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Published on: October 20, 2016
Prediction of malignant middle cerebral artery infarction using computed tomography-based intracranial volume reserve
Jens Minnerup1, Heike Wersching, E Bernd Ringelstein
1Department of Clinical Radiology, University of Münster, Albert-Schweitzer-Straße 33, 48149 Münster, Germany. minnerup@uni-muenster.de
Background And Purpose:
Early decompressive surgery in patients with malignant middle cerebral artery (MCA) infarction improves outcome. Elevation of intracranial pressure depends on both the space occupying brain edema and the intracranial volume reserve (cerebrospinal fluid [CSF]). However, CSF volume was not investigated as a predictor of malignant infarction so far. We hypothesize that assessment of CSF volume in addition to admission infarct size improves early prediction of malignant MCA infarction.
Methods:
Stroke patients with carotid-T or MCA main stem occlusion and ischemic lesion (reduced cerebral blood volume [CBV]) on perfusion CT were considered for the analysis. The end point malignant MCA infarction was defined by clinical signs of herniation. Volumes of CSF and CBV lesion were determined on admission. Receiver-operator characteristics analysis was used to calculate predictive values for radiological and clinical measurements.
Results:
Of 52 patients included, 26 (50%) developed malignant MCA infarction. Age, a decreased level of consciousness on admission, CBV lesion volume, CSF volume, and the ratio of CBV lesion volume to CSF volume were significantly different between malignant and nonmalignant groups. The best predictor of a malignant course was the ratio of CBV lesion volume to CSF volume with a cut-off value of 0.92 (96.2% sensitivity, 96.2% specificity, 96.2% positive predictive value, and 96.2% negative predictive value).
Conclusions:
Based on admission native CT and perfusion CT measurements, the ratio of ischemic lesion volume to CSF volume predicts the development of malignant MCA infarction with higher accuracy than other known predictors, including ischemic lesion volume or clinical characteristics.
