Computed tomography perfusion as an early predictor of malignant cerebral infarction

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.

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.

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.

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.