Role of Ultrasound and Ultrasound-Based Prediction Model in Differentiating Follicular Thyroid Carcinoma From Follicular Thyroid Adenoma

Abstract

Objectives: This study aims to identify distinct ultrasound (US) characteristics for distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA), and construct a user-friendly preoperative risk stratification model for thyroid follicular neoplasms.

Methods: In this retrospective study, patients diagnosed with pathologically confirmed FTA or FTC and undergoing US examinations between July 2017 and June 2021 were designated as the training cohort, and those from July 2021 to June 2023 were enrolled as the external validation set. We systematically assessed and compared the sonographic and clinical characteristics of FTC and FTA. Univariable and multivariable logistic regression analyses were used to assess the association of US features with FTC in the training set. A prediction nomogram model, incorporating US features independently associated with FTC, was developed and validated externally to assess its performance.

Results: A total of 645 patients (FTA/FTC = 530/115) were included in the training set, while 197 patients (FTA/FTC = 165/32) constituted the validation set. In the training set, solid composition, hypo-echogenicity, irregular margin, calcification, protrusion sign, trabecular formation, absent or thick halo, and mainly central hypervascularity were identified as independent factors associated with FTC. The prediction nomogram model constructed using these variables showed good performance in differentiating FTC from FTA with an area under the curve of 0.948 in the training set and 0.915 in the validation set.

Conclusions: The preoperative nomogram model constructed based on US features serves as an effective tool for the risk stratification of thyroid follicular neoplasms.