Thrombolysis and thrombectomy for acute ischaemic stroke

Tawil, Salwa El; Muir, Keith W.

doi:10.7861/clinmedicine.17-2-161

Cited by 55 publications

(35 citation statements)

References 30 publications

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“…The diagnosis of an acute ischemic infarction, where the damage of brain tissue may still be reversible, enables selection of appropriate treatment and contributes to a more favorable outcome [ 27 ]. Recent studies demonstrated a high efficacy of reperfusion therapies (intravenous thrombolysis and/or thrombectomy) in acute ischemic stroke patients regarding improvement in recovery [ 28 – 30 ]. Therefore, we focused on stroke patients with middle cerebral artery infarction receiving this gold standard treatment.…”

Section: Discussionmentioning

confidence: 99%

Early Progressive Changes in White Matter Integrity Are Associated with Stroke Recovery

Pinter

Gattringer

Fandler‐Höfler

et al. 2020

Transl. Stroke Res.

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Information on microstructural white matter integrity has been shown to explain post-stroke recovery beyond clinical measures and focal brain damage. Especially, knowledge about early white matter changes might improve prediction of outcome. We investigated 42 acute reperfused ischemic stroke patients (mean age 66.5 years, 40% female, median admission NIHSS 9.5) with a symptomatic MRI-confirmed unilateral middle cerebral artery territory infarction 24–72 h post-stroke and after 3 months. All patients underwent neurological examination and brain MRI. Fifteen older healthy controls (mean age 57.3 years) were also scanned twice. We assessed fractional anisotropy (FA), mean diffusivity (MD), axial (AD), and radial diffusivity (RD). Patients showed significantly decreased white matter integrity in the hemisphere affected by the acute infarction 24–72 h post-stroke, which further decreased over 3 months compared with controls. Less decrease in FA of remote white matter tracts was associated with better stroke recovery even after correcting for infarct location and extent. A regression model including baseline information showed that the modified Rankin Scale and mean FA of the genu of the corpus callosum explained 53.5% of the variance of stroke recovery, without contribution of infarct volume. Furthermore, early dynamic FA changes of the corpus callosum within the first 3 months post-stroke independently predicted stroke recovery. Information from advanced MRI measures on white matter integrity at the acute stage, as well as early dynamic white matter degeneration beyond infarct location and extent, improve our understanding of post-stroke reorganization in the affected hemisphere and contribute to an improved prediction of recovery.

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Section: Discussionmentioning

confidence: 99%

Early Progressive Changes in White Matter Integrity Are Associated with Stroke Recovery

Pinter

Gattringer

Fandler‐Höfler

et al. 2020

Transl. Stroke Res.

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“…Therefore, only 3.4%-5.2% of patients were treated within the short time window. Researchers have been focusing on how to improve the clinical diagnosis and treatment of cerebral infarction beyond the time window of thrombolysis (Feil et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

et al. 2020

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Stroke ranks the second leading cause of death among people over the age of 60 in the world. Stroke is widely regarded as a complex disease that is affected by genetic and environmental factors. Evidence from twin and family studies suggests that genetic factors may play an important role in its pathogenesis. Therefore, research on the genetic association of susceptibility genes can help understand the mechanism of stroke. Genome-wide association study (GWAS) has found a large number of stroke-related loci, but their mechanism is unknown. In order to explore the function of single-nucleotide polymorphisms (SNPs) at the molecular level, in this paper, we integrated 8 GWAS datasets with brain expression quantitative trait loci (eQTL) dataset to identify SNPs and genes which are related to four types of stroke (ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke). Thirty-eight SNPs which can affect 14 genes expression are found to be associated with stroke. Among these 14 genes, 10 genes expression are associated with ischemic stroke, one gene for large artery stroke, six genes for cardioembolic stroke and eight genes for small vessel stroke. To explore the effects of environmental factors on stroke, we identified methylation susceptibility loci associated with stroke using methylation quantitative trait loci (MQTL). Thirty-one of these 38 SNPs are at greater risk of methylation and can significantly change gene expression level. Overall, the genetic pathogenesis of stroke is explored from locus to gene, gene to gene expression and gene expression to phenotype.

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“…The preferred diagnostic procedure at acute stage involves the acquisition of multi-parametric magnetic resonance imaging (MRI). The possible options for treatment are largely limited to reperfusion therapies known as thrombolysis and thrombectomy, which must be for treatment are largely limited to reperfusion therapies known as thrombolysis and thrombectomy, which must be managed not later than four to six hours after the symptom onset [4]. This treatment is associated with high risk of intracranial hemorrhage.…”

Section: Introductionmentioning

confidence: 99%

Predicting Clinical Outcome in Acute Ischemic Stroke Using Parallel Multi-Parametric Feature Embedded Siamese Network

2020

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Stroke is the second leading cause of death and disability worldwide, with ischemic stroke as the most common type. The preferred diagnostic procedure at the acute stage is the acquisition of multi-parametric magnetic resonance imaging (MRI). This type of imaging not only detects and locates the stroke lesion, but also provides the blood flow dynamics that helps clinicians in assessing the risks and benefits of reperfusion therapies. However, evaluating the outcome of these risky therapies beforehand is a complicated task due to the variability of lesion location, size, shape, and cerebral hemodynamics involved. Though the fully automated model for predicting treatment outcomes using multi-parametric imaging would be highly valuable in clinical settings, MRI datasets acquired at the acute stage are mostly scarce and suffer high class imbalance. In this paper, parallel multi-parametric feature embedded siamese network (PMFE-SN) is proposed that can learn with few samples and can handle skewness in multi-parametric MRI data. Moreover, five suitable evaluation metrics that are insensitive to imbalance are defined for this problem. The results show that PMFE-SN not only outperforms other state-of-the-art techniques in all these metrics but also can predict the class with a small number of samples, as well as the class with high number of samples. An accuracy of 0.67 on leave one cross out testing has been achieved with only two samples (minority class) for training and accuracy of 0.61 with the highest number of samples (majority class). In comparison, state-of-the-art using hand crafted features has 0 accuracy for minority class and 0.33 accuracy for majority class.

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Thrombolysis and thrombectomy for acute ischaemic stroke

Cited by 55 publications

References 30 publications

Early Progressive Changes in White Matter Integrity Are Associated with Stroke Recovery

Early Progressive Changes in White Matter Integrity Are Associated with Stroke Recovery

Integrating Multi-Omics Data to Identify Novel Disease Genes and Single-Neucleotide Polymorphisms

Predicting Clinical Outcome in Acute Ischemic Stroke Using Parallel Multi-Parametric Feature Embedded Siamese Network

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