Radiomics based on 18F-FDG PET for predicting treatment response and prognosis in newly diagnosed diffuse large B-cell lymphoma patients: do lesion selection and segmentation methods matter?
Although there are differences in the selected radiomics features among lesion selection and segmentation methods, there is no substantial difference in the predictive power of each radiomics model. In addition, radiomics features have potential added value to clinical features.
Authors
- Rong Tian (ORCID: https://orcid.org/0000-0002-5191-9004)
- Xuelei Ma (ORCID: https://orcid.org/0000-0002-9148-5001)
- Xueyan Zhou
- Yi Zhou
- Yuchao Xu (ORCID: https://orcid.org/0000-0002-7646-8457)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- State Key Laboratory of Biotherapy
- University of South China (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-31
- DOI
- https://doi.org/10.21037/qims-24-585
- Citations
- 5
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.02
Funders
- National Natural Science Foundation of China
- Sichuan University
- West China Hospital, Sichuan University