Intratumoral and peritumoral radiomics based on automated breast volume scanner for predicting human epidermal growth factor receptor 2 status
The radiomics model integrating intratumoral and appropriate peritumoral features significantly outperformed the model based on intratumoral features alone. This integrated approach holds strong potential for noninvasive, preoperative prediction of HER2 status.
Authors
- Xuejun Ni
- Yan Fu (ORCID: https://orcid.org/0000-0002-4942-159X)
- Qing Jin (ORCID: https://orcid.org/0000-0002-2377-5218)
- Changjiang Gu (ORCID: https://orcid.org/0000-0001-6887-1978)
- Hao Zhang (ORCID: https://orcid.org/0000-0002-6397-8810)
- Qing Miao (ORCID: https://orcid.org/0000-0003-2478-9846)
- Ruike Pan
Institutions
- Nantong University (CN)
- Affiliated Hospital of Nantong University (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Traditional Chinese Medicine Hospital of Kunshan (CN)
- Jiangsu Cancer Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.3389/fonc.2025.1556317
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Natural Science Foundation of Nantong City
- Nantong Municipal Commission of Health and Family Planning