Abstract

Using conventional magnetic resonance imaging (MRI) methods, the differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is often difficult due to overlapping imaging characteristics. This study aimed to evaluate the diagnostic value of combining 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) with arterial spin labeling (ASL) for differentiating PCNSL from GBM. In all, 20 patients with PCNSL and 55 with GBM were retrospectively examined. From the FDG-PET data, the maximum standardized uptake values (SUVmax) and the ratio of tumor to normal contralateral gray matter (T/N_SUVmax) were calculated. From the ASL data, the T/N ratio of the maximum tumor blood flow (relative TBFmax: rTBFmax) was obtained. Diagnostic performance of each parameter was analyzed using univariate and multivariate logistic regression analyses and receiver-operating characteristic (ROC) curve analyses. A generalized linear model was applied for comparing the performance of FDG-PET and ASL individually, and in combination. In univariate analysis, SUVmax and T/N_SUVmax were statistically higher in patients with PCNSL and rTBFmax was higher in patients with GBM. In the multivariate analysis, T/N_SUVmax and rTBFmax were statistically independent. The sensitivity, specificity, and area under the curve (AUC) for discriminating PCNSL from GBM were 100%, 87.3%, and 0.950 in T/N_SUVmax; 90%, 72.7%, and 0.824 in rTBFmax; and 95%, 96.4%, and 0.991 in the combined model, respectively. The combined use of T/N_SUVmax and rTBFmax may contribute to better differentiation between PCNSL and GBM.

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