| 孙鑫,周平,赵永峰,章燕,梁永平,石一帆.AmCAD-UT Detection在甲状腺结节超声诊断中的应用[J].中国医学影像技术,2020,36(5):749~753 |
| AmCAD-UT Detection在甲状腺结节超声诊断中的应用 |
| Application of AmCAD-UT Detection in ultrasonic diagnosis of thyroid nodules |
| 投稿时间：2019-05-28 修订日期：2020-02-19 |
| DOI：10.13929/j.issn.1003-3289.2020.05.026 |
| 中文关键词: 甲状腺结节 超声检查 计算机辅助诊断 |
| 英文关键词:thyroid nodule ultrasonography computer-aided diagnosis |
| 基金项目:国家自然科学基金项目（81871367）、湖南省科技厅科技计划资助项目（2018SK21217）。 |
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| 中文摘要: |
| 目的 评估计算机辅助诊断（CAD）系统AmCAD-UT Detection（安克侦）用于甲状腺超声的诊断效能及临床价值。方法 采集171例甲状腺结节患者的甲状腺超声图像，分别由安克侦及4名超声科医师（A、B、C、D，分别具有10年、5年、1年及1个月以上甲状腺超声诊断经验）单独及以安克侦辅助医师分析图像，并根据美国放射学会甲状腺影像报告和数据系统（ACR-TIRADS）指南进行分类；以病理结果为金标准，绘制安克侦及4名医师辅以安克侦前后根据ACR-TIRADS指南对结节进行分类的ROC曲线，计算ACR-TIRADS指南诊断良恶性结节的最佳截断值及AUC，评价其诊断效能。结果 共纳入205个甲状腺结节，89个良性、116个恶性病变。ACR-TIRADS指南诊断良恶性结节的最佳截断值为TR5级。安克侦诊断甲状腺恶性结节的敏感度与医师B差异无统计学意义（P=1.00），特异度则低于医师A及B（P均<0.05），其AUC与医师A、B、D差异均有统计学意义（Z=4.34、3.71、2.76，P均<0.05）。辅以安克侦后，4名医师诊断甲状腺结节的敏感度（93.10%、90.52%、85.34%、75.00%）及AUC值（0.95、0.93、0.86、0.86）均较前提高（P均<0.05），特异度则仅医师C、D较前改善（P均<0.05）。结论 安克侦对诊断甲状腺结节具有一定价值，敏感度与具有5年诊断经验的超声科医师相似，用以辅助可提高超声科医师、尤其是低年资医师对于甲状腺结节的诊断效能。 |
| 英文摘要: |
| Objective To evaluate the diagnostic efficiency and clinical application value of computer-aided diagnosis (CAD) system AmCAD-UT Detection in thyroid ultrasound examination. Methods Totally 171 patients with thyroid nodules requiring ultrasonic examination were collected. Ultrasonic thyroid images of all patients were obtained, then were analyzed with AmCAD-UT Detection only, 4 ultrasound physicians (A, B, C, D, having more than 10 years, 5 years, 1 year and 1 month experience, respectively) with or without AmCAD-UT Detection, respectively, and the nodules were classified according to the American College of Radiology Thyroid Imaging Reporting and Data System guidelines (ACR-TIRADS).Taken pathologic results as the gold standards, ROC curves of the classification of nodules of mCAD-UT Detection and 4 radiologists using the former or not were drawn according to ACR-TIRADS, and the optimal cut-off value for diagnosis of nodule malignancy with ACR-TIRADS guidelines and AUC were calculated, and their diagnostic efficacy were then analyzed. Results A total of 205 thyroid nodules were involved, with 89 benign and 116 malignant lesions. TR5 was the optimal cut-off value for diagnosis of benign or malignant nodule with ACR-TIRADS. The diagnostic sensitivity of AmCAD-UT Detection to diagnose thyroid malignant nodule was similar to that of physician B (P=1.00), and the specificity was lower than that of physician A and B (both P<0.05), while its AUC was statistically different with physician A, B and D (Z=4.34, 3.71, 2.76, all P<0.05). With AmCAD-UT Detection, the sensitivity (93.10%, 90.52%, 85.34%, 75.00%) and AUC values (0.95, 0.93, 0.86, 0.86) of diagnosis of thyroid nodules of all physicians were improved (all P<0.05), while for the specificity, only physician C and D had better results (both P<0.05). Conclusion Thyroid CAD system AmCAD-UT Detection has certain value for diagnosing thyroid nodules, with sensitivity similar to physician with 5 years ultrasound diagnostic experience, therefore can be used to improve diagnosis efficiency of thyroid nodule of physicians, especially for those with less experiences. |
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