Advanced magnetic resonance imaging for glioblastoma: Oncology-radiology integration
Advanced radiomic and machine learning analysis of MRI can provide noninvasive glioma grading and characterization of tumor properties with clinical relevance. Combining advanced neuroimaging with histopathology may better integrate oncology and radiology for optimized glioblastoma management. However, further studies are needed to validate these findings with larger datasets and assess additional MRI sequences and radiomic features.
Authors
- Abdulsalam Mohammed Aleid (ORCID: https://orcid.org/0009-0008-3726-5148)
- Saud Nayef Aldanyowi
- Abdulrahim Saleh Alrasheed
- Sami Fadhel Almalki (ORCID: https://orcid.org/0000-0002-4077-0259)
Institutions
- King Faisal University (SA)
Publication Details
- Journal
- Surgical Neurology International
- Published
- 2024-08-30
- DOI
- https://doi.org/10.25259/sni_498_2024
- Citations
- 7
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.07