Mapping of Metabolic Heterogeneity of Glioma Using MR-Spectroscopy.
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Cited by: 2


Proton magnetic resonance spectroscopy (1H-MRS) delivers information about the non-invasive metabolic landscape of brain pathologies. 1H-MRS is used in clinical setting in addition to MRI for diagnostic, prognostic and treatment response assessments, but the use of this radiological tool is not entirely widespread. The importance of developing automated analysis tools for 1H-MRS lies in the possibility of a straightforward application and simplified interpretation of metabolic and genetic data that allow for incorporation into the daily practice of a broad audience. Here, we report a prospective clinical imaging trial (DRKS00019855) which aimed to develop a novel MR-spectroscopy-based algorithm for in-depth characterization of brain lesions and prediction of molecular traits. Dimensional reduction of metabolic profiles demonstrated distinct patterns throughout pathologies. We combined a deep autoencoder and multi-layer linear discriminant models for voxel-wise prediction of the molecular profile based on MRS imaging. Molecular subtypes were predicted by an overall accuracy of 91.2% using a classifier score. Our study indicates a first step into combining the metabolic and molecular traits of lesions for advancing the pre-operative diagnostic workup of brain tumors and improve personalized tumor treatment.


Spatial Transcriptomics
MR spectroscopy
chemical shift imaging
magnetic resonance spectroscopy


Franco, Pamela
Huebschle, Irene
Simon-Gabriel, Carl Philipp
Dacca, Karam
Schnell, Oliver
Beck, Juergen
Mast, Hansjoerg
Urbach, Horst
Wuertemberger, Urs
Prinz, Marco
Hosp, Jonas A
Delev, Daniel
Mader, Irina
Heiland, Dieter Henrik

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