Abstract
Background and PurposeBrain perfusion measurement in the subacute phase of stroke may support therapeutic decisions. We evaluated whether arterial spin labeling (ASL), a noninvasive perfusion imaging technique based on magnetic resonance imaging (MRI), adds diagnostic and prognostic benefit to diffusion‐weighted imaging (DWI) in subacute stroke.MethodsIn a single‐center imaging study, patients with DWI lesion(s) in the middle cerebral artery (MCA) territory were included. Onset to imaging time was ≤7 days and imaging included ASL and DWI sequences. Qualitative (standardized visual analysis) and quantitative perfusion analyses (region of interest analysis) were performed. Dichotomized early outcome (modified Rankin Scale [mRS] 0–2 vs. 3–6) was analyzed in two logistic regression models. Model 1 included DWI lesion volume, age, vascular pathology, admission NIHSS, and acute stroke treatment as covariates. Model 2 added the ASL‐based perfusion pattern to Model 1. Receiver‐operating‐characteristic (ROC) and area‐under‐the‐curve (AUC) were calculated for both models to assess their predictive power. The likelihood‐ratio‐test compared both models.ResultsThirty‐eight patients were included (median age 70 years, admission NIHSS 4, onset to imaging time 67 hr, discharge mRS 2). Qualitative perfusion analysis yielded additional diagnostic information in 84% of the patients. In the quantitative analysis, AUC for outcome prediction was 0.88 (95% CI 0.77–0.99) for Model 1 and 0.97 (95% CI 0.91–1.00) for Model 2. Inclusion of perfusion data significantly improved performance and outcome prediction (p = 0.002) of stroke imaging.ConclusionsIn patients with subacute stroke, our study showed that adding perfusion imaging to structural imaging and clinical data significantly improved outcome prediction. This highlights the usefulness of ASL and noninvasive perfusion biomarkers in stroke diagnosis and management.
Highlights
Predictors of clinical outcome after stroke are necessary to identify high‐risk patients and to guide therapy
Model 2 (DWI + arterial spin labeling (ASL)) contained a compound parameter for ASL‐cerebral blood flow (CBF) perfusion pattern. This parameter consisted of the follow‐ ing two dimensions: type of altered ASL perfusion and relevance
We compared the performance of the two predic‐ tive models: Model 1 (DWI) showed an AUC of 0.88 with a maximum accuracy of 87%, while Model 2 (DWI + ASL) showed an AUC of 0.97 with a maximum accu‐ racy of 95% (Figure 2). Both models were compared using the likeli‐ hood‐ratio‐test (p = 0.002). These results demonstrate that when both ASL‐CBF and ASL‐ bolus arrival time (BAT) maps are taken into consideration, predictions of early neuro‐ logical outcome are significantly improved
Summary
Predictors of clinical outcome after stroke are necessary to identify high‐risk patients and to guide therapy. Brain perfusion is highly dynamic within the first days and some patients may show mismatch patterns beyond 24 hr after stroke (Gonzalez, 2010). This underlines the need for extended hemodynamic validation in order to guide interventions for, for example, blood pressure management or further interventions in patients with high hemodynamic risk. We aimed to evaluate the performance of a certified and commercially available ASL imaging sequence in the subacute phase of stroke as a perfusion biomarker to predict early clinical outcome
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