Advanced MR Techniques for Preoperative Glioma Characterization

Part 1

Review (2023)
Author(s)

Lydiane Hirschler (Leiden University Medical Center)

Nico Sollmann (University Hospital Ulm, Technische Universität München)

Bárbara Schmitz-Abecassis (Leiden University Medical Center, Medical Delta)

Joana Pinto (University of Oxford)

Fatemehsadat Arzanforoosh (Erasmus MC)

Chih Hsien Tseng (TU Delft - ImPhys/Vos group, TU Delft - ImPhys/Computational Imaging, TU Delft - Medical Delta)

Frans Vos (TU Delft - ImPhys/Computational Imaging, Erasmus MC, TU Delft - ImPhys/Vos group, TU Delft - Medical Delta)

Esther Warnert (Erasmus MC)

Marion Smits (University of Oxford, Erasmus MC)

undefined More Authors (External organisation)

Research Group
ImPhys/Computational Imaging
DOI related publication
https://doi.org/10.1002/jmri.28662
More Info
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Publication Year
2023
Language
English
Research Group
ImPhys/Computational Imaging
Issue number
6
Volume number
57
Pages (from-to)
1655-1675
Downloads counter
474
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Abstract

Preoperative clinical magnetic resonance imaging (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 or lack thereof. 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 first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3. Technical Efficacy: Stage 2.