High-precision intraoperative diagnosis of gliomas: integrating imaging and intraoperative flow cytometry with machine learning
This integrated approach enhances the precision of intraoperative molecular diagnosis and has the potential to optimize surgical strategies for glioma treatment.
Authors
- Takahiro Shioyama
- Mikoto Onodera
- Shunichi Koriyama (ORCID: https://orcid.org/0000-0001-6613-8131)
- Takashi Komori (ORCID: https://orcid.org/0000-0002-6812-2149)
- Takakazu Kawamata (ORCID: https://orcid.org/0000-0002-6076-7065)
- Yoshihiro Muragaki (ORCID: https://orcid.org/0000-0001-8336-5328)
- Kenta Masui (ORCID: https://orcid.org/0000-0002-5824-6690)
- Tatsuya Kobayashi (ORCID: https://orcid.org/0000-0002-3889-5765)
- Buntou Ro
- Yutaka Matsui
- Manabu Tamura
Institutions
- University of Nagasaki (JP)
- Nihon Kohden (Japan) (JP)
- Atom Medical (Japan) (JP)
- Tokyo Metropolitan Neurological Hospital (JP)
- Tokyo Women's Medical University (JP)
- Nagasaki University (JP)
- Kobe University (JP)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3389/fneur.2025.1647009
- Citations
- 1
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.63
Funders
- Casio Science Promotion Foundation