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Neuroradiology

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01.11.2015 | Diagnostic Neuroradiology

MR image features predicting hemorrhagic transformation in acute cerebral infarction: a multimodal study

verfasst von: Chunming Liu, Zhengchao Dong, Liang Xu, Aiman Khursheed, Longchun Dong, Zhenxing Liu, Jun Yang, Jun Liu

Erschienen in: Neuroradiology | Ausgabe 11/2015

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Abstract

Introduction

The aims of this study were to observe magnetic resonance imaging (MRI) features and the frequency of hemorrhagic transformation (HT) in patients with acute cerebral infarction and to identify the risk factors of HT.

Methods

We first performed multimodal MRI (anatomical, diffusion weighted, and susceptibility weighted) scans on 87 patients with acute cerebral infarction within 24 hours after symptom onset and documented the image findings. We then performed follow-up examinations 3 days to 2 weeks after the onset or whenever the conditions of the patients worsened within 3 days. We utilized univariate statistics to identify the correlations between HT and image features and used multivariate logistical regression to correct for confounding factors to determine relevant independent image features of HT.

Results

HT was observed in 17 out of total 87 patients (19.5 %). The infarct size (p = 0.021), cerebral microbleeds (CMBs) (p = 0.004), relative apparent diffusion (rADC) (p = 0.023), and venous anomalies (p = 0.000) were significantly related with HT in the univariate statistics. Multivariate analysis demonstrated that CMBs (odd ratio (OR) = 0.082; 95 % confidence interval (CI) = 0.011–0.597; p = 0.014), rADC (OR = 0.000; 95 % CI = 0.000–0.692; p = 0.041), and venous anomalies (OR = 0.066; 95 % CI = 0.011–0.403; p = 0.003) were independent risk factors for HT.

Conclusions

The frequency of HT is 19.5 % in this study. CMBs, rADC, and venous anomalies are independent risk factors for HT of acute cerebral infarction.

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Titel: MR image features predicting hemorrhagic transformation in acute cerebral infarction: a multimodal study
verfasst von: Chunming Liu
Zhengchao Dong
Liang Xu
Aiman Khursheed
Longchun Dong
Zhenxing Liu
Jun Yang
Jun Liu
Publikationsdatum: 01.11.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Neuroradiology / Ausgabe 11/2015
Print ISSN: 0028-3940
Elektronische ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-015-1575-8

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Abstract

Introduction

Methods

Results

Conclusions

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