FINAL outcome ANALYSIS FROM THE PHASE II TUXEDO-1 TRIAL OF TRASTUZUMAB-DERUXTECAN IN HER2-positive breast cancer PATIENTS WITH active brain metastases.

BACKGROUND: Brain metastases (BM) are a devastating complication of HER2-positive metastatic breast cancer (BC) and treatment strategies providing optimized local and systemic disease control are urgently required. The antibody-drug conjugate (ADC) trastuzumab deruxtecan (T-DXd) improved progression-free survival (PFS) and overall survival (OS) over trastuzumab emtansine but data regarding intracranial activity is limited. In the primary outcome analysis of TUXEDO-1, a high intracranial response rate (RR) was reported with T-DXd. Here, we report final PFS and OS results. PATIENTS AND METHODS: TUXEDO-1 accrued adult patients with HER2-positive BC and active BM (newly diagnosed or progressing) without indication for immediate local therapy. The primary endpoint was intracranial RR; secondary endpoints included PFS, OS, safety, quality-of-life (QoL), and neurocognitive function. PFS and OS were estimated with the Kaplan-Meier method and analysed in the per-protocol population. RESULTS: At 26.5 months median follow-up, median PFS was 21 months (95% CI 13.3-n.r.) and median OS was not reached (95% CI 22.2-n.r.). With longer follow-up, no new safety signals were observed. The most common grade 3 adverse event was fatigue (20%). Grade 2 interstitial lung disease and a grade 3 symptomatic drop of left-ventricular ejection fraction were observed in one patient each. QoL was maintained over the treatment period. DISCUSSION: T-DXd yielded prolonged intra- and extracranial disease control in patients with active HER2-positive BC BM in line with results from the pivotal trials. These results support the concept of ADCs as systemic therapy for active BM.

Inequalities in access to neuro-oncology supportive care and rehabilitation: A survey of healthcare professionals' perspectives.

Background: Neuro-oncology patients and caregivers should have equitable access to rehabilitation, supportive-, and palliative care. To investigate existing issues and potential solutions, we surveyed neuro-oncology professionals to explore current barriers and facilitators to screening patients' needs and referral to services. Methods: Members of the European Association of Neuro-Oncology and the European Organisation for Research and Treatment of Cancer Brain Tumor Group (EORTC-BTG) were invited to complete a 39-item online questionnaire covering the availability of services, screening, and referral practice. Responses were analyzed descriptively; associations between sociodemographic/clinical variables and screening/referral practice were explored. Results: In total, 103 participants completed the survey (67% women and 57% medical doctors). Fifteen professions from 23 countries were represented. Various rehabilitation, supportive-, and palliative care services were available yet rated "inadequate" by 21-37% of participants. Most respondents with a clinical role (n = 94) declare to screen (78%) and to refer (83%) their patients routinely for physical/cognitive/emotional issues. Survey completers (n = 103) indicated the main reasons for not screening/referring were (1) lack of suitable referral options (50%); (2) shortage of healthcare professionals (48%); and (3) long waiting lists (42%). To improve service provision, respondents suggested there is a need for education about neuro-oncology-specific issues (75%), improving the availability of services (65%) and staff (64%), developing international guidelines (64%), and strengthening the existing evidence-base for rehabilitation (60%). Conclusions: Detecting and managing neuro-oncology patients' and caregivers' rehabilitation, supportive,- and palliative care needs can be improved. Better international collaboration can help address healthcare disparities.

Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands: version 1.0.

PURPOSE: To provide practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor (SSTR) ligands. METHODS: This joint practice guideline/procedure standard was collaboratively developed by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the PET task force of the Response Assessment in Neurooncology Working Group (PET/RANO). RESULTS: Positron emission tomography (PET) using somatostatin receptor (SSTR) ligands can detect meningioma tissue with high sensitivity and specificity and may provide clinically relevant information beyond that obtained from structural magnetic resonance imaging (MRI) or computed tomography (CT) imaging alone. SSTR-directed PET imaging can be particularly useful for differential diagnosis, delineation of meningioma extent, detection of osseous involvement, and the differentiation between posttherapeutic scar tissue and tumour recurrence. Moreover, SSTR-peptide receptor radionuclide therapy (PRRT) is an emerging investigational treatment approach for meningioma. CONCLUSION: These practice guidelines will define procedure standards for the application of PET imaging in patients with meningiomas and related SSTR-targeted PRRTs in routine practice and clinical trials and will help to harmonize data acquisition and interpretation across centers, facilitate comparability of studies, and to collect larger databases. The current document provides additional information to the evidence-based recommendations from the PET/RANO Working Group regarding the utilization of PET imaging in meningiomas Galldiks (Neuro Oncol. 2017;19(12):1576-87). The information provided should be considered in the context of local conditions and regulations.

7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading.

INTRODUCTION: With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients. METHODS: We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status. RESULTS: Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy. CONCLUSIONS: We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.

Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability.

PURPOSE: Pre-surgical information about tumor consistency could facilitate neurosurgical planning. This study used multi-dynamic-multi-echo (MDME)-based relaxometry for the quantitative determination of pituitary tumor consistency, with the aim of predicting lesion resectability. METHODS: Seventy-two patients with suspected pituitary adenomas, who underwent preoperative 3 T MRI between January 2020 and January 2022, were included in this prospective study. Lesion-specific T1-/T2-relaxation times (T1R/T2R) and proton density (PD) metrics were determined. During surgery, data about tumor resectability were collected. A Receiver Operating Characteristic (ROC) curve analysis was performed to investigate the diagnostic performance (sensitivity/specificity) for discriminating between easy- and hard-to-remove by aspiration (eRAsp and hRAsp) lesions. A Mann-Whitney-U-test was done for group comparison. RESULTS: A total of 65 participants (mean age, 54 years ± 15, 33 women) were enrolled in the quantitative analysis. Twenty-four lesions were classified as hRAsp, while 41 lesions were assessed as eRAsp. There were significant differences in T1R (hRAsp: 1221.0 ms ± 211.9; eRAsp: 1500.2 ms ±â€¯496.4; p = 0.003) and T2R (hRAsp: 88.8 ms ± 14.5; eRAsp: 137.2 ms ± 166.6; p = 0.03) between both groups. The ROC analysis revealed an area under the curve of 0.72 (95% CI: 0.60-0.85) at p = 0.003 for T1R (cutoff value: 1248 ms; sensitivity/specificity: 78%/58%) and 0.66 (95% CI: 0.53-0.79) at p = 0.03 for T2R (cutoff value: 110 ms; sensitivity/specificity: 39%/96%). CONCLUSION: MDME-based relaxometry enables a non-invasive, pre-surgical characterization of lesion consistency and, therefore, provides a modality with which to predict tumor resectability.

A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients.

This paper investigated the correlation between magnetic resonance spectroscopic imaging (MRSI) and magnetic resonance fingerprinting (MRF) in glioma patients by comparing neuro-oncological markers obtained from MRSI to T1/T2 maps from MRF. Data from 12 consenting patients with gliomas were analyzed by defining hotspots for T1, T2, and various metabolic ratios, and comparing them using Sørensen-Dice similarity coefficients (DSCs) and the distances between their centers of intensity (COIDs). The median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were the highest for Gln/tNAA (T1: 0.75, T2: 0.80, tumor: 0.78), followed by Gly/tNAA (T1: 0.57, T2: 0.62, tumor: 0.54) and tCho/tNAA (T1: 0.61, T2: 0.58, tumor: 0.45). The median values in the tumor hotspot were T1 = 1724 ms, T2 = 86 ms, Gln/tNAA = 0.61, Gly/tNAA = 0.28, Ins/tNAA = 1.15, and tCho/tNAA = 0.48, and, in the peritumoral region, were T1 = 1756 ms, T2 = 102 ms, Gln/tNAA = 0.38, Gly/tNAA = 0.20, Ins/tNAA = 1.06, and tCho/tNAA = 0.38, and, in the NAWM, were T1 = 950 ms, T2 = 43 ms, Gln/tNAA = 0.16, Gly/tNAA = 0.07, Ins/tNAA = 0.54, and tCho/tNAA = 0.20. The results of this study constitute the first comparison of 7T MRSI and 3T MRF, showing a good correspondence between these methods.

3D volume growth rate evaluation in the EORTC-BTG-1320 clinical trial for recurrent WHO grade 2 and 3 meningiomas.

BACKGROUND: We previously reported that tumor 3D volume growth rate (3DVGR) classification could help in the assessment of drug activity in patients with meningioma using 3 main classes and a total of 5 subclasses: class 1: decrease; 2: stabilization or severe slowdown; 3: progression. The EORTC-BTG-1320 clinical trial was a randomized phase II trial evaluating the efficacy of trabectedin for recurrent WHO 2 or 3 meningioma. Our objective was to evaluate the discriminative value of 3DVGR classification in the EORTC-BTG-1320. METHODS: All patients with at least 1 available MRI before trial inclusion were included. 3D volume was evaluated on consecutive MRI until progression. 2D imaging response was centrally assessed by MRI modified Macdonald criteria. Clinical benefit was defined as neurological or functional status improvement or steroid decrease or discontinuation. RESULTS: Sixteen patients with a median age of 58.5 years were included. Best 3DVGR classes were: 1, 2A, 3A, and 3B in 2 (16.7%), 4 (33.3%), 2 (16.7%), and 4 (33.3%) patients, respectively. All patients with progression-free survival longer than 6 months had best 3DVGR class 1 or 2. 3DVGR classes 1 and 2 (combined) had a median overall survival of 34.7 months versus 7.2 months for class 3 (P = .061). All class 1 patients (2/2), 75% of class 2 patients (3/4), and only 10% of class 3 patients (1/10) had clinical benefit. CONCLUSIONS: Tumor 3DVGR classification may be helpful to identify early signals of treatment activity in meningioma clinical trials.

Zotiraciclib (TG02) for newly diagnosed glioblastoma in the elderly or for recurrent glioblastoma: The EORTC 1608 STEAM trial.

BACKGROUND: Zotiraciclib (TG02) is an oral multi-cyclin dependent kinase (CDK) inhibitor thought to inhibit tumor growth via CDK-9-dependent depletion of survival proteins such as c-MYC and MCL-1 which are frequently overexpressed in glioblastoma. METHODS: EORTC 1608 (NCT03224104) (STEAM) had a three parallel group (A,B,C) phase Ib, open-label, non-randomized, multicenter design in IDH wild-type newly diagnosed glioblastoma or anaplastic astrocytoma. Groups A and B explored the maximum tolerated dose (MTD) of TG02 in elderly patients, in combination with hypofractionated radiotherapy alone (group A) or temozolomide alone (group B), according to O6-methylguanine DNA methyltransferase promoter methylation status determined centrally. Group C explored single agent activity of TG02 at first relapse after temozolomide chemoradiotherapy with a primary endpoint of progression-free survival at 6 months (PFS-6). Tumor expression of CDK-9, c-MYC and MCL-1 was determined by immunohistochemistry. RESULTS: The MTD was 150 mg twice weekly in combination with radiotherapy alone (group A) or temozolomide alone (group B). Two dose-limiting toxicities were observed at 150 mg: one in group A (grade 3 seizure), one in group B (multiple grade 1 events). Main toxicities included neutropenia, gastrointestinal disorders and hepatotoxicity. PFS-6 in group C was 6.7%. CDK-9, c-MYC and MCL-1 were confirmed to be expressed and their expression was moderately cross-correlated. High protein levels of MCL-1 were associated with inferior survival. CONCLUSIONS: TG02 exhibits overlapping toxicity with alkylating agents and low single agent clinical activity in recurrent glioblastoma. The role of CDK-9 and its down-stream effectors as prognostic factors and therapeutic targets in glioblastoma warrants further study.

Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks.

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVIDIA-net (nv-Net) were trained and tested using manual segmentations from preoperative MRI of glioblastoma (GBM) and low-grade gliomas (LGG) from the BraTS 2021 dataset (1251 in total), in addition to 275 GBM and 205 LGG acquired clinically across 12 hospitals worldwide. Data was split into 80% training, 5% validation, and 15% internal test data. An additional external test-set of 158 GBM and 69 LGG was used to assess generalisability to other hospitals' data. All models' median Dice similarity coefficient (DSC) for both test sets were within, or higher than, previously reported human inter-rater agreement (range of 0.74-0.85). For both test sets, nn-Unet achieved the highest DSC (internal = 0.86, external = 0.93) and the lowest Hausdorff distances (10.07, 13.87 mm, respectively) for all tumor classes (p < 0.001). By applying Sparsified training, missing MRI sequences did not statistically affect the performance. nn-Unet achieves accurate segmentations in clinical settings even in the presence of incomplete MRI datasets. This facilitates future clinical adoption of automated glioma segmentation, which could help inform treatment planning and glioma monitoring.

Reliability of signal intensity in the basal ganglia on non-contrast T1-weighted MR scans after repetitive application of a gadolinium-based contrast agent in pediatric neuro-oncology patients.

PURPOSE: To evaluate the reliability of signal intensity (SI) changes in the basal ganglia as a supposed indicator of gadolinium deposition in the brain after repetitive application of gadolinium-based contrast agents (GBCAs) in a pediatric neuro-oncological collective. METHODS: One hundred and eight neuropediatric patients (54 male, 54 female, 0-17 years old), with repetitive GBCA-enhanced cranial MRIs between 2003 and 2017, were retrospectively analyzed. Two radiologists measured SI in the nucleus dentatus (ND), globus pallidus (GP), thalamus (T), and the pons (P). The NDP and GPT ratio were calculated. An intraclass correlation coefficient, and multiple linear regressions with subsequent stepwise backward variable selection were performed to evaluate the influence of gender, patient's age at the first MRI, time interval between the first and last MRI, linear or macrocyclic GBCAs, residual pathology, treatments, and magnet field strengths. RESULTS: The inter-reader agreement was good for GPT and NDP in the whole collective (ICC = 0.837 and ICC = 0.793) and for children >2 years of age (ICC = 0.874 and ICC = 0.790), but poor to moderate for children ≤2 years of age (ICC = 0.397 and ICC = 0.748). The intra-reader agreement was good (ICC = 0.910 and ICC = 0.882). An SI increase was only observed for both readers in GPT (p = 0.003, or p < 0.001). None of the considered cofactors showed a consistent effect on SI changes for either readers or regions. CONCLUSION: Measurements of SI changes in the basal ganglia are not a reliable parameter with which to evaluate or estimate gadolinium deposition in the brain or to identify suspicious influential factors after repeated GBCA applications.

Radiomic features define risk and are linked to DNA methylation attributes in primary CNS lymphoma.

Background: The prognostic roles of clinical and laboratory markers have been exploited to model risk in patients with primary CNS lymphoma, but these approaches do not fully explain the observed variation in outcome. To date, neuroimaging or molecular information is not used. The aim of this study was to determine the utility of radiomic features to capture clinically relevant phenotypes, and to link those to molecular profiles for enhanced risk stratification. Methods: In this retrospective study, we investigated 133 patients across 9 sites in Austria (2005-2018) and an external validation site in South Korea (44 patients, 2013-2016). We used T1-weighted contrast-enhanced MRI and an L1-norm regularized Cox proportional hazard model to derive a radiomic risk score. We integrated radiomic features with DNA methylation profiles using machine learning-based prediction, and validated the most relevant biological associations in tissues and cell lines. Results: The radiomic risk score, consisting of 20 mostly textural features, was a strong and independent predictor of survival (multivariate hazard ratio = 6.56 [3.64-11.81]) that remained valid in the external validation cohort. Radiomic features captured gene regulatory differences such as in BCL6 binding activity, which was put forth as testable treatment target for a subset of patients. Conclusions: The radiomic risk score was a robust and complementary predictor of survival and reflected characteristics in underlying DNA methylation patterns. Leveraging imaging phenotypes to assess risk and inform epigenetic treatment targets provides a concept on which to advance prognostic modeling and precision therapy for this aggressive cancer.

The Site of Origin of Medulloblastoma: Surgical Observations Correlated to Molecular Groups.

Developmental gene expression data from medulloblastoma (MB) suggest that WNT-MB originates from the region of the embryonic lower rhombic lip (LRL), whereas SHH-MB and non-WNT/non-SHH MB arise from cerebellar precursor matrix regions. This study aimed to analyze detailed intraoperative data with regard to the site of origin (STO) and compare these findings with the hypothesized regions of origin associated with the molecular group. A review of the institutional database identified 58 out of 72 pediatric patients who were operated for an MB at our department between 1996 and 2020 that had a detailed operative report and a surgical video as well as clinical and genetic classification data available for analysis. The STO was assessed based on intraoperative findings. Using the intraoperatively defined STO, "correct" prediction of molecular groups was feasible in 20% of WNT-MB, 60% of SHH-MB and 71% of non-WNT/non-SHH MB. The positive predictive values of the neurosurgical inspection to detect the molecular group were 0.21 (95% CI 0.08-0.48) for WNT-MB, 0.86 (95% CI 0.49-0.97) for SHH-MB and 0.73 (95% CI 0.57-0.85) for non-WNT/non-SHH MB. The present study demonstrated a limited predictive value of the intraoperatively observed STO for the prediction of the molecular group of MB.

The relation of sarcopenia and disability in multiple sclerosis.

BACKGROUND: The relation of sarcopenia and disability in MS is unknown. OBJECTIVE: To investigate the relation of temporal muscle thickness (TMT) and disability. METHODS: A cohort of 132 people who presented with a clinically isolated syndrome (CIS) suggestive of MS at a mean age of 30.0 years, were prospectively followed clinically and with MRI over 30-years. TMT and expanded disability status scale (EDSS) were assessed at baseline, one- five- ten- fourteen- twenty- and thirty-year follow-up. RESULTS: At 30-years, 27 participants remained classified as having had a CIS, 34 converted to relapsing remitting MS, 26 to secondary progressive MS, and 16 had died due to MS. Using linear mixed effect models with subject nested in time, greater annualized TMT-thinning was seen in individuals who developed MS (-0.04 mm/a, 95%CI: -0.07 to -0.01, p = 0.023). In those who converted to MS, a thinner TMT was reached at 14- (p = 0.008), 20- (p = 0.002) and 30-years (p< 0.001). TMT was negatively correlated with EDSS at 20-years (R=-0.18, p = 0.032) and 30-years (R-0.244, p = 0.005). Longitudinally, TMT at earlier timepoints was not predictive for 30-year clinical outcomes. CONCLUSION: TMT thinning is accelerated in MS and correlated with disability in later disease stages, but is not predictive of future disability.

Proof-of-Concept for Liquid Biopsy Disease Monitoring of MYC-Amplified Group 3 Medulloblastoma by Droplet Digital PCR.

BACKGROUND: Liquid biopsy diagnostic methods are an emerging complementary tool to imaging and pathology techniques across various cancer types. However, there is still no established method for the detection of molecular alterations and disease monitoring in MB, the most common malignant CNS tumor in the pediatric population. In the presented study, we investigated droplet digital polymerase chain reaction (ddPCR) as a highly sensitive method for the detection of MYC amplification in bodily fluids of group 3 MB patients. METHODS: We identified a cohort of five MYC-amplified MBs by methylation array and FISH. Predesigned and wet-lab validated probes for ddPCR were used to establish the detection method and were validated in two MYC-amplified MB cell lines as well as tumor tissue of the MYC-amplified cohort. Finally, a total of 49 longitudinal CSF samples were analyzed at multiple timepoints during the course of the disease. RESULTS: Detection of MYC amplification by ddPCR in CSF showed a sensitivity and specificity of 90% and 100%, respectively. We observed a steep increase in amplification rate (AR) at disease progression in 3/5 cases. ddPCR was proven to be more sensitive than cytology for the detection of residual disease. In contrast to CSF, MYC amplification was not detectable by ddPCR in blood samples. CONCLUSIONS: ddPCR proves to be a sensitive and specific method for the detection of MYC amplification in the CSF of MB patients. These results warrant implementation of liquid biopsy in future prospective clinical trials to validate the potential for improved diagnosis, disease staging and monitoring.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

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.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.

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.