ArticleJournal of digital imaging2022
Differentiate Thyroid Follicular Adenoma from Carcinoma with Combined Ultrasound Radiomics Features and Clinical Ultrasound Features.
Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Sociodemographic and clinical predictors of malignancy in thyroid nodules: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- Dynamic Ensemble Transfer Learning with Multi-view Ultrasonography for Improving Thyroid Cancer Diagnostic Reliability.Journal of imaging informatics in medicine · 2026Article
- Construction and Validation of a Nomogram Based on Radiomics and Clinical Features for Discerning Malignant Soft Tissue TumorsCurrent medical imaging · 2026Article
- Thyroid cancer: From molecular insights to therapy (Review).Oncology letters · 2025Review
- Multimodal model enhances qualitative diagnosis of hypervascular thyroid nodules: integrating radiomics and deep learning features based on B-mode and PDI images.Gland surgery · 2025Article
- Deep learning-based differentiation of benign and malignant thyroid follicular neoplasms on multiscale intraoperative frozen pathological images: A multicenter diagnostic study.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025Article
- Multimodal ultrasound radiomics model combined with clinical model for differentiating follicular thyroid adenoma from carcinoma.BMC medical imaging · 2025Article
- Clinical Application of Artificial Intelligence in Ultrasound Imaging for Oncology.JMA journal · 2025Review
- Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI.Journal of imaging informatics in medicine · 2024Article
- Intratumoral and peritumoral radiomics based on ultrasound for the differentiation of follicular thyroid neoplasm.Gland surgery · 2024Article
- Radiomics and deep learning for large volume lymph node metastasis in papillary thyroid carcinoma.Gland surgery · 2024Article
- Ultrasound characteristics of follicular and parafollicular thyroid neoplasms: diagnostic performance of artificial neural network.Thyroid research · 2023Article
- Ultrasound-based radiomics analysis in the assessment of renal fibrosis in patients with chronic kidney disease.Abdominal radiology (New York) · 2023Article
- Differential diagnosis of gallbladder neoplastic polyps and cholesterol polyps with radiomics of dual modal ultrasound: a pilot study.BMC medical imaging · 2023Article
- Radiomics-based ultrasound models for thyroid nodule differentiation in Hashimoto's thyroiditis.Frontiers in endocrinology · 2023Article
- A Clinical Retrospective Study on the Qualitative Value of Multimodal Ultrasonography for ACR-TIRADS 4 Thyroid Nodules Ranging from 1 cm to 1.5 cm.Technology in cancer research & treatmentArticle
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
Noninvasive differentiating thyroid follicular adenoma from carcinoma preoperatively is of great clinical value to decrease the risks resulted from excessive surgery for patients with follicular neoplasm. The purpose of this study is to investigate the accuracy of ultrasound radiomics features integrating with ultrasound features in the differentiation between thyroid follicular carcinoma and adenoma. A total of 129 patients diagnosed as thyroid follicular neoplasm with pathologically confirmed follicular adenoma and carcinoma were enrolled and analyzed retrospectively. Radiomics features were extracted from preoperative ultrasound images with manually contoured targets. Ultrasound features and clinical parameters were also obtained from electronic medical records. Radiomics signature, combined model integrating radiomics features, ultrasound features, and clinical parameters were constructed and validated to differentiate the follicular carcinoma from adenoma. A total of 23 optimal features were selected from 449 extracted radiomics features. Clinical and ultrasound parameters of sex (p = 0.003), interior structure (p = 0.035), edge (p = 0.02), platelets (p = 0.007), and creatinine (p = 0.001) were associated with the differentiation between benign and malignant follicular neoplasm. The values of area under curves (AUCs) of the radiomics signature, clinical model, and combined model were 0.772 (95% CI: 0.707-0.838), 0.792 (95% CI: 0.715-0.869), and 0.861 (95% CI: 0.775-0.909), respectively. A final corrected AUC of 0.844 was achieved for the combined model after internal validation. Radiomics features from ultrasound images combined with ultrasound features and clinical factors are feasible to differentiate thyroid follicular carcinoma from adenoma noninvasive before operation to decrease the unnecessary of diagnostic thyroidectomy for patients with benign follicular adenoma.
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