Identification of intrinsic imaging subtypes using clustering analysis based on dynamic contrast-enhanced magnetic resonance imaging radiomics features for gliomas: preliminary associations with gene expression profiles
The intrinsic imaging subtypes obtained from DCE-MRI radiomics features provide a new insight into glioma classification, potentially guiding the diagnosis.
Authors
- Sixuan Chen (ORCID: https://orcid.org/0000-0002-6343-2092)
- Shaofeng Duan (ORCID: https://orcid.org/0000-0001-9413-7574)
- Zhengyang Zhu (ORCID: https://orcid.org/0000-0001-9916-3480)
- Huiquan Yang (ORCID: https://orcid.org/0009-0008-6980-8792)
- Meiping Ye
- Chuanshuai Tian (ORCID: https://orcid.org/0000-0003-4368-0985)
- Bing Zhang (ORCID: https://orcid.org/0000-0001-5650-2518)
- Han Wang (ORCID: https://orcid.org/0000-0003-2420-3147)
- Xin Zhang (ORCID: https://orcid.org/0000-0001-9826-1564)
- Jianan Zhou (ORCID: https://orcid.org/0000-0002-1775-6221)
Institutions
- Nanjing Drum Tower Hospital (CN)
- Nanjing Medical University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-04-30
- DOI
- https://doi.org/10.21037/qims-24-1459
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72