ArticleLa Radiologia medica2024
Utilizing grayscale ultrasound-based radiomics nomogram for preoperative identification of triple negative breast cancer.
Article in La Radiologia medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 15 citations in OpenAlex.
- From Multimodal Data to Clinical Insight: An Explainable Model for Preoperative Salivary Gland Lesion Diagnosis.Oral diseases · 2026Article
- AI-mediated ultrasound radiomics in the diagnosis and treatment of triple-negative breast cancer: research progress and future challenges.Frontiers in oncology · 2026Review
- The Effect of Ultrasound Image Pre-Processing on Radiomics Feature Quality: A Study on Shoulder Ultrasound.Journal of imaging informatics in medicine · 2025Article
- Diagnostic value of ultrasound radiomic features in differentiating benign and malignant breast lesions.Journal of ultrasound · 2025Article
- Knowledge mapping of ultrasound technology and triple-negative breast cancer: a visual and bibliometric analysis.Discover oncology · 2025Article
- Assessment of CuFeSeNano convergence · 2025Article
- Intratumoral and peritumoral ultrasound-based radiomics for preoperative prediction of HER2-low breast cancer: a multicenter retrospective study.Insights into imaging · 2025Article
- Integrating radiomics into predictive models for low nuclear grade DCIS using machine learning.Scientific reports · 2025Article
- Ultrasound-based radiogenomics: status, applications, and future direction.Ultrasonography (Seoul, Korea) · 2025Article
- A combined clinical-ultrasound radiomics model for differentiating benign and malignant BI-RADS category 4 breast masses.American journal of translational research · 2025Article
- Ultrasound-based radiomics for the evaluation of breast cancer.Frontiers in oncology · 2025Review
- An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies.Current oncology (Toronto, Ont.) · 2024Review
- Clinical and radiomics integrated nomogram for preoperative prediction of tumor-infiltrating lymphocytes in patients with triple-negative breast cancer.Frontiers in oncology · 2024Article
- Early precise screening of pulmonary nodules: risk factor analysis for malignant nodules.American journal of translational research · 2024Article
- Ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer.Frontiers in oncology · 2024Article
- The use of MFAP2 for diagnosis, prognosis and immunotherapy of triple-negative breast cancer.American journal of translational research · 2024Article
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
purposeThis study aimed to develop a radiomics nomogram based on grayscale ultrasound (US) to distinguish triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (NTNBC) prior to surgery.
methodsA retrospective analysis of 454 breast carcinoma patients confirmed by pathology was conducted, with 317 patients in the training dataset (59 with TNBC) and 137 patients in the validation dataset (27 with TNBC). Clinical information, conventional US features, and radiomics features were collected, and the Radscore model was constructed after feature selection. Independent risk factors were identified using univariate and multivariate logistic regression analysis. The nomogram model was assessed using the receiver operating characteristic (ROC) curve analysis, calibration curve, decision curve analysis (DCA), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).
resultsTumor shape, margin, and calcification were independent risk factors in the clinical prediction model. Additionally, 16 radiomics features were selected to construct the Radscore model out of a total of 474 extracted features. The radiomics nomogram model, which incorporated tumor shape, margin, calcification, and Radscore, achieved an AUC value of 0.837 in the training dataset and 0.813 in the validation dataset, outperforming both the Radscore and clinical models in terms of predictive performance. The significant improvement of NRI and IDI indicated that the Radscore may be useful biomarkers for TNBC.
conclusionThe US-based radiomics nomogram showed satisfactory preoperative prediction of TNBC.
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