三种甲状腺结节风险分层系统C-TIRADS、ACR-TIRADS和KTA/KSThR-TIRADS的比较研究
Comparison of three thyroid nodule risk stratification systems C-TIRADS,ACR-TIRADS and KTA/KSThR-TIRADS
隋洋 1王兵 1孙医学1
作者信息
- 1. 蚌埠医科大学第一附属医院 超声医学科,安徽 蚌埠 233004
- 折叠
摘要
目的:比较由中华医学会、美国放射学会和韩国甲状腺放射学会提出的甲状腺影像数据和报告系统(C-TIRADS、ACR-TIRADS、KTA/KSThR-TIRADS)的诊断效能.方法:基于手术病理结果,对 226 例病人的 226 枚甲状腺结节分别进行C-TIRADS、ACR-TIRADS和KTA/KSThR-TIRADS分类,评估三者的诊断效能.结果:226 枚甲状腺结节中,良性结节 140 枚(61.9%),恶性结节86 枚(38.1%).ROC曲线分析显示,C-TIRADS的AUC最高(0.834,P<0.05);KTA/KSThR-TIRADS和ACR-TIRADS间AUC差异无统计学意义(0.778 和 0.760,P>0.05);KTA/KSThR-TIRADS 的诊断敏感性最高(82.6%),C-TIRADS的特异性和准确性最高(83.6%和79.3%).3 种TI-RADS指南在诊断≤10 mm结节与>10 mm结节中的AUC差异均无统计学意义(P>0.05).结论:与ACR-TIRADS和KTA/KSThR-TIRADS相比,C-TIRADS对甲状腺结节的诊断效能最佳.同时,C-TIRADS简便易行,更适合中国人群的甲状腺结节.
Abstract
Objective:To compare the diagnostic performance of thyroid imaging reporting and data systems proposed by the Chinese Medical Association,the American Radiological Society,and the Korean Thyroid Radiological Society(C-TIRADS,ACR-TIRADS,KTA/KSThR TIRADS).Methods:Based on surgical pathological results,226 thyroid nodules from 226 patients were classified by C-TIRADS,ACR-TIRADS,and KTA/KSThR TIRADS to evaluate their diagnostic performance.Results:Among the 226 thyroid nodules,140 nodules were benign(61.9%)and 86 nodules were malignant(38.1%).ROC curve analysis showed that the AUC of C-TIRADS was the highest(0.834,P<0.05);there was no statistically significant difference in AUC between KTA/KSThR-TIRADS and ACR-TIRADS(0.778,0.760,P>0.05);KTA/KSThR-TIRADS had the highest diagnostic sensitivity(82.6%),while C-TIRADS had the highest specificity and accuracy(83.6%,79.3%).There was no statistically significant difference in AUC between the three TI-RADS guidelines in diagnosing nodules≤10 mm and nodules>10 mm(P>0.05).Conclusions:Comparedwith ACR-TIRADSand KSThR-TIRADS,C-TIRADS has the best diagnostic performance for thyroid nodules.Moreover,C-TIRADS is easy to perform and more suitable for thyroid nodules in the Chinese population.
关键词
甲状腺结节/超声/甲状腺影像数据和报告系统Key words
thyroid nodule/ultrasonography/thyroid imaging reporting and data systems引用本文复制引用
基金项目
蚌埠医学院自然科学研究重点项目(2021byzd071)
出版年
2024
NETL
NSTL
维普
万方数据