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

Abstract

Objectives: 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).

Methods: 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 (rSUV_max), relative maximum cerebral blood flow (rCBF_max) and relative minimum apparent diffusion coefficient (rADC_min) 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.

Results: In the ET, HGG showed significantly lower rSUV_max values but higher rCBF_max and rADC_min than PCNSL (all P < 0.05). In the PTR, HGG demonstrated significantly higher rSUV_max and rCBF_max but lower rADC_min than PCNSL (all P < 0.05). Multivariate logistic regression based on quantitative parameters revealed that the LRM consisting of rSUV_{max_ET}, rADC_{min_ET} and rCBF_{max_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 rSUV_{max_ET}, rCBF_{max_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).

Conclusions: 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.

Keywords: Differential diagnosis; Diffusion-weighted imaging; FDG PET; High-grade glioma; Perfusion-weighted imaging; Primary central nervous system lymphoma.