Wei Peiying, Jiang Niandong, Ding Jinwang, Xiang JingJing, Wang Luoyu, Wang Haibin, Gu Ying, Luo DingCun, Han Zhijiang
Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Department of Radiology, Chunan County Hospital of Traditional Chinese Medicine, Hangzhou, China.
Front Oncol. 2020 Jun 5;10:911. doi: 10.3389/fonc.2020.00911. eCollection 2020.
Coarse calcifications are prone to cause echo attenuation during ultrasonography (US) and hence affect the classification of benign and malignant nodules. This study aimed to investigate the diagnostic role of computed tomography (CT) for differentiating the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4-5 nodules with coarse calcifications. CT data of 216 ACR TI-RADS 4-5 nodules with coarse calcifications confirmed by surgery and pathology in 207 patients were analyzed retrospectively. Halo sign, artifacts, and CT values (i.e., Hounsfield unit) of the nodules were determined by two radiologists. Univariate analysis and binary logistic regression were used to determine the relationship of halo sign, artifact, and CT value with benign nodules. A predictive model for benign nodules with coarse calcifications was then constructed. The receiver operating characteristic (ROC) curve was used to analyze the predictive value of halo sign, artifact, CT value, and logistic regression model. Of the 216 ACR TI-RADS 4-5 nodules with coarse calcifications, 170 were benign and 46 were malignant. There were 92 benign and 7 malignant nodules with halo sign (χ = 22.067, < 0.001), and 79 benign and 10 malignant nodules with artifacts (χ = 9.140, < 0.001). The CT values of benign and malignant nodules were 791 (543-1,025) Hu and 486 (406-670) Hu, respectively ( = -5.394, < 0.001). Binary logistic regression demonstrated that the halo sign, artifact, and CT value were independent predictors for benign nodules with coarse calcifications. The area under the ROC curve (AUC) of halo sign, artifact, CT value and regression model for predicting benign nodules with coarse calcifications were 0.776, 0.711, 0.784, and 0.850, respectively, and the optimal threshold of CT value was 627.5 Hu. Halo sign, artifact, and CT value > 627.5 Hu were helpful for identifying ACR TI-RADS 4-5 thyroid benign nodules with coarse calcifications. The diagnostic performance of the logistic regression model was higher than that of any single indicator. Accurate identification of these indicators could identify benign nodules and reduce unnecessary surgical trauma.
粗大钙化在超声检查（US）过程中容易导致回声衰减，从而影响良性和恶性结节的分类。本研究旨在探讨计算机断层扫描（CT）对鉴别美国放射学会（ACR）甲状腺影像报告和数据系统（TI-RADS）4-5类伴有粗大钙化的结节的诊断作用。回顾性分析了207例患者中经手术及病理证实的216个ACR TI-RADS 4-5类伴有粗大钙化的结节的CT数据。由两名放射科医生确定结节的晕环征、伪影和CT值（即亨氏单位）。采用单因素分析和二元逻辑回归分析来确定晕环征、伪影和CT值与良性结节的关系。然后构建了一个伴有粗大钙化的良性结节的预测模型。采用受试者操作特征（ROC）曲线分析晕环征、伪影、CT值及逻辑回归模型的预测价值。在216个ACR TI-RADS 4-5类伴有粗大钙化的结节中，170个为良性，46个为恶性。有晕环征的良性结节92个，恶性结节7个（χ = 22.067，P < 0.001）；有伪影的良性结节79个，恶性结节10个（χ = 9.140，P < 0.001）。良性和恶性结节的CT值分别为791（543 - 1025）Hu和486（406 - 670）Hu（t = -5.394，P < 0.001）。二元逻辑回归分析表明，晕环征、伪影和CT值是伴有粗大钙化的良性结节的独立预测因素。晕环征、伪影、CT值及回归模型预测伴有粗大钙化的良性结节的ROC曲线下面积（AUC）分别为0.776、0.711、0.784和0.850，CT值的最佳阈值为627.5 Hu。晕环征、伪影及CT值>627.5 Hu有助于识别ACR TI-RADS 4-5类伴有粗大钙化的甲状腺良性结节。逻辑回归模型的诊断性能高于任何单一指标。准确识别这些指标可鉴别出良性结节并减少不必要的手术创伤。
