A Clinical Assessment of an Ultrasound Computer-Aided Diagnosis System in Differentiating Thyroid Nodules With Radiologists of Different Diagnostic Experience.
A Clinical Assessment of an Ultrasound Computer-Aided Diagnosis System in Differentiating Thyroid Nodules With Radiologists of Different Diagnostic Experience.
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具有不同诊断经验的放射科医生对超声计算机辅助诊断系统鉴别甲状腺结节的临床评估
DOI：
10.3389/fonc.2020.557169
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发表时间：
2020
影响因子：
4.7
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Zhang Y;Wu Q;Chen Y;Wang Y
本研究旨在评估甲状腺癌计算机辅助诊断(CAD)系统的诊断性能及其对不同级别放射科医生的附加值。方法回顾分析2018年10月至2019年7月收治的303例甲状腺切除术患者的临床资料。比较了高级放射科医生、初级放射科医生和CAD系统的诊断性能。对CAD系统的附加值进行评估，并根据甲状腺结节大小进行亚组分析。结果恶性结节186例，良性结节179例，其中乳头状癌168例，髓样癌7例，滤泡性癌11例，滤泡性腺瘤127例，结节性甲状腺肿52例。该系统显示出与高级放射科医师相似的特异度(86.0%比86.0%，p>；0.99)，但灵敏度较低，受试者操作特征曲线下面积较小(灵敏度：71.5%比95.2%，p<；0.001；AUROC：0.788比0.906，p<；0.001)。计算机辅助诊断系统提高了高级和初级放射科医生的诊断灵敏度(97.8%比95.2%，p=0.063；88.2%比75.3%，p<；0.001)。结论人工智能辅助诊断系统是鉴别甲状腺恶性结节的一种有潜力的工具，可作为经验较少的放射科医生提高诊断水平的参考。
Introduction This study aimed to assess the diagnostic performance and the added value to radiologists of different levels of a computer-aided diagnosis (CAD) system for the detection of thyroid cancers. Methods 303 patients who underwent thyroidectomy from October 2018 to July 2019 were retrospectively reviewed. The diagnostic performance of the senior radiologist, the junior radiologist, and the CAD system were compared. The added value of the CAD system was assessed and subgroup analyses were performed according to the size of thyroid nodules. Results In total, 186 malignant thyroid nodules, and 179 benign thyroid nodules were included; 168 were papillary thyroid carcinoma (PTC), 7 were medullary thyroid carcinoma (MTC), 11 were follicular carcinoma (FTC), 127 were follicular adenoma (FA) and 52 were nodular goiters. The CAD system showed a comparable specificity as the senior radiologist (86.0% vs. 86.0%, p > 0.99), but a lower sensitivity and a lower area under the receiver operating characteristic (AUROC) curve (sensitivity: 71.5% vs. 95.2%, p < 0.001; AUROC: 0.788 vs. 0.906, p < 0.001). The CAD system improved the diagnostic sensitivities of both the senior and the junior radiologists (97.8% vs. 95.2%, p = 0.063; 88.2% vs. 75.3%, p < 0.001). Conclusion The use of the CAD system using artificial intelligence is a potential tool to distinguish malignant thyroid nodules and is preferable to serve as a second opinion for less experienced radiologists to improve their diagnosis performance.
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影响因子：
1.1
作者：
Chang, Tien-Chun
通讯作者：
Chang, Tien-Chun
影响因子：
254.7
作者：
Fisher, Sarah B.;Perrier, Nancy D.
通讯作者：
Perrier, Nancy D.
影响因子：
6.6
作者：
Choi, Young Jun;Baek, Jung Hwan;Lee, Jeong Hyun
通讯作者：
Lee, Jeong Hyun
影响因子：
5
作者：
Reverter, Jordi L.;Vazquez, Federico;Puig-Domingo, Manuel
通讯作者：
Puig-Domingo, Manuel
影响因子：
3.4
作者：
Lam, J.;Ying, M.;Ahuja, A. T.
通讯作者：
Ahuja, A. T.