Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging.
Classification
Diffusion magnetic resonance imaging
Glioma
Isocitrate dehydrogenase
Neuroimaging
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
received:
15
12
2020
accepted:
29
03
2021
revised:
10
03
2021
pubmed:
30
4
2021
medline:
21
10
2021
entrez:
29
4
2021
Statut:
ppublish
Résumé
To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MK FA, MD, MK DIVIDE is a promising technique for glioma characterization and diagnosis. • DIVIDE metrics MK
Identifiants
pubmed: 33914116
doi: 10.1007/s00330-021-07959-x
pii: 10.1007/s00330-021-07959-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8197-8207Subventions
Organisme : national key research and development plan of China
ID : 2017YFC0108803
Organisme : Improvement Project for Theranostic ability on Difficulty miscellaneous disease(Tumor)
ID : ZLYNXM202016
Organisme : National Natural Science Foundation of China (CN)
ID : No.81771819
Organisme : National Natural Science Foundation of China
ID : No.81801667
Organisme : Swedish Foundation for Strategic Research
ID : ITM17-0267
Organisme : the Swedish Research Council
ID : 2018-03697
Informations de copyright
© 2021. European Society of Radiology.
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