Department of Ultrasound, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, 200025, China.
Department of Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
Endocrine. 2021 Apr;72(1):157-170. doi: 10.1007/s12020-020-02442-x. Epub 2020 Aug 27.
To establish a practical and simplified Chinese thyroid imaging reporting and data system (C-TIRADS) based on the Chinese patient database.
A total of 2141 thyroid nodules that were neither cystic nor spongy were used in the current study. These specimens were derived from 2141 patients in 131 alliance hospitals of the Chinese Artificial Intelligence Alliance for Thyroid and Breast Ultrasound. The ultrasound features, including location, orientation, margin, halo, composition, echogenicity, echotexture, echogenic foci and posterior features were assessed. Univariate and multivariate analyses were performed to investigate the association between ultrasound features and malignancy. The regression equation, the weighting, and the counting methods were used to determine the malignant risk of the thyroid nodules. The areas under the receiver operating characteristic curve (Az values) were calculated.
Of the 2141 thyroid nodules, 1572 were benign, 565 were malignant, and 4 were borderline. Vertical orientation, ill-defined, or irregular margin (including extrathyroidal extension), microcalcifications, solid, and markedly hypoechoic were positively associated with malignancy, while comet-tail artifacts were negatively associated with malignancy. The logistic regression equation yielded the highest Az value of 0.913, which was significantly higher than that obtained using the weighting method (0.893) and the counting method (0.890); however, no significant difference was found between the latter two. The C-TIRADS, based on the counting method, was designed following the principle of balancing the diagnostic performance and sensitivity of the risk stratification with the ease of use.
A relatively simple C-TIRADS was established using the counting value of positive and negative ultrasound features.
基于中国患者数据库，建立实用且简化的中文甲状腺影像报告和数据系统（C-TIRADS）。
本研究共纳入 2141 个非囊性和海绵状甲状腺结节，这些标本来源于中国人工智能甲状腺及乳腺超声联盟的 131 家联盟医院的 2141 名患者。评估超声特征，包括位置、方位、边界、晕环、成分、回声、回声纹理、回声灶和后方特征。进行单因素和多因素分析，以探讨超声特征与恶性肿瘤之间的关系。采用回归方程、加权和计数方法来确定甲状腺结节的恶性风险。计算受试者工作特征曲线下的面积（Az 值）。
在 2141 个甲状腺结节中，1572 个为良性，565 个为恶性，4 个为交界性。垂直方位、边界不清或不规则（包括甲状腺外延伸）、微钙化、实性和明显低回声与恶性肿瘤呈正相关，彗星尾伪影与恶性肿瘤呈负相关。逻辑回归方程产生的 Az 值最高，为 0.913，显著高于加权法（0.893）和计数法（0.890）；然而，后两者之间没有显著差异。基于计数法的 C-TIRADS 遵循平衡风险分层的诊断性能和敏感性与易用性的原则设计。
采用阳性和阴性超声特征的计数值建立了一种相对简单的 C-TIRADS。
