Postoperative Karnofsky performance status prediction in patients with IDH wild-type glioblastoma: A multimodal approach integrating clinical and deep imaging features
The integration of MRI features extracted from VAEs with clinical parameters in the multimodal model substantially enhanced KPS prediction performance. This approach has the potential to improve prognostic prediction, paving the way for more personalized and effective treatments for patients with glioblastoma.
Authors
- Akihiko Ueda (ORCID: https://orcid.org/0000-0001-8139-9292)
- Masahiro Tanji (ORCID: https://orcid.org/0009-0002-2459-1856)
- Yasushi Okuno (ORCID: https://orcid.org/0000-0003-3596-4208)
- Yukinori Terada (ORCID: https://orcid.org/0000-0002-1357-6178)
- Silsu Park
- Yoshiki Arakawa (ORCID: https://orcid.org/0000-0003-4626-4645)
- Yusuke Mochizuki (ORCID: https://orcid.org/0000-0002-3415-2796)
- Yohei Mineharu (ORCID: https://orcid.org/0000-0002-6346-3999)
- Tomoki Sasagasako (ORCID: https://orcid.org/0000-0003-0157-8093)
- Noritaka Sano (ORCID: https://orcid.org/0000-0002-8999-1976)
- S. Doi
Institutions
- Kyoto University (JP)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1371/journal.pone.0303002
- Citations
- 6
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- RIKEN