dc.contributor.author
Auer, Timo A.
dc.date.accessioned
2023-07-10T15:10:46Z
dc.date.available
2023-07-10T15:10:46Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/40040
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-39762
dc.description.abstract
The management of gliomas has changed dramatically since the presentation of the revised WHO Classification of Tumors of the Central Nervous System in 2016 emphasizing the tumor heterogeneity based on their molecular profile.
The need for a more noninvasive characterization of glioblastomas (GBM) by establishing reliable imaging biomarkers to predict patient outcome and improve therapy monitoring is bigger than ever.
Multiparametric MRI, including promising newer techniques like electrical property tomography and mapping, may have the potential to provide enough information for intelligent imaging postprocessing algorithms to face the challenge by decoding GBM heterogeneity noninvasively.
en
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Magnetic Resonance Imaging
en
dc.subject
Brain Neoplasms
en
dc.subject
Glioblastoma
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
Advanced MR techniques in glioblastoma imaging—upcoming challenges and how to face them
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1007/s00330-021-07978-8
dcterms.bibliographicCitation.journaltitle
European Radiology
dcterms.bibliographicCitation.number
9
dcterms.bibliographicCitation.originalpublishername
Springer Nature
dcterms.bibliographicCitation.pagestart
6652
dcterms.bibliographicCitation.pageend
6654
dcterms.bibliographicCitation.volume
31
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.funding
Springer Nature DEAL
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
33890147
dcterms.isPartOf.issn
0938-7994
dcterms.isPartOf.eissn
1432-1084