摘要
目的对比卵巢-附件报告及数据系统(O-RADS)、妇科影像报告与数据系统(GI-RADS)和简单法则风险预测模型(SRRisk)鉴别卵巢良、恶性肿瘤的价值。方法回顾性分析622例经病理证实的卵巢肿瘤的超声声像图,并分别以O-RADS、GI-RADS及SRRisk进行分类。采用受试者工作特征(ROC)曲线观察各方法鉴别卵巢良、恶性肿瘤的效能,比较其曲线下面积(AUC)、敏感度、特异度及准确率差异。结果622例中,454例良性、168例恶性(包含交界性)卵巢肿瘤。O-RADS、GI-RADS、SRRisk鉴别卵巢良、恶性肿瘤的AUC分别为0.94、0.93及0.93,敏感度分别为93.45%、91.67%及86.91%,特异度分别为88.33%、88.77%及89.87%,准确率分别为89.71%、89.55%及89.07%;其AUC、特异度、准确率相当(P均>0.05),而O-RADS的敏感度(93.45%)高于SRRisk(86.91%,χ^(2)=7.69,P<0.01),GI-RADS的敏感度(91.67%)与O-RADS及SRRisk相当(χ^(2)=0.80、3.50,P均>0.05)。结论O-RADS、GI-RADS及SRRisk鉴别卵巢良、恶性肿瘤的效能均较高且彼此相当。
Objective To compare the value of ovarian-adnexal reporting and data system(O-RADS),gynecologic imaging reporting and data system(GI-RADS)as well as simple rules risk model(SRRisk)for differentiating benign and malignant ovarian tumors.Methods Ultrasonographic data of 622 patients with ovarian mass confirmed pathologically were retrospectively analyzed,and were classified using O-RADS,GI-RADS and SRRisk,respectively.Then receiver operating characteristic(ROC)curve was drawn to analyze the efficacy of each method for differentiating benign and malignant ovarian tumors,and the corresponding area under the curve(AUC),sensitivity,specificity and accuracy of the 3 methods were compared.Results Among 622 patients,454 were found with benign and 168 with malignant ovarian tumors(including borderline).The AUC of O-RADS,GI-RADS and SRRisk was 0.94,0.93 and 0.93,the sensitivity was 93.45%,91.67%and 86.91%,the specificity was 88.33%,88.77%and 89.87%,and the accuracy was 89.71%,89.55%and 89.07%,respectively.The AUC,specificity and accuracy of 3 methods were similar(all P>0.05),while the sensitivity of O-RADS(93.45%)was higher than that of SRRisk(86.91%,χ^(2)=7.69,P<0.01),and the sensitivity of GI-RADS(91.67%)was similar to that of O-RADS and SRRisk(χ^(2)=0.80,3.50,both P>0.05).Conclusion O-RADS,GI-RADS and SRRisk showed high and comparable diagnostic efficiency for identification of benign and malignant ovarian tumors.
作者
杨文敏
吕国荣
陈秋月
YANG Wenmin;LYU Guorong;CHEN Qiuyue(Department of Ultrasound,the Second Affiliated Hospital of Fujian Medical University,Quanzhou 362000,China;Department of Clinical Medicine,Quanzhou Medical College,Quanzhou 362010,China)
出处
《中国医学影像技术》
CSCD
北大核心
2021年第9期1368-1372,共5页
Chinese Journal of Medical Imaging Technology
基金
泉州市科技计划项目(2019C074R)。