Radiomic and dosimetric parameter-based nomogram predicts radiation esophagitis in patients with non-small cell lung cancer undergoing combined immunotherapy and radiotherapy
We developed and validated a nomogram based on imaging histological features and RT dosimetric parameters. This model can effectively predict the occurrence of RE in patients with NSCLC treated using ICI-RT.
Authors
- Junfeng Zhao (ORCID: https://orcid.org/0009-0001-2846-9981)
- Li Li (ORCID: https://orcid.org/0000-0002-4712-2692)
- Kang Wang (ORCID: https://orcid.org/0000-0002-4963-2979)
- Ying Li (ORCID: https://orcid.org/0000-0001-5062-0230)
- Jinghao Duan (ORCID: https://orcid.org/0000-0001-6420-6743)
- Shuanghu Yuan
- Changxing Feng
Institutions
- University of Science and Technology of China (CN)
- Shandong Tumor Hospital (CN)
- Anhui Provincial Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-12-18
- DOI
- https://doi.org/10.3389/fonc.2024.1490348
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Natural Science Foundation of China