Quantifying Tumor Vascular Heterogeneity With DCE-MRI in Complex Adnexal Masses: A Preliminary Study

Purpose: To evaluate the value of quantifying dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) heterogeneity to characterize adnexal masses. Materials and Methods: Our database was retrospectively queried to identify all surgically proven adnexal masses characterized with a 1.5T DCE-MRI between January 1st 2008 and February 28th 2010 (n=113 masses, including 52 benign, 11 borderline, and 50 invasive malignant tumors). The solid component of the adnexal mass was segmented. Quantitative analysis with a compartmental model was performed to calculate microvascular parameters, including tissue blood flow (F-T), blood volume fraction (V-b), lag time (D-AT), interstitial volume fraction (V-e), permeability-surface area product (PS), and relative area under curve ((r)AUC), were calculated. Then heterogeneity parameters were evaluated using the analysis of the evolution of the standard deviation (SD) of signal intensities on DCE-MRI series. The area under the receiver operating characteristic (AUROC) curve was calculated to assess the overall discrimination of parameters. Results: Malignant tumors displayed higher F-T, V-b, and (r)AUC and lower D-AT than benign tumors (P=0.01, P < 0.0001, and P < 0.0001, respectively). Invasive malignant tumors displayed lower V-b and (r)AUC than borderline tumors (P < 0.01). After injection, whenever the heterogeneity parameter was considered, malignant tumors were more heterogeneous than benign tumors, invasive tumors were more heterogeneous than borderline ovarian tumors, and malignant tumors with carcinomatosis were more heterogeneous than tumors without carcinomatosis (P < 0.001). The most discriminant parameter was the SD during the 90 seconds after injection related to arterial input function (SDEARLY/AIF) with an AUROC between 0.715 and 0.808. Conclusion: This study proposes heterogeneity parameters as a new tool with a potential for clinical application, given that the technique uses routine imaging sequences.