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Updated: Oct 11, 2025

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
Published on: June 9, 2023
A computed tomography-based radiomic nomogram for predicting lymph node metastasis in patients with early-stage
Lisha Lai1, Qianwen Guan2, Yingying Liang1
1Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong Province, PR China.
Background:
Accurate assessment of lymph node metastasis (LNM) is important for the selection of the optimal therapeutic strategy in patients with papillary thyroid carcinoma (PTC).
Purpose:
To develop and validate a radiomics nomogram based on computed tomography (CT) for predicting LNM in patients with early-stage PTC.
Material And Methods:
A total of 92 patients with pathologically confirmed PTC were divided into a training cohort (n = 64) and validation cohort (n = 28). Radiomic features of the tumor and peritumoral interstitium were extracted from contrast-enhanced CT images. The radiomic signature was constructed and the radiomic score (Rad-score) was calculated. Combined with the Rad-score and independent clinical factors, a radiomic nomogram was constructed and its performance was assessed by receiver operating characteristic (ROC) curves and calibration plots. The comparison of ROC curves was performed with DeLong's test.
Results:
A combined nomogram model of the thyroid tumor and peritumoral interstitium was constructed based on the Rad-score, tumor location, maximum diameter, and T stage, and it had areas under the ROC curve of 0.956 (95% confidence interval [CI] = 0.913-1.000) and 0.876 (95% CI = 0.741-1.000) in the training and validation cohorts, respectively. Decision curve analysis suggested that the combined nomogram model had better clinical usefulness than the other models.
Conclusion:
A CT-based radiomics nomogram incorporating the radiomic signature and the selected clinical predictors can be a reliable approach to preoperatively predict the LNM status in patients with early-stage PTC, which is helpful for treatment decisions and prognosis.
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