001     878074
005     20210130005354.0
024 7 _ |a 10.1016/j.mri.2020.07.003
|2 doi
024 7 _ |a 0730-725X
|2 ISSN
024 7 _ |a 1873-5894
|2 ISSN
024 7 _ |a 2128/25554
|2 Handle
024 7 _ |a pmid:32653426
|2 pmid
024 7 _ |a WOS:000566701900014
|2 WOS
037 _ _ |a FZJ-2020-02616
082 _ _ |a 610
100 1 _ |a Choi, Chang-Hoon
|0 P:(DE-Juel1)164356
|b 0
|e Corresponding author
|u fzj
245 _ _ |a The state-of-the-art and emerging design approaches of double-tuned RF coils for X-nuclei, brain MR imaging and spectroscopy: A review
260 _ _ |a Amsterdam [u.a.]
|c 2020
|b Elsevier Science
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 1599479901_14754
|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 With the increasing availability of ultra-high field MRI systems, studying non-proton nuclei (X-nuclei), such as 23Na and 31P has received great interest. X-nuclei are able to provide insight into important cellular processes and energy metabolism in tissues and by monitoring these nuclei closely it is possible to establish links to pathological conditions and neurodegenerative diseases. In order to investigate X-nuclei, a well-designed radiofrequency (RF) system with a multi-tuned RF coil is required. However, as the intrinsic sensitivity of non-proton nuclei is lower compared to 1H, it is important to ensure that the signal-to-noise ratio (SNR) of the X-nuclei is as high as possible. This review aims to give a comprehensive overview of previous efforts, with particular focus on the design concept of multi-tuned coils, predominantly for brain applications. In order to guide the readers, the main body of the review is categorised into two parts: state-of-the art according to the single or multiple design structures and emerging technologies. A more detailed description is given in each subsection relating to the specific design approaches of, mostly, double-tuned coils, including using traps, PIN-diodes, nested and metamaterial, together with explanations of their novelties, optimal solutions and trade-offs.
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 Hong, Suk-Min
|0 P:(DE-Juel1)164150
|b 1
|u fzj
700 1 _ |a Felder, Jörg
|0 P:(DE-Juel1)131761
|b 2
|u fzj
700 1 _ |a Shah, N. Jon
|0 P:(DE-Juel1)131794
|b 3
|u fzj
773 _ _ |a 10.1016/j.mri.2020.07.003
|g Vol. 72, p. 103 - 116
|0 PERI:(DE-600)1500646-3
|p 103 - 116
|t Magnetic resonance imaging
|v 72
|y 2020
|x 0730-725X
856 4 _ |u https://juser.fz-juelich.de/record/878074/files/2020_Choi_MRI-2.pdf
856 4 _ |y Published on 2020-07-09. Available in OpenAccess from 2021-07-09.
|u https://juser.fz-juelich.de/record/878074/files/Post_print-2020_Choi_3108.pdf
856 4 _ |x pdfa
|u https://juser.fz-juelich.de/record/878074/files/2020_Choi_MRI-2.pdf?subformat=pdfa
909 C O |o oai:juser.fz-juelich.de:878074
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)164356
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)164150
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)131761
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|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 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2020-01-17
915 _ _ |a Embargoed OpenAccess
|0 StatID:(DE-HGF)0530
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b MAGN RESON IMAGING : 2018
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-01-17
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
|d 2020-01-17
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
|d 2020-01-17
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-01-17
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-01-17
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2020-01-17
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2020-01-17
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-01-17
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-Juel1)VDB1046
|k JARA-BRAIN
|l Jülich-Aachen Research Alliance - Translational Brain Medicine
|x 2
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-Juel1)VDB1046
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21