Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion

Introduction: Solitary brain metastasis (MET) and glioblastoma multiforme (GBM) can appear similar on conventional MRI. The purpose of this study was to identify magnetic resonance (MR) perfusion and diffusion-weighted biomarkers that can differentiate MET from GBM. Methods: In this retrospective study, patients were included if they met the following criteria: underwent resection of a solitary enhancing brain tumor and had preoperative 3.0 T MRI encompassing diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) perfusion. Using co-registered images, voxel-based fractional anisotropy (FA), mean diffusivity (MD), K^trans, and relative cerebral blood volume (rCBV) values were obtained in the enhancing tumor and non-enhancing peritumoral T2 hyperintense region (NET2). Data were analyzed by logistic regression and analysis of variance. Receiver operating characteristic (ROC) analysis was performed to determine the optimal parameter/s and threshold for predicting of GBM vs. MET. Results: Twenty-three patients (14 M, age 32–78 years old) met our inclusion criteria. Pathology revealed 13 GBMs and 10 METs. In the enhancing tumor, rCBV, K^trans, and FA were higher in GBM, whereas MD was lower, neither without statistical significance. In the NET2, rCBV was significantly higher (p = 0.05) in GBM, but MD was significantly lower (p < 0.01) in GBM. FA and K^trans were higher in GBM, though not reaching significance. The best discriminative power was obtained in NET2 from a combination of rCBV, FA, and MD, resulting in an area under the curve (AUC) of 0.98. Conclusion: The combination of MR diffusion and perfusion matrices in NET2 can help differentiate GBM over solitary MET with diagnostic accuracy of 98 %.