Imaging-based transformer model predicts early therapy response in advanced nasopharyngeal carcinoma: a dual-center study
Early treatment response prediction in locally advanced nasopharyngeal carcinoma lacks validated deep learning models using 2.5D imaging and Transformers. Transformer-based model achieved superior predictive performance compared to clinical or combined models. Integrating clinical data with Transformer imaging analysis improves personalized chemoradiotherapy outcome prediction.
Authors
- Yuchen Zhu (ORCID: https://orcid.org/0000-0001-5148-8569)
- Yinjiao Fei (ORCID: https://orcid.org/0000-0003-3354-4082)
- Changlong Chen
- Weilin Xu (ORCID: https://orcid.org/0000-0001-5476-5541)
- Yuandong Cao (ORCID: https://orcid.org/0000-0001-7263-8722)
- Kexin Shi
- Jinling Yuan
- Lei Qiu (ORCID: https://orcid.org/0000-0002-1080-1704)
- Jingyan Luo
- Shu Zhou (ORCID: https://orcid.org/0000-0002-6864-5177)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1186/s13244-025-02142-y
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Government of Jiangsu Province
- Nanjing University of Posts and Telecommunications
- Nanjing Medical University
- Nanjing University