Survival prediction with radiomics for patients with IDH mutated lower-grade glioma
Radiomics can capture quantitative prognostic information in patients with dLGG. Combined models show promise of synergetic effects and should be studied further in astrocytoma and oligodendroglioma patients separately for optimal modelling of individual risks.
Authors
- Louise Carstam (ORCID: https://orcid.org/0000-0001-6597-2570)
- Anja Smits (ORCID: https://orcid.org/0000-0003-4171-2672)
- Alice Neimantaite (ORCID: https://orcid.org/0009-0004-0293-6707)
- Maria Zetterling (ORCID: https://orcid.org/0000-0003-4590-7063)
- Malin Blomstrand
- Tora Dunås (ORCID: https://orcid.org/0000-0002-5911-9511)
- Margret Jensdottir (ORCID: https://orcid.org/0000-0002-6127-326X)
- Tomás Gómez Vecchio (ORCID: https://orcid.org/0009-0000-6765-0428)
- Erik Thurin (ORCID: https://orcid.org/0000-0002-9631-3989)
- Ida Häggström (ORCID: https://orcid.org/0000-0001-9178-6683)
- Asgeir Store Jakola (ORCID: https://orcid.org/0000-0002-2860-9331)
- Francesco Latini (ORCID: https://orcid.org/0000-0002-4702-526X)
- Jiri Bartek
Institutions
- Karolinska University Hospital (SE)
- Uppsala University Hospital (SE)
- Sahlgrenska University Hospital (SE)
- Rigshospitalet (DK)
- Karolinska Institutet (SE)
- Chalmers University of Technology (SE)
- University of Gothenburg (SE)
Publication Details
- Journal
- Journal of Neuro-Oncology
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1007/s11060-025-05006-z
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Göteborgs Universitet