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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., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

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., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) can reconstruct whole-brain multi-parametric quantitative maps (eg, T 1 , T 2 ) from a 5-minute MR acquisition. These quantitative maps can be leveraged for synthetization of clinical image contrasts., Purpose: The objective was to assess image quality and overall diagnostic accuracy of synthetic MR-STAT contrasts compared to conventional contrast-weighted images., Study Type: Prospective cross-sectional clinical trial., Population: Fifty participants with a median age of 45 years (range: 21-79 years) consisting of 10 healthy participants and 40 patients with neurological diseases (brain tumor, epilepsy, multiple sclerosis or stroke)., Field Strength/sequence: 3T/Conventional contrast-weighted imaging (T 1 /T 2 weighted, proton density [PD] weighted, and fluid-attenuated inversion recovery [FLAIR]) and a MR-STAT acquisition (2D Cartesian spoiled gradient echo with varying flip angle preceded by a non-selective inversion pulse)., Assessment: Quantitative T 1 , T 2 , and PD maps were computed from the MR-STAT acquisition, from which synthetic contrasts were generated. Three neuroradiologists blinded for image type and disease randomly and independently evaluated synthetic and conventional datasets for image quality and diagnostic accuracy, which was assessed by comparison with the clinically confirmed diagnosis., Statistical Tests: Image quality and consequent acceptability for diagnostic use was assessed with a McNemar's test (one-sided α = 0.025). Wilcoxon signed rank test with a one-sided α = 0.025 and a margin of Δ = 0.5 on the 5-level Likert scale was used to assess non-inferiority., Results: All data sets were similar in acceptability for diagnostic use (≥3 Likert-scale) between techniques (T 1 w:P = 0.105, PDw:P = 1.000, FLAIR:P = 0.564). However, only the synthetic MR-STAT T 2 weighted images were significantly non-inferior to their conventional counterpart; all other synthetic datasets were inferior (T 1 w:P = 0.260, PDw:P = 1.000, FLAIR:P = 1.000). Moreover, true positive/negative rates were similar between techniques (conventional: 88%, MR-STAT: 84%)., Data Conclusion: MR-STAT is a quantitative technique that may provide radiologists with clinically useful synthetic contrast images within substantially reduced scan time., Evidence Level: 1 Technical Efficacy: Stage 2., (© 2022 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications such as diagnosis, characterization, and treatment planning and monitoring in glioma patients. While APT-CEST has demonstrated high potential, reproducibility remains underexplored., Purpose: To investigate whether cerebral APT-CEST with clinically feasible scan time is reproducible in healthy tissue and glioma for clinical use at 3 T., Study Type: Prospective, longitudinal., Subjects: Twenty-one healthy volunteers (11 females; mean age ± SD: 39 ± 11 years) and 6 glioma patients (3 females; 50 ± 17 years: 4 glioblastomas, 1 oligodendroglioma, 1 radiologically suspected low-grade glioma)., Field Strength/sequence: 3 T, Turbo Spin Echo - ampling perfection with application optimized contrasts using different flip angle evolution - chemical exchange saturation transfer (TSE SPACE-CEST)., Assessment: APT-CEST measurement reproducibility was assessed within-session (glioma patients, scan session 1; healthy volunteers scan sessions 1, 2, and 3), between-sessions (healthy volunteers scan sessions 1 and 2), and between-days (healthy volunteers, scan sessions 1 and 3). The mean APT CEST values and standard deviation of the within-subject difference (SD diff ) were calculated in whole tumor enclosed by regions of interest (ROIs) in patients, and eight ROIs in healthy volunteers-whole-brain, cortical gray matter, putamen, thalami, orbitofrontal gyri, occipital lobes, central brain-and compared., Statistical Tests: Brown-Forsythe tests and variance component analysis (VCA) were used to assess the reproducibility of ROIs for the three time intervals. Significance was set at P < 0.003 after Bonferroni correction., Results: Intratumoral mean APT CEST was significantly higher than APT CEST in healthy-appearing tissue in patients (0.5 ± 0.46%). The average within-session, between-sessions, and between-days SD diff of healthy control brains was 0.2% and did not differ significantly with each other (0.76 > P > 0.22). The within-session SD diff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. VCA showed that within-session factors were the most important (60%) for scanning variance., Data Conclusion: Cerebral APT-CEST imaging may show good scan-rescan reproducibility in healthy tissue and tumors with clinically feasible scan times at 3 T. Short-term measurement effects may be the dominant components for reproducibility., Level of Evidence: 2 TECHNICAL EFFICACY: Stage 2., (© 2022 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: To investigate the effect of the choice of the curve-fitting model on the perfusion fraction (f IVIM ) with regard to tissue type characterization, correlation with microvascular anatomy, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters. Several curve-fitting models coexist in intravoxel incoherent motion (IVIM) MRI to derive the (f IVIM )., Materials and Methods: In all, 29 patients with brain lesions (12 gliomas, 11 meningiomas, three metastases, two gliotic scars, one multiple sclerosis) underwent IVIM-MRI (32 b-values, 0 to 2000 s/mm 2 ) at 3T. f IVIM was determined by classic monoexponential, biexponential, and a novel nonnegative least squares (NNLS) fitting in 352 regions of interest (lesion-containing and normal-appearing tissue) and tested their correlation with DCE-MRI kinetic parameters and microvascular anatomy derived from 57 region of interest (ROI)-based biopsies and their capacities to differentiate histologically different lesions., Results: f IVIM differed significantly between all three models and all tissue types (monoexponential confidence interval in percent [CI 3.4-3.8]; biexponential [CI 11.21-12.45]; NNLS [CI 2.06-2.60]; all P < 0.001). For all models an increase in f IVIM was associated with a shift to larger vessels and higher vessel area / tissue area ratio (regression coefficient 0.07-0.52; P = 0.04-0.001). Correlation with kinetic parameters derived from DCE-MRI was usually not significant. Only biexponential fitting allowed differentiation of both gliosis from edema and high- from low-grade glioma (both P < 0.001)., Conclusion: The curve-fitting model has an important impact on f IVIM and its capacity to differentiate tissues. f IVIM may possibly be used to assess microvascular anatomy and is weakly correlated with DCE-MRI kinetic parameters., Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1187-1199., (© 2017 International Society for Magnetic Resonance in Medicine.)