Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical School, No. 119, West Road of South 4th Ring, Beijing, China.
Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical School, No. 119, West Road of South 4th Ring, Beijing, China.
Eur J Radiol. 2022 May;150:110235. doi: 10.1016/j.ejrad.2022.110235. Epub 2022 Mar 7.
To investigate the value of the F-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 F-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 (rSUV), relative maximum cerebral blood flow (rCBF) and relative minimum apparent diffusion coefficient (rADC) 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 rSUV values but higher rCBF and rADC than PCNSL (all P < 0.05). In the PTR, HGG demonstrated significantly higher rSUV and rCBF but lower rADC than PCNSL (all P < 0.05). Multivariate logistic regression based on quantitative parameters revealed that the LRM consisting of rSUV, rADC and rCBF 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 rSUV, rCBF 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 F-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.
探讨 F-FDG PET/MRI 多参数模型在高级别胶质瘤（HGG）和原发性中枢神经系统淋巴瘤（PCNSL）鉴别诊断中的价值，重点在于对增强肿瘤（ET）和非增强肿瘤周围区域（PTR）的定量分析。
回顾性分析了 45 例 HGG 患者和 20 例 PCNSL 患者的资料，所有患者在治疗前均接受了 F-FDG PET、动脉自旋标记灌注加权成像和弥散加权成像的杂交 PET/MRI 检查。计算了 ET 和 NPR 中的相对最大标准化摄取值（rSUV）、相对最大脑血流（rCBF）和相对最小表观扩散系数（rADC），并比较了 HGG 和 PCNSL 之间的差异。采用多变量逻辑回归确定最佳逻辑回归模型（LRM）进行分类。采用受试者工作特征曲线分析评估诊断性能。
在 ET 中，HGG 的 rSUV 值明显低于 PCNSL，但 rCBF 和 rADC 值明显高于 PCNSL（均 P<0.05）。在 PTR 中，HGG 的 rSUV 和 rCBF 值明显高于 PCNSL，rADC 值明显低于 PCNSL（均 P<0.05）。基于定量参数的多变量逻辑回归显示，由 rSUV、rADC 和 rCBF 组成的 LRM 在区分 HGG 和 PCNSL 方面的诊断性能明显优于单一参数，其 AUC 为 0.980，准确率为 95.4%。包含定量参数和常规 MRI 特征的多变量逻辑回归显示，由 rSUV、rCBF 和增强模式组成的 LRM 的 AUC 略高（0.989），准确率相同（95.4%）。两种 LRM 的 AUC 无显著差异（P=0.233）。
基于常规 MRI 特征和增强肿瘤及肿瘤周围区域定量分析的 F-FDG PET/MRI 多参数诊断模型在 HGG 和 PCNSL 的鉴别诊断中优于单一参数，在临床实践中应予以考虑。
