Radiomic Consensus Clustering in Glioblastoma and Association with Gene Expression Profiles
Consensus clustering of radiomic features revealed unique gene expression profiles in the GBM cohort which likely represent subtle differences in tumor biology and radiosensitivity that are not visually discernible, underscoring the potential of radiomics to serve as a non-invasive alternative for identifying GBM molecular heterogeneity. Further investigation is still required to validate these findings and their clinical implications.
Authors
- Raymund L. Yong (ORCID: https://orcid.org/0000-0002-7585-4153)
- Tadeusz Wroblewski (ORCID: https://orcid.org/0000-0002-8082-1997)
- Konstantinos D. Margetis (ORCID: https://orcid.org/0000-0002-3715-8093)
- Mert Karabacak (ORCID: https://orcid.org/0000-0002-9263-9893)
- Carina Seah (ORCID: https://orcid.org/0000-0003-1604-1838)
Institutions
- Mount Sinai Health System (US)
- SUNY Downstate Health Sciences University (US)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- Cancers
- Published
- 2024-12-21
- DOI
- https://doi.org/10.3390/cancers16244256
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.40