001     905895
005     20230522125345.0
024 7 _ |a 10.1002/hbm.25778
|2 doi
024 7 _ |a 1065-9471
|2 ISSN
024 7 _ |a 1097-0193
|2 ISSN
024 7 _ |a 2128/31060
|2 Handle
024 7 _ |a WOS:000746511800001
|2 WOS
037 _ _ |a FZJ-2022-01095
082 _ _ |a 610
100 1 _ |a Kaulen, Nicolas
|0 P:(DE-Juel1)176967
|b 0
|u fzj
245 _ _ |a mGluR 5 and GABA A receptor‐specific parametric PET atlas construction— PET / MR data processing pipeline, validation, and application
260 _ _ |a New York, NY
|c 2022
|b Wiley-Liss
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 1650621642_27939
|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 The glutamate and γ-aminobutyric acid neuroreceptor subtypes mGluR5 and GABAA are hypothesized to be involved in the development of a variety of psychiatric diseases. However, detailed information relating to their in vivo distribution is generally unavailable. Maps of such distributions could potentially aid clinical studies by providing a reference for the normal distribution of neuroreceptors and may also be useful as covariates in advanced functional magnetic resonance imaging (MR) studies. In this study, we propose a comprehensive processing pipeline for the construction of standard space, in vivo distributions of non-displaceable binding potential (BPND), and total distribution volume (VT) based on simultaneously acquired bolus-infusion positron emission tomography (PET) and MR data. The pipeline was applied to [11C]ABP688-PET/MR (13 healthy male non-smokers, 26.6 ± 7.0 years) and [11C]Flumazenil-PET/MR (10 healthy males, 25.8 ± 3.0 years) data. Activity concentration templates, as well as VT and BPND atlases of mGluR5 and GABAA, were generated from these data. The maps were validated by assessing the percent error δ from warped space to native space in a selection of brain regions. We verified that the average δABP = 3.0 ± 1.0% and δFMZ = 3.8 ± 1.4% were lower than the expected variabilities σ of the tracers (σABP = 4.0%–16.0%, σFMZ = 3.9%–9.5%). An evaluation of PET-to-PET registrations based on the new maps showed higher registration accuracy compared to registrations based on the commonly used [15O]H2O-template distributed with SPM12. Thus, we conclude that the resulting maps can be used for further research and the proposed pipeline is a viable tool for the construction of standardized PET data distributions.
536 _ _ |a 5253 - Neuroimaging (POF4-525)
|0 G:(DE-HGF)POF4-5253
|c POF4-525
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Rajkumar, Ravichandran
|0 P:(DE-Juel1)164396
|b 1
700 1 _ |a Régio Brambilla, Cláudia
|0 P:(DE-Juel1)171754
|b 2
700 1 _ |a Mauler, Jörg
|0 P:(DE-Juel1)144215
|b 3
|u fzj
700 1 _ |a Ramkiran, Shukti
|0 P:(DE-Juel1)169201
|b 4
|u fzj
700 1 _ |a Orth, Linda
|0 P:(DE-Juel1)172782
|b 5
700 1 _ |a Sbaihat, Hasan
|0 P:(DE-Juel1)174570
|b 6
|u fzj
700 1 _ |a Lang, Markus
|0 P:(DE-Juel1)131831
|b 7
|u fzj
700 1 _ |a Wyss, Christine
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Rota Kops, Elena
|0 P:(DE-Juel1)131788
|b 9
|u fzj
700 1 _ |a Scheins, Jürgen
|0 P:(DE-Juel1)131791
|b 10
|u fzj
700 1 _ |a Neumaier, Bernd
|0 P:(DE-Juel1)166419
|b 11
|u fzj
700 1 _ |a Ermert, Johannes
|0 P:(DE-Juel1)131818
|b 12
|u fzj
700 1 _ |a Herzog, Hans
|0 P:(DE-Juel1)131768
|b 13
|u fzj
700 1 _ |a Langen, Karl-Joseph
|0 P:(DE-Juel1)131777
|b 14
|u fzj
700 1 _ |a Lerche, Christoph
|0 P:(DE-Juel1)164254
|b 15
|u fzj
700 1 _ |a Shah, N. J.
|0 P:(DE-Juel1)131794
|b 16
|u fzj
700 1 _ |a Veselinović, Tanja
|0 P:(DE-HGF)0
|b 17
700 1 _ |a Neuner, Irene
|0 P:(DE-Juel1)131781
|b 18
|e Corresponding author
|u fzj
773 _ _ |a 10.1002/hbm.25778
|g p. hbm.25778
|0 PERI:(DE-600)1492703-2
|n 7
|p 2148-2163
|t Human brain mapping
|v 43
|y 2022
|x 1065-9471
856 4 _ |u https://juser.fz-juelich.de/record/905895/files/1200177349_MDPL_K10449_Invoice.pdf
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/905895/files/Human%20Brain%20Mapping%20-%202022%20-%20Kaulen%20-%20mGluR5%20and%20GABAA%20receptor%E2%80%90specific%20parametric%20PET%20atlas%20construction%20PET%20MR%20data.pdf
909 C O |o oai:juser.fz-juelich.de:905895
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)176967
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)164396
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)171754
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)144215
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)169201
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)174570
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)131831
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 9
|6 P:(DE-Juel1)131788
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 10
|6 P:(DE-Juel1)131791
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 11
|6 P:(DE-Juel1)166419
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 12
|6 P:(DE-Juel1)131818
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 13
|6 P:(DE-Juel1)131768
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 14
|6 P:(DE-Juel1)131777
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 15
|6 P:(DE-Juel1)164254
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 16
|6 P:(DE-Juel1)131794
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 17
|6 P:(DE-HGF)0
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 18
|6 P:(DE-Juel1)131781
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5253
|x 0
914 1 _ |y 2022
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-27
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2021-01-27
915 _ _ |a DEAL Wiley
|0 StatID:(DE-HGF)3001
|2 StatID
|d 2021-01-27
|w ger
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-27
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2022-11-22
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2022-09-27T20:46:01Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2022-09-27T20:46:01Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2022-09-27T20:46:01Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2022-11-22
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b HUM BRAIN MAPP : 2021
|d 2022-11-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2022-11-22
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2022-11-22
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b HUM BRAIN MAPP : 2021
|d 2022-11-22
915 p c |a APC keys set
|2 APC
|0 PC:(DE-HGF)0000
915 p c |a Local Funding
|2 APC
|0 PC:(DE-HGF)0001
915 p c |a DFG OA Publikationskosten
|2 APC
|0 PC:(DE-HGF)0002
915 p c |a DOAJ Journal
|2 APC
|0 PC:(DE-HGF)0003
920 1 _ |0 I:(DE-Juel1)INM-11-20170113
|k INM-11
|l Jara-Institut Quantum Information
|x 0
920 1 _ |0 I:(DE-Juel1)INM-4-20090406
|k INM-4
|l Physik der Medizinischen Bildgebung
|x 1
920 1 _ |0 I:(DE-Juel1)VDB1046
|k JARA-BRAIN
|l Jülich-Aachen Research Alliance - Translational Brain Medicine
|x 2
920 1 _ |0 I:(DE-Juel1)INM-5-20090406
|k INM-5
|l Nuklearchemie
|x 3
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-11-20170113
980 _ _ |a I:(DE-Juel1)INM-4-20090406
980 _ _ |a I:(DE-Juel1)VDB1046
980 _ _ |a I:(DE-Juel1)INM-5-20090406
980 _ _ |a APC
980 1 _ |a APC
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21