Abstract

ObjectiveThe objective of this paper was to explore the utility of time to maximum concentration (Tmax)‐based target mismatch on computed tomography perfusion (CTP) in predicting radiological and clinical outcomes in patients with acute ischemic stroke (AIS) with anterior circulation large vessel occlusion (LVO) selected for endovascular treatment (EVT).MethodsPatients with AIS underwent CTP within 24 hours from onset followed by EVT. Critically hypoperfused tissue and ischemic core volumes were automatically calculated using Tmax thresholds >9.5 seconds and >16 seconds, respectively. The difference between Tmax > 9.5 seconds and Tmax > 16 seconds volumes and the ratio between Tmax > 9.5 seconds and Tmax > 16 seconds volumes were considered ischemic penumbra and Tmax mismatch ratio, respectively. Final infarct volume (FIV) was measured on follow‐up non‐contrast computed tomography (CT) at 24 hours. Favorable clinical outcome was defined as 90‐day modified Rankin Scale 0 to 2. Predictors of FIV and outcome were assessed with multivariable logistic regression. Optimal Tmax volumes for identification of good outcome was defined using receiver operating curves.ResultsA total of 393 patients were included, of whom 298 (75.8%) achieved successful recanalization and 258 (65.5%) achieved good outcome. In multivariable analyses, all Tmax parameters were independent predictors of FIV and outcome. Tmax > 16 seconds volume had the strongest association with FIV (beta coefficient = 0.596 p <0.001) and good outcome (odds ratio [OR] = 0.96 per 1 ml increase, 95% confidence interval [CI] = 0.95–0.97, p < 0.001). Tmax > 16 seconds volume had the highest discriminative ability for good outcome (area under the curve [AUC] = 0.88, 95% CI = 0.842–0.909). A Tmax > 16 seconds volume of ≤67 ml best identified subjects with favorable outcome (sensitivity = 0.91 and specificity = 0.73).InterpretationTmax target mismatch predicts radiological and clinical outcomes in patients with AIS with LVO receiving EVT within 24 hours from onset. ANN NEUROL 2022;91:878–888

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