ArticleFrontiers in oncology2020
Predicting Axillary Lymph Node Status With a Nomogram Based on Breast Lesion Ultrasound Features: Performance in N1 Breast Cancer Patients.
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 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- 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
- Nomogram prediction model for pathological complete response of metastatic axillary lymph nodes of breast cancer after neoadjuvant chemotherapy.BMC medical imaging · 2026Article
- Construction and Validation of a Nomogram Based on Radiomics and Clinical Features for Discerning Malignant Soft Tissue TumorsCurrent medical imaging · 2026Article
- Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model.European journal of medical research · 2025Article
- Prognosticating axillary lymph node metastasis in breast cancer through integrated photoacoustic imaging, ultrasound, and clinical parameters.Breast cancer research : BCR · 2025Article
- Ultrasound radiomics predicts preoperative axillary lymph node metastasis status in early-stage breast cancer to support surgical decisions: a machine learning, monocenter study.Frontiers in oncology · 2025Article
- Development of fully automated deep-learning-based approach for prediction of sentinel lymph node metastasis in breast cancer patients using ultrasound imaging.Frontiers in oncology · 2025Article
- An Intraoperative Ultrasound Evaluation of Axillary Lymph Nodes: Cassandra Predictive Models in Patients with Breast Cancer-A Multicentric Study.Medicina (Kaunas, Lithuania) · 2024Article
- Ultrasound-based radiomics nomogram for predicting axillary lymph node metastasis in early-stage breast cancer.La Radiologia medica · 2024Article
- Article
- A nomogram based on conventional and contrast-enhanced ultrasound radiomics for the noninvasively prediction of axillary lymph node metastasis in breast cancer patients.Frontiers in oncology · 2024Article
- Nomogram based on multiparametric analysis of early-stage breast cancer: Prediction of high burden metastatic axillary lymph nodes.Thoracic cancer · 2023Article
- Deep learning radiomics for prediction of axillary lymph node metastasis in patients with clinical stage T1-2 breast cancer.Quantitative imaging in medicine and surgery · 2023Article
- Diagnosing sentinel lymph node metastasis of T1/T2 breast cancer with conventional ultrasound combined with double contrast-enhanced ultrasound: a preliminary study.Quantitative imaging in medicine and surgery · 2023Article
- A machine learning model based on ultrasound image features to assess the risk of sentinel lymph node metastasis in breast cancer patients: Applications of scikit-learn and SHAP.Frontiers in oncology · 2022Article
- Accuracy of ultrasonographic changes during neoadjuvant chemotherapy to predict axillary lymph node response in clinical node-positive breast cancer patients.Frontiers in oncology · 2022Article
- Clinical Value of Preoperative Ultrasound Signs in Evaluating Axillary Lymph Node Status in Triple-Negative Breast Cancer.Journal of oncology · 2022Article
- Dilated Semantic Segmentation for Breast Ultrasonic Lesion Detection Using Parallel Feature Fusion.Diagnostics (Basel, Switzerland) · 2021Article
- A quantization assisted U-Net study with ICA and deep features fusion for breast cancer identification using ultrasonic data.PeerJ. Computer science · 2021Article
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10 authors.
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Abstract
objectiveTo develop a nomogram for predicting axillary lymph node (ALN) metastases using the breast imaging reporting and data system (BI-RADS) ultrasound lexicon.
methodsA total of 703 patients from July 2015 to January 2018 were included in this study as a primary cohort for model construction. Moreover, 109 patients including 51 pathologically confirmed N1 patients (TNM staging) and 58 non-metastatic patients were recruited as an external validation cohort from March 2018 to August 2019. Ultrasound images and clinical information of these patients were retrospectively reviewed. The ultrasonic features based on the BI-RADS lexicon were extracted by two radiologists. The features extracted from the primary cohort were used to develop a nomogram using multivariate analysis. Internal and external validations were performed to evaluate the predictive efficacy of the nomogram.
resultsThe nomogram was based on two features (size, lesion boundary) and showed an area under the curve of 0.75 (95% confidence interval [CI], 0.70-0.79) in the primary cohort and 0.91 (95% CI, 0.84-0.97) in the external validation cohort; it achieved an 88% sensitivity in N1 patients.
conclusionThe nomogram based on BI-RADS ultrasonic features can predict breast cancer ALN status with relatively high accuracy. It has potential clinical value in improving the sensitivity and accuracy of the preoperative diagnosis of ALN metastases, especially for N1 patients.
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