Sihua Yang1, Huan Tang2, Fuxia Xiao1, Jingqi Zhu1, Ting Hua1, Guangyu Tang3. 1. Department of Radiology, Shanghai Tenth People's Hospital of Tongji University, School of Medicine, Shanghai, 200072, China. 2. Department of Radiology, Huadong Hospital of Fudan University, Shanghai, 200040, China. 3. Department of Radiology, Shanghai Tenth People's Hospital of Tongji University, School of Medicine, Shanghai, 200072, China. tgy17@tongji.edu.cn.
Abstract
PURPOSE: To investigate the value of CT and MR imaging features in differentiating borderline ovarian tumor (BOT) from type I ovarian epithelial cancer (OEC), which could be significant for suitable clinical treatment and assessment of the prognosis of the patient. METHODS: Thirty-three patients with BOTs and 35 patients with type I OECs proven by pathology were retrospectively evaluated. The clinico-pathological information (age, premenopausal status, CA-125, and Ki-67) and imaging characteristics were compared between two groups of ovarian tumors. The diagnostic performance of the imaging features was evaluated using receiver operating characteristic analysis. The best predictor variables for type I EOCs were recognized via multivariate analyses. RESULTS: BOTs are more likely to involve younger patients and frequently show lower CA-125 values and lower proliferation indices (Ki-67 < 15%) than type I OECs. Compared with type I OECs, BOTs were more often purely cystic (15/33, 45.45% vs. 1/35, 2.86%; p < 0.001) and displayed less frequent mural nodules (16/33, 48.48% vs. 28/35, 80.00%; p = 0.007), less frequently unclear margin (3/33, 9.09% vs. 11/35, 31.43%; p = 0.023), smaller solid portion (0.56 ± 2.66 vs. 4.51 ± 3.88; p < 0.001), and thinner walls (0.3 ± 0.17 vs. 0.55 ± 0.24; p < 0.001). The maximum wall thickness presented the largest area under the curve (AUC, 0.848). Multivariate analysis revealed that the solid portion size (OR 10.822, p = 0.002) and maximum wall thickness (OR 9.130, p = 0.001) were independent indicators for the differential diagnosis between the two groups of lesions. CONCLUSION: The solid portion size and maximum wall thickness significantly influenced the classification of the two groups of ovarian tumors.
PURPOSE: To investigate the value of CT and MR imaging features in differentiating borderline ovarian tumor (BOT) from type I ovarian epithelial cancer (OEC), which could be significant for suitable clinical treatment and assessment of the prognosis of the patient. METHODS: Thirty-three patients with BOTs and 35 patients with type I OECs proven by pathology were retrospectively evaluated. The clinico-pathological information (age, premenopausal status, CA-125, and Ki-67) and imaging characteristics were compared between two groups of ovarian tumors. The diagnostic performance of the imaging features was evaluated using receiver operating characteristic analysis. The best predictor variables for type I EOCs were recognized via multivariate analyses. RESULTS: BOTs are more likely to involve younger patients and frequently show lower CA-125 values and lower proliferation indices (Ki-67 < 15%) than type I OECs. Compared with type I OECs, BOTs were more often purely cystic (15/33, 45.45% vs. 1/35, 2.86%; p < 0.001) and displayed less frequent mural nodules (16/33, 48.48% vs. 28/35, 80.00%; p = 0.007), less frequently unclear margin (3/33, 9.09% vs. 11/35, 31.43%; p = 0.023), smaller solid portion (0.56 ± 2.66 vs. 4.51 ± 3.88; p < 0.001), and thinner walls (0.3 ± 0.17 vs. 0.55 ± 0.24; p < 0.001). The maximum wall thickness presented the largest area under the curve (AUC, 0.848). Multivariate analysis revealed that the solid portion size (OR 10.822, p = 0.002) and maximum wall thickness (OR 9.130, p = 0.001) were independent indicators for the differential diagnosis between the two groups of lesions. CONCLUSION: The solid portion size and maximum wall thickness significantly influenced the classification of the two groups of ovarian tumors.