Delta-radiomics features combined with haematological index predict pathological complete response after neoadjuvant immunochemotherapy in resectable non-small cell lung cancer
The Delta-RF model based on enhanced CT and the combined model can aid in efficient prediction of PCR after neoadjuvant immunochemotherapy in NSCLC, and the combined model can predict PCR performance better than Delta-RF model alone after neoadjuvant immunochemotherapy.
Authors
- Yang Sun (ORCID: https://orcid.org/0000-0002-5739-8641)
- He Zhu (ORCID: https://orcid.org/0000-0001-8482-7029)
- T. Hu (ORCID: https://orcid.org/0000-0001-6884-5374)
- Shuanghu Yuan (ORCID: https://orcid.org/0000-0002-8327-2524)
- Da Xiong
- Li Li (ORCID: https://orcid.org/0000-0003-0935-8634)
- Jing Li (ORCID: https://orcid.org/0000-0003-1350-7460)
- Feng Xu (ORCID: https://orcid.org/0000-0003-0902-2858)
- Xiaofeng Xu (ORCID: https://orcid.org/0000-0002-8838-5333)
Institutions
- Qingdao University (CN)
- University of Science and Technology of China (CN)
- Shandong Tumor Hospital (CN)
- Qingdao Municipal Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Clinical Radiology
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1016/j.crad.2025.106906
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72