Literature DB >> 14716233

Malignant middle cerebral artery infarction in hyperacute ischemic stroke: evaluation with multiphasic perfusion computed tomography maps.

Jae Wook Ryoo1, Dong Gyu Na, Sam Soo Kim, Kwang Ho Lee, Soo Joo Lee, Chin-Sang Chung, Dae Seob Choi.   

Abstract

OBJECTIVE: The purpose of this study was to compare the incidence of large hypoperfusion (greater than two-thirds of MCA territory) on computed tomography (CT) perfusion maps between hyperacute middle cerebral artery (MCA) stroke patients without or with malignant cerebral edema.
METHODS: Twenty-seven patients diagnosed with a hyperacute MCA stroke who had an initial National Institutes of Health Stroke Scale (NIHSS) score greater than 10 were included. Multiphasic perfusion CT was performed within 6 hours of symptom onset. Patients were divided into 2 groups: the malignant group (n = 11), composed of patients who died within 7 days, and the nonmalignant group, which included all other patients (n = 16). Unenhanced CT and CT perfusion maps were assessed and compared between the 2 groups with special emphasis on examining the CT findings, including hyperdense MCA sign, large (greater than two-thirds) hypoattenuation and hypoperfusion in the MCA territory, and hypoattenuation in the basal ganglia and other vascular territories.
RESULTS: The incidence of large hypoattenuation (greater than two-thirds of MCA territory) on unenhanced CT and large hypoperfusion on CT perfusion maps differed significantly between the 2 groups (P < 0.05). Large hypoperfusion on the CT total perfusion map was most accurate (93%) among various CT findings for the prediction of malignant MCA infarction with high sensitivity (91%), specificity (94%), and positive predictive value (91%).
CONCLUSIONS: The incidence of large hypoperfusion on a CT perfusion map was higher in the malignant group than the nonmalignant group. CT perfusion maps may provide added information about cerebral perfusion and could be a useful predictor of malignant MCA infarction.

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Year:  2004        PMID: 14716233     DOI: 10.1097/00004728-200401000-00009

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  10 in total

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