Prediction of Malignant Middle Cerebral Artery Infarction by Diffusion-Weighted Imaging

Autor: R Manaï, A. Srour, T. Lalam, Didier Dormont, Yves Samson, Sophie Crozier, G. Rancurel, Claude Marsault, X. Vandamme, Catherine Oppenheim, Philippe Cornu
Rok vydání: 2000
Předmět:
Zdroj: Stroke. 31:2175-2181
ISSN: 1524-4628
0039-2499
Popis: Background and Purpose —This study was designed to analyze whether early diffusion-weighted imaging (DWI) provides reliable quantitative information for the prediction of stroke patients at risk of malignant brain infarct. Methods —We selected 28 patients with a middle cerebral artery (MCA) infarct and proven MCA or carotid T occlusion on DWI and MRI angiography performed within 14 hours after onset (mean 6.5±3.5 hours, median 5.2 hours). Of these, 10 patients developed malignant MCA infarct, whereas 18 did not. For the 2 groups, we compared the National Institutes of Health Stroke Scale (NIHSS) score at admission, site of arterial occlusion, standardized visual analysis of DWI abnormalities, quantitative volume measurement of DWI abnormalities (volume DWI ), and apparent diffusion coefficient values. Univariate and multivariate discriminant analysis was used to determine the most accurate predictors of malignant MCA infarct. Results —Univariate analysis showed that an admission NIHSS score >20, total versus partial MCA infarct, and volume DWI >145 cm 3 were highly significant predictors of malignant infarct. The best predictor was volume DWI >145 cm 3 , which achieved 100% sensitivity and 94% specificity. Prediction was further improved by bivariate models combining volume DWI and apparent diffusion coefficient measurements, which reached 100% sensitivity and specificity in this series of patients. Conclusions —Quantitative measurement of infarct volume on DWI is an accurate method for the prediction of malignant MCA infarct in patients with persistent arterial occlusion imaged within 14 hours of onset. This may be of importance for early management of severe stroke patients.
Databáze: OpenAIRE