Diagnostic examination performance by using microvascular leakage, cerebral blood volume, and blood flow derived from 3-T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in the differentiation of glioblastoma multiforme and brain metastasis
Diagnostic examination performance by using microvascular leakage, cerebral blood volume, and blood flow derived from 3-T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in the differentiation of glioblastoma multiforme and brain metastasis
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DOI：
10.1007/s00234-010-0740-3
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发表时间：
2011-05-01
期刊：
影响因子：
2.8
通讯作者：
Nakstad, Per H.
中科院分区：
文献类型：
--
作者：
Server, Andres;Orheim, Tone E. Doli;Nakstad, Per H.
传统的磁共振（MR）成像在鉴别多形性胶质母细胞瘤（GBM）和转移瘤方面能力有限。本研究的目的是：（1）采用动态磁共振增强灌注成像（DSC-MRI）比较微血管渗漏（MVL）、脑血容量（CBV）和血流量（CBF）在鉴别GBM转移中的作用，（2）评价灌注和渗透性MR成像的诊断准确性。（40例GBM和21例转移瘤）在3 T下使用DSC-MRI进行。计算肿瘤的标准化rCBV和rCBF（rCBVt、rCBFt）、周围增强区的标准化rCBVe、rCBFe，以及肿瘤中的值除以周围增强区的值（rCBVt/e、rCBFt/e），以及MVL。血流动力学和组织病理学变量进行统计学分析和斯皮尔曼/皮尔逊相关性。对每个变量进行受试者工作特征曲线分析，GBM的rCBVe、rCBFe和MVL均显著高于转移瘤。鉴别GBM与转移的最佳临界值为0.80，这意味着rCBVe比率的敏感性为95%，特异性为92%，阳性预测值为86%，阴性预测值为97%。我们发现rCBVt和rCBFt比值之间存在适度的相关性，GBM的MVL测量值显著高于转移瘤。在统计学上，rCBVe、rCBVt/e和rCBFe、rCBFt/e均有助于鉴别GBM和转移瘤，支持灌注MR成像可检测增强周围区域肿瘤细胞浸润的假设。
Conventional magnetic resonance (MR) imaging has limited capacity to differentiate between glioblastoma multiforme (GBM) and metastasis. The purposes of this study were: (1) to compare microvascular leakage (MVL), cerebral blood volume (CBV), and blood flow (CBF) in the distinction of metastasis from GBM using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC-MRI), and (2) to estimate the diagnostic accuracy of perfusion and permeability MR imaging.A prospective study of 61 patients (40 GBMs and 21 metastases) was performed at 3 T using DSC-MRI. Normalized rCBV and rCBF from tumoral (rCBVt, rCBFt), peri-enhancing region (rCBVe, rCBFe), and by dividing the value in the tumor by the value in the peri-enhancing region (rCBVt/e, rCBFt/e), as well as MVL were calculated. Hemodynamic and histopathologic variables were analyzed statistically and Spearman/Pearson correlations. Receiver operating characteristic curve analysis was performed for each of the variables.The rCBVe, rCBFe, and MVL were significantly greater in GBMs compared with those of metastases. The optimal cutoff value for differentiating GBM from metastasis was 0.80 which implies a sensitivity of 95%, a specificity of 92%, a positive predictive value of 86%, and a negative predictive value of 97% for rCBVe ratio. We found a modest correlation between rCBVt and rCBFt ratios.MVL measurements in GBMs are significantly higher than those in metastases. Statistically, both rCBVe, rCBVt/e and rCBFe, rCBFt/e were useful in differentiating between GBMs and metastases, supporting the hypothesis that perfusion MR imaging can detect infiltration of tumor cells in the peri-enhancing region.