Differentiating between Glioblastoma and Primary CNS Lymphoma Using Combined Whole-tumor Histogram Analysis of the Normalized Cerebral Blood Volume and the Apparent Diffusion Coefficient.
Differentiating between Glioblastoma and Primary CNS Lymphoma Using Combined Whole-tumor Histogram Analysis of the Normalized Cerebral Blood Volume and the Apparent Diffusion Coefficient.
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DOI：
10.2463/mrms.mp.2017-0135
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发表时间：
2019-01-10
期刊：
影响因子：
--
通讯作者：
Tomiyama N
中科院分区：
文献类型：
--
作者：
Bao S;Watanabe Y;Takahashi H;Tanaka H;Arisawa A;Matsuo C;Wu R;Fujimoto Y;Tomiyama N
本研究旨在确定对比增强病变的标准化脑血容量（nCBV）和表观扩散系数（ADC）的全肿瘤直方图分析是否可用于区分胶质母细胞瘤（GBM）和原发性中枢神经系统淋巴瘤（PCNSL）。20例患者，9例PCNSL和11例GBM无任何出血性病变，接受MRI检查，包括扩散加权成像和动态磁敏感对比灌注加权成像术前。对造影剂增强病变中来自全肿瘤体素的nCBV和ADC进行直方图分析。使用非配对t检验比较每种类型肿瘤的平均值。使用ADC和nCBV的最佳参数进行多变量逻辑回归模型（LRM）以分类GBM和PCNSL。GBM的所有nCBV直方图参数均大于PCNSL，但Bonferroni校正后仅平均nCBV具有统计学意义。同时，GBM的ADC直方图参数也大于PCNSL，但差异无统计学意义。根据受试者工作特征曲线分析，nCBV平均值和ADC第25百分位数的曲线下面积最大，分别为0.869和0.838。结合这两个参数的LRM区分了GBM和PCNSL，曲线下面积值更高（Logit（P）=-21.12 +10.00 × ADC第25百分位数（10 - 3 mm 2/s）+5.420 × nCBV平均值，P < 0.001）。我们的研究结果表明，nCBV和ADC的整体肿瘤直方图分析相结合，可以是一个有价值的客观诊断方法，用于区分GBM和PCNSL。
This study aimed to determine whether whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) and apparent diffusion coefficient (ADC) for contrast-enhancing lesions can be used to differentiate between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL). From 20 patients, 9 with PCNSL and 11 with GBM without any hemorrhagic lesions, underwent MRI, including diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging before surgery. Histogram analysis of nCBV and ADC from whole-tumor voxels in contrast-enhancing lesions was performed. An unpaired t-test was used to compare the mean values for each type of tumor. A multivariate logistic regression model (LRM) was performed to classify GBM and PCNSL using the best parameters of ADC and nCBV. All nCBV histogram parameters of GBMs were larger than those of PCNSLs, but only average nCBV was statistically significant after Bonferroni correction. Meanwhile, ADC histogram parameters were also larger in GBM compared to those in PCNSL, but these differences were not statistically significant. According to receiver operating characteristic curve analysis, the nCBV average and ADC 25th percentile demonstrated the largest area under the curve with values of 0.869 and 0.838, respectively. The LRM combining these two parameters differentiated between GBM and PCNSL with a higher area under the curve value (Logit (P) = −21.12 + 10.00 × ADC 25th percentile (10−3 mm2/s) + 5.420 × nCBV mean, P < 0.001). Our results suggest that whole-tumor histogram analysis of nCBV and ADC combined can be a valuable objective diagnostic method for differentiating between GBM and PCNSL.
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