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Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.
Hirschler, Lydiane; Sollmann, Nico; Schmitz-Abecassis, Bárbara; Pinto, Joana; Arzanforoosh, Fatemehsadat; Barkhof, Frederik; Booth, Thomas; Calvo-Imirizaldu, Marta; Cassia, Guilherme; Chmelik, Marek; Clement, Patricia; Ercan, Ece; Fernández-Seara, Maria A; Furtner, Julia; Fuster-Garcia, Elies; Grech-Sollars, Matthew; Guven, Nazmiye Tugay; Hatay, Gokce Hale; Karami, Golestan; Keil, Vera C; Kim, Mina; Koekkoek, Johan A F; Kukran, Simran; Mancini, Laura; Nechifor, Ruben Emanuel; Özcan, Alpay; Ozturk-Isik, Esin; Piskin, Senol; Schmainda, Kathleen; Svensson, Siri F; Tseng, Chih-Hsien; Unnikrishnan, Saritha; Vos, Frans; Warnert, Esther; Zhao, Moss Y; Jancalek, Radim; Nunes, Teresa; Emblem, Kyrre E; Smits, Marion; Petr, Jan; Hangel, Gilbert.
Affiliation
  • Hirschler L; C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Sollmann N; Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany.
  • Schmitz-Abecassis B; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Pinto J; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Arzanforoosh F; Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Barkhof F; Medical Delta Foundation, Delft, The Netherlands.
  • Booth T; Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
  • Calvo-Imirizaldu M; Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Cassia G; Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
  • Chmelik M; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK.
  • Clement P; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Ercan E; Department of Neuroradiology, King's College Hospital NHS Foundation Trust, London, UK.
  • Fernández-Seara MA; Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain.
  • Furtner J; Hospital Santa Luzia, Rede D'Or São Luiz, Brasília, Brazil.
  • Fuster-Garcia E; Department of Technical Disciplines in Medicine, Faculty of Health Care, University of Presov, Presov, Slovakia.
  • Grech-Sollars M; Department of Diagnostic Sciences, Ghent University, Ghent, Belgium.
  • Guven NT; Department of Medical Imaging, Ghent University Hospital, Ghent, Belgium.
  • Hatay GH; Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Karami G; Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain.
  • Keil VC; IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain.
  • Kim M; Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Koekkoek JAF; Research Center of Medical Image Analysis and Artificial Intelligence, Danube Private University, Krems an der Donau, Austria.
  • Kukran S; Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, Valencia, Spain.
  • Mancini L; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Nechifor RE; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK.
  • Özcan A; Institute of Biomedical Engineering, Bogazici University Istanbul, Istanbul, Turkey.
  • Ozturk-Isik E; Institute of Biomedical Engineering, Bogazici University Istanbul, Istanbul, Turkey.
  • Piskin S; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Schmainda K; Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
  • Svensson SF; Cancer Center Amsterdam, Amsterdam, The Netherlands.
  • Tseng CH; Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of Neuroinflammation, University College London, London, UK.
  • Unnikrishnan S; Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands.
  • Vos F; Department of Neurology, Haaglanden Medical Center, The Hague, The Netherlands.
  • Warnert E; Department of Bioengineering, Imperial College London, London, UK.
  • Zhao MY; Department of Radiotherapy and Imaging, Institute of Cancer Research, London, UK.
  • Jancalek R; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK.
  • Nunes T; Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.
  • Emblem KE; Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania.
  • Smits M; Electrical and Electronics Engineering Department, Bogazici University Istanbul, Istanbul, Turkey.
  • Petr J; Institute of Biomedical Engineering, Bogazici University Istanbul, Istanbul, Turkey.
  • Hangel G; Department of Mechanical Engineering, Faculty of Natural Sciences and Engineering, Istinye University Istanbul, Istanbul, Turkey.
J Magn Reson Imaging ; 57(6): 1655-1675, 2023 06.
Article in En | MEDLINE | ID: mdl-36866773
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Glioma Type of study: Guideline Limits: Humans Language: En Journal: J Magn Reson Imaging Year: 2023 Document type: Article
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Glioma Type of study: Guideline Limits: Humans Language: En Journal: J Magn Reson Imaging Year: 2023 Document type: Article