUC = 0.74 vs. 0.87; DeLong p 0.009).

CONCLUSION

Plasma BD-tau can provide information on the extent of acute neuronal damage in ischemic stroke and adds prognostic value for outcome, especially for mild and posterior circulation strokes.

Mobile stroke units based on rural emergency medical stations for pre-hospital intravenous thrombolysis of stroke in remote areas

OBJECTIVES

To explore a novel model of mobile stroke units (MSUs) integrated with rural emergency medical stations for pre-hospital care of stroke patients in remote areas.

METHODS

We used MSUs + Ambulance mode, where both the MSUs and conventional ambulances are sent to the patient's location. The conventional ambulance coordinates with the MSUs to choose the fastest route to meet and transfer the patient at the point along the way. We collected data from 149 patients from March 2022 to April 2023, including National Institutes of Health Stroke Scale (NIHSS) scores (on admission, 24 hours, day 7), 90-day modified Rankin Scale (mRS) scores, and other clinical variables. We performed propensity score matching (PSM) to balance the potential confounding variables between groups.

RESULTS

We found that the MSUs + Ambulance mode (OR = 12.507, 95% confidence interval [CI] [3.633, 43.061], p < 0.001) and admission NIHSS score (OR = 0.583, 95% CI [0.493, 0.690], p < 0.001) were independent prognostic risk factors for stroke patients. The MSUs + Ambulance mode reduced NIHSS scores 7 days prior to admission (OR = 0.679, 95% CI [0.563, 0.819], p < 0.001). After PSM, patients who received MSUs + Ambulance mode had a better prognosis (χ2 = 9.573, p = 0.004), as well as a lower mRS score at 90 days (Z = -3.371, p = 0.001).

CONCLUSIONS

MSUs integrated with rural emergency medical stations show the feasibility and potential benefits of pre-hospital intravenous thrombolysis for stroke patients in geographically distant regions.

Survival implications of postoperative restricted diffusion in high-grade glioma and limitations of intraoperative MRI detection

PURPOSE

Here we assess whether the volume of cerebral ischemia induced during glioma surgery may negatively impact survival independently of neurological function. We also evaluate the sensitivity of intraoperative MRI (iMRI) in detecting cerebral ischemia during surgery.

METHODS

We retrospectively reviewed 361 cranial surgeries that used a 3 Tesla iMRI. 165 patients met all inclusion criteria and were included in the final analysis. Diffusion weighted imaging (DWI) obtained during iMRI was compared to postoperative DWI obtained within 7 days of the operation in cases where no further resection occurred after the iMRI.

RESULTS

42 of 165 patients (25%) showed at least some evidence of restricted diffusion on postoperative (poMRI). 37 of these 42 (88%) cases lacked evidence of restricted diffusion on iMRI, meaning iMRI had a false-negative rate of 88% and a sensitivity of 12% in assessing the extent of ischemic brain after surgery. In high-grade gliomas, the volume of restricted diffusion on poMRI was predictive of overall survival, independent of new functional deficits acquired during surgery (p = 0.011).

CONCLUSION

This study presents the largest case series to date analyzing the sensitivity of iMRI in detecting surgical ischemia. In high-grade gliomas, increased volume of ischemia correlated with worsening median overall survival (OS) irrespective of postoperative neurologic deficits. Future work will focus on improving intraoperative detection of ischemia during the hyperacute phase when interventions such as blood pressure modulation or direct application of vasodilator agents may be effective.

Correlation between DWI-ASPECTS Score, Ischemic Stroke Volume on DWI, Clinical Severity and Short-Term Prognosis: A Single-Center Study

Ischemic stroke is a significant public health concern, with its incidence expected to double over the next 40 years, particularly among individuals over 75 years old. Previous studies, such as the DAWN trial, have highlighted the importance of correlating clinical severity with ischemic stroke volume to optimize patient management. Our study aimed to correlate the clinical severity of ischemic stroke, as assessed by the NIHSS score, with ischemic stroke volume measured using DWI, and short-term prognosis quantified by the mRS score at discharge. Conducted at the largest hospital in Gorj County from January 2023 to December 2023, this study enrolled 43 consecutive patients with acute ischemic stroke. In our patient cohort, we observed a strong positive correlation between NIHSS score and ischemic stroke volume (Spearman correlation coefficient = 0.982, p < 0.01), and a strong negative correlation between ASPECTS-DWI score and mRS score (Spearman correlation coefficient = -0.952, p < 0.01). Multiple linear regression analysis revealed a significant collective relationship between ASPECTS score, ischemic stroke volume, and NIHSS score (F(1, 41) = 600.28, p < 0.001, R2 = 0.94, R2adj = 0.93). These findings underscore the importance of DWI in assessing ischemic stroke severity and prognosis, warranting further investigation for its integration into clinical practice.

A Study to Estimate the Red Cell Width Distribution and the Mean Platelet Volume in Predicting the 30-Day Mortality in Acute Ischemic Stroke Patients

Background Acute ischemic stroke, a clinical disorder caused by nontraumatic cerebrovascular disease, has an acute onset, frequently causes neurological deficit, and may persist for >24 hours or can be fatal in <24 hours. This study aimed to assess the red cell width distribution (RDW) and the mean platelet volume (MPV) in predicting 30-day mortality in acute ischemic stroke patients. In general, patients with acute ischemic stroke have a rather high mortality rate in the first 30 days due to various complications, but post the 30-day mark, the prognosis is comparatively better. Material and methods The present study was conducted on patients with a confirmed diagnosis of acute ischemic stroke based on history, physical examination, CT scan, and/or diffusion-weighted MRI scan performed during the first 24 hours. It was a prospective and cross-sectional study done at Saveetha Medical College over a period of two years. The data was collected by using the intra-hospital network and was analyzed using the IBM SPSS Statistics for Windows, Version 20 (Released 2011; IBM Corp., Armonk, New York, United States). Results In the present study, among 100 patients, the mean age was 57.4 ± 13.36 years. About 55% of our subjects were males in our study. The RDW on the 1stday was 14.17 ± 0.708, and it reduced drastically on the 30thday to1st 13.55 ± 1.11, and it was statically significant (p = 0.000). The MPV on day 1 was 11.11 ± 0.969 and, on day 30, was 10.82 ± 0.90; the MPV was reduced considerably on day 30, which was statistically significant (p = 0.000). RDW on the 1st day was significantly correlated with the MPV and the volume of stroke. The correlation was significant at the 0.01 level (two-tailed). On the 30th day of acute ischemic stroke patients, the red blood cell (RBC) width was significantly correlated with the MPV. The correlation was significant at the 0.01 level (two-tailed). At the end of 30 days, 10% mortality was observed in the present study. Day 30 saw a significant decrease in the MPV and RDW, particularly in the moderate to severe and severe categories. The National Institutes of Health Stroke Scale (NIHSS) score and the volume of stroke were significantly associated with the 30-day outcome.  Conclusion The RDW and the MPV are well correlated in predicting the 30-day mortality in acute ischemic stroke patients. This could potentially be used as a significant marker for predicting mortality in stroke patients in the future, but to increase the generalization, further studies need to be carried out at other demographically distinct medical centers.

Learning ADC maps from accelerated radial k-space diffusion-weighted MRI in mice using a deep CNN-transformer model

PURPOSE

To accelerate radially sampled diffusion weighted spin-echo (Rad-DW-SE) acquisition method for generating high quality ADC maps.

METHODS

A deep learning method was developed to generate accurate ADC maps from accelerated DWI data acquired with the Rad-DW-SE method. The deep learning method integrates convolutional neural networks (CNNs) with vision transformers to generate high quality ADC maps from accelerated DWI data, regularized by a monoexponential ADC model fitting term. A model was trained on DWI data of 147 mice and evaluated on DWI data of 36 mice, with acceleration factors of 4× and 8× compared to the original acquisition parameters.

RESULTS

Ablation studies and experimental results have demonstrated that the proposed deep learning model generates higher quality ADC maps from accelerated DWI data than alternative deep learning methods under comparison when their performance is quantified in whole images as well as in regions of interest, including tumors, kidneys, and muscles.

CONCLUSIONS

The deep learning method with integrated CNNs and transformers provides an effective means to accurately compute ADC maps from accelerated DWI data acquired with the Rad-DW-SE method.

Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP)

OBJECTIVES

To investigate whether utilizing a convolutional neural network (CNN)-based arterial input function (AIF) improves the volumetric estimation of core and penumbra in association with clinical measures in stroke patients.

METHODS

The study included 160 acute ischemic stroke patients (male = 87, female = 73, median age = 73 years) with approval from the institutional review board. The patients had undergone CTP imaging, NIHSS and ASPECTS grading. convolutional neural network (CNN) model was trained to fit a raw AIF curve to a gamma variate function. CNN AIF was utilized to estimate the core and penumbra volumes which were further validated with clinical scores.

RESULTS

Penumbra estimated by CNN AIF correlated positively with the NIHSS score (r = 0.69; p < 0.001) and negatively with the ASPECTS (r =  - 0.43; p < 0.001). The CNN AIF estimated penumbra and core volume matching the patient symptoms, typically in patients with higher NIHSS (> 20) and lower ASPECT score (< 5). In group analysis, the median CBF < 20%, CBF < 30%, rCBF < 38%, Tmax > 10 s, Tmax > 10 s volumes were statistically significantly higher (p < .05).

CONCLUSIONS

With inclusion of the CNN AIF in perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.

CRITICAL RELEVANCE STATEMENT

With CNN AIF perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.

Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network

Purpose

The interpretation of image data plays a critical role during acute brain stroke diagnosis, and promptly defining the requirement of a surgical intervention will drastically impact the patient's outcome. However, determining stroke lesions purely from images can be a daunting task. Many studies proposed automatic segmentation methods for brain stroke lesions from medical images in different modalities, though heretofore results do not satisfy the requirements to be clinically reliable. We investigate the segmentation of brain stroke lesions using a geometric deep learning model that takes advantage of the intrinsic interconnected diffusion features in a set of multi-modal inputs consisting of computer tomography (CT) perfusion parameters.

Approach

We propose a geometric deep learning model for the segmentation of ischemic stroke brain lesions that employs spline convolutions and unpooling/pooling operators on graphs to excerpt graph-structured features in a fully convolutional network architecture. In addition, we seek to understand the underlying principles governing the different components of our model. Accordingly, we structure the experiments in two parts: an evaluation of different architecture hyperparameters and a comparison with state-of-the-art methods.

Results

The ablation study shows that deeper layers obtain a higher Dice coefficient score (DCS) of up to 0.3654. Comparing different pooling and unpooling methods shows that the best performing unpooling method is the proportional approach, yet it often smooths the segmentation border. Unpooling achieves segmentation results more adapted to the lesion boundary corroborated with systematic lower values of Hausdorff distance. The model performs at the level of state-of-the-art models without optimized training methods, such as augmentation or patches, with a DCS of 0.4553 ± 0.0031 .

Conclusions

We proposed and evaluated an end-to-end trainable fully convolutional graph network architecture using spline convolutional layers for the ischemic stroke lesion prediction. We propose a model that employs graph-based operations to predict acute stroke brain lesions from CT perfusion parameters. Our results prove the feasibility of using geometric deep learning to solve segmentation problems, and our model shows a better performance than other models evaluated. The proposed model achieves improved metric values for the DCS metric, ranging from 8.61% to 69.05%, compared with other models trained under the same conditions. Next, we compare different pooling and unpooling operations in relation to their segmentation results, and we show that the model can produce segmentation outputs that adapt to irregular segmentation boundaries when using simple heuristic unpooling operations.

Crossed Cerebellar Diaschisis Worsens the Clinical Presentation in Acute Large Vessel Occlusion

INTRODUCTION

Initial NIHSS in anterior large vessel occlusion (LVO) correlates partially with the hypoperfusion volume. We aimed at assessing the contribution of crossed cerebellar diaschisis (CCD) from the hypoperfused territory on LVO initial clinical deficit.

METHODS

CCD was retrospectively identified by brain CT perfusion imaging (CTP) in patients with anterior LVO treated by mechanical thrombectomy from January 2017 to July 2021. CCD was defined by CTP parameter alteration in the contralateral cerebellar hemisphere to the LVO. NIHSS, clinical/perfusion variables, and CCD were included in regression models to assess their interrelationships.

RESULTS

206 patients were included. CCD was present in 90 patients (69%). NIHSS scores were higher on admission and at stroke discharge among patients with CCD (17.90 ± 6.1 vs. 11.4 ± 8.4, p < 0.001; 9.6 ± 7.7 vs. 6.6 ± 7.9, p = 0.049; respectively). Patients with a CCD had higher stroke volumes (118.2 ± 60.3 vs. 69.3 ± 59.7, p < 0.001) and lower rate of known atrial fibrillation (22% vs. 41%, p = 0.021). On multivariable logistic regression, CCD independently worsened the initial NIHSS (OR 4.85 [2.37-7.33]; p < 0.001).

CONCLUSION

CCD is found in 69% of LVO on admission CTP, correlates with stroke volumes, and independently worsens initial NIHSS.

The Impact of Cortical Cerebral Microinfarcts on Functional Outcomes in Patients With Ischemic Stroke

The present study examined cortical cerebral microinfarcts (CMIs) on a 3T magnetic resonance imaging and investigated the impact of CMIs on the comprehensive functional outcomes during the post-stroke rehabilitation period. Patients with acute phase of first-ever ischemic stroke were retrospectively recruited (n = 62) and divided into 2 groups with and without CMIs. Clinical parameters including age, sex, stroke lesion laterality, location, the National Institutes of Health Stroke Scale score, as well as history of hypertension, dyslipidemia, diabetes mellitus, and smoking were obtained. Functional outcomes were assessed twice at baseline and one month later with the Korean version of the Mini-Mental State Examination, the Berg balance scale (BBS), and the functional independence measure. Partial correlation and multiple linear regression analyses were used to examine the relationship between the presence of CMIs and the change in functional outcomes. At least one CMI was reported in 27 patients, who were older (p = 0.043). The presence of CMIs was significantly associated with functional impairment in all 3 functional outcomes, after controlling for confounding factors (p < 0.05). CMIs might contribute to poor functional outcomes during the post-stroke rehabilitation period. These results suggest that CMIs should be considered when establishing rehabilitation treatment strategies or making a prognosis.

The Effect of Oleoylethanolamide (OEA) Add-On Treatment on Inflammatory, Oxidative Stress, Lipid, and Biochemical Parameters in the Acute Ischemic Stroke Patients: Randomized Double-Blind Placebo-Controlled Study

Methods

Sixty patients with a mean age of 68.60 ± 2.10 comprising 29 females (48.33%), who were admitted to an academic tertiary care facility within the first 12 hours poststroke symptoms onset or last known well (LKW), in case symptom onset time is not clear, were included in this study. AIS was confirmed based on a noncontrast head CT scan and also neurological symptoms. Patients were randomly and blindly assigned to OEA of 300 mg/day (n = 20) or 600 mg/day (n = 20) or placebo (n = 20) in addition to the standard AIS treatment for three days. A blood sample was drawn at 12 hours from symptoms onset or LKW as the baseline followed by the second blood sample at 72 hours post symptoms onset or LKW. Blood samples were assessed for inflammatory and biochemical parameters, oxidative stress (OS) biomarkers, and lipid profile.

Results

Compared to the baseline, there is a significant reduction in the urea, creatinine, triglyceride, high-density lipoprotein, cholesterol, alanine transaminase, total antioxidant capacity, malondialdehyde (MDA), total thiol groups (TTG), interleukin-6 (IL-6), and C-reactive protein levels on the follow-up blood testing in the OEA (300 mg/day) group. In patients receiving OEA (600 mg/day) treatment, there was only a significant reduction in the MDA level comparing baseline with follow-up blood testing. Also, the between-group analysis revealed a statistically significant difference between patients receiving OEA (300 mg/day) and placebo in terms of IL-6 and TTG level reduction when comparing them between baseline and follow-up blood testing.

Conclusion

OEA in moderate dosage, 300 mg/day, add-on to the standard stroke treatment improves short-term inflammatory, OS, lipid, and biochemical parameters in patients with AIS. This effect might lead to a better long-term neurological prognosis.

Predicting the Severity of Neurological Impairment Caused by Ischemic Stroke Using Deep Learning Based on Diffusion-Weighted Images

Purpose: To develop a preliminary deep learning model that uses diffusion-weighted imaging (DWI) images to classify the severity of neurological impairment caused by ischemic stroke. Materials and Methods: This retrospective study included 851 ischemic stroke patients (711 patients in the training set and 140 patients in the test set). The patients’ NIHSS scores, which reflect the severity of neurological impairment, were reviewed upon admission and on Day 7 of hospitalization and were classified into two stages (stage 1 for NIHSS < 5 and stage 2 for NIHSS ≥ 5). A 3D-CNN was trained to predict the stage of NIHSS based on different preprocessed DWI images. The performance in predicting the severity of anterior and posterior circulation stroke was also investigated. The AUC, specificity, and sensitivity were calculated to evaluate the performance of the model. Results: Our proposed model obtained better performance in predicting the NIHSS stage on Day 7 of hospitalization than that at admission (best AUC 0.895 vs. 0.846). Model D trained with DWI images (normalized with z-score and resized to 256 × 256 × 64 voxels) achieved the best AUC of 0.846 in predicting the NIHSS stage at admission. Model E rained with DWI images (normalized with maximum−minimum and resized to 128 × 128 × 32 voxels) achieved the best AUC of 0.895 in predicting the NIHSS stage on Day 7 of hospitalization. Our model also showed promising performance in predicting the NIHSS stage on Day 7 of hospitalization for anterior and posterior circulation stroke, with the best AUCs of 0.905 and 0.903, respectively. Conclusions: Our proposed 3D-CNN model can effectively predict the neurological severity of IS using DWI images and performs better in predicting the NIHSS stage on Day 7 of hospitalization. The model also obtained promising performance in subgroup analysis, which can potentially help clinical decision making.

DNA Methylation and Ischemic Stroke Risk: An Epigenome-Wide Association Study

BACKGROUND

Ischemic stroke (IS) risk heritability is partly explained by genetics. Other heritable factors, such as epigenetics, could explain an unknown proportion of the IS risk. The objective of this study is to evaluate DNA methylation association with IS using epigenome-wide association studies (EWAS).

METHODS

 We performed a two-stage EWAS comprising 1,156 subjects. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) were assessed using the Infinium 450K and EPIC BeadChip in the discovery cohort (252 IS and 43 controls). Significant DMPs were replicated in an independent cohort (618 IS and 243 controls). Stroke subtype associations were also evaluated. Differentially methylated cell-type (DMCT) was analyzed in the replicated CpG sites using EpiDISH. We additionally performed pathway enrichment analysis and causality analysis with Mendelian randomization for the replicated CpG sites.

RESULTS

 A total of 957 CpG sites were epigenome-wide-significant (p ≤ 10^-7) in the discovery cohort, being CpG sites in the top signals (logFC = 0.058, p = 2.35 × 10^-22; logFC = 0.035, p = 3.22 × 10^-22, respectively). ZFHX3 and MAP3K1 were among the most significant DMRs. In addition, 697 CpG sites were replicated considering Bonferroni-corrected p-values (p < 5.22 × 10^-5). All the replicated DMPs were associated with risk of cardioembolic, atherothrombotic, and undetermined stroke. The DMCT analysis demonstrated that the significant associations were driven by natural killer cells. The pathway enrichment analysis showed overrepresentation of genes belonging to certain pathways including oxidative stress. ZFHX3 and MAP3K1 methylation was causally associated with specific stroke-subtype risk.

CONCLUSION

 Specific DNA methylation pattern is causally associated with IS risk. These results could be useful for specifically predicting stroke occurrence and could potentially be evaluated as therapeutic targets.

Predictive Factors of Acute Symptomatic Seizures in Patients With Ischemic Stroke Due to Large Vessel Occlusion

Introduction

Acute symptomatic seizures (ASz) after ischemic stroke are associated with increased mortality; therefore, identifying predictors of ASz is important. The purpose of this study was to analyze predictors of ASz in a population of patients with ischemic stroke due to large arterial vessel occlusion (LVO).

Materials and Methods

This retrospective study examined patients with acute ischemic stroke caused by LVO between 2016 and 2020. Identification of predictive factors was performed using univariate and subsequent multiple logistic regression analysis. In addition, subgroup analysis regarding seizure semiology and time of seizure occurrence (≤ 24 h and > 24 h after stroke) was performed.

Results

The frequency of ASz among 979 patients was 3.9 % (n = 38). Univariate logistic regression analysis revealed an increased risk of ASz in patients with higher National Institutes of Health Stroke Scale (NIHSS) score at admission or 24 h after admission, hypernatremia at admission ≥ 145 mmol/L, and pneumonia. Further multiple logistic regression analysis revealed that NIHSS 24 h after admission was the strongest predictor of ASz, particularly relating to ASz occurring later than 24 h after stroke. Patients who experienced a seizure within the first 24 h after stroke were more likely to have a generalized tonic-clonic (GTCS) and focal motor seizure; beyond 24 h, seizures with impaired awareness and non-convulsive status epilepticus were more frequent.

Conclusion

NIHSS score 24 h after admission is a strong predictive factor for the occurrence of ASz in patients with ischemic stroke caused by LVO. The semiology of ASz varied over time, with GTCS occurring more frequently in the first 24 h after stroke.

Predictive Value of Globulin to Prealbumin Ratio for 3-Month Functional Outcomes in Acute Ischemic Stroke Patients

Objective

We aimed to evaluate and compare the association between globulin to albumin ratio (GAR) and globulin to prealbumin ratio (GPR) and 3-month functional prognosis of acute ischemic stroke (AIS) patients receiving intravenous thrombolysis therapy.

Methods

234 AIS patients undergoing intravenous thrombolysis were retrospectively enrolled with acute ischemic stroke from February 2016 to October 2019. Blood sample was collected within 24 h after admission. Poor outcome was defined as the modified Rankin Scale (mRS) ≥ 3 and a favorable outcome as mRS < 3. Severe stroke was defined as the National Institutes of Health Stroke Scale (NIHSS) score > 10 on admission. Student's t-test, Mann–Whitney U test, Chi-square test, logistics' regression analysis, and receiver operating characteristic (ROC) analysis were performed.

Results

Patients with poor functional outcome had higher GAR and GPR levels compared with favorable functional group (p = 0.001, p < 0.001, respectively). Severe stroke was also associated with these two increasing variables. After adjustment for confounding factors, multivariate logistic regression analysis indicated that GPR was an independent indicator predictor of AIS.

Conclusions

The 24 h GPR level can predict the 3-month functional outcome in AIS patients accepting recombinant tissue plasminogen activator (r-tPA) intravenous thrombosis.

Primer reporte de inmaduros de Cryptocephalus Geoffroy, 1762 (Coleoptera: Chrysomelidae) de Brasil con notas de su bioecología sobre Wedelia goyazensis Gardner (Asteraceae) y síntesis de los registros de presencia del género en territorio brasileño

Cryptocephalus Geoffroy, 1762 es reconocido por su distribución cosmopolita y gran riqueza, con al menos 1700 especies descritas. Sin embargo, falta información para Brasil: (1) no hay registro de inmaduros; y (2) no se conoce casi nada sobre la biología de este género. En este trabajo se documentan por primera vez las etapas inmaduras de Cryptocephalus de Brasil y se presentan algunas notas sobre su bioecología en la planta huésped. Además, se recopilan sus registros en territorio brasileño a partir de la bibliografía.

Association of serum growth differentiation factor-15 levels with the risks of death and vascular events in patients with ischemic stroke: The role of diabetes

BACKGROUND AND AIMS

Researchers have not determined whether the association between growth differentiation factor-15 (GDF-15) levels and stroke outcomes is modified by the diabetes status. We aimed to evaluate the prognostic value of GDF-15 among patients with ischemic stroke stratified by diabetes.

METHODS AND RESULTS

A total of 3001 patients with ischemic stroke were selected from the China Antihypertensive Trial in Acute Ischemic Stroke (CATIS) and included in this study. The primary outcome was a composite outcome of death and vascular events at 3 months after acute ischemic stroke. An elevated GDF-15 level was significantly associated with the primary outcome in patients with diabetes but not in those without diabetes (p_interaction = 0.038). The multivariate-adjusted hazard ratio (95% confidence intervals) for the primary outcome was 3.33 (1.07-10.35) when 2 extreme tertiles were compared, and a linear association between GDF-15 levels and the primary outcome was observed in patients with diabetes (p for linearity = 0.046). The addition of serum GDF-15 to conventional risk factors improved the risk prediction for the primary outcome in patients with diabetes (net reclassification improvement: 31.98%, p = 0.043; integrated discrimination index: 0.85%, p = 0.034) but not in those without diabetes.

CONCLUSIONS

A modifying effect of the diabetes status on the association between serum GDF-15 levels and ischemic stroke prognosis was observed. Elevated serum GDF-15 levels were associated with the primary outcome within 3 months after ischemic stroke in patients with diabetes, suggesting that GDF-15 may be an important prognostic factor for ischemic stroke in patients with diabetes.

Acute Ischemic Stroke, Depressed Left Ventricular Ejection Fraction, and Sinus Rhythm: Prevalence and Practice Patterns

BACKGROUND

There are limited data about the epidemiology and secondary stroke prevention strategies used for patients with depressed left ventricular ejection fraction (LVEF) and sinus rhythm following an acute ischemic stroke (AIS). We sought to describe the prevalence of LVEF ≤40% and sinus rhythm among patients with AIS and antithrombotic treatment practice in a multi-center cohort from 2002 to 2018.

METHODS

This was a multi-center, retrospective cohort study comprised of patients with AIS hospitalized in the Greater Cincinnati Northern Kentucky Stroke Study and 4 academic, hospital-based cohorts in the United States. A 1-stage meta-analysis of proportions was undertaken to calculate a pooled prevalence. Univariate analyses and an adjusted multivariable logistic regression model were performed to identify demographic, clinical, and echocardiographic characteristics associated with being prescribed an anticoagulant upon AIS hospitalization discharge.

RESULTS

Among 14 338 patients with AIS with documented LVEF during the stroke hospitalization, the weighted pooled prevalence of LVEF ≤40% and sinus rhythm was 5.0% (95% CI, 4.1-6.0%; I², 84.4%). Of 524 patients with no cardiac thrombus and no prior indication for anticoagulant who survived postdischarge, 200 (38%) were discharged on anticoagulant, 289 (55%) were discharged on antiplatelet therapy only, and 35 (7%) on neither. There was heterogeneity by site in the proportion discharged with an anticoagulant (22% to 45%, P<0.0001). Cohort site and National Institutes of Health Stroke Severity scale >8 (odds ratio, 2.0 [95% CI, 1.1-3.8]) were significant, independent predictors of being discharged with an anticoagulant in an adjusted analysis.

CONCLUSIONS

Nearly 5% of patients with AIS have a depressed LVEF and are in sinus rhythm. There is significant variation in the clinical practice of antithrombotic therapy prescription by site and stroke severity. Given this clinical equipoise, further study is needed to define optimal antithrombotic treatment regimens for secondary stroke prevention in this patient population.

A Fully Convolutional Network (FCN) based Automated Ischemic Stroke Segment Method using Chemical Exchange Saturation Transfer Imaging

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration. However, the accurate segmentation of pH-altered regions remains difficult due to the complicated sources in water signal changes of CEST MRI. Meanwhile, manual localization and quantification of stroke lesions are laborious and time-consuming, which cannot meet the urgent need for timely therapeutic interventions.

PURPOSE

The goal of this study was to develop an automatic lesion segmentation approach of ischemic region based on CEST MR images. A novel segmentation framework based on fully convolutional neural network was investigated for our task.

METHODS

Z-spectra from 10 rats were manually labeled as ground truth and split into two datasets, where the training dataset including 3 rats was used to generate a segmentation model, and the remaining rats were used as test datasets to evaluate the model's performance. Then a 1-D fully convolutional neural network equipped with bottleneck structures was set up, and a Grad-CAM approach was used to produce a coarse localization map, which can reflect the relevancy to the 'ischemia' class of each pixel.

RESULTS

As compared with the ground truth, the proposed network model achieved satisfying segmentation results with high values of evaluation metrics including specificity (SPE), sensitivity (SEN), accuracy (ACC), and Dice similarity coefficient (DSC), especially in some intractable situations where conventional MRI modalities and CEST quantitative method failed to distinguish between ischemic and normal tissues, and the model with augmentation was robust to input perturbations. The Grad-CAM maps performed clear tissue change distributions and interpreted the segmentations, and showed a strong correlation with the quantitative method, gave extended thinking to the function of networks.

CONCLUSIONS

The proposed method can segment ischemia region from CEST images, with the Grad-CAM maps give access to interpretative information about the segmentations, which demonstrates great potential in clinical routines. This article is protected by copyright. All rights reserved.

The Clinical Significance of the Hyperintense Acute Reperfusion Marker Sign in Subacute Infarction Patients

Purpose: The hyperintense acute reperfusion marker (HARM) is characterized by the delayed enhancement of the subarachnoid or subpial space observed on postcontrast fluid-attenuated inversion recovery (FLAIR) images, and is considered a cerebral reperfusion marker for various brain disorders, including infarction. In this study, we evaluated the cerebral distribution patterns of HARM for discriminating between an enhancing subacute infarction and an enhancing mass located in the cortex and subcortical white matter. Materials and methods: We analyzed consecutive patients who experienced a subacute ischemic stroke, were hospitalized, and underwent conventional brain magnetic resonance imaging including postcontrast FLAIR within 14 days from symptom onset, as well as those who had lesions corresponding to a clinical sign detected by diffusion-weighted imaging and postcontrast T1-weighted imaging between May 2019 and May 2021. A total of 199 patients were included in the study. Of them, 94 were finally included in the subacute infarction group. During the same period, 76 enhancing masses located in the cortex or subcortical white matter, which were subcategorized as metastasis, malignant glioma, and lymphoma, were analyzed. We analyzed the overall incidence of HARM in subacute ischemic stroke cases, and compared the enhancement patterns between cortical infarctions and cortical masses. Results: Among 94 patients with subacute stroke, 78 patients (83%) presented HARM, and among 76 patients with subcortical masses, 48 patients (63%) presented peripheral rim enhancement. Of 170 subcortical enhancing lesions, 88 (51.8%) showed HARM, and 78 (88.6%) were determined to be subacute infarction. Among 94 patients with subacute stroke, 48 patients (51%) had diffusion restrictions, and HARM was found in 39 patients (81.2%). Of the 46 patients (49%) without diffusion restriction, 39 patients (84.8%) showed HARM. Conclusions: The presence of HARM was significantly associated with subacute infarctions. For the masses, a peripheral rim enhancement pattern was observed around the mass rather than the cerebral sulci on postcontrast FLAIR.

Reduced Cerebral Blood Flow in Benign Oligemia Relates to Poor Clinical Outcome in Acute Ischemic Stroke Patients

The imaging of cerebral blow flow (CBF) has shown great promise in predicting the tissue outcome or functional outcome of acute ischemic stroke patients. Arterial spin labeling (ASL) provides a noninvasive tool for quantitative CBF measurement and does not require a contrast agent, which makes it an attractive technology for perfusion imaging in clinical settings. Previous studies have shown the feasibility of using ASL for acute stroke imaging and its potential in stroke outcome prediction. However, the relationship between the tissue-level CBF reduction in hypoperfused region and clinical outcome in acute stroke patients remains not well understood. In this study, we obtained the quantitative measurements of CBF in acute ischemic stroke patients (N = 18) using pseudocontinuous ASL (pCASL) perfusion imaging technology. The tissue-level CBF changes were evaluated and their correlations with patient clinical outcome were explored. Our results showed different CBF values between hypoperfused tissues recruited into infarction and those that survived. Moreover, a significant correlation was found specifically between the CBF reduction in benign oligemia area and patient neurological deficit severity. These findings showed the validity of pCASL perfusion imaging in the assessment of tissue-level CBF information in acute stroke. The association of CBF with patient clinical outcome might provide useful insights in early diagnosis of acute stroke patients.

Preconditioning by Preceding Ischemic Cerebrovascular Events

Background Emerging yet contrasting evidence from animal and human studies associates ischemic preconditioning with improvement of subsequent stroke severity, although long-term outcome remains unclear. The purpose of this study was to analyze how preceding cerebral ischemic events influence subsequent stroke severity and outcome. Methods and Results Data for this retrospective cohort study were extracted from ASTRAL (Acute Stroke Registry and Analysis of Lausanne). This registry includes a sample of all consecutive patients with acute ischemic strokes admitted to the stroke unit and/or intensive care unit of the Lausanne University Hospital, Switzerland. We investigated associations between preceding ischemic events (transient ischemic attacks or ischemic strokes) and the impact on subsequent stroke severity and clinical improvement within 24 hours, measured through National Institute of Health Stroke Scale, as well as 3-month outcome, determined through a shift in the modified Rankin Scale. Of 3530 consecutive patients with ischemic stroke (43% women, median age 73 years), 1001 (28%) had ≥1 preceding cerebral ischemic events (45% transient ischemic attack, 55% ischemic stroke; 31% multiple events). After adjusting for multiple prehospital, clinical, and laboratory confounders, admission stroke severity was significantly lower in patients preconditioned through a preceding ischemic event, but 24-hour improvement was not significant and 3-month outcome was unfavorable. Conclusions Preceding ischemic events were independently associated with a significant reduction in subsequent stroke severity but worsened long-term clinical outcome. These results, if confirmed by future randomized studies, may help design neuroprotective strategies. The unfavorable effect on stroke outcome is probably a consequence of the cumulative disability burden after multiple ischemic events.

Brain magnetic resonance imaging lesion load at diagnosis, severity at onset and outcomes in Susac syndrome: A prospective cohort study

BACKGROUND

Susac syndrome (SuS) is a rare occlusive microvessel disease of the brain, retina and inner ear. We aimed to determine whether brain lesion load at the acute phase predicts poor outcomes in SuS.

METHODS

A prospective national cohort study was conducted from December 2012 to December 2019 in 20 centres in France. Patients included at the principal investigator's center with available brain magnetic resonance imaging (MRI) at diagnosis were analyzed. MRI was reviewed by an experienced neuroradiologist blinded to clinical status. The size, topography and number of hyperintense lesions on diffusion-weighted imaging (DWI-HL) were analyzed at diagnosis and during follow-up. Outcomes involved descriptive characteristics of patients at onset and last follow-up.

RESULTS

Twenty-three patients (38.1 [18.8-56.5] years, 16 females) were prospectively studied. The triad (i.e., brain, eye and ear involvement) was complete at onset in 17 patients. Brain MRI was performed 1.1 (0.1-3.4) months after the first symptom. All patients had DWI-HL at the acute phase. Patients were separated into two groups according to the number of DWI-HL on first MRI: a first group of patients (n=15) displaying low brain lesion load (<50 DWI-HL per patient) and a second group of patients (n=8) displaying high brain lesion load (≥100 DWI-HL). The median follow-up was 57.9 (9.7-98) months. Clinical features, treatment, relapse rate, time to disappearance of DWI-HL, disabilities and professional outcome did not differ according to brain lesion load.

CONCLUSION

Brain lesion load assessed by DWI at the acute phase is not associated with risks of disability in SuS.

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.

A Clinical-Radiomics Nomogram for Functional Outcome Predictions in Ischemic Stroke

INTRODUCTION

Stroke remains a leading cause of death and disability worldwide. Effective and prompt prognostic evaluation is vital for determining the appropriate management strategy. Radiomics is an emerging noninvasive method used to identify the quantitative imaging indicators for predicting important clinical outcomes. This study was conducted to investigate and validate a radiomics nomogram for predicting ischemic stroke prognosis using the modified Rankin scale (mRS).

METHODS

A total of 598 consecutive patients with subacute infarction confirmed by diffusion-weighted imaging (DWI), from January 2018 to December 2019, were retrospectively assessed. They were assigned to the good (mRS ≤ 2) and poor (mRS > 2) functional outcome groups, respectively. Then, 399 patients examined by MR scanner 1 and 199 patients scanned by MR scanner 2 were assigned to the training and validation cohorts, respectively. Infarction lesions underwent manual segmentation on DWI, extracting 402 radiomic features. A radiomics nomogram encompassing patient characteristics and the radiomics signature was built using a multivariate logistic regression model. The performance of the nomogram was evaluated in the training and validation cohorts. Ultimately, decision curve analysis was implemented to assess the clinical value of the nomogram. The performance of infarction lesion volume was also evaluated using univariate analysis.

RESULTS

Stroke lesion volume showed moderate performance, with an area under the curve (AUC) of 0.678. The radiomics signature, including 11 radiomics features, exhibited good prediction performance. The radiomics nomogram, encompassing clinical characteristics (age, hemorrhage, and 24 h National Institutes of Health Stroke Scale score) and the radiomics signature, presented good discriminatory potential in the training cohort [AUC = 0.80; 95% confidence interval (CI) 0.75-0.86], which was validated in the validation cohort (AUC = 0.73; 95% CI 0.63-0.82). In addition, it demonstrated good calibration in the training (p = 0.55) and validation (p = 0.21) cohorts. Decision curve analysis confirmed the clinical value of this nomogram.

CONCLUSION

This novel noninvasive clinical-radiomics nomogram shows good performance in predicting ischemic stroke prognosis.

Multi-view iterative random walker for automated salvageable tissue delineation in ischemic stroke from multi-sequence MRI

BACKGROUND AND OBJECTIVE

Non-invasive and robust identification of salvageable tissue (penumbra) is crucial for interventional stroke therapy. Besides identifying stroke injury as a whole, the ability to automatically differentiate core and penumbra tissues, using both diffusion and perfusion magnetic resonance imaging (MRI) sequences is essential for ischemic stroke treatment.

METHOD

A fully automated and novel one-shot multi-view iterative random walker (MIRW) method with an automated injury seed point detection is developed for lesion delineation. MIRW utilizes the heirarchical decomposition of multi-sequence MRI physical properties of the underlying tissue within the lesion to maximize the inter-class variations of the volumetric histogram to estimate the probable seed points. These estimates are further utilized to conglomerate the lesion estimations iteratively from axial, coronal and sagittal MRI volumes for a computationally efficient segmentation and quantification of salvageable and necrotic tissues from multi-sequence MRI.

RESULTS

Comprehensive experimental analysis of MIRW is performed on three challenging adult(sub-)acute ischemic stroke datasets using performance measures like precision, sensitivity, specificity and Dice similarity score (DSC), which are computed with respect to the manual ground-truth.

COMPARISON WITH EXISTING METHODS

MIRW method resulted in a high DSC of 83.5% in a very less computational time of 98.23 s/volume, which is a significant improvement on the ISLES benchmark dataset for penumbra detection, compared to the state-of-the-art techniques.

CONCLUSION

Quantitative measures demonstrate the promising potential of MIRW for computational analysis of adult stroke and quantifying penumbra in stroke patients which is essential for selecting the good candidates for recanalization.

Modeling and simulation to predict the degree of disability over time in acute ischemic stroke patients

Disability in patients with acute stroke varies over time, with the prediction of outcomes being critical for proper management. This study aimed to develop a model to predict the cumulative probability of each modified Rankin Scale (mRS) score over time with inclusion of significant covariates. Longitudinal data obtained from 193 patients, 1–24 months after onset of acute ischemic stroke, were included for a modeling analysis using nonlinear mixed‐effect modeling (NONMEM). After selecting a model that best described the time course of the probability of different mRS scores, potential covariates were tested. Visual predicted check plots, parameter estimates, and decreases in minimum objective function values were used for model evaluation. The inclusion of disease progression (DP) in the baseline proportional odds cumulative logit model significantly improved the model compared to the baseline model without DP. An inhibitory maximum effect (E_max) model was determined to be the best DP model for describing the probability of specific mRS scores over time. In the final model, DP was multiplied with the baseline cumulative logit probability with a baseline adjustment. In addition to differences in lesion volume (DLV), the final model included comorbid diabetes mellitus (DM) and baseline National Institutes of Health Stroke Scale (NIHSS) scores on E_max as statistically significant covariates. This study developed a model including DLV, NIHSS score, and comorbid DM for predicting the disability time course in patients with acute ischemic stroke. This model may help to predict disease outcomes and to develop more appropriate management plans for patients with acute stroke.

Extracellular Vesicle Application as a Novel Therapeutic Strategy for Ischemic Stroke

Ischemic stroke (IS) accounts for most of the cases of stroke onset, and due to short therapeutic time window for thrombolysis and numerous limited treatment measures and contraindications, lots of patients cannot receive satisfying therapeutic effects resulting in high disability and mortality worldly. In recent years, extracellular vesicles (EVs), as nanosized membrane-structured vesicles secreted from almost all cells, especially from stem/progenitor cells, have been reported to exert significant beneficial effects on IS from multiple approaches and notably ameliorate neurological outcome. Moreover, based on nano-size and lipid bilayer structure, EVs can easily penetrate the blood-brain barrier and migrate into the brain. In this review, we mainly systematically summarize the therapeutic effects of EVs on IS and explore their potential applications. Simultaneously, we also discuss administration routines, dosages, experimental observation time, and some key issues of EV application during IS treatment. It contributes to a comprehensive understanding of the progress of EV treatment for IS and providing confident evidence for further EV clinical application widely.

An integrative multivariate approach for predicting functional recovery using magnetic resonance imaging parameters in a translational pig ischemic stroke model

Magnetic resonance imaging (MRI) is a clinically relevant, real-time imaging modality that is frequently utilized to assess stroke type and severity. However, specific MRI biomarkers that can be used to predict long-term functional recovery are still a critical need. Consequently, the present study sought to examine the prognostic value of commonly utilized MRI parameters to predict functional outcomes in a porcine model of ischemic stroke. Stroke was induced via permanent middle cerebral artery occlusion. At 24 hours post-stroke, MRI analysis revealed focal ischemic lesions, decreased diffusivity, hemispheric swelling, and white matter degradation. Functional deficits including behavioral abnormalities in open field and novel object exploration as well as spatiotemporal gait impairments were observed at 4 weeks post-stroke. Gaussian graphical models identified specific MRI outputs and functional recovery variables, including white matter integrity and gait performance, that exhibited strong conditional dependencies. Canonical correlation analysis revealed a prognostic relationship between lesion volume and white matter integrity and novel object exploration and gait performance. Consequently, these analyses may also have the potential of predicting patient recovery at chronic time points as pigs and humans share many anatomical similarities (e.g., white matter composition) that have proven to be critical in ischemic stroke pathophysiology. The study was approved by the University of Georgia (UGA) Institutional Animal Care and Use Committee (IACUC; Protocol Number: A2014-07-021-Y3-A11 and 2018-01-029-Y1-A5) on November 22, 2017.

Clinical-CT mismatch defined NIHSS ≥ 8 and CT-ASPECTS ≥ 9 as a reliable marker of candidacy for intravenous thrombolytic therapy in acute ischemic stroke

Background

Clinical-diffusion mismatch between stroke severity and diffusion-weighted imaging lesion volume seems to identify stroke patients with penumbra. However, urgent magnetic resonance imaging is sometimes inaccessible or contraindicated. Thus, we hypothesized that using brain computed tomography (CT) to determine a baseline “clinical-CT mismatch” may also predict the responses to thrombolytic therapy.

Methods

Brain CT lesions were measured using the Alberta Stroke Program Early CT Score (ASPECTS). A total of 104 patients were included: 79 patients with a baseline National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 and a CT-ASPECTS ≥ 9 who were defined as clinical-CT mismatch-positive (P group) and 25 patients with an NIHSS score ≥ 8 and a CT-ASPECTS < 9 who were defined as clinical-CT mismatch-negative (the N group). We compared their clinical outcomes, including early neurological improvement (ENI), early neurological deterioration (END), delta NIHSS score (admission NIHSS—baseline NIHSS score), symptomatic intracranial hemorrhage (sICH), mortality, and favorable outcome at 3 months.

Results

Patients in the P group had a greater proportion of favorable outcome at 3 months (p = 0.032) and more frequent ENI (p = 0.038) and a greater delta NIHSS score (p = 0.001), as well as a lower proportion of END (p = 0.004) than those in the N group patients. There were no significant differences in the incidence rates of sICH and mortality between the two groups.

Conclusions

Clinical-CT mismatch may be able to predict which patients would benefit from intravenous thrombolysis.

Multimodal CT pc-ASPECTS in infratentorial stroke: diagnostic and prognostic value

BACKGROUND AND PURPOSE

Diagnosis of posterior circulation stroke may be challenged. National Institutes of Health Stroke Scale (NIHSS) and brain imaging (non-contrast brain computed tomography-CT) are used for diagnosis; evaluation on posterior circulation stroke remains a limit of NIHSS, and the value of non-contrast CT (NCCT) is limited due to artifacts caused by the bones of the base of the skull. We tested the validity and prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) in patients with posterior circulation stroke.

METHODS

Pc-ASPECTS allots the posterior circulation 10 points. We studied 50 patients with posterior circulation stroke. We applied pc-ASPECTS to NCCT, CT angiography, and CT Perfusion. We evaluated the correlation of pc-ASPECT with outcome parameters for stroke.

RESULTS

Out of 50 patients, CTP showed abnormalities in 34 cases. The pc-ASPECT score calculated on brain CT and on the brain CT + angio CT had a sensibility of 24%, calculated on brain CT, angio CT and CTPerfusion gain a sensibility of 72%. Pc-ASPECT MTT resulted to be the more reliable parameter: outcome given by NIHSS score at discharge, mRS at discharge, and at 3 months was more severe in patients with Pc-ASPECT MTT alteration. Outcome given by NIHSS score at discharge and mRS at discharge and 1 at 3 months was more severe in patients with higher NIHSS score at admission.

CONCLUSION

We evaluated the usefulness of pc-ASPECTS on CTP in predicting functional outcome in acute posterior circulation stroke that appears to be a powerful marker for predicting functional outcome.

Infarct Volumes of Patients with Acute Ischemic Stroke Receiving Direct Oral Anticoagulants due to Non-Valvular Atrial Fibrillation

Direct oral anticoagulants (DOACs) have been shown to decrease the risk of ischemic stroke in non-valvular atrial fibrillation (NVAF). This study aims to investigate whether DOACs result in a significant change in lesion volume and the severity of the subsequent disability in patients who have experienced a stroke.

CT perfusion in hyper-acute ischemic stroke: the acid test for COVID-19 fear

PURPOSE

The fear of COVID-19 infection may discourage patients from going to the hospital even in case of sudden onset of disabling symptoms. There is growing evidence of the reduction of stroke admissions and higher prevalence of severe clinical presentation. Yet, no studies have investigated the perfusion pattern of acute strokes admitted during the lockdown. We aimed to evaluate the effects of the COVID-19 pandemic on hyper-acute stroke CT perfusion (CTP) pattern during the first months of the pandemic in Italy.

METHODS

In this retrospective observational study, we analyzed CTP images and clinical data of ischemic stroke patients admitted between 9 March and 2 June 2020 that underwent CTP (n = 30), to compare ischemic volumes and clinical features with stroke patients admitted during the same period in 2019 (n = 51). In particular, CTP images were processed to calculate total hypoperfused volumes, core volumes, and mismatch. The final infarct volumes were calculated on follow-up CT.

RESULTS

Significantly higher total CTP hypoperfused volume (83.3 vs 18.5 ml, p = 0.003), core volume (27.8 vs 1.0 ml, p < 0.001), and unfavorable mismatch (0.51 vs 0.91, p < 0.001) were found during the COVID-19 period compared to no-COVID-19 one. The more unfavorable perfusion pattern at admission resulted in higher infarct volume on follow-up CT during COVID-19 (35.5 vs 3.0 ml, p < 0.001). During lockdown, a reduction of stroke admissions (- 37%) and a higher prevalence of severe clinical presentation (NIHSS ≥ 10; 53% vs 36%, p = 0.029) were observed.

CONCLUSION

The results of CTP analysis provided a better insight in the higher prevalence of major severity stroke patients during the COVID-19 period.

RUN-UP: Accelerated multishot diffusion-weighted MRI reconstruction using an unrolled network with U-Net as priors

PURPOSE

To accelerate and improve multishot diffusion-weighted MRI reconstruction using deep learning.

METHODS

An unrolled pipeline containing recurrences of model-based gradient updates and neural networks was introduced for accelerating multishot DWI reconstruction with shot-to-shot phase correction. The network was trained to predict results of jointly reconstructed multidirection data using single-direction data as input. In vivo brain and breast experiments were performed for evaluation.

RESULTS

The proposed method achieves a reconstruction time of 0.1 second per image, over 100-fold faster than a shot locally low-rank reconstruction. The resultant image quality is comparable to the target from the joint reconstruction with a peak signal-to-noise ratio of 35.3 dB, a normalized root-mean-square error of 0.0177, and a structural similarity index of 0.944. The proposed method also improves upon the locally low-rank reconstruction (2.9 dB higher peak signal-to-noise ratio, 29% lower normalized root-mean-square error, and 0.037 higher structural similarity index). With training data from the brain, this method also generalizes well to breast diffusion-weighted imaging, and fine-tuning further reduces aliasing artifacts.

CONCLUSION

A proposed data-driven approach enables almost real-time reconstruction with improved image quality, which improves the feasibility of multishot DWI in a wide range of clinical and neuroscientific studies.

Increased Serum Complement C3 Levels Are Associated With Adverse Clinical Outcomes After Ischemic Stroke

BACKGROUND AND PURPOSE

Complement C3 has been implicated in inflammation and ischemia/reperfusion injury, but its impact on the prognosis of ischemic stroke remains unclear. Aim of this study was to prospectively investigate the association between serum complement C3 and adverse clinical outcomes after ischemic stroke.

METHODS

We measured serum complement C3 levels for 3474 patients with ischemic stroke in 26 participating hospitals and collected data of clinical outcomes at 3 months after ischemic stroke. The primary outcome was composite outcome of death and major disability (modified Rankin Scale score ≥3) at 3 months after stroke onset and secondary outcomes included major disability, death, and vascular events.

RESULTS

During 3 months of follow-up, 866 participants (25.4%) developed primary outcome. After multivariate adjustment, elevated serum complement C3 levels were associated with increased risk of primary outcome (odds ratio, 1.30 [95% CI, 1.02-1.65]; P_trend=0.038) when 2 extreme tertiles were compared. Each SD increase of log-transformed complement C3 was associated with 13% (95% CI, 2%-25%) increased risk of primary outcome. Multivariable-adjusted spline regression model showed a linear relationship between serum complement C3 and the risk of primary outcome (P_linearity=0.022). Addition of serum complement C3 to conventional risk factors significantly improved the risk prediction of primary outcome (net reclassification index: 8.87%, P=0.028; integrated discrimination index: 0.19%, P=0.029).

CONCLUSIONS

High serum complement C3 levels at baseline were associated with increased risks of adverse clinical outcomes at 3 months after ischemic stroke, suggesting that serum complement C3 may be a valuable prognostic biomarker for ischemic stroke.

Recanalization Therapy for Acute Ischemic Stroke with Large Vessel Occlusion: Where We Are and What Comes Next?

In the past 5 years, the success of multiple randomized controlled trials of recanalization therapy with endovascular thrombectomy has transformed the treatment of acute ischemic stroke with large vessel occlusion. The evidence from these trials has now established endovascular thrombectomy as standard of care. This review will discuss the chronological evolution of large vessel occlusion treatment from early medical therapy with tissue plasminogen activator to the latest mechanical thrombectomy. Additionally, it will highlight the potential areas in endovascular thrombectomy for acute ischemic stroke open to exploration and further progress in the next decade.

Machine learning identifies stroke features between species

Identification and localization of ischemic stroke (IS) lesions is routinely performed to confirm diagnosis, assess stroke severity, predict disability and plan rehabilitation strategies using magnetic resonance imaging (MRI). In basic research, stroke lesion segmentation is necessary to study complex peri-infarction tissue changes. Moreover, final stroke volume is a critical outcome evaluated in clinical and preclinical experiments to determine therapy or intervention success. Manual segmentations are performed but they require a specialized skill set, are prone to inter-observer variation, are not entirely objective and are often not supported by histology. The task is even more challenging when dealing with large multi-center datasets, multiple experimenters or large animal cohorts. On the other hand, current automatized segmentation approaches often lack histological validation, are not entirely user independent, are often based on single parameters, or in the case of complex machine learning methods, require vast training datasets and are prone to a lack of model interpretation.

Methods: We induced IS using the middle cerebral artery occlusion model on two rat cohorts. We acquired apparent diffusion coefficient (ADC) and T2-weighted (T2W) images at 24 h and 1-week after IS induction. Subsets of the animals at 24 h and 1-week post IS were evaluated using histology and immunohistochemistry. Using a Gaussian mixture model, we segmented voxel-wise interactions between ADC and T2W parameters at 24 h using one of the rat cohorts. We then used these segmentation results to train a random forest classifier, which we applied to the second rat cohort. The algorithms' stroke segmentations were compared to manual stroke delineations, T2W and ADC thresholding methods and the final stroke segmentation at 1-week. Volume correlations to histology were also performed for every segmentation method. Metrics of success were calculated with respect to the final stroke volume. Finally, the trained random forest classifier was tested on a human dataset with a similar temporal stroke on-set. Manual segmentations, ADC and T2W thresholds were again used to evaluate and perform comparisons with the proposed algorithms' output.

Results: In preclinical rat data our framework significantly outperformed commonly applied automatized thresholding approaches and segmented stroke regions similarly to manual delineation. The framework predicted the localization of final stroke regions in 1-week post-stroke MRI with a median Dice similarity coefficient of 0.86, Matthew's correlation coefficient of 0.80 and false positive rate of 0.04. The predicted stroke volumes also strongly correlated with final histological stroke regions (Pearson correlation = 0.88, P < 0.0001). Lastly, the stroke region characteristics identified by our framework in rats also identified stroke lesions in human brains, largely outperforming thresholding approaches in stroke volume prediction (P<0.01).

Conclusion: Our findings reveal that the segmentation produced by our proposed framework using 24 h MRI rat data strongly correlated with the final stroke volume, denoting a predictive effect. In addition, we show for the first time that the stroke imaging features can be directly translated between species, allowing identification of acute stroke in humans using the model trained on animal data. This discovery reduces the gap between the clinical and preclinical fields, unveiling a novel approach to directly co-analyze clinical and preclinical data. Such methods can provide further biological insights into human stroke and highlight the differences between species in order to help improve the experimental setups and animal models of the disease.

Risk factors for in-hospital mortality among acute ischemic stroke patients in China: a nationwide prospective study

Objective: We aimed to investigate factors related to in-hospital mortality (IHM) in acute ischemic stroke (AIS) patients.Methods: We prospectively investigated 827,314 patients who were admitted within 7 days of AIS between August 2015 and July 2019. Demographic characteristics, risk factors, and clinical and laboratory characteristics of patients were assessed. Univariate and multivariate logistic regression analyses were performed to identify predictors associated with IHM.Results: The IHM rate in this study was 0.5% in women and 0.3% in men. Factors associated with IHM in AIS included diabetes (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.03-1.43), female (OR 0.84, 95%CI 0.74-0.96), hypertension (OR 1.16, 95%CI 1.01-1.34), atrial fib/flutter (OR 1.51, 95%CI 1.29-1.77), other heart disease (OR1.43, 95%CI 1.23-1.67), prior myocardial infarction (OR 2.00, 95%CI 1.54-2.60), antiplatelet therapies (OR 0.71, 95%CI 0.60-0.84), gastrointestinal bleeding (OR 3.54, 95%CI 2.83-4.44), pulmonary embolism (OR 2.53, 95%CI1.41-4.53), dysphagia(OR7.32, 95%CI6.23-8.61), glycosylated hemoglobin (OR1.05, 95%CI 1.02-1.09), serum creatinine (OR 1.001, 95%CI 1.001-1.002), urea nitrogen (OR 1.10, 95%CI 1.08-1.12), National Institutes of Health Stroke Scale (NIHSS) score (4-5 vs. 0-4: OR 3.58; ≥15 vs. 0-4: OR 8.78), stroke rehabilitation (OR 0.27, 95%CI 0.23-0.30), age (third IQR vs. first IQR: OR 1.57; fourth IQR vs. first IQR: OR 2.23), and in-hospital stroke/TIArecurrence (OR 2.38, 95%CI 2.03-2.78).Conclusions: The findings from this study may help clinicians control the risk of IHM better for patients with AIS.

Normalized wall index, intraplaque hemorrhage and ulceration of carotid plaques correlate with the severity of ischemic stroke

BACKGROUND AND AIMS

Carotid atherosclerosis is considered an important cause of ischemic stroke. Tthis study aimed to explore the relationship between plaque features and the severity of stroke, and to identify plaque risk factors for the assessment of the severity of ischemic stroke.

METHODS

Symptomatic patients with carotid atherosclerotic plaques were prospectively recruited and underwent high-resolution vessel wall magnetic resonance imaging (VW-MRI). Two trained MRI readers independently identified intraplaque hemorrhage (IPH), calcification (CA), surface CA, deep CA, and ulceration. They measured and calculated the maximum vessel diameter (Max VD), maximum wall thickness (Max WT), total vessel area, lumen area, normalized wall index (NWI), plaque volume, IPH volume, IPH proportion, CA volume, and CA proportion. Patients were divided into two groups according to their National Institutes of Health Stroke Scale (NIHSS) scores (NIHSS ≤1 vs. NIHSS >1). Clinical characteristics and carotid plaque features were compared using the Mann-Whitney U test or Chi-square test as appropriate. Odds ratio (OR) and corresponding 95% confidence interval (CI) of plaque features to distinguish patients with NIHSS >1 were calculated. Spearman's rank correlations or Pearson correlations were determined for plaque features and NIHSS scores.

RESULTS

Of the 97 included patients, 34 (35.05%) with NIHSS >1 had significantly greater NWI (p < 0.05), larger IPH volume (p < 0.01), and greater IPH proportion (p < 0.01), and higher prevalence of IPH (OR, 5.654; 95%CI, 2.272-14.070; p < 0.01) and ulceration (OR, 2.891; 95%CI, 1.090-7.667; p = 0.033) than patients with NIHSS ≤1. Max WT (r = 0.24, p = 0.018), NWI (r = 0.22, p = 0.032), IPH (r = 0.27, p = 0.007), IPH volume (r = 0.35, p < 0.01), IPH proportion (r = 0.28, p = 0.005), and ulceration (r = 0.35, p < 0.01) had positive correlations with NIHSS scores.

CONCLUSIONS

NWI, IPH, and ulceration of carotid atherosclerotic plaque based on high-resolution VW-MRI may be useful indicators for assessing the severity of ischemic stroke in patients with atherosclerosis. NIHSS score is related to max WT, NWI, IPH, IPH volume, IPH proportion, and ulceration.

The Diagnostic Value of sTWEAK in Acute Ischemic Stroke

Background

Considering the critical role of early diagnosis and management of acute ischemic stroke, biomarkers that can reliable assist in the diagnosis are still needed. These biomarkers should rapidly analyze, have high specificity for brain damage, and be available in the emergency settings for early diagnosis and exclusion of other conditions that mimic acute ischemic stroke. Soluble tumor necrosis factor-like weak inducer of apoptosis, a protein involved in the regulation of several biological functions, could be a potential acute ischemic stroke biomarker.

Aims

To investigate the diagnostic value of soluble tumor necrosis factor-like weak inducer of apoptosis in patients with acute ischemic stroke and examine the relationship between ischemic area volume determined at diffusion-weighted magnetic resonance imaging and soluble tumor necrosis factor-like weak inducer of apoptosis.

Study Design

A prospective, case-control study.

Methods

This case-control prospective study included 36 patients with acute ischemic stroke and 36 healthy volunteers. Information on age, sex, presence of chronic disease, neurological examination findings, times of presentation to the emergency department after acute ischemic stroke, soluble tumor necrosis factor-like weak inducer of apoptosis levels, ischemic area volumes at diffusion-weighted magnetic resonance imaging, and 6-month mortality rates after stroke were recorded. The results were analyzed on SPSS 22.0 software (SPSS Inc., Chicago, IL, USA), and p<0.05 was considered statistically significant.

Results

A soluble tumor necrosis factor-like weak inducer of apoptosis cut-off value of 995.5 pg/mL exhibited a sensitivity of 80.5% and a positive predictive value of 82.5% with an area under the curve of 0.84 (95% confidence interval: 0.74-0.94; p<0.001). The mean soluble tumor necrosis factor-like weak inducer of apoptosis levels in the acute ischemic stroke group (1968.08±1441.99 μg/L) were significantly higher than those in the control group (704.81±291.72 μg/L) (p<0.001). No correlation was observed between soluble tumor necrosis factor-like weak inducer of apoptosis levels and ischemic area volume measured at diffusion-weighted magnetic resonance imaging (r=-0.008; p=0.07). The mean ischemic area volume was 505.68±381.10 and 60.96±80.89 mm³ in the nonsurviving and surviving patients, respectively (p=0.002).

Conclusion

Soluble tumor necrosis factor-like weak inducer of apoptosis can be used in the diagnosis of acute ischemic stroke. However, it is inconclusive in estimating ischemic area volume and early mortality following acute ischemic stroke. Ischemic area volume measured at diffusion-weighted magnetic resonance imaging is a marker of poor prognosis and can be used in predicting early mortality.

Texture analysis based on ADC maps and T2-FLAIR images for the assessment of the severity and prognosis of ischaemic stroke

OBJECTIVES

To explore the feasibility of texture analysis based on T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) images and apparent diffusion coefficient (ADC) maps in the assessment of the severity and prognosis of ischaemic stroke using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin scale (mRS) scores, respectively.

METHODS

Overall, 116 patients diagnosed with subacute ischaemic stroke were included in this retrospective study. Based on T2-FLAIR images and ADC maps, 15 texture features were extracted from the ROIs of each patient using grey-level co-occurrence matrix (GLCM) and local binary pattern histogram Fourier (LBP-HF) methods. The correlations of NIHSS score on admission (NIHSS_baseline), NIHSS score 24 h after stroke onset (NIHSS_24h) and mRS score with the texture features were evaluated using Spearman's partial correlations. The receiver operating characteristic (ROC) curve was used to compare the performance of the selected texture features in the evaluation of stroke severity and prognosis.

RESULTS

Texture features derived from the T2-FLAIR images and ADC maps were correlated with NIHSS score and mRS score. Entropy_ADC and 0.75Quantile_T2-FLAIR showed the best diagnostic performance for assessing stroke severity. The combination of Entropy_ADC and 0.75Quantile_T2-FLAIR achieved a better performance in the evaluation of stroke severity (AUC = 0.7, p = 0.01) than either feature alone. Only 0.05Quantile_T2-FLAIR was found to be correlated with mRS score, and none of the texture features were predictive of mRS score.

CONCLUSION

Texture features derived from T2-FLAIR images and ADC maps might serve as biomarkers to evaluate stroke severity, but were insufficient to predict stroke prognosis.

Characterization of tissue and functional deficits in a clinically translational pig model of acute ischemic stroke

The acute stroke phase is a critical time frame used to evaluate stroke severity, therapeutic options, and prognosis while also serving as a major tool for the development of diagnostics. To further understand stroke pathophysiology and to enhance the development of treatments, our group developed a translational pig ischemic stroke model. In this study, the evolution of acute ischemic tissue damage, immune responses, and functional deficits were further characterized. Stroke was induced by middle cerebral artery occlusion in Landrace pigs. At 24 h post-stroke, magnetic resonance imaging revealed a decrease in ipsilateral diffusivity, an increase in hemispheric swelling resulting in notable midline shift, and intracerebral hemorrhage. Stroke negatively impacted white matter integrity with decreased fractional anisotropy values in the internal capsule. Like patients, pigs showed a reduction in circulating lymphocytes and a surge in neutrophils and band cells. Functional responses corresponded with structural changes through reductions in open field exploration and impairments in spatiotemporal gait parameters. Characterization of acute ischemic stroke in pigs provided important insights into tissue and functional-level assessments that could be used to identify potential biomarkers and improve preclinical testing of novel therapeutics.

Effect of Whey Protein Supplementation on Inflammatory and Antioxidant Markers, and Clinical Prognosis in Acute Ischemic Stroke (TNS Trial): A Randomized, Double Blind, Controlled, Clinical Trial

Purpose: Malnutrition is extensively prevalent amongst critically ill patients afflicted by ischemic stroke (IS). This study purpose was to evaluate the protein whey effect on inflammatory and antioxidant markers and functional prognosis in acute IS patients.

Methods: out of 42 patients with acute IS who were referred to Imam Reza Educational Hospital, Tabriz, Iran, 40 patients participated in the study. Twenty-one patients as control group received the hospital routine formula, and 19 patients as intervention group received 20 g/daily of whey protein through oral gavage. Inflammation and oxidative stress indicators (e.g., albumin, malondialdehyde (MDA), total antioxidant capacity (TAC), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and high sensitivity C reactive protein (hs-CRP)and clinical variables included in were evaluated using National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) during admission and also 3 weeks after intervention.

Results: Whey protein supplementation significantly decreased the NIHSS and mRS scores, TNF-α, IL-6, and hs-CRP by passing 3 weeks from intervention (P<0.05). However, whey formula had no significant effect on other markers including albumin, and MDA. The hs-CRP (P = 0.02) reduction was significantly higher in whey protein group in comparison with control group.

Conclusion: Whey protein supplementation reduced inflammation markers in those patients with IS. However, these changes should be studied in larger-scale trials.

The Influence of β-Adrenergic Receptor Kinase-1 on Stroke-induced Immunodeficiency Syndrome

BACKGROUND

Immunodeficiency in acute ischemic stroke (AIS) is thought to be a result of norepinephrine suppression of the lymphoid tissue. The possible differences in the distribution of lymphocytes after stroke may be due to differences in responsiveness of lymphocyte β-adrenergic receptors to their kinase (BARK-1).

OBJECTIVE

The objective was to quantify the influence of lymphocyte BARK-1 on stroke-induced immunodeficiency in AIS patients.

METHODS

A prospective clinical cohort study was conducted (N = 44). Measures included age, gender, race, risk factors for stroke, stroke severity, comorbidities, presence of infection, white blood cell counts and differential proportions, and lymphocyte BARK-1. Student t tests, effect sizes, and linear and logistic regressions were conducted to test the study objective. The study was approved by the Oregon Health & Science University Institutional Review Board.

RESULTS

There were significant changes in all white blood cells and differential proportions and in the National Institutes of Health Stroke Scale from admission to 48 hours after onset of stroke deficits. Higher BARK-1 influenced the lower lymphocyte proportion at 48 hours, independent of age, P < .0001. Furthermore, BARK-1 also was associated with an increase in the likelihood of having sustained or stroke-induced immunodeficiency at 48 hours: odds ratio, 2.41; 95% confidence interval, 1.10-5.25; P = .027, and odds ratio, 2.79; 95% confidence interval, 1.03-7.52; P = .043, respectively. In all backward stepwise selection of factors, BARK-1 was the only factor consistently retained in the models.

CONCLUSIONS

β-Adrenergic receptor kinase-1 has a significant quantifiable influence on lymphocyte proportion at 48 hours and on the classification of sustained stroke-induced immunodeficiency.

CLINICAL IMPLICATIONS

β-Adrenergic stimulation influences immunodeficiency in AIS.

Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke

Objective: To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS). Methods: Consecutive AIS patients (N = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression. Results: Of 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (OR_NIHSS 1.08, 95%CI 1.06-1.11; OR_mRS 1.05, 95%CI 1.03-1.07) and age (OR_NIHSS 1.03, 95%CI 1.01-1.05; OR_mRS 1.05, 95%CI 1.03-1.07). Conclusion: In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.

Sex-specific differences in white matter microvascular integrity after ischaemic stroke

Background and purpose

Functional outcomes after ischaemic stroke are worse in women, despite adjusting for differences in comorbidities and treatment approaches. White matter microvascular integrity represents one risk factor for poor long-term functional outcomes after ischaemic stroke. The aim of the study is to characterise sex-specific differences in microvascular integrity in individuals with acute ischaemic stroke.

Methods

A retrospective analysis of subjects with acute ischaemic stroke and brain MRI with diffusion-weighted (DWI) and dynamic-susceptibility contrast-enhanced (DSC) perfusion-weighted imaging obtained within 9 hours of last known well was performed. In the hemisphere contralateral to the acute infarct, normal-appearing white matter (NAWM) microvascular integrity was measured using the K₂ coefficient and apparent diffusion coefficient (ADC) values. Regression analyses for predictors of K₂ coefficient, DWI volume and good outcome (90-day modified Rankin scale (mRS) score <2) were performed.

Results

105 men and 79 women met inclusion criteria for analysis. Despite no difference in age, women had increased NAWM K₂ coefficient (1027.4 vs 692.7×10^–6/s; p=0.006). In women, atrial fibrillation (β=583.6; p=0.04) and increasing NAWM ADC (β=4.4; p=0.02) were associated with increased NAWM K₂ coefficient. In multivariable regression analysis, the K₂ coefficient was an independent predictor of DWI volume in women (β=0.007; p=0.01) but not men.

Conclusions

In women with acute ischaemic stroke, increased NAWM K₂ coefficient is associated with increased infarct volume and chronic white matter structural integrity. Prospective studies investigating sex-specific differences in white matter microvascular integrity are needed.

Implications of insular cortex laterality for treatment of nicotine addiction

BACKGROUND

Damage to the insula disrupts nicotine-induced cravings and is associated with greater odds of cessation. The role of laterality in regulating these changes is unclear. Neuroimaging studies in cigarette smokers show left hemispheric activation during a period of forced withdrawal and right hemispheric activation after having just smoked. Among current smokers hospitalized for stroke involving their insula, we compared left versus right insular damage and its effect on smoking outcomes.

METHODS

A total of 37 smokers hospitalized with unilateral insular strokes (14 right, 23 left) were administered questionnaires to assess urge (Questionnaire on Smoking Urges) before (retrospectively) and during hospitalization and 3 months post-stroke, withdrawal during hospitalization (Wisconsin Smoking Withdrawal Scale), and prolonged abstinence at 3 months post-stroke. Crude and adjusted linear regression models were performed controlling for baseline covariates.

RESULTS

Right and left insular-damaged smokers experienced a significant decrease in urge from baseline to hospitalization and three-month follow-up (p < 0.01). Smokers with left-sided insular infarcts relative to right-sided experienced a larger decrease in acute urge (adjusted β=-1.16, 95% CI: -2.59, 0.27, p = 0.11) but not chronically (adjusted β=-0.06, 95% CI: -1.53, 1.40, p = 0.93). Left-sided insular damage was also associated with significantly fewer and less severe withdrawal symptoms during hospitalization (adjusted β=-3.52, 95% CI: -7.01, -0.04, p = 0.05). No differences were noted between groups for prolonged abstinence (p = 0.50).

CONCLUSIONS

Left insular adaptations are suggestive to have an impact on acute changes in urge and withdrawal more so than the right insula, however lateral asymmetries did not exist for long-term changes.