001     837081
005     20210129231158.0
024 7 _ |a 10.1007/s00259-017-3812-3
|2 doi
024 7 _ |a 0340-6997
|2 ISSN
024 7 _ |a 1432-105X
|2 ISSN
024 7 _ |a 1619-7070
|2 ISSN
024 7 _ |a 1619-7089
|2 ISSN
024 7 _ |a pmid:28831534
|2 pmid
024 7 _ |a WOS:000415085500013
|2 WOS
037 _ _ |a FZJ-2017-06078
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Verger, Antoine
|0 P:(DE-Juel1)171957
|b 0
245 _ _ |a Comparison of $^{18}$F-FET PET and perfusion-weighted MRI for glioma grading: a hybrid PET/MR study
260 _ _ |a Heidelberg [u.a.]
|c 2017
|b Springer-Verl.
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1510581840_28474
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a PurposeBoth perfusion-weighted MR imaging (PWI) and O-(2-18F-fluoroethyl)-L-tyrosine PET (18F–FET) provide grading information in cerebral gliomas. The aim of this study was to compare the diagnostic value of 18F–FET PET and PWI for tumor grading in a series of patients with newly diagnosed, untreated gliomas using an integrated PET/MR scanner.MethodsSeventy-two patients with untreated gliomas [22 low-grade gliomas (LGG), and 50 high-grade gliomas (HGG)] were investigated with 18F–FET PET and PWI using a hybrid PET/MR scanner. After visual inspection of PET and PWI maps (rCBV, rCBF, MTT), volumes of interest (VOIs) with a diameter of 16 mm were centered upon the maximum of abnormality in the tumor area in each modality and the contralateral unaffected hemisphere. Mean and maximum tumor-to-brain ratios (TBRmean, TBRmax) were calculated. In addition, Time-to-Peak (TTP) and slopes of time–activity curves were calculated for 18F–FET PET. Diagnostic accuracies of 18F–FET PET and PWI for differentiating low-grade glioma (LGG) from high-grade glioma (HGG) were evaluated by receiver operating characteristic analyses (area under the curve; AUC).ResultsThe diagnostic accuracy of 18F–FET PET and PWI to discriminate LGG from HGG was similar with highest AUC values for TBRmean and TBRmax of 18F–FET PET uptake (0.80, 0.83) and for TBRmean and TBRmax of rCBV (0.80, 0.81). In case of increased signal in the tumor area with both methods (n = 32), local hot-spots were incongruent in 25 patients (78%) with a mean distance of 10.6 ± 9.5 mm. Dynamic FET PET and combination of different parameters did not further improve diagnostic accuracy.ConclusionsBoth 18F–FET PET and PWI discriminate LGG from HGG with similar diagnostic performance. Regional abnormalities in the tumor area are usually not congruent indicating that tumor grading by 18F–FET PET and PWI is based on different pathophysiological phenomena.
536 _ _ |a 572 - (Dys-)function and Plasticity (POF3-572)
|0 G:(DE-HGF)POF3-572
|c POF3-572
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Filss, Christian
|0 P:(DE-Juel1)141877
|b 1
700 1 _ |a Lohmann, Philipp
|0 P:(DE-Juel1)145110
|b 2
700 1 _ |a Stoffels, Gabriele
|0 P:(DE-Juel1)131627
|b 3
700 1 _ |a Sabel, Michael
|0 P:(DE-Juel1)165921
|b 4
700 1 _ |a Wittsack, Hans J.
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Rota Kops, Elena
|0 P:(DE-Juel1)131788
|b 6
700 1 _ |a Galldiks, Norbert
|0 P:(DE-Juel1)143792
|b 7
700 1 _ |a Fink, Gereon R.
|0 P:(DE-Juel1)131720
|b 8
700 1 _ |a Shah, Nadim J.
|0 P:(DE-Juel1)131794
|b 9
700 1 _ |a Langen, Karl-Josef
|0 P:(DE-Juel1)131777
|b 10
|e Corresponding author
773 _ _ |a 10.1007/s00259-017-3812-3
|0 PERI:(DE-600)2098375-X
|n 13
|p 2257–2265
|t European journal of nuclear medicine and molecular imaging
|v 44
|y 2017
|x 1619-7089
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.pdf
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.gif?subformat=icon
|x icon
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.jpg?subformat=icon-1440
|x icon-1440
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.jpg?subformat=icon-180
|x icon-180
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.jpg?subformat=icon-640
|x icon-640
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/837081/files/s00259-017-3812-3.pdf?subformat=pdfa
|x pdfa
|y Restricted
909 C O |o oai:juser.fz-juelich.de:837081
|p VDB
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)171957
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)141877
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)145110
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)131627
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)131788
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)143792
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 8
|6 P:(DE-Juel1)131720
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 9
|6 P:(DE-Juel1)131794
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 10
|6 P:(DE-Juel1)131777
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-572
|2 G:(DE-HGF)POF3-500
|v (Dys-)function and Plasticity
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b EUR J NUCL MED MOL I : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b EUR J NUCL MED MOL I : 2015
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-3-20090406
|k INM-3
|l Kognitive Neurowissenschaften
|x 0
920 1 _ |0 I:(DE-Juel1)INM-4-20090406
|k INM-4
|l Physik der Medizinischen Bildgebung
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-3-20090406
980 _ _ |a I:(DE-Juel1)INM-4-20090406
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21