Time-dependent diffusion magnetic resonance imaging for the analysis of parotid gland tumors

Background Different parotid tumors differ in terms of treatment strategies due to their distinct biological behaviors. Time-dependent diffusion magnetic resonance imaging (t d -dMRI) can characterize and quantify the cytological indexes, and then aid the differential diagnosis of various tumors. However, the value of t d -dMRI in the analysis of parotid gland tumors remains unclear. Purpose To investigate the value of quantitative parameters derived from t d -dMRI in the analysis of parotid gland tumors. Material and Methods In total, 39 patients with parotid gland tumors were prospectively enrolled, including 24 patients with polymorphic adenomas (PAs), eight with Warthin's tumors (WTs), and seven with malignant tumors (MTs). T d -dMRI was performed for preoperative evaluation. Intracellular volume fraction ( V in ), mean cell size ( d), extracellular diffusion coefficient ( D ex ), and cellularity were obtained based on the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion model, and compared among the three groups. One-way ANOVA, Kruskal–Wallis test, and receiver operating characteristic (ROC) curve analysis were performed for further statistical analysis as appropriate. Results Significant differences were found in all t d -dMRI-derived indexes among PAs, WTs, and MTs (all P < 0.05). V in was the sole parameter with significant differences for all sub-group comparisons (PAs vs. WTs, P < 0.001; PAs vs. MTs, P = 0.031; WTs vs. MTs, P = 0.047). With V in values of 0.267, 0.231, and 0.260 as threshold, respectively, optimal performance levels were obtained for differentiating PAs from WTs (area under the ROC curve [AUC]=0.932, sensitivity=0.917, and specificity=0.875), PAs from MTs (AUC=0.744, sensitivity=0.833, and specificity=0.714), and WTs from MTs (AUC=0.750, sensitivity=0.875, and specificity=0.714). Conclusion Microstructural parameters derived from t d -dMRI, especially V in , might be promising imaging biomarkers for characterizing parotid gland tumors.