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.
Original language | English |
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Pages (from-to) | 1676-1695 |
Number of pages | 20 |
Journal | Journal of Magnetic Resonance Imaging |
Volume | 57 |
Issue number | 6 |
Early online date | 13 Mar 2023 |
DOIs | |
Publication status | Published - Jun 2023 |
Bibliographical note
Funding Information:Contract grant sponsor: This review was funded by grants from the following agencies: Dutch Research Council (NWO); Contract grant number: Veni project numbers 91619121 and 16862, VICI project number 016.160.351; Contract grant sponsor: Wellcome Trust; Contract grant number: 2022‐24, 203148/A/16/Z; Contract grant sponsor: Spanish Ministry of Science and Innovation; Contract grant number: PI18/00084; Contract grant sponsor: Spanish State Research Agency, Subprogram for Knowledge Generation (PROGRESS); Contract grant number: No PID2021‐127110OA‐I00;. Contract grant sponsor: Austrian Science Funds (FWF) projects; Contract grant number: KLI 646 and 1089; Contract grant sponsor: a 2021 Comprehensive Cancer Center grant of the Medical University of Vienna; Contract grant sponsor: The Turkish Directorate of Strategy and Budget under the TAM Project number 2007 K12‐873; Contract grant sponsor: INTER‐EXCELLENCE, subprogram INTER‐COST of the Ministry of Education, Youth and Sports CZ; Contract grant number: LTC20027; Contract grant sponsor: TUBITAK 1003; Contract grant number: grant 216S432; Contract grant sponsor: European Research Agency, Marie Sklodowska Curie Fellowship, Horizon 2020; Contract grant number: NIH/NCI U01 CA176110, NIH/NCI R01 CA264992, NIH/NCI CA255123; Contract grant sponsor: HollandPTC‐Varian; Contract grant number: 2018017; Contract grant sponsor: European Union's Horizon 2020 Programme; Contract grant number: ERC Grant Agreement No. 758657‐ImPRESS; Contract grant sponsor: South‐Eastern Norway Regional Health Authority Grant Agreements; Contract grant number: No. 2016102, 2017073, 2013069; Contract grant sponsor: the Norwegian Cancer Society and the Research Council of Norway FRIPRO Grant Agreements; Contract grant number: No. 261984, 303249; Contract grant sponsor: the MS Society of the United Kingdom; Contract grant number: 125; and Contract grant sponsor: the American Heart Association; Contract grant number: 826254. This publication is part of the COST Action CA18206 Glioma MR Imaging 2.0, supported by COST (European Cooperation in Science and Technology), www.cost.eu www.glimr.eu .
Funding Information:
The authors want to thank Rosa Ayesa Arriola, Martin Barak, Paula Croal, Philip De Witt Hamer, Vasileios K. Katsaros, Mary Pelechrini, Zahra Shams, Danai-Eleni Stefanou, Ioannis John Toliopoulos, and Hana Valekova for their assistance with earlier versions of this manuscript.
Publisher Copyright:
© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.