Saini J, Kumar Gupta P, Awasthi A, Pandey C M, Singh A, Patir R, Ahlawat S, Sadashiva N, Mahadevan A, Kumar Gupta R
Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India.
Departments of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, India.
Clin Radiol. 2018 Nov;73(11):986.e7-986.e15. doi: 10.1016/j.crad.2018.07.107. Epub 2018 Sep 7.
To compare the diagnostic performance of T1 perfusion magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and susceptibility-weighted imaging (SWI) for differentiating primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM).
This retrospective study comprised a cohort of 70 patients with glioblastoma and 30 patients with PCNSL. T1 perfusion MRI-derived rCBV_corr (leakage corrected relative cerebral blood volume), apparent diffusion coefficient (ADC) derived from DWI, and intratumoural susceptibility signals intensity (ITSS) measured on SWI were evaluated in these 100 patients. The Mann-Whitney U-test was used for pairwise comparison between groups. The diagnostic performance for differentiating PCNSL from glioblastoma was evaluated by using univariate and multivariable logistic regression analyses and receiver operating characteristic (ROC) analysis.
Minimum ADC, maximum rCBVs_corr, k (back flux exchange rate), and ITSS scores were significantly lower in patients with PCNSL than in those with glioblastoma (p<0.05). On ROC analysis, ITSS showed the best discrimination ability for differentiation of GBM and PCNSL with an area under the ROC curve (AUC) of 0.80. rCBV_corr and ADC showed AUCs of 0.68 and 0.63, respectively. Multiparametric assessment using ADC, rCBV_corr, k, and ITSS scores significantly increased the diagnostic ability for differentiating PCNSL from GBM as compared to mean ADC, mean rCBV_corr, and ITSS alone or a combination of these parameters. The multiparametric model could correctly discriminate 84% of tumours with a sensitivity and specificity of 90% and 70% with an AUC of 0.92.
Multiparametric MRI evaluation using DWI, T1 perfusion MRI, and SWI enabled reliable differentiation of PCNSL and GBM in the majority patients, and these results support an integration of advanced MRI techniques for the diagnostic work-up of patients with these tumours.
比较T1灌注磁共振成像(MRI)、扩散加权成像(DWI)和磁敏感加权成像(SWI)在鉴别原发性中枢神经系统淋巴瘤(PCNSL)和胶质母细胞瘤(GBM)方面的诊断性能。
这项回顾性研究纳入了70例胶质母细胞瘤患者和30例PCNSL患者。对这100例患者评估了T1灌注MRI得出的rCBV_corr(渗漏校正相对脑血容量)、DWI得出的表观扩散系数(ADC)以及SWI测量的肿瘤内磁敏感信号强度(ITSS)。采用Mann-Whitney U检验进行组间两两比较。通过单变量和多变量逻辑回归分析以及受试者工作特征(ROC)分析评估鉴别PCNSL和胶质母细胞瘤的诊断性能。
PCNSL患者的最小ADC、最大rCBVs_corr、k(反流交换率)和ITSS评分显著低于胶质母细胞瘤患者(p<0.05)。在ROC分析中,ITSS对GBM和PCNSL的鉴别能力最佳,ROC曲线下面积(AUC)为0.80。rCBV_corr和ADC的AUC分别为0.68和0.63。与单独的平均ADC、平均rCBV_corr和ITSS或这些参数的组合相比,使用ADC、rCBV_corr、k和ITSS评分进行多参数评估显著提高了鉴别PCNSL和GBM的诊断能力。多参数模型能够正确鉴别84%的肿瘤,敏感性和特异性分别为90%和70%,AUC为0.92。
使用DWI、T1灌注MRI和SWI进行多参数MRI评估能够在大多数患者中可靠地区分PCNSL和GBM,这些结果支持将先进的MRI技术整合到这些肿瘤患者的诊断检查中。