Xu Weilin, Wang Qun, Shao Anwen, Xu Bainan, Zhang Jianmin
Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Department of Neurosurgery, Chinese PLA General Hospital, Haidian District, Beijing, China.
PLoS One. 2017 Mar 16;12(3):e0173430. doi: 10.1371/journal.pone.0173430. eCollection 2017.
It is always a great challenge to distinguish high-grade glioma (HGG) from primary central nervous system lymphoma (PCNSL). We conducted a meta-analysis to assess the performance of MR perfusion-weighted imaging (PWI) in differentiating HGG from PCNSL. The heterogeneity and threshold effect were evaluated, and the sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC) were calculated. Fourteen studies with a total of 598 participants were included in this meta-analysis. The results indicated that PWI had a high level of accuracy (area under the curve (AUC) = 0.9415) for differentiating HGG from PCNSL by using the best parameter from each study. The dynamic susceptibility-contrast (DSC) technique might be an optimal index for distinguishing HGGs from PCNSLs (AUC = 0.9812). Furthermore, the DSC had the best sensitivity 0.963 (95%CI: 0.924, 0.986), whereas the arterial spin-labeling (ASL) displayed the best specificity 0.896 (95% CI: 0.781, 0.963) among those techniques. However, the variability of the optimal thresholds from the included studies suggests that further evaluation and standardization are needed before the techniques can be extensively clinically used.
区分高级别胶质瘤（HGG）与原发性中枢神经系统淋巴瘤（PCNSL）一直是一项巨大挑战。我们进行了一项荟萃分析，以评估磁共振灌注加权成像（PWI）在鉴别HGG与PCNSL方面的性能。评估了异质性和阈值效应，并计算了敏感性（SEN）、特异性（SPE）和汇总接受者操作特征曲线（SROC）下的面积。本荟萃分析纳入了14项研究，共598名参与者。结果表明，通过使用每项研究的最佳参数，PWI在区分HGG与PCNSL方面具有较高的准确性（曲线下面积（AUC）=0.9415）。动态磁敏感对比（DSC）技术可能是区分HGG与PCNSL的最佳指标（AUC=0.9812）。此外，在这些技术中，DSC的敏感性最佳，为0.963（95%CI：0.924，0.986），而动脉自旋标记（ASL）的特异性最佳，为0.896（95%CI：0.781，0.963）。然而，纳入研究中最佳阈值的变异性表明，在这些技术能够广泛应用于临床之前，还需要进一步评估和标准化。
