ArticleGland surgery2024
Combined model integrating clinical, radiomics, BRAF
Article in Gland surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Integrating miRNA profiling and machine learning for improved thyroid cancer diagnosis.Frontiers in oncology · 2026Article
- Development of a malignancy risk prediction model combining ultrasound and cytology for Bethesda category III thyroid nodules.World journal of surgical oncology · 2025Article
- Review
- A Mixed Model of Clinical Characteristics, Strain Elastography and ACR-TIRADS Predicts Malignancy in Small Thyroid Nodules: A Prospective Single-Center Study.Medicina (Kaunas, Lithuania) · 2025Article
- A predictive nomogram of thyroid nodules based on deep learning ultrasound image analysis.Frontiers in endocrinology · 2025Article
- Prediction of malignancy risk in Bethesda III nodules: development and validation of multiple machine learning models.Frontiers in endocrinology · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
Background: The management of thyroid nodules diagnosed as Bethesda III by fine-needle aspiration presents certain challenges, and there is an urgent need for a non-invasive and accurate method for early identification of the benign or malignant nature of Bethesda III nodules. Our objective is to develop and validate a clinical-radiomics nomogram based on preoperative ultrasound (US) images and clinical features, for predicting the malignancy of thyroid nodules with indeterminate cytology (Bethesda III). Methods: Between June 2017 and June 2022, we conducted a retrospective study on 274 patients with surgically confirmed indeterminate cytology (Bethesda III) across two separate medical centers in Shanghai. The training and internal validation sets were comprised of 136 and 58 patients, respectively, all sourced from Shanghai's Sixth People's Hospital. To facilitate external test, a further 80 patients were selected from Tinglin Hospital. Utilizing preoperative US data, we obtained imaging markers for radiomic features. After feature selection, we developed a comprehensive diagnostic model to evaluate the predictive value for Bethesda III benign and malignant cases. The model's diagnostic accuracy, calibration, and clinical applicability were systematically assessed. Results: The results showed that the prediction model, which integrated US radiomics, and clinical risk features, exhibited superior stability in distinguishing between benign and malignant indeterminate thyroid nodules (Bethesda III). In the external test set, the area under the curve (AUC) was 0.824 [95% confidence interval (CI): 0.718-0.929], and the accuracy, sensitivity, specificity, precision, and recall were 0.775, 0.731, 0.796, 0.633, and 0.731, respectively. Conclusions: An integrated model, utilizing US radiomics and clinical risk features, effectively discriminates between benign and malignant indeterminate thyroid nodules (Bethesda III), thereby minimizing the need for unnecessary diagnostic surgeries and subsequent complications.
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