Department of Radiology, Fujita Health University.
Department of Neurosurgery, Fujita Health University.
Magn Reson Med Sci. 2018 Jan 10;17(1):42-49. doi: 10.2463/mrms.mp.2016-0113. Epub 2017 May 18.
We evaluated the diagnostic performance of histogram analysis of data from a combination of dynamic susceptibility contrast (DSC)-MRI and dynamic contrast-enhanced (DCE)-MRI for quantitative differentiation between central nervous system lymphoma (CNSL) and high-grade glioma (HGG), with the aim of identifying useful perfusion parameters as objective radiological markers for differentiating between them.
Eight lesions with CNSLs and 15 with HGGs who underwent MRI examination, including DCE and DSC-MRI, were enrolled in our retrospective study. DSC-MRI provides a corrected cerebral blood volume (cCBV), and DCE-MRI provides a volume transfer coefficient (K) for transfer from plasma to the extravascular extracellular space. K and cCBV were measured from a round region-of-interest in the slice of maximum size on the contrast-enhanced lesion. The differences in t values between CNSL and HGG for determining the most appropriate percentile of K and cCBV were investigated. The differences in K, cCBV, and K/cCBV between CNSL and HGG were investigated using histogram analysis. Receiver operating characteristic (ROC) analysis of K, cCBV, and K/cCBV ratio was performed.
The 30 percentile (C30) in K and 80 percentile (C80) in cCBV were the most appropriate percentiles for distinguishing between CNSL and HGG from the differences in t values. CNSL showed significantly lower C80 cCBV, significantly higher C30 K, and significantly higher C30 K/C80 cCBV than those of HGG. In ROC analysis, C30 K/C80 cCBV had the best discriminative value for differentiating between CNSL and HGG as compared to C30 K or C80 cCBV.
The combination of K by DCE-MRI and cCBV by DSC-MRI was found to reveal the characteristics of vascularity and permeability of a lesion more precisely than either K or cCBV alone. Histogram analysis of these vascular microenvironments enabled quantitative differentiation between CNSL and HGG.
我们评估了动态对比磁共振成像（DSC-MRI）和动态对比增强磁共振成像（DCE-MRI）数据的直方图分析在中枢神经系统淋巴瘤（CNSL）和高级别胶质瘤（HGG）的定量鉴别中的诊断性能，旨在确定有用的灌注参数作为客观的影像学标志物来区分它们。
我们回顾性研究了 8 例 CNSL 病变和 15 例 HGG 病变患者，这些患者均接受了 MRI 检查，包括 DCE 和 DSC-MRI。DSC-MRI 提供校正的脑血容量（cCBV），DCE-MRI 提供从血浆到血管外细胞外空间的容积转移系数（K）。在对比增强病变的最大层面上，使用圆形 ROI 测量 K 和 cCBV。研究了 K 和 cCBV 的 t 值差异，以确定确定 K 和 cCBV 的最佳百分位数。使用直方图分析研究了 K、cCBV 和 K/cCBV 之间的差异。对 K、cCBV 和 K/cCBV 比值进行了接收器工作特征（ROC）分析。
K 的 30 百分位数（C30）和 cCBV 的 80 百分位数（C80）是从 t 值差异中区分 CNSL 和 HGG 的最佳百分位数。与 HGG 相比，CNSL 显示出明显更低的 C80 cCBV、明显更高的 C30 K 和明显更高的 C30 K/C80 cCBV。在 ROC 分析中，与 C30 K 或 C80 cCBV 相比，C30 K/C80 cCBV 对区分 CNSL 和 HGG 具有最佳的鉴别价值。
与单独的 K 或 cCBV 相比，DCE-MRI 的 K 和 DSC-MRI 的 cCBV 的组合能够更准确地揭示病变的血管生成和通透性特征。这些血管微环境的直方图分析能够对 CNSL 和 HGG 进行定量区分。
