ArticleFrontiers in endocrinology2025
Building radiomics models based on ACR TI-RADS combining clinical features for discriminating benign and malignant thyroid nodules.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Interpretable SVM-Based Integrated Ultrasound Model for Preoperative Thyroid Nodule Subtype Classification: Improved Identification of Follicular Variant Papillary Thyroid Carcinoma.Diagnostics (Basel, Switzerland) · 2026Article
- The Role of Cytology, Histology and Molecular Pathology in the Diagnostic Process of Thyroid Nodules.Cancers · 2026Review
- Radiomics: Current Applications and Future Directions.MedComm · 2026Review
- Malignancy-Aware Dual-Task Heatmap Decoupling for thyroid ultrasound nodule detection and classification.Frontiers in oncology · 2026Article
- Thyroid intelligent diagnosis based on THMSNet.Frontiers in endocrinology · 2025Article
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Abstract
Purpose: The aim of this study was to establish and validate a radiomics model combining the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and clinical features and to build a nomogram that could be utilized to enhance the diagnostic performance of malignant thyroid nodules. Method: From January 2019 to September 2022, 329 thyroid nodules from 323 patients who had been referred for surgery and had pathological evidence of them were gathered retrospectively and randomly allocated to training and test cohorts (8:2 ratio). A total of 107 radiomics features were extracted from the US images, and the radiomics score (Rad-score) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Different models were created using logistic regression, including the clinic-ACR score (Clin+ACR), clinic-Rad score (Clin+Rad), ACR score-Rad score (ACR+Rad), and combined clinic-ACR score-Rad score (Clin+ACR+Rad). The diagnostic performance of different models was calculated and compared using the area under the receiver operating curve (AUC) and the corresponding sensitivity and specificity. Results: Eight radiomics features were independent signatures for predicting malignant TNs, with malignant TNs having higher Rad-scores in both cohorts ( Conclusion: The current study offers preliminary support that the model of combined clinic-ACR score-radiomics score can be helpful for predicting malignancy in thyroid nodules by looking at a retrospective cohort of surgically treated thyroid nodules. The Clin-ACR-Rad nomogram may be a more practical instrument and more accurate prediction model for malignant thyroid nodules.
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