Magnetic Resonance Perfusion Imaging Provides a Significant Tool for the Identification of Cardioembolic Stroke

Diagnostic Value of Perfusion Parameters for Differentiation of Underlying Etiology in Internal Carotid Artery Occlusions

PURPOSE

Occlusions of the internal carotid artery (ICA) may be caused by dissection, embolic or macroangiopathic pathogenesis, which partially influences the treatment; however, inferring the underlying etiology in computed tomography angiography can be challenging. In this study, we investigated whether computed tomography perfusion (CT-P) parameters could be used to distinguish between etiologies.

METHODS

Patients who received CT‑P in acute ischemic stroke due to ICA occlusion between 2012 and 2019 were retrospectively analyzed. Group comparisons between etiologies regarding the ratios of CT‑P parameters between both hemispheres for relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), time to maximum (Tmax), and mean transit time (MTT) were calculated by one-factorial analysis of variance (ANOVA) and compared by pairwise Bonferroni post hoc tests. An receiver operating characteristics (ROC) analysis was performed if differences in group comparisons were found. Multinomial logistic regression (MLR) including pretherapeutic parameters was calculated for etiologies.

RESULTS

In this study 69 patients (age = 70 ± 14 years, dissection = 10, 14.5%, embolic = 19, 27.5% and macroangiopathic = 40, 58.0%) were included. Group differences in ANOVA were only found for MTT ratio (p = 0.003, η2 = 0.164). In the post hoc test, MTT ratio showed a differentiability between embolic and macroangiopathic occlusions (p = 0.002). ROC analysis for differentiating embolic and macroangiopathic ICA occlusions based on MTT ratio showed an AUC of 0.77 (p < 0.001, CI = 0.65-0.89) and a cut-off was yielded at a value of 1.15 for the MTT ratio (sensitivity 73%, specificity 68%). The MLR showed an overall good model performance.

CONCLUSION

It was possible to differentiate between patients with embolic and macroangiopathic ICA occlusions based on MTT ratios and to define a corresponding cut-off. Differentiation from patients with dissection versus the other etiologies was not possible by CT‑P parameters in our sample.

Identification of magnetic resonance imaging features for the prediction of unrecognized atrial fibrillation in acute ischemic stroke

Background and purpose

The early identification of cardioembolic stroke is critical for the early initiation of anticoagulant treatment. However, it can be challenging to identify the major cardiac source, particularly since the predominant source, paroxysmal atrial fibrillation (AF), may not be present at the time of stroke. In this study, we aimed to evaluate imaging predictors for unrecognized AF in patients with acute ischemic stroke.

Methods

We performed a cross-sectional analysis of data and magnetic resonance imaging (MRI) scans from two prospective cohorts of patients who underwent serial 12-lead electrocardiography and 24-h Holter monitoring to detect unrecognized AF. The imaging patterns in diffusion-weighted imaging and imaging characteristics were assessed and classified. A logistic regression model was used to identify predictive factors for newly detected AF in patients with acute ischemic stroke.

Results

A total of 734 patients were recruited for analysis, with a median age of 72 (interquartile range: 65–79) years and a median National Institutes of Health Stroke Scale score of 4 (interquartile range: 2–6). Of these patients, 64 (8.7%) had newly detected AF during the follow-up period. Stepwise multivariate logistic regression revealed that age ≥75 years [adjusted odds ratio (aOR) 5.66, 95% confidence interval (CI) 2.98–10.75], receiving recombinant tissue plasminogen activator treatment (aOR 4.36, 95% CI 1.65–11.54), congestive heart failure (aOR 6.73, 95% CI 1.85–24.48), early hemorrhage in MRI (aOR 3.62, 95% CI 1.52–8.61), single cortical infarct (aOR 6.49, 95% CI 2.35–17.92), and territorial infarcts (aOR 3.54, 95% CI 1.06–11.75) were associated with newly detected AF. The C-statistic of the prediction model for newly detected AF was 0.764.

Conclusion

Initial MRI at the time of stroke may be useful to predict which patients have cardioembolic stroke caused by unrecognized AF. Further studies are warranted to verify these findings and their application to high-risk patients.

Comparisons of Characteristics and Outcomes after Mechanical Thrombectomy for Vertebrobasilar Occlusion with Cardioembolism or Atherosclerotic Brain Infarction: Data from the Tokyo-Tama-Registry of Acute Endovascular Thrombectomy (TREAT)

BACKGROUND

Some reports suggest the efficacy of mechanical thrombectomy (MT) for acute vertebrobasilar artery (VBA) occlusion. The major causes of VBA occlusion include cardioembolism (CE) and large-artery atherosclerosis (LAA). However, the clinical characteristics of each cause remain unclear, and they might be important for decision making related to the indications and strategy of MT.

OBJECTIVE

This study aimed to compare functional outcomes and factors affecting outcomes between patients with CE and LAA with acute VBA occlusion.

METHODS

This was a retrospective and prospective observational study using data from TREAT (Tokyo-Tama-Registry of Acute Endovascular Thrombectomy), a multicenter registry of MT for acute large-vessel occlusion in the Tokyo metropolitan area. Patients with VBA occlusion classified into CE and LAA groups were analyzed. The primary outcome was a modified Rankin Scale score of 0-2 at 90 days.

RESULTS

Seventy-nine patients (57 with CE and 22 with LAA) were eligible from January 2015 to March 2020. Despite significantly shorter puncture-to-recanalization and onset-or-last-well-known-to-recanalization times in the CE group, the primary outcome was not significantly different between the 2 groups (CE, 31.6% vs. LAA, 45.5%; P = 0.248). In the subgroup analysis, patients with CE had worse clinical outcomes in the onset-or-last-well-known-to-door time ≥180 minutes, onset-or-last-well-known-to-door time ≥300 minutes, and low posterior circulation Alberta Stroke Program Early CT Score (≤7) subgroups.

CONCLUSIONS

Functional outcomes of VBA occlusion were not significantly different between CE and LAA. Based on the subgroup analysis, patients with CE might have poorer collateral status than do patients with LAA, and earlier recanalization might therefore be desired.

Cardiac natriuretic peptides for diagnosis of covert atrial fibrillation after acute ischaemic stroke: a meta-analysis of diagnostic accuracy studies

Background and purpose

Detection of atrial fibrillation (AF) after acute ischaemic stroke is pivotal for the timely initiation of anticoagulation to prevent recurrence. Besides heart rhythm monitoring, various blood biomarkers have been suggested as complimentary diagnostic tools for AF. We aimed to summarise data on the performance of cardiac natriuretic peptides for the diagnosis of covert AF after acute ischaemic stroke and to assess their potential clinical utility.

Methods

We searched PubMed and Embase for prospective studies reporting the performance of B-type natriuretic peptide (BNP) or N-terminal pro-BNP (NT-proBNP) for the diagnosis of covert AF after acute ischaemic stroke. Summary diagnostic performance measures were pooled using bivariate meta-analysis with a random-effect model.

Results

We included six studies focusing on BNP (n=1930) and three studies focusing on NT-proBNP (n=623). BNP had a sensitivity of 0.83 (95% CI 0.64 to 0.93), a specificity of 0.74 (0.67 to 0.81), a positive likelihood ratio of 3.2 (2.6 to 4.0) and a negative likelihood ratio of 0.23 (0.11 to 0.49). NT-proBNP had a sensitivity of 0.91 (0.65 to 0.98), a specificity of 0.77 (0.52 to 0.91), a positive likelihood ratio of 3.9 (1.8 to 8.7) and a negative likelihood ratio of 0.12 (0.03 to 0.48). Considering a pretest probability of 20%, BNP and NT-proBNP had post-test probabilities of 45% and 50%.

Conclusions

NT-proBNP has a better performance than BNP for the diagnosis of covert AF after acute ischaemic stroke. Both biomarkers have low post-test probabilities and may not be used as a stand-alone decision-making tool for the diagnosis of covert AF in patients with acute ischaemic stroke. However, they may be useful for a screening strategy aiming to select patients for long-term monitoring of the heart rhythm.

WITHDRAWN: Diagnosis of Neural Deterioration in Patients with Cerebral Infarction Combined with Non-valvular Atrial Fibrillation under Magnetic Resonance Imaging and Exploration of the Prognostic Infection Factors

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A Novel Neuroimaging Model to Predict Early Neurological Deterioration After Acute Ischemic Stroke

Objective:

In acute ischemic stroke, early neurological deterioration (END) may occur in up to one-third of patients. However, there is still no satisfying or comprehensive predictive model for all the stroke subtypes. We propose a practical model to predict END using magnetic resonance imaging (MRI).

Method:

Patients with anterior circulation infarct were recruited and they underwent an MRI within 24 hours of stroke onset. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 72 hours of stroke onset. We examined the relationships of END to individual END models, including: A, infarct swelling; B, small subcortical infarct; C, mis-match; and D, recurrence.

Results:

There were 163 patients recruited and 43 (26.4%) of them had END. The END models A, B and C significantly predicted END respectively after adjusting for confounding factors (p=0.022, p=0.007 and p<0.001 respectively). In END model D, we examined all imaging predictors of Recur-rence Risk Estimator (RRE) individually and only the “multiple acute infarcts” pattern was signifi-cantly associated with END (p=0.032). When applying END models A, B, C and D, they success-fully predicted END (p<0.001; odds ratio: 17.5[95% confidence interval: 5.1–60.8]), with 93.0% sensitivity, 60.0% specificity, 45.5% positive predictive value and 96.0% negative predictive value.

Conclusion:

The results demonstrate that the proposed model could predict END in all stroke sub-types of anterior circulation infarction. It provides a practical model for clinical physicians to select high-risk patients for more aggressive treatment to prevent END.