Deep Learning-Based Multimodal Prediction of NAC Response in LARC by Integrating MRI and Proteomics
Our study established a novel MRI-proteomics integration framework for NAC response prediction, with MRI defining spatial resistance patterns and proteomics deciphering molecular drivers, enabling early organ preservation strategies. The zero-imputation design ensured deplorability in diverse clinical settings.
Authors
- Zhongxing Wang (ORCID: https://orcid.org/0000-0003-3620-5529)
- Qiuju Zhang (ORCID: https://orcid.org/0000-0003-3407-2136)
- Fenqi Du (ORCID: https://orcid.org/0000-0003-4278-8791)
- Yang Zhou (ORCID: https://orcid.org/0009-0008-2853-8351)
- Yan Li (ORCID: https://orcid.org/0000-0002-4694-4926)
- Liu Ze-yuan (ORCID: https://orcid.org/0000-0003-2663-7440)
- Yanlong Liu (ORCID: https://orcid.org/0000-0002-5254-3897)
- Jiaxuan Ding (ORCID: https://orcid.org/0000-0002-0127-8982)
Institutions
- Harbin Medical University (CN)
- Third Affiliated Hospital of Harbin Medical University (CN)
Publication Details
- Journal
- Cancer Research and Treatment
- Published
- 2025-09-01
- DOI
- https://doi.org/10.4143/crt.2025.707
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China