ArticleBreast cancer research : BCR2025
Prognosticating axillary lymph node metastasis in breast cancer through integrated photoacoustic imaging, ultrasound, and clinical parameters.
Article in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Diagnostic Potential of Apparent Diffusion Coefficient-Based Lymph Node Classification in Breast Cancer Patients Undergoing [Diagnostics (Basel, Switzerland) · 2026Article
- Mapping the research landscape of photoacoustic imaging in breast cancer: a text-based bibliometric analysis.Gland surgery · 2026Article
- Recent advances in photoacoustic-ultrasound dual-modality fusion imaging for functional visualization of the superficial tumor microenvironment.Oncology reviews · 2026Review
- A multimodal ultrasound-based model combining tumor radiomics and axillary lymph node morphologic classification for predicting axillary nodal burden in breast cancer.Frontiers in endocrinology · 2026Article
- Interpretable prediction of Ki-67 expression in breast cancer through integrated photoacoustic radiomics and clinical parameters.Frontiers in oncology · 2026Article
- Low prognostic nutritional index score is associated with lymph node metastasis in patients with breast cancer, whereas hemoglobin-albumin-lymphocyte-platelet score is not.Frontiers in oncology · 2026Article
- From Innovation to Application: Can Emerging Imaging Techniques Transform Breast Cancer Diagnosis?Diagnostics (Basel, Switzerland) · 2025Review
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Authors and funding
10 authors.
Funding
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Abstract
purposeTo develop and validate a predictive model for axillary lymph node metastasis (ALNM) in breast cancer (BC) by integrating clinicopathological factors, ultrasound features, and photoacoustic imaging-derived SO
methodsA total of 317 BC patients were included, with the cohort split into a training set (70%) and a testing set (30%). Univariate and multivariate logistic regression identified key predictive factors, leading to the creation of three models: ModA (clinicopathological factors only), ModB (clinicopathological and ultrasound features), and ModC (clinicopathological, ultrasound, and SO
resultsMultivariate analysis showed that maximum diameter, Ki67 expression, AUS report and SO
conclusionIntegrating SO
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