Yuan Ya, Shu Hua, Li Lu, Wu Liuxi, Yu Fei
Department of Ultrasound, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, 210029, China.
Department of Ultrasound, Nanjing Drum Tower Hospital, Nanjing, Jiangsu Province, 210000, China.
BMC Med Imaging. 2025 Apr 10;25(1):114. doi: 10.1186/s12880-025-01633-0.
To develop an ultrasound feature-based risk stratification system for differentiating benign, low-risk and malignant thyroid tumors and compare it with existing TI-RADS.
The retrospective study included patients who underwent preoperative neck ultrasound examination from January 2018 to June 2023, and their ultrasound characteristics were recorded. According to surgical pathological findings, they were classified into three categories: benign, low-risk, and malignant. Univariable and multivariable logistic regression analyses were used to assess the association of qualitative ultrasound features with different risk stratifications and a new scoring system was established to evaluate its diagnostic efficacy, and to compare it with TI-RADS.
Aspect ratio ≥1 was an independent risk factor in the comparison of benign and low-risk thyroid nodules, and in the comparison of benign and malignant nodules, hypoechoic,irregular margin,nodule max diameter ≤1 cm,the aspect ratio ≥1 and elasticity score ≥3 were independent risk factors. According to the multivariate analysis, they were assigned 1, 2, 2, 3, 2/4 points respectively, and we established a new scoring system. According to ROC analysis, the total score of 0-4.5 was considered as benign nodules, 4.5-5.5 was considered as low-risk nodules, and more than 5.5 were considered as malignant nodules. Compared it to ACR-TI-RADS, this scoring system performed better than in differentiating benign and malignant nodules (P = 0.001, P = 0.018, respectively).
The scoring system based on ultrasound features established in this study can be used for risk stratification of thyroid nodules more efficiently, it has higher sensitivity and specificity for the differentiation of benign and malignant nodules.
开发一种基于超声特征的风险分层系统，用于区分良性、低风险和恶性甲状腺肿瘤，并将其与现有的甲状腺影像报告和数据系统（TI-RADS）进行比较。
这项回顾性研究纳入了2018年1月至2023年6月接受术前颈部超声检查的患者，并记录了他们的超声特征。根据手术病理结果，将他们分为三类：良性、低风险和恶性。采用单变量和多变量逻辑回归分析来评估定性超声特征与不同风险分层之间的关联，并建立一个新的评分系统来评估其诊断效能，并与TI-RADS进行比较。
在良性与低风险甲状腺结节的比较中，纵横比≥1是独立危险因素；在良性与恶性结节的比较中，低回声、边界不规则、结节最大直径≤1 cm、纵横比≥1和弹性评分≥3是独立危险因素。根据多变量分析，分别赋予它们1、2、2、3、2/4分，我们建立了一个新的评分系统。根据ROC分析，总分0-4.5被认为是良性结节，4.5-5.5被认为是低风险结节，超过5.5被认为是恶性结节。与美国放射学会（ACR）-TI-RADS相比，该评分系统在区分良性和恶性结节方面表现更好（P分别为0.001和0.018）。
本研究建立的基于超声特征的评分系统可更有效地用于甲状腺结节的风险分层，对区分良性和恶性结节具有更高的敏感性和特异性。
