Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT
Background: Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Journal of Bone Oncology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2212137424001337 |
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| author | Hao-Nan Zhu Yi-Fan Guo YingMin Lin Zhi-Chao Sun Xi Zhu YuanZhe Li |
| author_facet | Hao-Nan Zhu Yi-Fan Guo YingMin Lin Zhi-Chao Sun Xi Zhu YuanZhe Li |
| author_sort | Hao-Nan Zhu |
| collection | DOAJ |
| description | Background: Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis. Methods: This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA). Results: The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model’s area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram. Conclusion: CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer. |
| format | Article |
| id | doaj-art-d4e38e5530ed4e7c9d4e86f5d2a0c403 |
| institution | Kabale University |
| issn | 2212-1374 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Bone Oncology |
| spelling | doaj-art-d4e38e5530ed4e7c9d4e86f5d2a0c4032025-01-20T04:17:24ZengElsevierJournal of Bone Oncology2212-13742025-02-0150100653Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CTHao-Nan Zhu0Yi-Fan Guo1YingMin Lin2Zhi-Chao Sun3Xi Zhu4YuanZhe Li5The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China; Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China; Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, ChinaThe Department of Thyroid and Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China; Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, China; Corresponding authors.Department of Radiology, Northern Jiangsu People’s Hospital Affiliated to Yangzhou, University, Yangzhou, Jiangsu, China; Corresponding authors.Center of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China; Corresponding authors.Background: Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis. Methods: This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA). Results: The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model’s area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram. Conclusion: CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer.http://www.sciencedirect.com/science/article/pii/S2212137424001337Bone metastasisBone marrow microenvironmentBreast cancerTomographyX-ray computedRadiomics |
| spellingShingle | Hao-Nan Zhu Yi-Fan Guo YingMin Lin Zhi-Chao Sun Xi Zhu YuanZhe Li Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT Journal of Bone Oncology Bone metastasis Bone marrow microenvironment Breast cancer Tomography X-ray computed Radiomics |
| title | Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT |
| title_full | Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT |
| title_fullStr | Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT |
| title_full_unstemmed | Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT |
| title_short | Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT |
| title_sort | radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest ct |
| topic | Bone metastasis Bone marrow microenvironment Breast cancer Tomography X-ray computed Radiomics |
| url | http://www.sciencedirect.com/science/article/pii/S2212137424001337 |
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