ArticleFrontiers in oncology2020
Radiomics Nomogram of DCE-MRI for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Dynamic nomogram for predicting axillary lymph node metastasis in breast cancer based on MRI analysis and the platelet-to-lymphocyte ratio (PLR).Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- An interpretable weighted ensemble based on routinely collected clinical data for the accurate prediction of axillary lymph node metastasis.Quantitative imaging in medicine and surgery · 2026Article
- Radiomics-based signature of breast cancer on preoperative contrast-enhanced MRI to predict axillary metastasis.Future oncology (London, England) · 2026Article
- Assessing the diagnostic value of hemodynamic distinctions between axillary lymph nodes and adjacent vessels in breast cancer axillary lymph node metastasis via breast magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2026Article
- Integrating intratumoral and peritumoral radiomics with deep transfer learning from multiparametric MRI for preoperative prediction of HER2 status in breast cancer: a multicenter study.Frontiers in oncology · 2026Article
- The value of different machine learning radiomics based on DCE-MRI in predicting axillary lymph node status of breast cancer.Translational cancer research · 2025Article
- Radiomics integrated with machine and deep learning analysis of T2-weighted and arterial-phase T1-weighted Magnetic Resonance Imaging for non-invasive detection of metastatic axillary lymph nodes in breast cancer.La Radiologia medica · 2025Article
- Multiphase dynamic contrast-enhanced magnetic resonance imaging radiomics nomogram for predicting axillary lymph node metastasis in breast cancer.Gland surgery · 2025Article
- Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using Radiomics Features of Voxel-Wise DCE-MRI Time-Intensity-Curve Profile Maps.Biomedicines · 2025Article
- The Role of Multiparametric MRI Radiomics for Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer: A Comparative Study.Cancer innovation · 2025Article
- Article
- Opportunistic Screening with Radiomics Model Based on CT Imaging of Adrenal Adenoma to Assess Bone Mass Change.Orthopedic research and reviews · 2025Article
- An immune-related seven-gene signature for predicting lymph node metastasis in breast cancer.Frontiers in molecular biosciences · 2025Article
- Research on the application of distinguishing between benign and malignant breast nodules using MRI and US radiomics.Frontiers in oncology · 2025Article
- Dynamic contrast-enhanced MRI-based radiomics model of intra-tumoral kinetic heterogeneity for predicting breast cancer molecular subtypes.Frontiers in molecular biosciences · 2025Article
- Intratumoral and peritumoral multiparametric MRI-based radiomics nomogram for preoperative risk stratification in patients with endometrial cancer.Frontiers in oncology · 2025Article
- Radiomics models based on thoracic and upper lumbar spine in chest LDCT to predict low bone mineral density.Scientific reports · 2024Article
- Longitudinal ultrasound-based AI model predicts axillary lymph node response to neoadjuvant chemotherapy in breast cancer: a multicenter study.European radiology · 2024Article
- Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography.European radiology · 2024Article
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to establish and validate a radiomics nomogram based on dynamic contrast-enhanced (DCE)-MRI for predicting axillary lymph node (ALN) metastasis in breast cancer.
methodThis retrospective study included 296 patients with breast cancer who underwent DCE-MRI examinations between July 2017 and June 2018. A total of 396 radiomics features were extracted from primary tumor. In addition, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the features. Radiomics signature and independent risk factors were incorporated to build a radiomics nomogram model. Calibration and receiver operator characteristic (ROC) curves were used to confirm the performance of the nomogram in the training and validation sets. The clinical usefulness of the nomogram was evaluated by decision curve analysis (DCA).
resultsThe radiomics signature consisted of three ALN-status-related features, and the nomogram model included the radiomics signature and the MR-reported lymph node (LN) status. The model showed good calibration and discrimination with areas under the ROC curve (AUC) of 0.92 [95% confidence interval (CI), 0.87-0.97] in the training set and 0.90 (95% CI, 0.85-0.95) in the validation set. In the MR-reported LN-negative (cN0) subgroup, the nomogram model also exhibited favorable discriminatory ability (AUC, 0.79; 95% CI, 0.70-0.87). DCA findings indicated that the nomogram model was clinically useful.
conclusionsThe MRI-based radiomics nomogram model could be used to preoperatively predict the ALN metastasis of breast cancer.
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