Home > Publications database > Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T > print

001     838008
005     20220930130132.0
024 7 _ |a 10.1371/journal.pone.0184759
|2 doi
024 7 _ |a 2128/15337
|2 Handle
024 7 _ |a pmid:28945780
|2 pmid
024 7 _ |a WOS:000411645100009
|2 WOS
024 7 _ |a altmetric:26560561
|2 altmetric
037 _ _ |a FZJ-2017-06756
082 _ _ |a 500
100 1 _ |a Yun, Seong Dae
|0 P:(DE-Juel1)141899
|b 0
|u fzj
245 _ _ |a Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T
260 _ _ |a Lawrence, Kan.
|c 2017
|b PLoS
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 1506498541_1301
|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 relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods.
536 _ _ |a 573 - Neuroimaging (POF3-573)
|0 G:(DE-HGF)POF3-573
|c POF3-573
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Shah, N. J.
|0 P:(DE-Juel1)131794
|b 1
|e Corresponding author
|u fzj
773 _ _ |a 10.1371/journal.pone.0184759
|g Vol. 12, no. 9, p. e0184759 -
|0 PERI:(DE-600)2267670-3
|n 9
|p e0184759 -
|t PLoS one
|v 12
|y 2017
|x 1932-6203
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.pdf
856 4 _ |y OpenAccess
|x icon
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.gif?subformat=icon
856 4 _ |y OpenAccess
|x icon-1440
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.jpg?subformat=icon-1440
856 4 _ |y OpenAccess
|x icon-180
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.jpg?subformat=icon-180
856 4 _ |y OpenAccess
|x icon-640
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.jpg?subformat=icon-640
856 4 _ |y OpenAccess
|x pdfa
|u https://juser.fz-juelich.de/record/838008/files/journal.pone.0184759.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:838008
|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)141899
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)131794
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-573
|2 G:(DE-HGF)POF3-500
|v Neuroimaging
|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)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b PLOS ONE : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)INM-4-20090406
|k INM-4
|l Physik der Medizinischen Bildgebung
|x 0
920 1 _ |0 I:(DE-Juel1)INM-11-20170113
|k INM-11
|l Jara-Institut Quantum Information
|x 1
920 1 _ |0 I:(DE-82)080010_20140620
|k JARA-BRAIN
|l JARA-BRAIN
|x 2
980 1 _ |a FullTexts
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-4-20090406
980 _ _ |a I:(DE-Juel1)INM-11-20170113
980 _ _ |a I:(DE-82)080010_20140620
980 _ _ |a APC

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21