Lou Fen-lan, Shi Yi-fu
Departments of Diagnostic Radiology and Genecology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou 310006, China.
Zhonghua Zhong Liu Za Zhi. 2006 Sep;28(9):701-5.
To assess the value of computed tomography( CT) in the staging and predicting respectability of primary advanced ovarian carcinoma.
The data of preoperative abdomen and pelvis CT scan in 64 women with Stage II or IV ovarian carcinoma were collected from tumor registry database. All CT scans were analyzed retrospectively without knowledge of the operative findings, and the stage as based on CT was compared with the surgical and pathological findings. Residual lesion of < or = 2 cm in maximal diameter was considered as an optimal surgical result. Twenty-senven of these 64 patients (42.2%) underwent optimal cytoreduction surgery for residual disease C2 cm in diameter. Based on the ability of each parameter in predicting cytoreductive surgery outcome, 11 radiographic features were selected for the final model. Each predictive parameter was assigned a numeric value (1 to 7). Sensitivity, specificity, positive predictive value( PPV) , negative predictive value( NPV),and accuracy were calculated for each predictive parameter. Receiver operating characteristic( ROC) curve was used to assess the ability of the model to predict surgical outcome. The correlation between CT stage and surgical-pathologic stage was analyzed by Chi-square test and Spearman's rho analysis.
The overall accuracy of CT staging for advanced ovarian carcinoma was 87. 5% ; 86. 5% and 91.7% for stage III and IV patients respectively. The correlation between CT stage and surgicopathologic stage was found to be comformable. In the final predictive index model, when a predictive index scoreed > or = 2, the overall accuracy, sensitivity and specificity was 70. 3% , 67.6% and 74. 1% for identifying patients for suboptimal surgery. The PPV and the NPV was 78. 1% and 62. 5% , respectively. The ROC curve was generated with an area under the curve = 0. 792+/-0. 055 using the predictive index scores.
CT has a high accuracy in staging and a moderate ability to predict resectability for advanced ovarian carcinoma. Therefore, the predictive index model may be useful in the management of ovarian carcinoma patients.
评估计算机断层扫描（CT）在原发性晚期卵巢癌分期及预测可切除性方面的价值。
从肿瘤登记数据库收集64例Ⅱ期或Ⅳ期卵巢癌患者术前腹部及盆腔CT扫描数据。所有CT扫描均在不知手术结果的情况下进行回顾性分析，并将基于CT的分期与手术及病理结果进行比较。最大直径≤2 cm的残留病灶被视为最佳手术结果。这64例患者中有27例（42.2%）因直径≤2 cm的残留病灶接受了最佳细胞减灭术。根据每个参数预测细胞减灭术结果的能力，为最终模型选择了11个影像学特征。每个预测参数被赋予一个数值（1至7）。计算每个预测参数的敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和准确性。采用受试者操作特征（ROC）曲线评估模型预测手术结果的能力。通过卡方检验和Spearman秩相关分析分析CT分期与手术病理分期之间的相关性。
晚期卵巢癌CT分期的总体准确性为87.5%；Ⅲ期和Ⅳ期患者分别为86.5%和91.7%。发现CT分期与手术病理分期相符。在最终预测指数模型中，当预测指数得分≥2时，识别次优手术患者的总体准确性、敏感性和特异性分别为70.3%、67.6%和74.1%。PPV和NPV分别为78.1%和62.5%。使用预测指数得分生成的ROC曲线下面积为0.792±0.055。
CT在晚期卵巢癌分期方面具有较高准确性，在预测可切除性方面具有中等能力。因此，预测指数模型可能有助于卵巢癌患者的管理。
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