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.

Biomedical Data Science Laboratory Instituto Universitario de Tecnologías de la Información y Comunicaciones Universitat Politècnica de València Valencia Spain

Brain Tumour Centre Erasmus MC Cancer Institute Rotterdam the Netherlands

C J Gorter MRI Center Department of Radiology Leiden University Medical Center Leiden the Netherlands

Cancer Center Amsterdam Amsterdam Netherlands

Centre for Medical Image Computing Department of Computer Science University College London London UK

Centre for Medical Image Computing Department of Medical Physics and Biomedical Engineering and Department of Neuroinflammation University College London London UK

Christian Doppler Laboratory for MR Imaging Biomarkers Vienna Austria

Department of Bioengineering Imperial College London London UK

Department of Biomedical Imaging and Image guided Therapy Medical University of Vienna Vienna Austria

Department of Biophysics Medical College of Wisconsin Milwaukee Wisconsin USA

Department of Brain Repair and Rehabilitation Institute of Neurology University College London London UK

Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health Babes Bolyai University Romania

Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Munich Germany

Department of Diagnostic and Interventional Radiology University Hospital Ulm Ulm Germany

Department of Diagnostic Sciences Ghent University Ghent Belgium

Department of Imaging Physics Delft University of Technology Delft the Netherlands

Department of Mechanical Engineering Faculty of Natural Sciences and Engineering Istinye University Istanbul Istanbul Turkey

Department of Medical Imaging Ghent University Hospital Ghent Belgium

Department of Neurology Haaglanden Medical Center Netherlands

Department of Neurology Leiden University Medical Center Leiden the Netherlands

Department of Neuroradiology Hospital Garcia de Orta Almada Portugal

Department of Neuroradiology King's College Hospital NHS Foundation Trust London UK

Department of Neurosurgery Medical University of Vienna Vienna Austria

Department of Neurosurgery St Anne's University Hospital Brno Czechia

Department of Physics and Computational Radiology Oslo University Hospital Oslo Norway

Department of Physics University of Oslo Oslo Norway

Department of Radiology and Nuclear Medicine Amsterdam UMC Vrije Universiteit Amsterdam Netherlands

Department of Radiology and Nuclear Medicine Erasmus MC Rotterdam Netherlands

Department of Radiology Clínica Universidad de Navarra Pamplona Spain

Department of Radiology Leiden University Medical Center Leiden the Netherlands

Department of Radiology Stanford University Stanford California USA

Department of Radiotherapy and Imaging Institute of Cancer Research UK

Department of Technical Disciplines in Medicine Faculty of Health Care University of Prešov Prešov Slovakia

Electrical and Electronics Engineering Department Bogazici University Istanbul Istanbul Turkey

Faculty of Engineering and Design Atlantic Technological University Sligo Sligo Ireland

Faculty of Medicine Masaryk University Brno Czechia

Helmholtz Zentrum Dresden Rossendorf Institute of Radiopharmaceutical Cancer Research Dresden Germany

High Field MR Centre Department of Biomedical Imaging and Image guided Therapy Medical University of Vienna Vienna Austria

IdiSNA Instituto de Investigación Sanitaria de Navarra Pamplona Spain

Institute of Biomedical Engineering Bogazici University Istanbul Istanbul Turkey

Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford UK

Lysholm Department of Neuroradiology National Hospital for Neurology and Neurosurgery University College London Hospitals NHS Foundation Trust London UK

Mathematical Modelling and Intelligent Systems for Health and Environment ATU Sligo Sligo Ireland

Medical Delta Foundation Delft the Netherlands

Medical Imaging Cluster Medical University of Vienna Vienna Austria

Queen Square Institute of Neurology and Centre for Medical Image Computing University College London London UK

Rede D'Or São Luiz Hospital Santa Luzia Brazil

Research Center of Medical Image Analysis and Artificial Intelligence Danube Private University Austria

School of Biomedical Engineering and Imaging Sciences King's College London London UK

Stanford Cardiovascular Institute Stanford University Stanford California USA

TUM Neuroimaging Center Klinikum rechts der Isar Technical University of Munich Munich Germany

Erratum v

J Magn Reson Imaging. 2024 Apr;59(4):1468. doi: 10.1002/jmri.28934. PubMed

Zobrazit více v PubMed

Sanai N, Berger MS. Surgical oncology for gliomas: The state of the art. Nat Rev Clin Oncol 2018;15:112‐125. PubMed

Ellingson BM, Bendszus M, Boxerman J, et al. Consensus recommendations for a standardized brain tumor imaging protocol in clinical trials. Neuro Oncol 2015;17:1188‐1198. PubMed PMC

Smits M. MRI biomarkers in neuro‐oncology. Nat Rev Neurol 2021;17:486‐500. PubMed

Clement P, Booth T, Borovečki F, et al. GliMR: Cross‐border collaborations to promote advanced MRI biomarkers for glioma. J Med Biol Eng 2021;41:115‐125. PubMed PMC

Booth TC, Wiegers EC, Warnert EAH, et al. High‐grade glioma treatment response monitoring biomarkers: A position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and the latest bench‐to‐bedside developments. Part 2: Spectroscopy, chemical exchange saturation, multiparametric imaging, and radiomics. Front Oncol 2021;11:811425. PubMed PMC

Kreis R, Boer V, Choi I‐Y, et al. Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations. NMR Biomed 2020;34:e4347. PubMed PMC

Oz G, Alger JR, Barker PB, et al. Clinical proton MR spectroscopy in central nervous system disorders. Radiology 2014;270:658‐679. PubMed PMC

McCarthy L, Verma G, Hangel G, et al. Application of 7T MRS to high‐grade gliomas. AJNR Am J Neuroradiol 2022;43:1378‐1395. PubMed PMC

Hangel G, Jain S, Springer E, et al. High‐resolution metabolic mapping of gliomas via patch‐based super‐resolution magnetic resonance spectroscopic imaging at 7T. Neuroimage 2019;191:587‐595. PubMed PMC

Maudsley AA, Andronesi OC, Barker PB, et al. Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations. NMR Biomed 2021;34:e4309. PubMed PMC

Wang Q, Zhang H, Zhang J, et al. The diagnostic performance of magnetic resonance spectroscopy in differentiating high‐from low‐grade gliomas: A systematic review and meta‐analysis. Eur Radiol 2016;26:2670‐2684. PubMed

Smits M. Imaging of oligodendroglioma. Br J Radiol 2016;89:20150857. PubMed PMC

Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ. 2‐hydroxyglutarate MR spectroscopy for prediction of isocitrate dehydrogenase mutant glioma: A systemic review and meta‐analysis using individual patient data. Neuro Oncol 2018;20:1573‐1583. PubMed PMC

Di Ieva A, Magnussen JS, McIntosh J, Mulcahy MJ, Pardey M, Choi C. Magnetic resonance spectroscopic assessment of isocitrate dehydrogenase status in gliomas: The new frontiers of spectrobiopsy in neurodiagnostics. World Neurosurg 2020;133:e421‐e427. PubMed

Ozturk‐Isik E, Cengiz S, Ozcan A, et al. Identification of IDH and TERTp mutation status using 1 H‐MRS in 112 hemispheric diffuse gliomas. J Magn Reson Imaging 2020;51:1799‐1809. PubMed

Osborn AG, Louis DN, Poussaint TY, Linscott LL, Salzman KL. The 2021 World Health Organization classification of tumors of the central nervous system: What neuroradiologists need to know. AJNR Am J Neuroradiol 2022;43:928‐937. PubMed PMC

Chaumeil MM, Larson PEZ, Yoshihara HAI, et al. Non‐invasive in vivo assessment of IDH1 mutational status in glioma. Nat Commun 2013;4:2429. PubMed PMC

Hubesch B, Sappey‐Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW. P‐31 MR spectroscopy of normal human brain and brain tumors. Radiology 1990;174:401‐409. PubMed

Bulakbasi N, Kocaoglu M, Sanal HT, Tayfun C. Efficacy of in vivo31Phosphorus magnetic resonance spectroscopy in differentiation and staging of adult human brain tumors. Neuroradiol J 2007;20:646‐655. PubMed

Ha D‐H, Choi S, Oh JY, Yoon SK, Kang MJ, Kim K‐U. Application of 31P MR spectroscopy to the brain tumors. Korean J Radiol 2013;14:477‐486. PubMed PMC

Wilson M, Andronesi O, Barker PB, et al. Methodological consensus on clinical proton MRS of the brain: Review and recommendations. Magn Reson Med 2019;82:527‐550. PubMed PMC

van Zijl P, Knutsson L. In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound. J Magn Reson 2019;306:55‐65. PubMed PMC

Nelson SJ, Ozhinsky E, Li Y, Park IW, Crane J. Strategies for rapid in vivo 1H and hyperpolarized 13C MR spectroscopic imaging. J Magn Reson 2013;229:187‐197. PubMed PMC

Pope WB, Prins RM, Albert Thomas M, et al. Non‐invasive detection of 2‐hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy. J Neurooncol 2012;107:197‐205. PubMed PMC

Andronesi OC, Kim GS, Gerstner E, et al. Detection of 2‐hydroxyglutarate in IDH‐mutated glioma patients by in vivo spectral‐editing and 2D correlation magnetic resonance spectroscopy. Sci Transl Med 2012;4:116ra4. PubMed PMC

Usinskiene J, Ulyte A, Bjørnerud A, et al. Erratum to: Optimal differentiation of high‐ and low‐grade glioma and metastasis: A meta‐analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology 2016;58:741. PubMed

Vinogradov E, Sherry AD, Lenkinski RE. CEST: From basic principles to applications, challenges and opportunities. J Magn Reson 2013;229:155‐172. PubMed PMC

van Zijl PCM, Yadav NN. Chemical exchange saturation transfer (CEST): What is in a name and what isn't? Magn Reson Med 2011;65:927‐948. PubMed PMC

van Zijl PCM, Lam WW, Xu J, Knutsson L, Stanisz GJ. Magnetization transfer contrast and chemical exchange saturation transfer MRI. Features and analysis of the field‐dependent saturation spectrum. Neuroimage 2018;168:222‐241. PubMed PMC

Zu Z, Louie EA, Lin EC, et al. Chemical exchange rotation transfer imaging of intermediate‐exchanging amines at 2 ppm. NMR Biomed 2017;30:e3756. PubMed PMC

Xu X, Sehgal AA, Yadav NN, et al. d‐glucose weighted chemical exchange saturation transfer (glucoCEST)‐based dynamic glucose enhanced (DGE) MRI at 3T: Early experience in healthy volunteers and brain tumor patients. Magn Reson Med 2020;84:247‐262. PubMed PMC

Goldenberg JM, Pagel MD. Assessments of tumor metabolism with CEST MRI. NMR Biomed 2019;32:e3943. PubMed PMC

Togao O, Yoshiura T, Keupp J, et al. Amide proton transfer imaging of adult diffuse gliomas: Correlation with histopathological grades. Neuro Oncol 2014;16:441‐448. PubMed PMC

Zhang J, Zhu W, Tain R, Zhou XJ, Cai K. Improved differentiation of low‐grade and high‐grade gliomas and detection of tumor proliferation using APT contrast fitted from Z‐Spectrum. Mol Imaging Biol 2018;20:623‐631. PubMed PMC

Jiang S, Wen Z, Ahn SS, et al. Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas. NMR Biomed 2022:e4731. PubMed PMC

Louis DN, Perry A, Wesseling P, et al. The 2021 WHO classification of tumors of the central nervous system: A summary. Neuro Oncol 2021;23:1231‐1251. PubMed PMC

Su C, Xu S, Lin D, et al. Multi‐parametric Z‐spectral MRI may have a good performance for glioma stratification in clinical patients. Eur Radiol 2022;32:101‐111. PubMed

Warnert EAH, Wood TC, Incekara F, et al. Mapping tumour heterogeneity with pulsed 3D CEST MRI in non‐enhancing glioma at 3 T. Magma 2022;35:53‐62. PubMed PMC

Jiang S, Eberhart CG, Lim M, et al. Identifying recurrent malignant glioma after treatment using amide proton transfer‐weighted MR imaging: A validation study with image‐guided stereotactic biopsy. Clin Cancer Res 2019;25:552‐561. PubMed PMC

Zhou J, Zaiss M, Knutsson L, et al. Review and consensus recommendations on clinical APT‐weighted imaging approaches at 3T: Application to brain tumors. Magn Reson Med 2022;88:546‐574. PubMed PMC

Herz K, Lindig T, Deshmane A, et al. T1ρ‐based dynamic glucose‐enhanced (DGEρ) MRI at 3 T: Method development and early clinical experience in the human brain. Magn Reson Med 2019;82:1832‐1847. PubMed

McVicar N, Li AX, Meakin SO, Bartha R. Imaging chemical exchange saturation transfer (CEST) effects following tumor‐selective acidification using lonidamine. NMR Biomed 2015;28:566‐575. PubMed

Yao J, Tan CHP, Schlossman J, et al. pH‐weighted amine chemical exchange saturation transfer echoplanar imaging (CEST‐EPI) as a potential early biomarker for bevacizumab failure in recurrent glioblastoma. J Neurooncol 2019;142:587‐595. PubMed PMC

Cai K, Singh A, Poptani H, et al. CEST signal at 2ppm (CEST@2ppm) from Z‐spectral fitting correlates with creatine distribution in brain tumor. NMR Biomed 2015;28:1‐8. PubMed PMC

Cai K, Tain R‐W, Zhou XJ, et al. Creatine CEST MRI for differentiating gliomas with different degrees of aggressiveness. Mol Imaging Biol 2017;19:225‐232. PubMed PMC

Neal A, Moffat BA, Stein JM, et al. Glutamate weighted imaging contrast in gliomas with 7 tesla magnetic resonance imaging. Neuroimage Clin 2019;22:101694. PubMed PMC

Reichenbach JR, Venkatesan R, Schillinger DJ, Kido DK, Haacke EM. Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 1997;204:272‐277. PubMed

Hsu CC‐T, Watkins TW, Kwan GNC, Haacke EM. Susceptibility‐weighted imaging of glioma: Update on current imaging status and future directions. J Neuroimaging 2016;26:383‐390. PubMed

Park MJ, Kim HS, Jahng G‐H, Ryu C‐W, Park SM, Kim SY. Semiquantitative assessment of intratumoral susceptibility signals using non‐contrast‐enhanced high‐field high‐resolution susceptibility‐weighted imaging in patients with gliomas: Comparison with MR perfusion imaging. AJNR Am J Neuroradiol 2009;30:1402‐1408. PubMed PMC

Pinker K, Noebauer‐Huhmann IM, Stavrou I, et al. High‐resolution contrast‐enhanced, susceptibility‐weighted MR imaging at 3T in patients with brain tumors: Correlation with positron‐emission tomography and histopathologic findings. AJNR Am J Neuroradiol 2007;28:1280‐1286. PubMed PMC

Mohammed W, Xunning H, Haibin S, Jingzhi M. Clinical applications of susceptibility‐weighted imaging in detecting and grading intracranial gliomas: A review. Cancer Imaging 2013;13:186‐195. PubMed PMC

Li X, Zhu Y, Kang H, et al. Glioma grading by microvascular permeability parameters derived from dynamic contrast‐enhanced MRI and intratumoral susceptibility signal on susceptibility weighted imaging. Cancer Imaging 2015;15:4. PubMed PMC

Wang X‐C, Zhang H, Tan Y, et al. Combined value of susceptibility‐weighted and perfusion‐weighted imaging in assessing who grade for brain astrocytomas. J Magn Reson Imaging 2014;39:1569‐1574. PubMed

Bhattacharjee R, Gupta RK, Patir R, Vaishya S, Ahlawat S, Singh A. Quantitative vs. semiquantitative assessment of intratumoral susceptibility signals in patients with different grades of glioma. J Magn Reson Imaging 2020;51:225‐233. PubMed

Saini J, Gupta PK, Sahoo P, et al. Differentiation of grade II/III and grade IV glioma by combining “T1 contrast‐enhanced brain perfusion imaging” and susceptibility‐weighted quantitative imaging. Neuroradiology 2018;60:43‐50. PubMed

Yang X, Lin Y, Xing Z, She D, Su Y, Cao D. Predicting 1p/19q codeletion status using diffusion‐, susceptibility‐, perfusion‐weighted, and conventional MRI in IDH‐mutant lower‐grade gliomas. Acta Radiol 2021;62:1657‐1665. PubMed

Pinker K, Noebauer‐Huhmann IM, Stavrou I, et al. High‐field, high‐resolution, susceptibility‐weighted magnetic resonance imaging: Improved image quality by addition of contrast agent and higher field strength in patients with brain tumors. Neuroradiology 2008;50:9‐16. PubMed

Fahrendorf D, Schwindt W, Wölfer J, et al. Benefits of contrast‐enhanced SWI in patients with glioblastoma multiforme. Eur Radiol 2013;23:2868‐2879. PubMed

Kang H, Jang S. The diagnostic value of postcontrast susceptibility‐weighted imaging in the assessment of intracranial brain neoplasm at 3T. Acta Radiol 2021;62:791‐798. PubMed

Lai P‐H, Chung H‐W, Chang H‐C, et al. Susceptibility‐weighted imaging provides complementary value to diffusion‐weighted imaging in the differentiation between pyogenic brain abscesses, necrotic glioblastomas, and necrotic metastatic brain tumors. Eur J Radiol 2019;117:56‐61. PubMed

Peters S, Knöß N, Wodarg F, Cnyrim C, Jansen O. Glioblastomas vs. lymphomas: More diagnostic certainty by using susceptibility‐weighted imaging (SWI). Rofo 2012;184:713‐718. PubMed

Haller S, Haacke EM, Thurnher MM, Barkhof F. Susceptibility‐weighted imaging: Technical essentials and clinical neurologic applications. Radiology 2021;299:3‐26. PubMed

Ozturk K, Soylu E, Cayci Z. Differentiation between primary CNS lymphoma and atypical glioblastoma according to major genomic alterations using diffusion and susceptibility‐weighted MR imaging. Eur J Radiol 2021;141:109784. PubMed

Vaquero JJ, Kinahan P. Positron emission tomography: Current challenges and opportunities for technological advances in clinical and preclinical imaging systems. Annu Rev Biomed Eng 2015;17:385‐414. PubMed PMC

Park CR, Lee Y. Comparison of PET image quality using simultaneous PET/MR by attenuation correction with various MR pulse sequences. Nucl Eng Technol 2019;51:1610‐1615.

Albert NL, Weller M, Suchorska B, et al. Response assessment in neuro‐oncology working group and European Association for Neuro‐Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol 2016;18:1199‐1208. PubMed PMC

Galldiks N, Langen K‐J, Pope WB. From the clinician's point of view ‐ what is the status quo of positron emission tomography in patients with brain tumors? Neuro Oncol 2015;17:1434‐1444. PubMed PMC

Law I, Albert NL, Arbizu J, et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: Version 1.0. Eur J Nucl Med Mol Imaging 2019;46:540‐557. PubMed PMC

Glaudemans AWJM, Enting RH, Heesters MAAM, et al. Value of 11C‐methionine PET in imaging brain tumours and metastases. Eur J Nucl Med Mol Imaging 2013;40:615‐635. PubMed

Rapp M, Heinzel A, Galldiks N, et al. Diagnostic performance of 18F‐FET PET in newly diagnosed cerebral lesions suggestive of glioma. J Nucl Med 2013;54:229‐235. PubMed

Katsanos AH, Alexiou GA, Fotopoulos AD, Jabbour P, Kyritsis AP, Sioka C. Performance of 18F‐FDG, 11C‐methionine, and 18F‐FET PET for glioma grading: A meta‐analysis. Clin Nucl Med 2019;44:864‐869. PubMed

Suchorska B, Giese A, Biczok A, et al. Identification of time‐to‐peak on dynamic 18F‐FET‐PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma. Neuro Oncol 2018;20:279‐288. PubMed PMC

Kunz M, Albert NL, Unterrainer M, et al. Dynamic 18F‐FET PET is a powerful imaging biomarker in gadolinium‐negative gliomas. Neuro Oncol 2019;21:274‐284. PubMed PMC

Suchorska B, Jansen NL, Linn J, et al. Biological tumor volume in 18FET‐PET before radiochemotherapy correlates with survival in GBM. Neurology 2015;84:710‐719. PubMed

Verburg N, Koopman T, Yaqub MM, et al. Improved detection of diffuse glioma infiltration with imaging combinations: A diagnostic accuracy study. Neuro Oncol 2020;22:412‐422. PubMed PMC

Song S, Wang L, Yang H, et al. Static 18F‐FET PET and DSC‐PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status. Eur Radiol 2021;31:4087‐4096. PubMed

Mohajer JK, Nisbet A, Velliou E, Ajaz M, Schettino G. Biological effects of static magnetic field exposure in the context of MR‐guided radiotherapy. Br J Radiol 2019;92:20180484. PubMed PMC

Jadvar H, Colletti PM. Competitive advantage of PET/MRI. Eur J Radiol 2014;83:84‐94. PubMed PMC

Hiscox LV, Johnson CL, Barnhill E, et al. Magnetic resonance elastography (MRE) of the human brain: Technique, findings and clinical applications. Phys Med Biol 2016;61:R401‐R437. PubMed

Streitberger K‐J, Reiss‐Zimmermann M, Freimann FB, et al. High‐resolution mechanical imaging of glioblastoma by multifrequency magnetic resonance elastography. PLoS One 2014;9:e110588. PubMed PMC

Simon M, Guo J, Papazoglou S, et al. Non‐invasive characterization of intracranial tumors by magnetic resonance elastography. New J Phys 2013;15:085024. 10.1088/1367-2630/15/8/085024. DOI

Reiss‐Zimmermann M, Streitberger K‐J, Sack I, et al. High resolution imaging of viscoelastic properties of intracranial tumours by multi‐frequency magnetic resonance elastography. Clin Neuroradiol 2015;25:371‐378. PubMed

Pepin KM, McGee KP, Arani A, et al. MR elastography analysis of glioma stiffness and IDH1‐mutation status. AJNR Am J Neuroradiol 2018;39:31‐36. PubMed PMC

Streitberger K‐J, Lilaj L, Schrank F, et al. How tissue fluidity influences brain tumor progression. Proc Natl Acad Sci U S A 2020;117:128‐134. PubMed PMC

Fløgstad Svensson S, Fuster‐Garcia E, Latysheva A, et al. Decreased tissue stiffness in glioblastoma by MR elastography is associated with increased cerebral blood flow. Eur J Radiol 2022;147:110136. PubMed

Bunevicius A, Schregel K, Sinkus R, Golby A, Patz S. REVIEW: MR elastography of brain tumors. Neuroimage Clin 2020;25:102109. PubMed PMC

Jain RK, Martin JD, Stylianopoulos T. The role of mechanical forces in tumor growth and therapy. Annu Rev Biomed Eng 2014;16:321‐346. PubMed PMC

Pepin KM, Ehman RL, McGee KP. Magnetic resonance elastography (MRE) in cancer: Technique, analysis, and applications. Prog Nucl Magn Reson Spectrosc 2015;90‐91:32‐48. PubMed PMC

Jamin Y, Boult JKR, Li J, et al. Exploring the biomechanical properties of brain malignancies and their pathologic determinants in vivo with magnetic resonance elastography. Cancer Res 2015;75:1216‐1224. PubMed PMC

Schregel K, Nazari N, Nowicki MO, et al. Characterization of glioblastoma in an orthotopic mouse model with magnetic resonance elastography. NMR Biomed 2018;31:e3840. PubMed PMC

Manduca A, Bayly PJ, Ehman RL, et al. MR elastography: Principles, guidelines, and terminology. Magn Reson Med 2021;85:2377‐2390. PubMed PMC

Murphy MC, Huston J 3rd, Ehman RL. MR elastography of the brain and its application in neurological diseases. Neuroimage 2019;187:176‐183. PubMed PMC

Svensson SF, De Arcos J, Darwish OI, et al. Robustness of MR elastography in the healthy brain: Repeatability, reliability, and effect of different reconstruction methods. J Magn Reson Imaging 2021;53:1510‐1521. PubMed

Calabrese E, Rudie JD, Rauschecker AM, et al. Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma. Neurooncol Adv 2022;4:vdac060. PubMed PMC

Hashido T, Saito S, Ishida T. A radiomics‐based comparative study on arterial spin labeling and dynamic susceptibility contrast perfusion‐weighted imaging in gliomas. Sci Rep 2020;10:6121. PubMed PMC

Zhang X, Yan L‐F, Hu Y‐C, et al. Optimizing a machine learning based glioma grading system using multi‐parametric MRI histogram and texture features. Oncotarget 2017;8:47816‐47830. PubMed PMC

Kumar R, Gupta A, Arora HS, Pandian GN, Raman B. CGHF: A computational decision support system for glioma classification using hybrid radiomics‐ and stationary wavelet‐based features. IEEE Access 2020;8:79440‐79458.

Lin DJ, Johnson PM, Knoll F, Lui YW. Artificial intelligence for MR image reconstruction: An overview for clinicians. J Magn Reson Imaging 2021;53:1015‐1028. PubMed PMC

Chen Z, Pawar K, Ekanayake M, Pain C, Zhong S, Egan GF. Deep learning for image enhancement and correction in magnetic resonance imaging‐state‐of‐the‐art and challenges. J Digit Imaging 2022. PubMed PMC

Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ. Imaging prediction of isocitrate dehydrogenase (IDH) mutation in patients with glioma: A systemic review and meta‐analysis. Eur Radiol 2019;29:745‐758. PubMed

Lasocki A, Buckland ME, Drummond KJ, et al. Conventional MRI features can predict the molecular subtype of adult grade 2‐3 intracranial diffuse gliomas. Neuroradiology 2022;64:2295‐2305. PubMed PMC

Pease M, Gersey ZC, Ak M, et al. Pre‐operative MRI radiomics model non‐invasively predicts key genomic markers and survival in glioblastoma patients. J Neurooncol 2022;160:253‐263. PubMed

Yan J, Zhang B, Zhang S, et al. Quantitative MRI‐based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients. NPJ Precis Oncol 2021;5:72. PubMed PMC

Ahn SS, An C, Park YW, et al. Identification of magnetic resonance imaging features for the prediction of molecular profiles of newly diagnosed glioblastoma. J Neurooncol 2021;154:83‐92. PubMed

Ali MB, Gu IY‐H, Berger MS, et al. Domain mapping and deep learning from multiple MRI clinical datasets for prediction of molecular subtypes in low grade gliomas. Brain Sci 2020;10:463. 10.3390/brainsci10070463. PubMed DOI PMC

van der Voort SR, Incekara F, Wijnenga MMJ, et al. Combined molecular subtyping, grading, and segmentation of glioma using multi‐task deep learning. Neuro Oncol 2023;25:279‐289. PubMed PMC

Kickingereder P, Sahm F, Radbruch A, et al. IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non‐invasively predictable with rCBV imaging in human glioma. Sci Rep 2015;5:16238. PubMed PMC

Kim M, Jung SY, Park JE, et al. Diffusion‐ and perfusion‐weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma. Eur Radiol 2020;30:2142‐2151. PubMed

Park JE, Kim HS, Park SY, et al. Prediction of Core signaling pathway by using diffusion‐ and perfusion‐based MRI radiomics and next‐generation sequencing in isocitrate dehydrogenase wild‐type glioblastoma. Radiology 2020;294:388‐397. PubMed

Alsop DC, Detre JA, Golay X, et al. Recommended implementation of arterial spin‐labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med 2015;73:102‐116. PubMed PMC

Tian Q, Yan L‐F, Zhang X, et al. Radiomics strategy for glioma grading using texture features from multiparametric MRI. J Magn Reson Imaging 2018;48:1518‐1528. PubMed

Tian H, Wu H, Wu G, Xu G. Noninvasive prediction of TERT promoter mutations in high‐grade glioma by radiomics analysis based on multiparameter MRI. Biomed Res Int 2020;2020:3872314. PubMed PMC

Li XT, Huang RY. Standardization of imaging methods for machine learning in neuro‐oncology. Neurooncol Adv 2020;2(4):iv49‐iv55. PubMed PMC

Park JE, Park SY, Kim HJ, Kim HS. Reproducibility and generalizability in radiomics modeling: Possible strategies in radiologic and statistical perspectives. Korean J Radiol 2019;20:1124‐1137. PubMed PMC

Zwanenburg A, Vallières M, Abdalah MA, et al. The image biomarker standardization initiative: Standardized quantitative radiomics for high‐throughput image‐based phenotyping. Radiology 2020;295:328‐338. PubMed PMC

Pati S, Baid U, Edwards B, et al. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022;13:7346. PubMed PMC

Barredo Arrieta A, Díaz‐Rodríguez N, Del Ser J, et al. Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Inf Fusion 2020;58:82‐115.

Henriksen OM, Del Mar Á‐TM, Figueiredo P, et al. High‐grade glioma treatment response monitoring biomarkers: A position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and the latest bench‐to‐bedside developments. Part 1: Perfusion and diffusion techniques. Front Oncol 2022;12:810263. PubMed PMC

Petr J, Hogeboom L, Nikulin P, et al. A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal‐appearing brain tissue. MAGMA 2022;35:163‐186. PubMed PMC

Han S, Liu Y, Cai SJ, et al. IDH mutation in glioma: Molecular mechanisms and potential therapeutic targets. Br J Cancer 2020;122:1580‐1589. PubMed PMC

Life expectancy in glioblastoma patients who had undergone stereotactic biopsy: a retrospective single-center study