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Aim: To explore the neuroprotective effects of ARA290 and the role of β-common receptor (βCR) in a mouse model of middle cerebral artery occlusion (MCAO)., Methods: This study included male C57BL/6J mice that underwent MCAO and reperfusion. The neuroprotective effect of ARA290 on MCAO-induced brain injury was investigated using neurological function tests (Longa and modified neurological severity score). Cerebral infarction was examined by 2, 3, 5-triphenyl tetrazolium chloride staining, neuronal apoptosis was assessed by immunofluorescence staining, blood parameters were measured using a flow cytometry-based automated hematology analyzer, liquid chromatography with tandem mass spectrometry was used to identify the serum metabolomics signature, inflammatory cytokines and liver index were detected by commercially available kits, and the protein levels of the erythropoietin (EPO) receptor and βCR were measured by western blot., Results: ARA290 exerted a qualitatively similar neuroprotective effect after MCAO as EPO. ARA290 significantly reduced neuronal apoptosis and the level of inflammatory cytokines in the brain tissue. However, ARA290's neuroprotective effect was significantly suppressed following the injection of siRNA against βCR., Conclusion: ARA290 provided a neuroprotective effect via βCR in cerebral ischemic mice without causing erythropoiesis. This study provides novel insights into the role of ARA290 in ischemic stroke intervention., (© 2024 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Accurate determination of the onset time in acute ischemic stroke (AIS) patients helps to formulate more beneficial treatment plans and plays a vital role in the recovery of patients. Considering that the whole brain may contain some critical information, we combined the Radiomics features of infarct lesions and whole brain to improve the prediction accuracy. First, the radiomics features of infarct lesions and whole brain were separately calculated using apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences of AIS patients with clear onset time. Then, the least absolute shrinkage and selection operator (Lasso) was used to select features. Four experimental groups were generated according to combination strategies: Features in infarct lesions (IL), features in whole brain (WB), direct combination of them (IW) and Lasso selection again after direct combination (IWS), which were used to evaluate the predictive performance. The results of ten-fold cross-validation showed that IWS achieved the best AUC of 0.904, which improved by 13.5% compared with IL (0.769), by 18.7% compared with WB (0.717) and 4.2% compared with IW (0.862). In conclusion, combining infarct lesions and whole brain features from multiple sequences can further improve the accuracy of AIS onset time.

Background Cerebral oxygenation is closely related to neural function in acute ischemic stroke (AIS) and can be measured noninvasively from asymmetrically prominent cortical veins (APCVs) using quantitative susceptibility mapping (QSM). Purpose To quantify venous oxygen saturation (SvO 2 ) using brain MRI with QSM in patients with AIS, to analyze its change at 2-week follow-up, and to assess the influence of SvO 2 in clinical prognosis. Materials and Methods Between 2016 and 2020, consecutive patients with AIS who underwent brain MRI within 24 hours from symptom onset and 2 weeks after treatment were retrospectively enrolled. The SvO 2 of APCVs was quantified using QSM. The independent sample t test was used to compare the SvO 2 between patients with and patients without APCVs. The paired sample t test was used to assess the dynamic change in SvO 2 . Pearson and Spearman correlation analysis was used to explore the relationship among dynamic change in SvO 2 and hypoperfusion, National Institutes of Health Stroke Scale (NIHSS) score change, and 90-day modified Rankin Scale (mRS) score. The independent sample t test was used to compare the dynamic change in SvO 2 between different clinical prognoses and outcome subgroups. Results APCVs were detected in 39 of 73 patients (mean age, 70 years ± 10 [standard deviation]; 49 men) at admission and disappeared in 35 patients at 2-week follow-up MRI. The mean SvO 2 increased from 35.0% ± 5.8 to 64.5% ± 10.0 ( P < .001) in 39 patients. For the 35 patients with APCVs that disappeared, the dynamic change in SvO 2 negatively correlated with change in NIHSS score ( r = -0.37, R 2 = 0.19, P = .03) and 90-day mRS score ( r = -0.54, R 2 = 0.27, P = .001), and the dynamic change in SvO 2 in the subgroup with good 90-day outcomes ( n .03). Conclusion Improved oxygen saturation of asymmetric cortical veins detected using brain MRI with quantitative susceptibility mapping corresponded with better acute ischemic stroke outcomes for patients with asymmetrically prominent cortical veins that disappeared at 2-week follow-up MRI. © RSNA, 2021 n = 16) (mean, 34.5% ± 5.8 vs 29.7% ± 6.3; 95% CI: 0.6, 8.9; P = .03). Conclusion Improved oxygen saturation of asymmetric cortical veins detected using brain MRI with quantitative susceptibility mapping corresponded with better acute ischemic stroke outcomes for patients with asymmetrically prominent cortical veins that disappeared at 2-week follow-up MRI. © RSNA, 2021 Online supplemental material is available for this article.

Objectives: The present study is aimed at investigating the frequency and associated factors of asymmetrical prominent veins (APV) in patients with acute ischemic stroke (AIS)., Methods: Consecutive patients with AIS admitted to the Comprehensive Stroke Center of Shanghai Fourth People's Hospital between January 2013 and December 2017 were enrolled. MRI including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and susceptibility-weighted imaging (SWI) was performed within 12 hours of symptom onset. The volume of asymmetrical prominent veins (APV) was evaluated using the Signal Processing In nuclear magnetic resonance software (SPIN, Detroit, Michigan, USA). Multivariate analysis was used to assess relationships between APV findings and medical history, clinical variables as well as cardio-metabolic indices., Results: Seventy-six patients met the inclusion criteria. The frequency of APV ≥ 10 mL was 46.05% (35/76). Multivariate analyses showed that proximal artery stenosis or occlusion (≥50%) ( P < 0.001, adjusted odds ratio (OR) = 660.0, 95%CI = 57.28-7604.88) and history of atrial fibrillation ( P < 0.001, adjusted OR = 10.48, 95%CI = 1.78-61.68) were independent factors associated with high APV (≥10 mL)., Conclusion: Our findings suggest that the frequency of APV ≥ 10 mL is high in patients with AIS within 12 hours of symptom onset. History of atrial fibrillation and severe proximal artery stenosis or occlusion are strong predictors of high APV as calculated by SPIN on the SWI map., Competing Interests: The authors declare that there is no conflict of interests., (Copyright © 2021 Yue Wang et al.)

Objectives: We aimed to investigate differential characteristics of plaque in the middle cerebral artery (MCA) and hemodynamics in patients with ischemic stroke and transient ischemic attack (TIA), and to develop a predictive model for the presence of ischemic stroke and neurological impairment., Methods: Sixty-seven patients with acute ischemic events in MCA territory who underwent high-resolution vessel wall imaging between September 2016 and August 2018 were reviewed retrospectively. Patients were assigned to either the stroke group or TIA group, according to diffusion-weighted imaging and neurological examination. Plaque characteristics and anterograde score (AnS) were calculated. Tmax > 6.0-s volume was acquired by RApid Processing of perfusIon and Diffusion software. Multivariate logistic regression analysis and multiple linear regression analysis were performed to establish a predictive model for irreversible infarction occurrence and clinical severity., Results: Forty-five patients were assigned to the stroke group, and 22 were assigned to the TIA group. Plaque length, intraplaque hemorrhage (IPH), enhancement, AnS, and Tmax > 6.0-s volumes were significantly different between the two groups (p < 0.05). IPH and AnS were independent predictors for patients with stroke (p = 0.020 and 0.034, respectively). Tmax > 6.0-s volume, IPH, hypertension, and AnS were associated with high National Institutes of Health Stroke Scale (NIHSS) scores (all p < 0.05, R = 0.725, and adjusted R 2 = 0.494)., Conclusions: IPH and AnS are useful in predicting stroke occurrence. Tmax > 6.0-s volume, IPH, hypertension, and AnS are associated with neurological impairment of the patients., Key Points: • Ischemic stroke and TIA patients have different plaque characteristics and hemodynamics. • Intraplaque hemorrhage and anterograde score have high diagnostic efficiency for ischemic stroke. • The combination of Tmax > 6.0-s volume, intraplaque hemorrhage, hypertension, and anterograde score can predict the National Institutes of Health Stroke Scale scores of patients.

Background: Acute ischemic stroke (AIS) results in high morbidity, disability, and mortality. Early and automatic diagnosis of AIS can help clinicians administer the appropriate interventions., Objective: To develop a deep symmetric 3D convolutional neural network (DeepSym-3D-CNN) for automated AIS diagnosis via diffusion-weighted imaging (DWI) images., Methods: This study includes 190 study subjects (97 AIS and 93 Non-AIS) by collecting both DWI and Apparent Diffusion Coefficient (ADC) images. 3D DWI brain images are split into left and right hemispheres and input into two paths. A map with 125×253×14×12 features is extracted by each path of Inception Modules. After the features computed from two paths are subtracted through L-2 normalization, four multi-scale convolution layers produce the final predation. Three comparative models using DWI images including MedicalNet with transfer learning, Simple DeepSym-3D-CNN (each 3D Inception Module is replaced by a simple 3D-CNN layer), and L-1 DeepSym-3D-CNN (L-2 normalization is replaced by L-1 normalization) are constructed. Moreover, using ADC images and the combination of DWI and ADC images as inputs, the performance of DeepSym-3D-CNN is also investigated. Performance levels of all three models are evaluated by 5-fold cross-validation and the values of area under ROC curve (AUC) are compared by DeLong's test., Results: DeepSym-3D-CNN achieves an accuracy of 0.850 and an AUC of 0.864. DeLong's test of AUC values demonstrates that DeepSym-3D-CNN significantly outperforms other comparative models (p < 0.05). The highlighted regions in the feature maps of DeepSym-3D-CNN spatially match with AIS lesions. Meanwhile, DeepSym-3D-CNN using DWI images presents the significant higher AUC than that either using ADC images or using DWI-ADC images based on DeLong's test (p < 0.05)., Conclusions: DeepSym-3D-CNN is a potential method for automatically identifying AIS via DWI images and can be extended to other diseases with asymmetric lesions.

Erythropoietin has been researched for its neuroprotective effects in ischemic stroke for over 30 years. Although erythropoietin can cause side effects that need to be controlled, it has been suggested to be effective in enhancing the prognosis of patients who are out of the therapeutic time window and have not received recombinant tissue plasminogen activator therapy. Studies on the mechanism of the function of erythropoietin have shown that it has various protective effects in ischemic brain injury after stroke, including promoting neurogenesis. In this review, we discuss the effects of erythropoietin on neurogenesis after ischemic brain injury and provide references for effective treatments for ischemic stroke, which is one of the leading causes of death worldwide., Competing Interests: All authors declare no conflicts of interest., (© 2020 Zhang et al. Published by IMR press.)

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to evaluate the accuracy of automated software (iStroke) on magnetic resonance (MR) apparent diffusion coefficient (ADC) and perfusion-weighted imaging (PWI) against ground truth in assessing infarct core, and compare the hypoperfusion volume and mismatch volume on iStroke with those on Food and Drug Administration-approved software (RAPID) in patients with acute ischemic stroke. Methods: We used the single-volume decomposition method to develop the iStroke (iStroke; Beijing Tiantan Hospital, Beijing, China) software. Patients with ischemic stroke were collected from two educational hospitals in China with MR-PWI performed in the emergency department within 24 h of symptom onset. Infarct core volume was defined as ADC < 620 × 10−6 mm2/s and hypoperfusion volume was defined as Tmax > 6 s. We compared the accuracy of infarct core volume using iStroke and RAPID (iSchema View Inc, Menlo Park, CA) software with ground truth. Results: We included 405 patients with acute ischemic stroke with MR ADC and PWI sequences. The infarct core volume on iStroke (median 2.43 ml, interquartile range [IQR] 0.60–10.32 ml) was not significantly different from the ground truth (median 2.89 ml, IQR 0.77–9.17 ml) (P = 0.07); Bland–Altman curves showed that the core volume of iStroke and RAPID software were comparable with each other on individual agreement with ground truth. The hypoperfusion volume and mismatch volume on iStroke were not statistically different from those on the RAPID software, respectively. In patients with large vessel occlusion (n = 74), the agreement between iStroke and RAPID was substantial (kappa = 0.76) according to DEFUSE 3 criteria (infarct core < 70 ml, mismatch volume ≥ 15 ml, and mismatch ratio ≥ 1.8). Conclusions: The iStroke automatic processing of ADC and PWI is a reliable software for the identification of diffusion–perfusion mismatch in acute ischemic stroke. [ABSTRACT FROM AUTHOR]

Background: The ability to accurately detect ischemic stroke and predict its neurological recovery is of great clinical value. This study intended to evaluate the performance of whole-brain dynamic radiomics features (DRF) for ischemic stroke detection, neurological impairment assessment, and outcome prediction. Methods: The supervised feature selection (Lasso) and unsupervised feature-selection methods (five-feature dimension-reduction algorithms) were used to generate four experimental groups with DRF in different combinations. Ten machine learning models were used to evaluate their performance by ten-fold cross-validation. Results: In experimental group_A, the best AUCs (0.873 for stroke detection, 0.795 for NIHSS assessment, and 0.818 for outcome prediction) were obtained by outstanding DRF selected by Lasso, and the performance of significant DRF was better than the five-feature dimension-reduction algorithms. The selected outstanding dimension-reduction DRF in experimental group_C obtained a better AUC than dimension-reduction DRF in experimental group_A but were inferior to the outstanding DRF in experimental group_A. When combining the outstanding DRF with each dimension-reduction DRF (experimental group_B), the performance can be improved in ischemic stroke detection (best AUC = 0.899) and NIHSS assessment (best AUC = 0.835) but failed in outcome prediction (best AUC = 0.806). The performance can be further improved when combining outstanding DRF with outstanding dimension-reduction DRF (experimental group_D), achieving the highest AUC scores in all three evaluation items (0.925 for stroke detection, 0.853 for NIHSS assessment, and 0.828 for outcome prediction). By the method in this study, comparing the best AUC of Ft-test in experimental group_A and the best_AUC in experimental group_D, the AUC in stroke detection increased by 19.4% (from 0.731 to 0.925), the AUC in NIHSS assessment increased by 20.1% (from 0.652 to 0.853), and the AUC in prognosis prediction increased by 14.9% (from 0.679 to 0.828). This study provided a potential clinical tool for detailed clinical diagnosis and outcome prediction before treatment. [ABSTRACT FROM AUTHOR]

Background: Accurate outcome prediction is of great clinical significance in customizing personalized treatment plans, reducing the situation of poor recovery, and objectively and accurately evaluating the treatment effect. This study intended to evaluate the performance of clinical text information (CTI), radiomics features, and survival features (SurvF) for predicting functional outcomes of patients with ischemic stroke. Methods: SurvF was constructed based on CTI and mRS radiomics features (mRSRF) to improve the prediction of the functional outcome in 3 months (90-day mRS). Ten machine learning models predicted functional outcomes in three situations (2-category, 4-category, and 7-category) using seven feature groups constructed by CTI, mRSRF, and SurvF. Results: For 2-category, ALL (CTI + mRSRF+ SurvF) performed best, with an mAUC of 0.884, mAcc of 0.864, mPre of 0.877, mF1 of 0.86, and mRecall of 0.864. For 4-category, ALL also achieved the best mAuc of 0.787, while CTI + SurvF achieved the best score with mAcc = 0.611, mPre = 0.622, mF1 = 0.595, and mRe-call = 0.611. For 7-category, CTI + SurvF performed best, with an mAuc of 0.788, mPre of 0.519, mAcc of 0.529, mF1 of 0.495, and mRecall of 0.47. Conclusions: The above results indicate that mRSRF + CTI can accurately predict functional outcomes in ischemic stroke patients with proper machine learning models. Moreover, combining SurvF will improve the prediction effect compared with the original features. However, limited by the small sample size, further validation on larger and more varied datasets is necessary. [ABSTRACT FROM AUTHOR]

Objectives: To quantitatively evaluate the volume of the ischemic penumbra using susceptibility-weighted imaging and mapping (SWIM) of asymmetrical prominent cortical veins (APCVs) in patients with acute ischemic stroke. Methods: Eighty-five eligible patients with acute ischemic stroke on admission within 12 h from symptom onset were studied. The APCVs on SWIM were quantitatively (SWI-volume) and semi-quantitatively (SWI-Alberta Stroke Program Early CT Score, SWI-ASPECTS) evaluated to calculate mismatch. To assess the diagnostic efficacy of APCVs on SWIM, comparative analyses were performed between SWIvolume-DWI mismatch and SWIASPECTS-DWI mismatch, using PWI-DWI mismatch as a reference. Correlations were calculated between the mismatches, as well as between SWI-volume and time-to-maximum (Tmax) > 6 s volume. Additionally, each of these mismatches was correlated with the National Institute of Health Stroke Scale (NIHSS). Results: The sensitivity, negative predictive value, and accuracy of SWIvolume-DWI mismatch were demonstrably higher than SWIASPECTS-DWI mismatch (100% vs. 53.7%, 100% vs. 9.5%, 97.7% vs. 54.5%, respectively). A significant positive correlation was found between SWIvolume-DWI and PWI-DWI mismatch (r = 0.691, p < 0.01), as well as between SWI-volume and Tmax > 6 s volume (r = 0.786, p < 0.001). A significant negative correlation was found between SWIvolume-DWI mismatch and NIHSS (r = − 0.360, p = 0.022), as well as between SWIASPECTS-DWI mismatch and NIHSS (r = − 0.499, p = 0.001). Conclusions: SWIvolume-DWI mismatch had higher diagnostic efficacy than SWIASPECTS-DWI mismatch in defining the ischemic penumbra and showed good consistency with PWI-DWI mismatch in acute ischemic stroke. Quantitation of APCVs using SWIM provided an accurate method for determining hypoperfusion and provided a reliable method to reflect the hypoxia of penumbra. Key Points: • SWIvolume-DWI mismatch has higher diagnostic efficacy than SWIASPECTS-DWI mismatch in defining the ischemic penumbra. • SWIvolume-DWI mismatch shows good consistency with PWI-DWI mismatch in managing penumbra in acute ischemic stroke. • Quantitation of APCV volume using SWIM provided an accurate method for determining the hypoperfusion area and provided a reliable method to reflect the hypoxia of penumbra. [ABSTRACT FROM AUTHOR]

Angiogenesis after ischemic brain injury contributes to the restoration of blood supply in the ischemic zone. Strategies to improve angiogenesis may facilitate the function recovery after stroke. Recent researches have demonstrated that dysfunction of long non-coding RNAs are associated with angiogenesis. We have previously reported that long non-coding RNAs (lncRNAs) are aberrantly expressed in ischemic stroke. However, little is known about long non-coding RNAs and theirs role in angiogenesis after stroke. In this study, we identified a rat lncRNAs, Meg3, and found that Meg3 was significantly decreased after ischemic stroke. Overexpression of Meg3 suppressed functional recovery and decreased capillary density after ischemic stroke. Downregulation of Meg3 ameliorated brain lesion and increased angiogenesis after ischemic stroke. Silencing of Meg3 resulted in a proangiogenic effect evidenced by increased endothelial cell migration, proliferation, sprouting, and tube formation. Mechanistically, we showed that Meg3 negatively regulated notch pathway both in vivo and in vitro. Inhibition of notch signaling in endothelial cells reversed the proangiogenic effect induced by Meg3 downregulation. This study revealed the function of Meg3 in ischemic stroke and elucidated its mechanism in angiogenesis after ischemic stroke. [ABSTRACT FROM AUTHOR]

Abstract Previously study has proved the non-erythropoietic mutant erythropoietin (MEPO) exerted neuroprotective effects against ischemic cerebral injury, with an efficacy similar to that of wild-type EPO. This study investigates its effects on neurogenesis, angiogenesis, and gliogenesis in cerebral ischemic mice. Male C57BL/6 mice were subjected to middle cerebral artery occlusion (MCAO) and reperfusion. EPO (5000 U/kg), MEPO (5000 U/kg) or equal volume of normal saline was injected intraperitoneally. Neurological function was evaluated by Rota-rod test, Neurological severity scores (NSS) and Adhesive removal test. After ischemia and reperfusion (I/R), the survival rate, brain tissue loss, neurogenesis, angiogenesis and gliogenesis were detected by Nissl staining, Immunofluorescence and Western blot, respectively. The results shown that MEPO significantly increased survival rate, reduced brain tissue loss, and improved neurological function after MCAO (P < 0.05). Furthermore, MEPO obviously enhanced the proliferation of neuronal precursors (DCX) and promoted its differentiation into mature neurons (NeuN) (P < 0.05). In addition, compared to normal saline treatment mice, MEPO increased the number of BrdU-positive cells in the cerebral vasculature (P < 0.05). Whereas, MEPO treatment also reduced the numbers of newly generated astrocytes (GFAP) and microglia (Iba1) (P < 0.05). Among all the tests in this study, there was no significant difference between EPO group and MEPO group. Taken together, MEPO promoted the regeneration of neurons and blood vessels in peripheral area of infarction, and suppressed the gliogenesis, thus promoting neurogenesis, improving neurological function and survival rate. Our findings suggest that the MEPO may be a therapeutic drug for ischemic stroke intervention. [ABSTRACT FROM AUTHOR]