ArticleThe British journal of radiology2022
Ultrasound-based radiomics nomogram for differentiation of triple-negative breast cancer from fibroadenoma.
Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Prognostic value of ultrasound Breast Imaging Reporting and Data System for disease-free survival in early-stage breast cancer: a retrospective study (2011-2018).Quantitative imaging in medicine and surgery · 2026Article
- TMAN: A Triple Morphological Feature Attention Network for Fine-Grained Classification of Breast Ultrasound Images.Journal of imaging informatics in medicine · 2026Article
- Prognostic prediction model for triple-negative breast cancer using artificial intelligence and ultrasound radiomics.Frontiers in oncology · 2026Article
- A delta radiomics model based on ultrasound images predicts response to neoadjuvant therapy in triple negative breast cancer.Journal of applied clinical medical physics · 2025Article
- Early prediction of neoadjuvant chemotherapy efficacy among patients with triple-negative breast cancer using an ultrasound-based radiomics nomogram.Diagnostic and interventional radiology (Ankara, Turkey) · 2025Article
- Differentiating triple-negative breast cancer and atypical fibroadenomas using an ultrasound-based radiomics nomogram.BMC medical imaging · 2025Article
- Ultrasound-based radiomic nomogram for predicting the invasive status of breast cancer: a multicenter study.European journal of medical research · 2025Article
- Bi-modal ultrasound radiomics and habitat analysis enhanced the pre-operative prediction of axillary lymph node burden in patients with early-stage breast cancer.Frontiers in oncology · 2025Article
- Ultrasound-based radiomics for the evaluation of breast cancer.Frontiers in oncology · 2025Review
- A combined clinical-ultrasound radiomics model for differentiating benign and malignant BI-RADS category 4 breast masses.American journal of translational research · 2025Article
- Ultrasound characteristics comparison and development of a predictive nomogram for intraductal papilloma and ductal carcinomaFrontiers in oncology · 2025Article
- An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.Radiological physics and technology · 2024Review
- Expansive Receptive Field and Local Feature Extraction Network: Advancing Multiscale Feature Fusion for Breast Fibroadenoma Segmentation in Sonography.Journal of imaging informatics in medicine · 2024Article
- An Intraoperative Ultrasound Evaluation of Axillary Lymph Nodes: Cassandra Predictive Models in Patients with Breast Cancer-A Multicentric Study.Medicina (Kaunas, Lithuania) · 2024Article
- The potential role of breast MRI in evaluation of triple-negative breast cancer and fibroadenoma of less than 3 cm.Translational cancer research · 2024Article
- Predicting hormone receptor status in invasive breast cancer through radiomics analysis of long-axis and short-axis ultrasound planes.Scientific reports · 2024Article
- Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer.BMC medical imaging · 2024Article
- Article
- Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review).Oncology reports · 2024Review
- Artificial Intelligence Decision Support for Triple-Negative Breast Cancers on Ultrasound.Journal of breast imaging · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
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Abstract
objectiveThis study aimed to develop a radiomics nomogram that incorporates radiomics, conventional ultrasound (US) and clinical features in order to differentiate triple-negative breast cancer (TNBC) from fibroadenoma.
methodsA total of 182 pathology-proven fibroadenomas and 178 pathology-proven TNBCs, which underwent preoperative US examination, were involved and randomly divided into training (
resultsThe radiomics signature, composed of 12 selected features, achieved good diagnostic performance. The nomogram incorporated with radiomics signature and clinical data showed favorable diagnostic efficacy in the training cohort (AUC 0.986, 95% CI, 0.975-0.997) and validation cohort (AUC 0.977, 95% CI, 0.953-1.000). The radiomics nomogram outperformed the Rad-score and clinical models (
conclusionThe radiomics signature is a potential predictive indicator for differentiating TNBC and fibroadenoma. The radiomics nomogram associated with Rad-score, US conventional features, and clinical data outperformed the Rad-score and clinical models. ADVANCES IN KNOWLEDGE: Recent advances in radiomics-based US are increasingly showing potential for improved diagnosis, assessment of therapeutic response and disease prediction in oncology. Rad-score is an independent predictive indicator for differentiating TNBC and fibroadenoma. The radiomics nomogram associated with Rad-score, US conventional features, and clinical data outperformed the Rad-score and clinical models.
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