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中华医学超声杂志(电子版) ›› 2019, Vol. 16 ›› Issue (04) : 252 -256. doi: 10.3877/cma.j.issn.1672-6448.2019.04.004

所属专题: 文献

浅表器官超声影像学

计算机辅助诊断系统鉴别甲状腺结节良恶性的诊断效能及其影响因素
许敏1, 韩峰1, 罗晓1, 王建伟1, 郑玮1, 郭智兴1, 林庆光1, 李安华1,()   
  1. 1. 510060 广州,中山大学肿瘤防治中心超声心电科 华南肿瘤学国家重点实验室 肿瘤医学协同创新中心
  • 收稿日期:2019-03-10 出版日期:2019-04-01
  • 通信作者: 李安华

Diagnostic efficacy of computer aided diagnosis system in differentiating benign and malignant thyroid nodules and its influencing factors

Min Xu1, Feng Han1, Xiao Luo1, Jianwei Wang1, Wei Zheng1, Zhixing Guo1, Qingguang Lin1, Anhua Li1,()   

  1. 1. Department of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
  • Received:2019-03-10 Published:2019-04-01
  • Corresponding author: Anhua Li
  • About author:
    Corresponding author: Li Anhua, Email:
引用本文:

许敏, 韩峰, 罗晓, 王建伟, 郑玮, 郭智兴, 林庆光, 李安华. 计算机辅助诊断系统鉴别甲状腺结节良恶性的诊断效能及其影响因素[J/OL]. 中华医学超声杂志(电子版), 2019, 16(04): 252-256.

Min Xu, Feng Han, Xiao Luo, Jianwei Wang, Wei Zheng, Zhixing Guo, Qingguang Lin, Anhua Li. Diagnostic efficacy of computer aided diagnosis system in differentiating benign and malignant thyroid nodules and its influencing factors[J/OL]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2019, 16(04): 252-256.

目的

评估计算机辅助诊断系统(CAD)鉴别甲状腺结节良恶性的诊断效能及其影响因素。

方法

回顾性分析2013年1月至2017年12月就诊于中山大学附属肿瘤医院的1035例患者资料(共1065个甲状腺结节),所有甲状腺结节均经超声引导下细针穿刺活检或外科手术证实。利用CAD系统基于Kwak提出的甲状腺影像报告与数据系统(K-TI-RADS)、美国甲状腺协会(ATA)指南、美国放射协会(ACR)发表的ACR-TI-RADS指南分为3组并进行分析,以病理结果为"金标准",建立受试者工作特征(receiver operator characteristic,ROC)曲线,计算曲线下面积(area under the ROC curve,AUC),采用Z检验比较组间AUC的差异。根据约登指数最大的切点值确定最佳诊断临界点,计算以最佳诊断临界点区分良恶性时,不同组间的敏感度、特异度、阳性预测值、阴性预测值和准确性,采用McNemar检验比较各组间差异。

结果

ACR-TI-RADS指南诊断甲状腺结节的曲线下面积(AUC)高于K-TI-RADS及ATA指南(0.743 vs 0.703,0.743 vs 0.693),差异均有统计学意义(Z=3.026、3.669,P均<0.01)。ACR-TI-RADS指南敏感度高于K-TI-RADS指南(91.95% vs 63.98%),差异有统计学意义(P<0.001),与ATA指南比较(91.95% vs 90.04%),差异无统计学意义(P=0.7123)。以4c类为诊断界值时,K-TI-RADS指南特异度最高(66.23% vs 49.74%,66.23% vs 47.38%),差异均有统计学意义(P均<0.001)。结节大小影响CAD的诊断效能,其中当结节最大径线为5~<10 mm或≥20 mm时,CAD的AUC最大,差异有统计学意义(P<0.001)。而CAD在正常甲状腺背景与桥本甲状腺炎背景下,AUC比较,差异无统计学意义(P=0.82)。

结论

甲状腺CAD基于ACR-TI-RADS指南进行诊断时,显示出更好的诊断效能,而结节大小影响CAD的诊断效能。

Objective

To determine the diagnostic efficacy of the computer aided diagnosis (CAD) system in discriminating malignant and benign thyroid nodules and the possible influencing factors.

Methods

This retrospective study analyzed 1035 patients with 1065 thyroid nodules at Sun Yat-sen University Cancer Center between May 2013 and October 2017. All the nodules was proven by ultrasound guided fine needle aspiration cytology or thyroidectomy. The CAD system was used to analyze the thyroid nodules, according to the categories defined by the K-TI-RADS, ATA, and ACR-TI-RADS guidelines. Using pathology as the gold standard, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of the CAD system. In addition, the differences of CAD diagnostic efficacy were compared among different thyroid nodule sizes and thyroid background.

Results

The area under the ROC curve (AUC) of the ACR-TI-RADS was higher than those of the K-TI-RADS (Z=3.026, P=0.0025) and ATA (Z=3.669, P<0.001). The sensitivity of the ACR-TI-RADS was better than that of the K-TI-RADS (P<0.001), and was comparable to that of the ATA (P=0.7123). Using 4C as the cutoff value, the K-TI-RADS demonstrated a significantly higher specificity than the ATA and ACR-TI-RADS (P<0.001). The size of thyroid nodules influenced the diagnostic efficacy of CAD. The AUCs of CAD in the 5~<10 mm and ≥20 mm group were higher than those in the 10~<15 mm and 15~<20 mm group (P<0.001). There was no significant difference in AUC of the CAD between the normal background and Hashimoto thyroiditis background groups (P=0.82).

Conclusion

The CAD system exhibits a better diagnostic efficacy based on the ACR-TI-RADS, and the size of thyroid nodules influences the diagnostic efficacy of CAD

图1 CAD的使用流程。图a将图片以文件夹的形式导入工作站,可分析的图片格式包括DICOM或JPG/BMP;图b为方便下一步结节大小的测量,需要在图片上选取1 cm长的距离进行定标(红色虚线所示);图c定位结节最长径线及与之垂直的最长径线;图d基于上述2条线,CAD可自动勾画ROI区域;图e在勾画ROI区域之后,CAD可自动对病灶的6个特征(回声类型、边缘、内部回声、强回声点、纵/横比>1、无回声区域)进行分析;图f为CAD结合所提取的特征自动生成诊断报告,诊断报告根据7个指南对甲状腺结节进行恶性风险分层
图2 CAD基于ATA、ACR-TIRADS及K-TI-RADS三个指南进行诊断时的受试者工作特征曲线
表1 基于K-TI-RADS、ATA和ACR-TI-RADS指南时CAD的诊断效能
表2 不同结节大小时计算机辅助诊断系统的诊断效能
表3 不同甲状腺背景时计算机辅助诊断系统的诊断效能
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