MR Imaging-Based Analysis of Glioblastoma Multiforme: Estimation of IDH1 Mutation Status

基于磁共振成像的多形性胶质母细胞瘤分析:IDH1突变状态的评估

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Abstract

BACKGROUND AND PURPOSE: Glioblastoma multiforme is highly aggressive and the most common type of primary malignant brain tumor in adults. Imaging biomarkers may provide prognostic information for patients with this condition. Patients with glioma with isocitrate dehydrogenase 1 (IDH1) mutations have a better clinical outcome than those without such mutations. Our purpose was to investigate whether the IDH1 mutation status in glioblastoma multiforme can be predicted by using MR imaging. MATERIALS AND METHODS: We retrospectively studied 55 patients with glioblastoma multiforme with wild type IDH1 and 11 patients with mutant IDH1. Absolute tumor blood flow and relative tumor blood flow within the enhancing portion of each tumor were measured by using arterial spin-labeling data. In addition, the maximum necrosis area, the percentage of cross-sectional necrosis area inside the enhancing lesions, and the minimum and mean apparent diffusion coefficients were obtained from contrast-enhanced T1-weighted images and diffusion-weighted imaging data. Each of the 6 parameters was compared between patients with wild type IDH1 and mutant IDH1 by using the Mann-Whitney U test. The performance in discriminating between the 2 entities was evaluated by using receiver operating characteristic analysis. RESULTS: Absolute tumor blood flow, relative tumor blood flow, necrosis area, and percentage of cross-sectional necrosis area inside the enhancing lesion were significantly higher in patients with wild type IDH1 than in those with mutant IDH1 (P < .05 each). In contrast, no significant difference was found in the ADC(minimum) and ADC(mean). The area under the curve for absolute tumor blood flow, relative tumor blood flow, percentage of cross-sectional necrosis area inside the enhancing lesion, and necrosis area were 0.850, 0.873, 0.739, and 0.772, respectively. CONCLUSIONS: Tumor blood flow and necrosis area calculated from MR imaging are useful for predicting the IDH1 mutation status.

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