CT对进展期原发性卵巢癌的分期和手术切除可能性的预测

目的探讨CT对进展期原发性卵巢癌的分期和初次手术时能否完全切除的可能性。方法收集64例术前行全腹CT扫描的进展期原发性卵巢癌患者的临床资料,在不了解手术结果的情况下,对CT图像进行回顾性分析,将CT分期与手术病理分期进行对照。理想手术的标准是单个残余肿瘤的最大直径≤2 cm,64例中,37例为不理想手术,27例为理想手术。对每种预测手术结果的放射学表现进行统计分析,确定11种放射学表现作为最终的预测参数并评分,对预测指数值≥1及以上者进行灵敏度、特异度、阳性预测值(PPV)、阴性预测值(NPV)和准确度的统计。ROC曲线分析用于评价CT预测手术结果的能力。CT分期与手术病理分期的关系应用似然比X2检验和Spearman相关分析。结果CT对进展期卵巢癌的分期准确度为87．5％,其中Ⅲ期为86．5％,Ⅳ期为91．7％,CT对进展期卵巢癌的分期与手术病理分期呈正相关。对手术切除可能性的预测,当预测指数值≥2时,具有70．3％的准确度,确定为不理想手术,其灵敏度为67．6％,特异度为74．1％,PPV为78．1％,NPV为62．5％。使用预测指数值,ROC曲线下的面积为0．792±0．055。结论CT对进展期卵巢癌患者分期准确性较高,预测手术切除的可能性为中等,预测指数评分模式对进展期卵巢癌患者具有一定的临床效用。

Value of computed tomography in the staging and predicting resectability of primary advanced ovarian carcinoma

OBJECTIVE: To assess the value of computed tomography( CT) in the staging and predicting respectability of primary advanced ovarian carcinoma. METHODS: 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. RESULTS: 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. CONCLUSION: 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.