Differentiation of epithelial ovarian cancer subtypes by use of imaging and clinical data: a detailed analysis

BACKGROUND: Primary epithelial ovarian carcinoma is sub-classified into serous, mucinous, endometrioid and clear cell subtypes. Neoadjuvant chemotherapy has become an alternative treatment option past several years, as serous carcinoma, the most common subtype, is known as chemotherapy-sensitive tumor. On the other hand, mucinous and clear cell carcinoma are known as chemotherapy-resistive. Therefore, it may be meaningful to estimate subtype of ovarian carcinoma using imaging modality. The purpose of this study is to study whether CT or MRI can determine the subtypes of epithelial ovarian cancers. METHODS: The imaging and clinical findings obtained from 125 consecutive patients with primary ovarian carcinoma were retrospectively analyzed. Forty-four of the patients had serous carcinoma; 13, mucinous carcinoma; 53, clear cell carcinoma; and 15, endometrioid carcinoma. We studied the bilateralism, morphological type, tumor diameter, solid portion ratio, relative signal intensity on T2WI and DWI, contrast ratio, and endometriosis on MRI and the calcification, peritoneal dissemination and lymph node metastasis, clinical staging, and thromboembolism on CT. We also studied the tumor markers and serum calcium concentrations. Each parameter was statistically analyzed by univariate and multivariate analyses. RESULTS: Serous carcinoma showed a significantly higher incidence of bilateral disease, smaller tumor size, higher signal intensity on DWI, and less frequent hypercalcemia. The CA19-9 level was significantly higher in mucinous carcinoma, in which most of the tumors appeared as multilocular cystic masses. Clear cell carcinoma appeared as unilateral disease with a larger solid portion and hypercalcemia in younger patients. Endometrioid carcinoma only showed a lower incidence of intraperitoneal dissemination. CONCLUSIONS: CT and MRI combined with clinical data especially tumor markers and presence of paraneoplastic syndrome could partly predict epithelial ovarian cancer subtypes.