Differentiation of borderline tumors from type I ovarian epithelial cancers on CT and MR imaging
Differentiation of borderline tumors from type I ovarian epithelial cancers on CT and MR imaging
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DOI：
10.1007/s00261-020-02467-w
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发表时间：
2020-03-11
影响因子：
2.4
通讯作者：
Tang, Guangyu
中科院分区：
文献类型：
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作者：
Yang, Sihua;Tang, Huan;Tang, Guangyu
目的探讨卵巢交界性肿瘤（BOT）与I型卵巢上皮性癌（OEC）的CT和MR影像学特征，为临床合理治疗和判断预后提供依据。方法回顾性分析经病理证实的33例BOTs和35例I型OECs的临床资料。比较两组卵巢肿瘤的临床病理资料（年龄、绝经前状态、CA-125、Ki-67）及影像学特征。使用受试者工作特征分析评价成像特征的诊断性能。通过多变量分析确定I型EOCs的最佳预测变量。结果BOTs较I型OECs更易发生于年轻患者，CA-125值和增殖指数（Ki-67 < 15%）较I型OECs低。与I型嗅鞘细胞相比，BOT更常为单纯囊性（15/33，45.45% vs. 1/35，2.86%; p < 0.001），显示较少的壁结节（16/33，48.48% vs. 28/35，80.00%; p = 0.007），边缘不清的频率较低（3/33，9.09% vs. 11/35，31.43%; p = 0.023），固体部分较小（0.56 +/- 2.66 vs. 4.51 +/- 3.88; p < 0.001），壁较薄（0.3 +/- 0.17 vs. 0.55 +/- 0.24; p < 0.001）。最大壁厚的曲线下面积最大（AUC，0.848）。多因素分析显示，实性部分大小（OR 10.822，p = 0.002）和最大壁厚（OR 9.130，p = 0.001）是鉴别两组病变的独立指标。结论实性部分大小和最大壁厚对两组卵巢肿瘤的分型有显著影响。
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.