摘要
目的通过对比美国放射学会(ACR)-甲状腺影像报告和数据系统(TIRADS),探讨中国版TIRADS(C-TIRADS)对甲状腺结节良恶性的鉴别诊断价值。方法回顾性收集2021年8月~2022年7月在本院接受甲状腺超声检查并得到明确病理诊断的甲状腺结节患者166例(195枚结节);以病理结果为金标准,分别评估C-TIRADS和TIRADS不同分类的恶性占比,绘制两种系统诊断甲状腺结节良恶性的ROC曲线,并对比二者诊断效能。结果两种TIRADS的风险分层级别下的实际恶性占比与指南推荐的恶性率相符。C-TIRADS诊断甲状腺结节良恶性ROC曲线的AUC为0.796(95%CI:0.741~0.852),相比ACR-TIRADS的0.658(95%CI:0.587~0.724)增大(P<0.05)。C-TIRADS、ACR-TIRADS的最佳临界点分别为4C类、5类,两种分类系统的敏感度差异无统计学意义(94.12%vs 95.10%,P>0.05),但C-TIRADS的特异性高于ACR-TIRADS(56.99%vs 35.48%,P<0.05)。结论对于甲状腺结节的鉴别,C-TIRADS相比ACR-TIRADS诊断效能更高,提高了特异性。
Objective To explore the value of Chinese version of thyroid imaging reporting and data system(C-TIRADS)by comparing with the American College of Radiology(ACR)TIRADS in the differential diagnosis between benign and malignant thyroid nodules.Methods A total of 166 patients with thyroid nodules(195 nodules)who underwent thyroid ultrasonography and confirmed by pathology from August 2021 to July 2022 were retrospectively collected.The pathological results were used as the gold standard to evaluate the malignant proportion of different classifications of C-TIRADS and TIRADS respectively.The ROC curves of the two systems for diagnosing benign and malignant thyroid nodules were drawn,and the diagnostic efficacy of the two systems were compared.Results The actual malignant proportion of the two TIRADS risk stratification levels were consistent with the malignant rate recommended by the guidelines.The AUC of C-TIRADS in the diagnosis between benign and malignant thyroid nodules was 0.796(95%CI:0.741-0.852),which was significantly higher than 0.658(95%CI:0.587-0.724)of ACR-TIRADS(P<0.05).The optimal critical points of C-TIRADS and ACR-TIRADS were 4C and 5,respectively.There was no significant difference in sensitivity between the two classification systems(94.12%vs 95.10%,P>0.05),but the specificity of C-TIRADS was significantly higher than that of ACR-TIRADS(56.99%vs 35.48%,P<0.05).Conclusion For the identification of thyroid nodules,C-TIRADS has higher diagnostic efficiency and higher specificity than ACR-TIRADS.
作者
王忆原
朱国强
黄甜
刘学敏
崔立娟
张红艳
姜一鹍
WANG Yiyuan;ZHU Guoqiang;HUANG Tian;LIU Xuemin;CUI Lijuan;ZHANG Hongyan;JIANG Yikun(Department of Ultrasound,Zhangjiagang Hospital of Traditional Chinese Medicine,Zhangjiagang 215600,China)
出处
《分子影像学杂志》
2023年第2期316-320,共5页
Journal of Molecular Imaging
基金
张家港市科技计划项目(ZKS2044)。
关键词
甲状腺癌
甲状腺结节
超声检查
甲状腺影像报告和数据系统
thyroid cancer
thyroid nodules
ultrasound examination
thyroid imaging reporting and data system
