陶玲玲,詹维伟,樊金芳,李伟伟,王怡,徐皪,周伟.超微血管成像结合TI-RADS鉴别诊断甲状腺良恶性结节[J].中国医学影像技术,2020,36(5):671~674
超微血管成像结合TI-RADS鉴别诊断甲状腺良恶性结节
Superb micro-vascular imaging combined with TI-RADS in differential diagnosis of benign and malignant thyroid nodules
投稿时间:2019-08-10  修订日期:2020-02-29
DOI:10.13929/j.issn.1003-3289.2020.05.007
中文关键词:  甲状腺结节  超声检查  诊断,鉴别  超微血管成像  甲状腺影像报告和数据系统
英文关键词:thyroid nodule  ultrasonography  diagnosis,differential  superb micro-vascular imaging  thyroid imaging reporting and data system
基金项目:上海市黄浦区科研项目基金(HKM201704)。
作者单位E-mail
陶玲玲 上海交通大学医学院附属瑞金医院卢湾分院超声科, 上海 200020  
詹维伟 上海交通大学医学院附属瑞金医院超声科, 上海 200025  
樊金芳 上海交通大学医学院附属瑞金医院卢湾分院超声科, 上海 200020  
李伟伟 上海交通大学医学院附属瑞金医院卢湾分院超声科, 上海 200020  
王怡 上海交通大学医学院附属瑞金医院卢湾分院超声科, 上海 200020  
徐皪 上海交通大学医学院附属瑞金医院卢湾分院超声科, 上海 200020  
周伟 上海交通大学医学院附属瑞金医院超声科, 上海 200025 Zw11468@126.com 
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中文摘要:
      目的 探讨超微血管成像(SMI)技术结合2017年美国放射学会甲状腺影像报告和数据系统(TI-RADS)鉴别诊断甲状腺良恶性结节的价值。方法 首先以常规超声根据TI-RADS将179例患者的甲状腺187个结节分为TR 1~5类,之后结合SMI技术调整TI-RADS分类;通过ROC曲线确定最佳截断值,比较两种方法的鉴别诊断效能。结果 校正前TR 1~5类别实际恶性率分别为0、0、5.00%、37.74%和64.29%。经SMI校正后分别为0、0、5.56%、23.26%和66.36%。校正前敏感度、特异度、阳性预测值、阴性预测值和准确率分别为75.00%、66.02%、64.29%、76.40%和70.05%,经SMI校正后分别为86.91%、64.08%、66.36%、85.71%和74.33%。校正后的AUC(Z=-2.616,P=0.009)和敏感度(Z=-1.988,P=0.047)均高于校正前。结论 SMI技术能显示甲状腺结节内穿支血流,与TI-RADS结合可提高诊断甲状腺结节的效能。
英文摘要:
      Objective To explore the value of superb micro-vascular imaging (SMI) combined with the 2017 American Radiological Society thyroid imaging reporting and data system (TI-RADS) in differential diagnosis of benign and malignant thyroid nodules. Methods A total of 187 thyroid nodules in 179 patients were classified into TR types 1 to 5 according to TI-RADS with conventional ultrasound, and then TI-RADS classification was re-adjusted in combination with SMI technology. The optimal diagnostic boundary was determined by ROC curve, and the diagnostic efficacy of the two methods was compared. Results Before correction, the actual malignant rates of TR 1 to 5 was 0, 0, 5.00%, 37.74% and 64.29%. After correction with SMI technology, the actual malignant rates of TR 1 to 5 was 0, 0, 5.56%, 23.26% and 66.36%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy before and after correction with SMI technology was 75.00%, 66.02%, 64.29%, 76.40%, 70.05% and 86.91%, 64.08%, 66.36%, 85.71%, 74.33%, respectively. AUC and sensitivity after correction were both higher than before (Z=-2.616, -1.988; P=0.009, 0.047). Conclusion SMI technology can show perforating blood flow in thyroid nodules, which combined with TI-RADS can improve the diagnostic efficacy of thyroid nodules.
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