Prediction of neoadjuvant chemotherapy efficacy in patients with HER2-low breast cancer based on ultrasound radiomics
Ultrasound radiomics is a non-invasive and promising approach for predicting response to neoadjuvant chemotherapy in HER2-low breast cancer. The pre-treatment model yielded reliable performance after feature selection. While the combined model did not substantially enhance predictive accuracy, its stable performance suggests that longitudinal ultrasound imaging may help capture treatment-induced phenotypic changes. These findings offer preliminary support for individualized therapeutic decision-making.
Authors
- Qing Peng (ORCID: https://orcid.org/0000-0002-2238-8400)
- Jun Xie (ORCID: https://orcid.org/0000-0002-1444-9234)
- Feng Jin (ORCID: https://orcid.org/0000-0002-5141-3986)
- Le Qu (ORCID: https://orcid.org/0000-0001-9499-4277)
- Tian Zhang (ORCID: https://orcid.org/0000-0002-4871-1771)
- Zixian Dong (ORCID: https://orcid.org/0009-0002-3325-3437)
- Bo Chen (ORCID: https://orcid.org/0009-0009-0184-3556)
- Jiangdian Song (ORCID: https://orcid.org/0000-0002-3355-9930)
- Ziyao Ji
- Min Ding (ORCID: https://orcid.org/0000-0002-6197-5376)
- Nan Xu (ORCID: https://orcid.org/0000-0002-8811-6459)
- Yimo Liu (ORCID: https://orcid.org/0000-0001-6893-1328)
- Ang Zheng (ORCID: https://orcid.org/0000-0003-1078-6660)
Institutions
- First Hospital of China Medical University (CN)
- China Medical University (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-09-26
- DOI
- https://doi.org/10.1186/s40644-025-00934-5
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- National Natural Science Foundation of China