ArticleNPJ digital medicine2025
Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multimodal radiomics incorporating intratumoral heterogeneity for prognostic assessment of metastatic outcomes in invasive breast cancer.Breast cancer research : BCR · 2026Article
- Development and validation of a non-invasive nomogram for predicting bone metastasis in newly diagnosed breast cancer.Translational cancer research · 2026Article
- Combining ultrasound and core needle histology imaging Radiopathomics model in predicting axillary lymph node metastasis in triple-negative breast cancer.World journal of surgical oncology · 2026Article
- A combined model based on clinical, radiomics, and deep transfer learning features for differentiating endometrial hyperplasia with polyps from endometrial cancer.Frontiers in oncology · 2026Article
- MRI-Based Deep Learning Guides Multi-Omics Discovery of NBPF4 as a Therapeutic Target for Breast Cancer Lymph Node Metastasis.Research (Washington, D.C.) · 2026Article
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Authors and funding
14 authors.
Funding
Abstract
With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary staging. This study employed advancements in deep learning to comprehensively evaluate routine mammograms for preoperative lymph node metastasis prediction. Mammograms and clinicopathological data from 1265 cN0 T1-T2 breast cancer patients (primary surgery, no neoadjuvant therapy) were retrospectively collected from three Swedish institutions. Compared to models using only clinical variables, incorporating full-breast mammograms with preoperative clinical variables improved the ROC AUC from 0.690 to 0.774 (improvement: 0.001-0.154) in the independent test set. The combined model showed good calibration and, at sensitivity ≥90%, achieved a significantly better net benefit, and a sentinel lymph node biopsy reduction rate of 41.7% (13.0-62.6%). Our findings suggest that routine mammograms, particularly full-breast images, can enhance preoperative nodal status prediction. They may substitute key predictors such as pathological tumor size and multifocality, aiding patient stratification before surgery.
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Registered trials
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