Computed tomography perfusion as an early predictor of malignant cerebral infarction

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Abstract Introduction: Malignant middle cerebral artery infarction (MCI) needs rapid intervention. This study aimed to enhance the prediction of MCI using computed tomography perfusion (CTP) with varied quantitative benchmarks. Materials and Methods: We retrospectively analyzed 253 patients from a single-center registry presenting with acute, severe, proximal large vessel occlusion studied with whole-brain CTP imaging at hospital arrival within the first 24 h of symptoms-onset. MCI was defined by clinical and imaging criteria, including decreased level of consciousness, anisocoria, death due to cerebral edema, or need for decompressive craniectomy, together with midline shift ⩾6 mm, or infarction of more than 50% of the MCA territory. The predictive accuracy of baseline ASPECTS and CTP quantifications for MCI was assessed by receiver operating characteristic (ROC) area under the curve (AUC) while F-score was calculated as an indicator of precision and sensitivity. Results: Sixty-three out of 253 patients (25%) fulfilled MCI criteria and had worse clinical and imaging results than the non-MCI group. The capacity to predict MCI was lower for baseline ASPECTS (AUC 0.83, F-score 0.52, Youden’s index 6), than with perfusion-based measures: relative cerebral blood volume threshold <40% (AUC 0.87, F-score 0.71, Youden’s index 34 mL) or relative cerebral blood flow threshold <35% (AUC 0.87, F-score 0.62, Youden’s index 67 mL). CTP based on rCBV measurements identified twice as many MCI as baseline CT ASPECTS. Discussion and conclusion: CTP-based quantifications may offer enhanced predictive capabilities for MCI compared to non-contrast baseline CT ASPECTS, potentially improving the monitoring of severe ischemic stroke patients at risk of life-threatening edema and its treatment.

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