Differentiation of high-grade glioma and primary central nervous system lymphoma: Multiparametric imaging of the enhancing tumor and peritumoral regions based on hybrid 18F-FDG PET/MRI

医学 核医学 原发性中枢神经系统淋巴瘤 接收机工作特性 逻辑回归 有效扩散系数 胶质瘤 多元分析 曲线下面积 淋巴瘤 磁共振成像 放射科 病理 内科学 癌症研究
作者
Shu Zhang,Jie Wang,Kai Wang,Xiaotong Li,Xiaobin Zhao,Qian Chen,Wei Zhang,Lin Ai
出处
期刊:European Journal of Radiology [Elsevier]
卷期号:150: 110235-110235 被引量:10
标识
DOI:10.1016/j.ejrad.2022.110235
摘要

To investigate the value of the 18F-FDG PET/MRI multiparametric model in the differentiation of high-grade glioma (HGG) and primary central nervous system lymphoma (PCNSL), with emphasis on the quantitative analysis of the enhancing tumor (ET) and non-enhancing peritumoral region (PTR).Forty-five patients with HGG and 20 patients with PCNSL who underwent simultaneous 18F-FDG PET, arterial spin labelling perfusion-weighted imaging and diffusion-weighted imaging with hybrid PET/MRI before treatment were retrospectively enrolled. The relative maximum standardized uptake value (rSUVmax), relative maximum cerebral blood flow (rCBFmax) and relative minimum apparent diffusion coefficient (rADCmin) in both the ET and NPR were calculated and compared between HGG and PCNSL. Multivariate logistic regression was used to determine the best logistic regression model (LRM) for classification. Receiver operating curve analysis was used to assess diagnostic performance.In the ET, HGG showed significantly lower rSUVmax values but higher rCBFmax and rADCmin than PCNSL (all P < 0.05). In the PTR, HGG demonstrated significantly higher rSUVmax and rCBFmax but lower rADCmin than PCNSL (all P < 0.05). Multivariate logistic regression based on quantitative parameters revealed that the LRM consisting of rSUVmax_ET, rADCmin_ET and rCBFmax_PTR had significantly improved diagnostic performance in differentiating HGG from PCNSL than single parameter alone, with an AUC of 0.980 and an accuracy of 95.4%. Multivariate logistic regression incorporating quantitative parameters and conventional MRI features revealed that the LRM consisting of rSUVmax_ET, rCBFmax_PTR and enhancement pattern yielded a slightly higher AUC of 0.989 and an identical accuracy of 95.4%. No significant difference in AUCs was detected between the two LRMs (P = 0.233).Multiparametric 18F-FDG PET/MRI diagnostic model based on conventional MRI features and quantitative analysis of the enhancing tumors and peritumoral regions is superior to single parameter in the differentiation of HGG and PCNSL, which should be considered in the clinical practice.
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