Related Experiment Video
Updated: Nov 20, 2025
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Development and Validation of a Diagnostic Nomogram for the Preoperative Differentiation Between Follicular Thyroid
Objective:
The aim of the study was to construct and validate a nomogram for differentiating follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA).
Methods:
Two hundred patients with pathologically confirmed thyroid follicular neoplasms were retrospectively analyzed. The patients were randomly divided into a training set (n = 140) and validation set (n = 60). Baseline data including demographics, CT (computed tomography) signs, and radiomic features were analyzed. Predictive models were developed and compared to build a nomogram. The predictive effectiveness of it was evaluated by the area under receiver operating characteristic curve (AUC).
Results:
The CT model, radiomic model and combination model showed excellent discrimination (AUCs [95% confidence interval] = 0.847 [0.766-0.928], 0.863 [0.746-0.932], 0.913 [0.850-0.975]). The nomogram based on the combination model showed remarkable discrimination in the training and validation sets. The calibration curves suggested good consistency between actual observation and prediction.
Conclusions:
This study proposed a nomogram that can accurately and intuitively predict the malignancy potential of follicular thyroid neoplasms.
