不同 TI-RADS 应用超声计算机辅助诊断甲状腺结节的诊断性能评估：调整设置后的经验。

Diagnostic performance evaluation of different TI-RADS using ultrasound computer-aided diagnosis of thyroid nodules: An experience with adjusted settings.

机构信息

Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, SAR, China.

Department of Surgery, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, SAR, China.

出版信息

PLoS One. 2021 Jan 15;16(1):e0245617. doi: 10.1371/journal.pone.0245617. eCollection 2021.

BACKGROUND

Thyroid cancer diagnosis has evolved to include computer-aided diagnosis (CAD) approaches to overcome the limitations of human ultrasound feature assessment. This study aimed to evaluate the diagnostic performance of a CAD system in thyroid nodule differentiation using varied settings.

METHODS

Ultrasound images of 205 thyroid nodules from 198 patients were analysed in this retrospective study. AmCAD-UT software was used at default settings and 3 adjusted settings to diagnose the nodules. Six risk-stratification systems in the software were used to classify the thyroid nodules: The American Thyroid Association (ATA), American College of Radiology Thyroid Imaging, Reporting, and Data System (ACR-TIRADS), British Thyroid Association (BTA), European Union (EU-TIRADS), Kwak (2011) and the Korean Society of Thyroid Radiology (KSThR). The diagnostic performance of CAD was determined relative to the histopathology and/or cytology diagnosis of each nodule.

RESULTS

At the default setting, EU-TIRADS yielded the highest sensitivity, 82.6% and lowest specificity, 42.1% while the ATA-TIRADS yielded the highest specificity, 66.4%. Kwak had the highest AUROC (0.74) which was comparable to that of ACR, ATA, and KSThR TIRADS (0.72, 0.73, and 0.70 respectively). At a hyperechoic foci setting of 3.5 with other settings at median values; ATA had the best-balanced sensitivity, specificity and good AUROC (70.4%; 67.3% and 0.71 respectively).

CONCLUSION

The default setting achieved the best diagnostic performance with all TIRADS and was best for maximizing the sensitivity of EU-TIRADS. Adjusting the settings by only reducing the sensitivity to echogenic foci may be most helpful for improving specificity with minimal change in sensitivity.

背景

甲状腺癌的诊断已经发展到包括计算机辅助诊断（CAD）方法，以克服人类超声特征评估的局限性。本研究旨在评估 CAD 系统在使用不同设置区分甲状腺结节方面的诊断性能。

方法

在这项回顾性研究中，对 198 名患者的 205 个甲状腺结节的超声图像进行了分析。AmCAD-UT 软件在默认设置和 3 种调整设置下用于诊断结节。软件中使用了 6 种风险分层系统对甲状腺结节进行分类：美国甲状腺协会（ATA）、美国放射学院甲状腺成像、报告和数据系统（ACR-TIRADS）、英国甲状腺协会（BTA）、欧盟（EU-TIRADS）、Kwak（2011 年）和韩国甲状腺放射学会（KSThR）。CAD 的诊断性能相对于每个结节的组织病理学和/或细胞学诊断来确定。

结果

在默认设置下，EU-TIRADS 的敏感性最高，为 82.6%，特异性最低，为 42.1%，而 ATA-TIRADS 的特异性最高，为 66.4%。Kwak 的 AUROC 最高（0.74），与 ACR、ATA 和 KSThR TIRADS（分别为 0.72、0.73 和 0.70）相当。在其他设置为中位数，而回声焦点设置为 3.5 时；ATA 的敏感性、特异性和良好的 AUROC 最佳（分别为 70.4%、67.3%和 0.71）。