LAUSR

Simple Summary Epithelial ovarian cancer (EOC) has always been considered one of the most challenging problems for gynecologic oncologists. This is not only due to difficulties in treatment, but also in the diagnosis and differentiation of this malignant tumor. MR imaging techniques, combined with diffusion-weighted imaging (DWI) or dynamic contrast enhancement (DCE), make it possible not only to identify the exact location of lesions, but also to identify the types of EOC. In our study, we described the characteristics of a rare ovarian malignancy, mucinous ovarian cancer (MOC), on MRI. We compared the DWI and DCE values for MOC and more or less aggressive histological types of EOC, such as high-grade serous carcinoma (HGSC) (type I and type II) as well as the low-grade serous carcinoma (LGSC) (both type I). Abstract (1) Background. The purpose of this study is to evaluate the diagnostic accuracy of a quantitative analysis of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI of mucinous ovarian cancer (MOC). It also aims to differentiate between low grade serous carcinoma (LGSC), high-grade serous carcinoma (HGSC) and MOC in primary tumors. (2) Materials and Methods. Sixty-six patients with histologically confirmed primary epithelial ovarian cancer (EOC) were included in the study. Patients were divided into three groups: MOC, LGSC and HGSC. In the preoperative DWI and DCE MRI, selected parameters were measured: apparent diffusion coefficients (ADC), time to peak (TTP), and perfusion maximum enhancement (Perf. Max. En.). ROI comprised a small circle placed in the solid part of the primary tumor. The Shapiro–Wilk test was used to test whether the variable had a normal distribution. The Kruskal–Wallis ANOVA test was used to determine the p-value needed to compare the median values of interval variables. (3) Results. The highest median ADC values were found in MOC, followed by LGSC, and the lowest in HGSC. All differences were statistically significant (p < 0.000001). This was also confirmed by the ROC curve analysis for MOC and HGSC, showing that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC (p < 0.001). In the type I EOCs, i.e., MOC and LGSC, ADC has less differential value (p = 0.032), and TTP can be considered the most valuable parameter for diagnostic accuracy (p < 0.001). (4) Conclusions. DWI and DCE appear to be very good diagnostic tools in differentiating between serous carcinomas (LGSC, HGSC) and MOC. Significant differences in median ADC values between MOC and LGSC compared with those between MOC and HGSC indicate the usefulness of DWI in differentiating between less and more aggressive types of EOC, not only among the most common serous carcinomas. ROC curve analysis showed that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC. In contrast, TTP showed the greatest value for differentiating between LGSC and MOC.