Multiparametric Framework Magnetic Resonance Imaging Assessment of Subtypes of Intracranial Germ Cell Tumors Using Susceptibility Weighted Imaging, Diffusion-Weighted Imaging, and Dynamic Susceptibility-Contrast Perfusion-Weighted Imaging Combined With Conventional Magnetic Resonance Imaging.

Abstract

Intracranial germ cell tumors (iGCTs) are classified into two pathological subtypes (germinomas [GEs] and nongerminomatous germ cell tumors [NGGCTs]), with distinct treatment strategy and prognosis. Accurate preoperative determination of iGCT subtypes is essential to guide clinical decision-making and prognosis assessment. To investigate the diagnostic value of diffusion-weighted imaging (DWI), susceptibility weighted imaging (SWI), and dynamic susceptibility-contrast perfusion-weighted imaging (DSC-PWI) combined with conventional magnetic resonance imaging (cMRI) in finding subtypes of iGCTs. Retrospective. A total of 40 patients (45% male and 55% female) with iGCTs. A 3 T; <T1WI, T2WI, T1WI + C, DWI, SWI, DSC-PWI>. The parameters of DWI and DSC-PWI were calculated based on extracted parameters of multiparametric MRIs. The characteristics of SWI and cMRI were also compared in GEs and NGGCTs. The diagnostic efficacy of the minimum apparent diffusion coefficient (ADCmin), time-to-peak (TTP), relative mean transit time (rMTT), relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV) maps, and cMRI features in iGCT classification was evaluated by receiver operating characteristic curve (ROC) analyses. We calculated the sensitivity, specificity, AUC, and Youden index of the hybrid MR evaluation methods. A prospective cohort (five GEs and five NGGCTs) was designed as a simulation set to test the model. The significance threshold was set at P < 0.01. The ADCmin (1039.100 ± 453.830 vs. 1400.050 ± 394.650), rCBF values (20.650 ± 6.260 vs. 51.170 ± 6.570), and TTP values (24.450 ± 3.160 vs. 28.950 ± 5.120) were significantly lower in GEs than in NGGCTs. The combination of ADCmin, DSC-PWI, and cMRI showed the heights AUC (AUC=0.962). The iGCT multiparametric framework showed the AUC was 0.958 in the simulation set. The iCGT multiparametric framework might be an effective diagnostic approach of iGCT subtype. The application of cMRI (T1WI, T2WI, and Gd-T1WI) with advanced imaging modalities (DWI, SWI, and PWI) had the best performance for classifying iGCT subtypes. 3 TECHNICAL EFFICACY: Stage 2.