Print Email Facebook Twitter Advanced MR Techniques for Preoperative Glioma Characterization Title Advanced MR Techniques for Preoperative Glioma Characterization: Part 2 Author Hangel, Gilbert (Medical University of Vienna; Christian Doppler Laboratory for Precision Engineering for Automated In-Line Metrology) Schmitz-Abecassis, Bárbara (Leiden University Medical Center; Medical Delta) Pinto, Joana (University of Oxford) Sollmann, Nico (University Hospital Ulm; Technische Universität München) Tseng, C. (TU Delft ImPhys/Vos group; TU Delft ImPhys/Computational Imaging; TU Delft Medical Delta) Vos, F.M. (TU Delft ImPhys/Computational Imaging; TU Delft ImPhys/Vos group; TU Delft Medical Delta; Erasmus MC) Warnert, E.A.H. (Erasmus MC) Smits, M. (TU Delft Medical Delta; Erasmus MC) Petr, Jan (Institute of Radiation Physics) Date 2023 Abstract Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). Evidence Level: 3. Technical Efficacy: Stage 2. Subject braincontrastsGliMR 2.0gliomalevel of clinical validationpreoperative To reference this document use: http://resolver.tudelft.nl/uuid:d46c2655-1691-454c-81e9-ee96ec427ae5 DOI https://doi.org/10.1002/jmri.28663 ISSN 1053-1807 Source Journal of Magnetic Resonance Imaging, 57 (6), 1676-1695 Part of collection Institutional Repository Document type review Rights © 2023 Gilbert Hangel, Bárbara Schmitz-Abecassis, Joana Pinto, Nico Sollmann, C. Tseng, F.M. Vos, E.A.H. Warnert, M. Smits, Jan Petr, More Authors Files PDF Magnetic_Resonance_Imagin ... Part_2.pdf 5.41 MB Close viewer /islandora/object/uuid:d46c2655-1691-454c-81e9-ee96ec427ae5/datastream/OBJ/view