ArticleFrontiers in oncology2024
Preliminary study on DCE-MRI radiomics analysis for differentiation of HER2-low and HER2-zero breast cancer.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The value of non-enhanced magnetic resonance imaging based on T2-weighted imaging and apparent diffusion coefficient in the study of three-tiered HER2 status in patients with breast cancer.Quantitative imaging in medicine and surgery · 2026Article
- Value of intratumoral and peritumoral radiomics based on DCE-MRI in predicting HER2-low and HER2-zero in breast cancer.BMC medical imaging · 2026Article
- Multiparametric MRI and artificial intelligence for non-invasive HER2 assessment in breast cancer: a comprehensive review.Frontiers in medicine · 2026Review
- Multiparametric MRI-based radiomics of whole-tumor and habitat regions for predicting HER2 status in young breast cancer: a two-center study.Frontiers in oncology · 2026Article
- Development and validation of a multimodality radiomics-based nomogram for predicting HER2 expression status in invasive breast cancer.Frontiers in oncology · 2026Article
- Tumor Imaging Heterogeneity Index-Inspired Insights into the Unveiling Tumor Microenvironment of Breast Cancer.International journal of molecular sciences · 2025Article
- Multimodal imaging and advanced quantitative techniques for HER-2 status prediction in breast cancer.Discover oncology · 2025Review
- Intratumoral and peritumoral ultrasound radiomics analysis for predicting HER2-low expression in HER2-negative breast cancer patients: a retrospective analysis of dual-central study.Discover oncology · 2025Article
- Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI.Biomolecules & biomedicine · 2025Article
- Prediction of lymphovascular invasion in invasive breast cancer based on clinical-MRI radiomics features.BMC medical imaging · 2024Article
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9 authors.
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Abstract
Purpose: This study aims to evaluate the utility of radiomic features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in distinguishing HER2-low from HER2-zero breast cancer. Patients and methods: We retrospectively analyzed 118 MRI cases, including 78 HER2-low and 40 HER2-zero patients confirmed by immunohistochemistry or fluorescence Results: The radiomics model, clinical model, and nomogram successfully distinguished between HER2-low and HER2-zero. The radiomics model showed excellent performance, with area under the curve (AUC) values of 0.875 in the training set and 0.845 in the test set, outperforming the clinical model (AUC = 0.691 and 0.672, respectively). HER2 status correlated with increased rad-score and Time Intensity Curve (TIC). The nomogram outperformed both models, with AUC, sensitivity, and specificity values of 0.892, 79.6%, and 82.8% in the training set, and 0.886, 83.3%, and 90.9% in the test set. Conclusions: The DCE-MRI-based nomogram shows promising potential in differentiating HER2-low from HER2-zero status in breast cancer patients.
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