医学
流体衰减反转恢复
磁共振成像
溶栓
冲程(发动机)
梗塞
高强度
放射科
血栓
磁共振弥散成像
有效扩散系数
脑梗塞
核医学
内科学
心脏病学
心肌梗塞
缺血
工程类
机械工程
作者
Rody El Nawar,Jennifer Yeung,Julien Labreuche,Marie‐Laure Chadenat,Duc Long Duong,Maxime De Malherbe,Yves‐Sebastien Cordoliani,Bertrand Lapergue,Fernando Pico
标识
DOI:10.3389/fneur.2019.00897
摘要
Clinical and biological risk factors for hemorrhagic transformation (HT) after intravenous thrombolysis (IT) have been well established in several registries. The added value of magnetic resonance imaging (MRI) variables has been studied in small samples, and is controversial. We aimed to assess the added value of MRI variables in HT, beyond that of clinical and biological factors. We enrolled 474 consecutive patients with brain infarction treated by IT alone at our primary stroke center between January 2011 and August 2017. Baseline demographic, clinical, biological, and imaging characteristics were collected. MRI variables were: brain infarction volume in cm3; parenchymal fluid attenuated inversion recovery (FLAIR) hyperintensity; FLAIR hyperintense vessel signs; number of microbleeds; subcortical white matter hyperintensity; and thrombus length. Overall, 301patients were included out of 474 (64%). The main causes of exclusion were combined thrombectomy (n=98) and no MRI before IT (n=44). In the bivariate analysis, HT was significantly associated with the presence of more FLAIR hyperintense vessel signs, thrombus length (>8mm), and larger brain infarction volume (diffusion-weighted imaging (DWI) and apparent diffusion coefficient<500´10-6 mm2/s). In the multivariable analysis, only brain infarction volume was significantly associated with HT. The discrimination value of the multivariable model, including both the DWI volume and the clinical model (area under the receiver operating characteristic curve, 0.80;95%confidence interval 0.74 to 0.86), was improved significantly compared with the model based only on clinical variables (P=0.012). Brain infarction volume on DWI was the only MRI variable that added value to clinico biological variables for predicting HT after IT.
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