7T MRSI-based k-means clustering of glioma
Motivation: Preoperative glioma classification and management is still a challenge to be solved. Goal(s): To enhance the understanding of glioma characteristics and potentially improve patient outcomes, we analyzed 7T Magnetic Resonance Spectroscopic Imaging (MRSI) data in 36 glioma patients. Approach: Our approach focused on k-Means clustering of 60 metabolic ratios in the tumor to identify an overlap with the WHO 2021 diagnosis. Important metabolic ratios identified include Glu+Gln/tCho and Ins/tCr ratios, highlighting their biomarker significance. Results: Our 7T MRSI can add metabolic profiles across the entire glioma and brain, possibly contributing to future glioma research. Impact: We performed k-Means clustering of preoperative 7T MRSI metabolic ratios in 36 glioma patients. Correlation with histological WHO 2021 diagnosis was identified. With this approach, we could potentially enhance surgery planning and optimize glioma treatment and targeted drug monitoring.
Authors
- Cornelius Cadrien (ORCID: https://orcid.org/0000-0002-0341-2209)
- R. Quinn Thomas (ORCID: https://orcid.org/0000-0003-1282-7825)
- Lukas Hingerl (ORCID: https://orcid.org/0000-0003-1808-8349)
- Julia Furtner (ORCID: https://orcid.org/0000-0001-8258-3681)
- Weidenbach Michael
- Gilbert Hangel (ORCID: https://orcid.org/0000-0002-3986-3159)
- Bernhard Strasser (ORCID: https://orcid.org/0000-0001-9542-3855)
- Georg Widhalm (ORCID: https://orcid.org/0000-0001-6014-0273)
- Roxane Licandro
- Philipp Lazen (ORCID: https://orcid.org/0000-0002-9952-3084)
- Trattnig Siegfried
- Kiesel Barbara
- Mischkulnig Mario
- Woehrer Adelheid
- Dorfer Christian
- Roessler Karl
- Bogner Wolfgang
- Huskic Sara
- Acharya Sagar
- Preusser Matthias
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/3693
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00