Diagnostic nomogram model for ACR TI-RADS 4 nodules based on clinical, biochemical data, and sonographic patterns

In this study, we aim to establish and validate a nomogram model for predicting the malignancy rates in the Thyroid Imaging Reporting and Data System 4 (TR4) nodules. Briefly, 1557 cases were retrospectively collected from our medical center. 8 out of 22 variables (age, margin, extrathyroidal extension, halo, calcification, suspicious lymph node metastasis, aspect ratio, and thyroid peroxidase antibody) were used to build a diagnostic nomogram model. The presented nomogram model has satisfied clinical practicability in predicting the malignancy probability of the TR4 nodules.

本研究旨在构建并验证一款用于预测甲状腺影像报告和数据系统4级（Thyroid Imaging Reporting and Data System 4，TR4）结节恶性率的列线图模型。简言之，本研究回顾性收集了本医学中心的1557例病例资料，从22项变量中筛选出8项（年龄、结节边缘、甲状腺外侵犯、晕征、钙化、可疑淋巴结转移、纵横比及甲状腺过氧化物酶抗体）用于构建诊断性列线图模型。所构建的列线图模型在预测TR4结节恶性概率方面具备良好的临床实用性。