ArticleFrontiers in cell and developmental biology2023
Radiomics signatures for predicting the Ki-67 level and HER-2 status based on bone metastasis from primary breast cancer.
Article in Frontiers in cell and developmental biology, 2023. 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.
- Independent Risk Factors and a New Nomogram for Predicting Breast Cancer Risk for Bone Metastasis in Chinese Women: A Retrospective Study with External Validation.Journal of clinical medicine · 2026Article
- Artificial Intelligence for Non-Invasive Prediction of Molecular Signatures in Spinal Metastases: A Systematic Review.Bioengineering (Basel, Switzerland) · 2025Review
- Single Photon Emission Computed Tomography/X-ray Computed Tomography-based radiomics analysis for diagnosis of bone metastases in patients with breast cancer.Journal of bone oncology · 2025Article
- Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer.Scientific reports · 2025Article
- An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in TTechnology in cancer research & treatmentArticle
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Authors and funding
11 authors.
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Abstract
This study explores the potential of radiomics to predict the proliferation marker protein Ki-67 levels and human epidermal growth factor receptor 2 (HER-2) status based on MRI images of patients with spinal metastasis from primary breast cancer. A total of 110 patients with pathologically confirmed spinal metastases from primary breast cancer were enrolled between Dec. 2017 and Dec. 2021. All patients underwent T1-weighted contrast-enhanced MRI scans. The PyRadiomics package was used to extract features from the MRI images based on the intraclass correlation coefficient and least absolute shrinkage and selection operator. The most predictive features were used to develop the radiomics signature. The Chi-Square test, Fisher's exact test, Student's
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