7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading

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 classificat...

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Vydáno v:	Cancer imaging Ročník 24; číslo 1; s. 67 - 11
Hlavní autoři:	Cadrien, Cornelius, Sharma, Sukrit, Lazen, Philipp, Licandro, Roxane, Furtner, Julia, Lipka, Alexandra, Niess, Eva, Hingerl, Lukas, Motyka, Stanislav, Gruber, Stephan, Strasser, Bernhard, Kiesel, Barbara, Mischkulnig, Mario, Preusser, Matthias, Roetzer-Pejrimovsky, Thomas, Wöhrer, Adelheid, Weber, Michael, Dorfer, Christian, Trattnig, Siegfried, Rössler, Karl, Bogner, Wolfgang, Widhalm, Georg, Hangel, Gilbert
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 27.05.2024 BioMed Central Ltd BMC
Témata:	Adult Aged Amino acids Brain Neoplasms - diagnostic imaging Brain Neoplasms - genetics Brain Neoplasms - pathology Cancer Research Choline Choline - analysis Choline - metabolism Diagnostic imaging Female Glioma - diagnostic imaging Glioma - genetics Glioma - pathology Gliomas Humans Imaging Isocitrate Dehydrogenase - genetics Magnetic Resonance Imaging - methods Magnetic Resonance Spectroscopy - methods Male Medical imaging equipment Medicine Medicine & Public Health Middle Aged Mutation Neoplasm Grading Nuclear magnetic resonance spectroscopy Nuclear Medicine Oncology Prospective Studies Radiology Research Article
ISSN:	1470-7330, 1740-5025, 1470-7330
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Shrnutí:	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. 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. 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. 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.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1470-7330 1740-5025 1470-7330
DOI:	10.1186/s40644-024-00704-9