Evaluation of Ovarian Tumors with Multidetector Computed Tomography and Tumor Markers: Differentiation of Stage I Serous Borderline Tumors and Stage I Serous Malignant Tumors Presenting as Solid-Cystic Mass

BACKGROUND The aim of this study was to determine multidetector computed tomography (MDCT) features and tumor markers for differentiating stage I serous borderline ovarian tumors (SBOTs) from stage I serous malignant ovarian tumors (SMOTs). MATERIAL AND METHODS In total, 48 patients with stage I SBOTs and 54 patients with stage I SMOTs who underwent MDCT and tumor markers analysis were analyzed. MDCT features included location, shape, margins, texture, papillary projections, vascular abnormalities, size, and attenuation value. Tumor markers included serum cancer antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and human epididymis protein 4 (HE4). Parameters of clinical characteristic, MDCT features, and tumor markers were compared using a chi-square test and Mann-Whitney U tests. A binary logistic regression analysis was performed to detect predictors for SMOTs. A receiver operating characteristic (ROC) curve analysis was used to assess the potential diagnostic value of the quantitative parameters. Kappa and intraclass correlation coefficients were used to evaluate interobserver reproducibility for MDCT features. RESULTS Median ages between patients with SBOTs and SMOTs were significantly different. Compared with SBOTs, vascular abnormalities were significantly more common in SMOTs. CA125, HE4, the maximum thickness of the wall, the maximum thickness of the septa, and the maximum diameter of the solid portions were significantly higher in patients with SMOTs. A binary logistic regression analysis revealed that age, vascular abnormalities, and the maximum diameter of the solid portion were independent factors of SMOTs. ROC analysis was used to assess the potential diagnostic value for predicting SMOTs. Moderate or good interobserver reproducibility for MDCT features were identified. CONCLUSIONS Age, vascular abnormalities, and the maximum diameter of the solid portion were independent factors for differentiating SBOTs from SMOTs. The combined analysis of age, vascular abnormalities, and the maximum diameter of the solid portion may allow better differentiation between SBOTs and SMOTs.