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7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading.
- Source :
-
Cancer imaging : the official publication of the International Cancer Imaging Society [Cancer Imaging] 2024 May 27; Vol. 24 (1), pp. 67. Date of Electronic Publication: 2024 May 27. - Publication Year :
- 2024
-
Abstract
- Introduction: With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients.<br />Methods: We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status.<br />Results: Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy.<br />Conclusions: We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.<br /> (© 2024. The Author(s).)
- Subjects :
- Humans
Female
Male
Middle Aged
Adult
Prospective Studies
Aged
Magnetic Resonance Imaging methods
Choline metabolism
Choline analysis
Glioma genetics
Glioma diagnostic imaging
Glioma pathology
Isocitrate Dehydrogenase genetics
Brain Neoplasms diagnostic imaging
Brain Neoplasms genetics
Brain Neoplasms pathology
Neoplasm Grading
Magnetic Resonance Spectroscopy methods
Mutation
Subjects
Details
- Language :
- English
- ISSN :
- 1470-7330
- Volume :
- 24
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Cancer imaging : the official publication of the International Cancer Imaging Society
- Publication Type :
- Academic Journal
- Accession number :
- 38802883
- Full Text :
- https://doi.org/10.1186/s40644-024-00704-9