Quantitative Multiparametric MRI of Ovarian Cancer

PurposeTo identify parameters associated with ovarian malignancy using multiparametric quantitative magnetic resonance imaging (MRI). Materials and MethodsAfter Institutional Review Board (IRB) approval, women with ovarian masses underwent preoperative imaging with 3 T MRI. Dynamic contrast-enhanced (DCE)-MRI with pharmacokinetic modeling, quantitative T-2 mapping, and diffusion-weighted imaging with quantitative mapping of the water diffusion parameters were performed. Ovarian masses had one or more discreet regions of interest, categorized as cystic or solid, and histologically diagnosed as benign or malignant. Mean region of interest (ROI) values were compared between benign and malignant masses using generalized estimating equations. In addition, we compared classification accuracy for the mean ROI value to a combination of histogram characteristics (standard deviation, skewness, and kurtosis) from T-2 map ROIs using logistic regression and ROC curve. The significance level was P = 0.05. ResultsSeveral DCE-MRI parameters differentiated solid benign from malignant masses. Toft's rate constant (k(ep)) was significantly higher in malignant masses (P < 0.001), as well as quantitative T-2 values (P = 0.003), and signal intensity on T-2 weighted imaging (P = 0.008). A linear combination of the mean, standard deviation, skewness, and kurtosis of T-2 within solid regions (area under the curve [AUC] 0.90) provided better classification accuracy than the mean of T-2 alone (AUC 0.81). ConclusionQuantitative parameters from DCE-MRI and T-2 mapping can differentiate benign from malignant ovarian masses.