Differentiation of Borderline Epithelial Ovarian Tumors from Benign and Malignant Epithelial Ovarian Tumors by MRI Scoring - Babaoglu, Seyma; Atas, Abdullah Enes; Kerimoglu, Ulku; Iyisoy, Mehmet Sinan; Kilinc, Fahriye (Current Medical Imaging, 2024)
IntroductionThe distinction between benign and borderline epithelial ovarian tumors is important because treatment and follow-up strategies differ. ObjectiveWe aimed to evaluate benign, borderline, and malignant epithelial ovarian tumors using MRI features and contributed to the preoperative evaluation.MethodsMRIs of 81 patients (20 bilateral), including 31 benign, 27 borderline, and 23 malignant, who had pelvic imaging between 2013-2020, were evaluated retrospectively. The evaluation was made blindly to the pathology result by two radiologists with MRI scoring and features that we determined. MRI evaluation was performed with T1 TSE, T2 TSE, fat-suppressed T2 TSE, and before and after contrast T1 fat-suppressed and non-fat-suppressed TSE images. The numbers and findings obtained in scoring were evaluated by Chi-Square, ordinal logistic regression, and 2 and 3 category ROC analysis.ResultsThe total score varied between 7 and 24. Among the three groups, a significant difference was found in terms of T1, T2 signal intensity (p <0.01), size (p = 0.055), solid area (p <0.001), septa number (p <0.05), ovarian parenchyma (p = 0.001), ascites (p <0.001), peritoneal involvement (p <0.001), laterality (p <0.001), contrast enhancement pattern (p <0.001). On the other hand, no significant difference was found in terms of wall thickness, lymph node involvement and endometrial thickness (p> 0.05). Cut-off values were found as 11.5 and 18.5 in the 3-category ROC analysis performed for the score (VUS: 0.8109). Patients with a score below 11.5 were classified as benign, those between 11.5-18.5 as borderline, and those over 18.5 as malignant.ConclusionThe differentiation of borderline tumors from benign and malignant tumors by MRI scoring will contribute to the preoperative diagnosis.
Keywords: Differential diagnosis