首页|期刊导航|分子影像学杂志|ACR-TIRADS、C-TIRADS与AI-TIRADS在甲状腺结节良恶性诊断中的应用效果

ACR-TIRADS、C-TIRADS与AI-TIRADS在甲状腺结节良恶性诊断中的应用效果OA

The application effects of ACR-TIRADS,C-TIRADS and AI-TIRADS in the diagnosis of benign and malignant thyroid nodules

中文摘要英文摘要

目的 对比美国放射学会甲状腺影像报告与数据系统(ACR-TIRADS)、中国甲状腺影像报告与数据系统(C-TIRADS)与人工智能甲状腺影像报告与数据系统(AI-TIRADS)对甲状腺结节良恶性的诊断效能.方法 纳入2022年4月~2025年5月合肥市第二人民医院(安徽医科大学附属合肥医院)收治的102例甲状腺结节患者,经病理检查确诊恶性的患者作为恶性组、良性患者作为良性组,比较两组临床资料、各超声征象,将恶性甲状腺结节作为阳性病例,将良性甲状腺结节作为阴性对照,采用ROC曲线分析3种检测方案对甲状腺结节良恶性的诊断效能.结果 相较良性组,恶性组结节内部构成实性、回声强度低/极低回声、边界不规则或外扩、形态纵横比≥1占比更高(P<0.05).经病理确诊恶性甲状腺结节71例,ACR-TIRADS、C-TIRADS与AI-TIRADS正确确诊恶性甲状腺结节分别59例、61例、65例.ROC曲线分析结果显示,ACR-TIRADS、C-TIRADS与AI-TIRADS的曲线下面积(AUC)为0.835(95%CI:0.756~0.914,P<0.05)、0.865(95%CI:0.793~0.934,P<0.05)、0.909(95%CI:0.847~0.972,P<0.05),其敏感度为83.10%、85.92%、91.55%,特异度分别为83.87%、87.10%、90.32%.DeLong检验显示AI-TIRADS的AUC高于ACR-TIRADS(P=0.008,95%CI:0.020~0.129)和C-TIRADS(P=0.037,95%CI:0.003~0.086),但ACR-TIRADS和C-TIRADS的AUC差异无统计学意义(P=0.110,95%CI:-0.007~0.067).Holm多重比较校正后,AI-TIRADS与ACR-TIRADS的AUC差异仍有统计学意义(校正后P=0.024),而AI-TIRADS与C-TIRADS的差异在校正后呈边缘显著(校正后P=0.074).ACR-TIRADS与C-TIRADS之间的差异无统计学意义(校正后P=0.110).结论 AI-TIRADS对甲状腺结节良恶性的诊断效能相对较高,C-TIRADS临床可操作性强,可优化甲状腺结节的诊疗流程.

Objective To compare the diagnostic efficiency of the American College of Radiology(ACR)Thyroid Imaging Reporting and Data System(TIRADS),the Chinese(C)-TIRADS,and the Artificial Intelligence(AI)-TIRADS for benign and malignant thyroid nodules,and to provide a basis for their clinical application.Methods A total of 102 thyroid nodules from 102 patients admitted to Hefei Second People's Hospital from April 2022 to May 2025 were included in the study.After pathological examination,diagnosed as malignant and included in the malignant group,and diagnosed as benign and included in the benign group.The clinical data,various ultrasound signs of the malignant and benign groups were compared.The malignant patients were regarded as positive cases,and the benign ones as negative controls.The ROC curve was used to analyze the diagnostic efficiency of ACR-TIRADS,C-TIRADS,and AI-TIRADS for benign and malignant thyroid nodules.Results Compared with the benign group,the malignant group had a higher proportion of solid internal composition,low/very low echo,irregular or expansive borders,and an aspect ratio≥1(P<0.05).A total of 71 cases of malignant thyroid nodules were diagnosed by pathology.ACR-TIRADS,C-TIRADS and AI-TIRADS correctly diagnosed 59 cases,61 cases and 65 cases of malignant thyroid nodules respectively.The results of ROC curve analysis showed that the area under the curve(AUC)of ACR-TIRADS,C-TIRADS and AI-TIRADS was 0.835(95%CI:0.756-0.914,P<0.05),0.865(95%CI:0.793-0.934,P<0.05),and 0.909(95%CI:0.847-0.972,P<0.05),with sensitivities of 83.10%,85.92%,91.55%and specificities of 83.87%,87.10%,90.32%,respectively.The DeLong test revealed that the AUC area of AI-TIRADS was significantly higher than that of ACR-TIRADS(P=0.008,95%CI:0.020-0.129)and C-TIRADS(P=0.037,95%CI:0.003-0.086),but there was no statistically significant difference in the AUC between ACR-TIRADS and C-TIRADS(P=0.110,95%CI:-0.007-0.067).After Holm multiple comparison correction,the difference in AUC between AI-TIRADS and ACR-TIRADS was still statistically significant(adjusted P=0.024),while the difference between AI-TIRADS and C-TIRADS was marginally significant after correction(adjusted P=0.074).There was no statistically significant difference between ACR-TIRADS and C-TIRADS(adjusted P=0.110).Conclusion For benign and malignant thyroid nodules,the diagnostic efficiency of AI-TIRADS was higher,C-TIRADS was had strong clinical operability and could optimize the diagnosis and treatment process of thyroid nodules.

徐杰;魏杰;范伟健;马芳

合肥市第二人民医院(安徽医科大学附属合肥医院)超声医学科,安徽 合肥 230011合肥市第二人民医院(安徽医科大学附属合肥医院)超声医学科,安徽 合肥 230011合肥市第二人民医院(安徽医科大学附属合肥医院)介入血管疼痛科,安徽 合肥 230011合肥市第二人民医院(安徽医科大学附属合肥医院)超声医学科,安徽 合肥 230011

甲状腺结节美国放射学会甲状腺影像报告与数据系统中国甲状腺影像报告与数据系统人工智能甲状腺影像报告与数据系统受试者工作特征

thyroid nodulesAmerican College of Radiology Thyroid Imaging Reporting and Data SystemChinese Thyroid Imaging Reporting and Data SystemArtificial Intelligence Thyroid Imaging Reporting and Data Systemreceiver operating characteristic

《分子影像学杂志》 2026 (5)

604-610,7

安徽省卫生健康科研项目(AHWJ2022c001)合肥市第二人民医院(安徽医科大学附属合肥医院)科研基金项目(2024ykc046)

10.12122/j.issn.1674-4500.2026.05.06

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