Efficiently building receive arrays with electromagnetic simulations and additive manufacturing: A two-layer, 32-channel prototype for 7T brain MRI.

additive manufacturing coil electromagnetic receive array ultrahigh field

Journal

Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245

Informations de publication

Date de publication:
20 Nov 2023
Historique:
revised: 26 10 2023
received: 18 04 2023
accepted: 30 10 2023
medline: 21 11 2023
pubmed: 21 11 2023
entrez: 21 11 2023
Statut: aheadofprint

Résumé

We propose a comprehensive workflow to design and build fully customized dense receive arrays for MRI, providing prediction of SNR and g-factor. Combined with additive manufacturing, this method allows an efficient implementation for any arbitrary loop configuration. To demonstrate the methodology, an innovative two-layer, 32-channel receive array is proposed. The design workflow is based on numerical simulations using a commercial 3D electromagnetic software associated with circuit model co-simulations to provide the most accurate results in an efficient time. A model to compute the noise covariance matrix from circuit model scattering parameters is proposed. A 32-channel receive array at 7 T is simulated and fabricated with a two-layer design made of non-geometrically decoupled loops. Decoupling between loops is achieved using home-built direct high-impedance preamplifiers. The loops are 3D-printed with a new additive manufacturing technique to speed up integration while preserving the detailed geometry as simulated. The SNR and parallel-imaging performances of the proposed design are compared with a commercial coil, and in vivo images are acquired. The comparison of SNR and g-factors showed a good agreement between simulations and measurements. Experimental values are comparable with the ones measured on the commercial coil. Preliminary in vivo images also ensured the absence of any unexpected artifacts. A new design and performance analysis workflow is proposed and tested with a non-conventional 32-channel prototype at 7 T. Additive manufacturing of dense arrays of loops for brain imaging at ultrahigh field is validated for clinical use.

Identifiants

pubmed: 37986237
doi: 10.1002/mrm.29931
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Aix-Marseille University
ID : A*MIDEX
Organisme : M-ONE project, EU grant
ID : 952106
Organisme : Leducq Foundation
ID : NEUROVASC7T
Organisme : ANRTCIFRE
ID : 2019/1553

Informations de copyright

© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

Références

Roemer PB, Edelstein WA, Hayes CE, Souza SP, Mueller OM. The NMR phased array. Magn Reson Med. 1990;16:192-225. doi:10.1002/mrm.1910160203
Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 1999;42:952-962.
Griswold MA, Jakob PM, Heidemann RM, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47:1202-1210. doi:10.1002/mrm.10171
FDA clears first 7T magnetic resonance imaging device. https://www.fda.gov/news-events/press-announcements/fda-clears-first-7t-magnetic-resonance-imaging-device (accessed March 22, 2018)
Siemens 7T MRI gets CE mark for clinical use. https://www.auntminnieeurope.com/index.aspx?sec=ser&sub=def&pag=dis&ItemID=614794. (accessed May 1, 2023).
Le Ster C, Grant A, Van de Moortele PF, et al. Magnetic field strength dependent SNR gain at the center of a spherical phantom and up to 11.7T. Magn Reson Med. 2022;88:2131-2138. doi:10.1002/mrm.29391
Park JE, Cheong EN, Jung DE, Shim WH, Lee JS. Utility of 7 tesla magnetic resonance imaging in patients with epilepsy: a systematic review and meta-analysis. Front Neurol. 2021;12:1-11. doi:10.3389/fneur.2021.621936
Beisteiner R, Robinson S, Wurnig M, et al. Clinical fMRI: evidence for a 7T benefit over 3T. Neuroimage. 2011;57:1015-1021. doi:10.1016/j.neuroimage.2011.05.010
Trattnig S, Springer E, Bogner W, et al. Key clinical benefits of neuroimaging at 7T. Neuroimage. 2018;168:477-489. doi:10.1016/j.neuroimage.2016.11.031
Ugurbil K, Auerbach E, Moeller S, et al. Brain imaging with improved acceleration and SNR at 7 tesla obtained with 64-channel receive array. Magn Reson Med. 2019;82:495-509. doi:10.1002/mrm.27695
Gruber B, Stockmann JP, Mareyam A, Ghotra A, Feinberg DA, Wald LL. A 128-channel head coil array for cortical imaging at 7 tesla. In: Proceedings of the 29th Annual Meeting of ISMRM [Virtual]. 2021. Abstract #0176
Clément J, Gruetter R, Ipek Ö. A combined 32-channel receive-loops/8-channel transmit-dipoles coil array for whole-brain MR imaging at 7T. Magn Reson Med. 2019;82:1229-1241. doi:10.1002/mrm.27808
Avdievich NI, Nikulin AV, Ruhm L, et al. A 32-element loop/dipole hybrid array for human head imaging at 7 T. Magn Reson Med. 2022;88:1926. doi:10.1002/mrm.29347
Gilbert KM, Klassen LM, Mashkovtsev A, Zeman P, Menon RS, Gati JS. Radiofrequency coil for routine ultra-high-field imaging with an unobstructed visual field. NMR Biomed. 2021;34:e4457. doi:10.1002/nbm.4457
Reykowski A, Saylor C, Duensing GR. Do we need preamplifier decoupling? In: Proceedings of the 19th Annual Meeting of ISMRM, Montréal, Canada. 2011. Abstract #3883
Keil B, Wald LL. Massively parallel MRI detector arrays. J Magn Reson. 2013;229:75-89. doi:10.1016/j.jmr.2013.02.001
Reykowski A, Wright SM, Porter JR. Design of Matching Networks for low noise preamplifiers. Magn Reson Med. 1995;33:848-852. doi:10.1002/mrm.1910330617
Wang W, Zhurbenko V, Sánchez-Heredia JD, Ardenkjaer-Larsen JH. Three-element matching networks for receive-only MRI coil decoupling. Magn Reson Med. 2021;85:544-550. doi:10.1002/mrm.28416
Fujita H, Zheng T, Yang X, Finnerty MJ, Handa S. RF surface receive Array coils: the art of an LC circuit: RF surface receive Array coils. J Magn Reson Imaging. 2013;38:12-25. doi:10.1002/jmri.24159
Cao X, Fischer E, Hennig J, Zaitsev M. Direct matching methods for coils and preamplifiers in MRI. J Magn Reson. 2018;290:85-91. doi:10.1016/j.jmr.2018.03.009
Wang W, Zhurbenko V, Sánchez-Heredia JD, Ardenkjaer-Larsen JH. Trade-off between preamplifier noise figure and decoupling in MRI detectors. Magn Reson Med. 2023;89:859-871. doi:10.1002/mrm.29489
Pozar DM. Microwave Engineering. 4th ed. Wiley; 2012.
Lu M, Zhang B, Gore JC, Yan X. Analysis of preampli er decoupling e ect in MRI coil array with electromagnetic eld and RF circuit co-simulation. In: Proceedings of the 30th Annual Meeting of ISMRM. [Virtual] 2021 Abstract 1412.
Kozlov M, Turner R. Fast MRI coil analysis based on 3-D electromagnetic and RF circuit co-simulation. J Magn Reson. 2009;200:147-152. doi:10.1016/j.jmr.2009.06.005
Beqiri A, Hand JW, Hajnal JV, Malik SJ. Comparison between simulated decoupling regimes for specific absorption rate prediction in parallel transmit MRI. Magn Reson Med. 2015;74:1423-1434. doi:10.1002/mrm.25504
Stumpf C, Malzacher M, Schmidt LP. Radio frequency modeling of receive coil arrays for magnetic resonance imaging. J Imaging. 2018;4:67. doi:10.3390/jimaging4050067
Guschlbauer R, Arumskog P, Eichler S. Electron beam melting of pure copper-from research to industrialization. In: Proceedings of the 2020 IEEE 21st International Conference on Vacuum Electronics (IVEC). 2020. p. 89-90. doi:10.1109/IVEC45766.2020.9520506
Lodes MA, Guschlbauer R, Korner C. Process development for the manufacturing of 99.94% pure copper via selective electron beam melting. Mater Lett. 2015;143:298-301. doi:10.1016/j.matlet.2014.12.105
Lassegue P, Salvan C, De Vito E, et al. Laser powder bed fusion (L-PBF) of Cu and CuCrZr parts: influence of an absorptive physical vapor deposition (PVD) coating on the printing process. Addit Manuf. 2021;39:101888. doi:10.1016/j.addma.2021.101888
Vanduffel H, Parra-Cabrera C, Gsell W, et al. Additive manufacturing of subject-conformal receive coils for magnetic resonance imaging. Adv Mater Technol. 2022;7:2200647. doi:10.1002/admt.202200647
Schildknecht CM, Pruessmann KP. Additive manufacturing of MRI coils by printing and electroplating a conductive polymer. In: Proceedings of the 30th Annual Meeting of ISMRM [Virtual]. 2021. Abstract #1600
Zamarayeva AM, Gopalan K, Corea JR, et al. Custom, spray coated receive coils for magnetic resonance imaging. Sci Rep. 2021;11:2635. doi:10.1038/s41598-021-81833-0
Behzadnezhad B, Collick BD, Behdad N, McMillan AB. Dielectric properties of 3D-printed materials for anatomy specific 3D-printed MRI coils. J Magn Reson. 2018;289:113-121. doi:10.1016/j.jmr.2018.02.013
Kumar A, Edelstein WA, Bottomley PA. Noise figure limits for circular loop MR coils. Magn Reson Med. 2009;61:1201-1209. doi:10.1002/mrm.21948
Vergara TS, Dubois M, Rustomji K, et al. Hilbert fractal inspired dipoles for passive RF shimming in ultra-high field MRI. Photonics Nanostruc Fundam Appl. 2022;48:100988. doi:10.1016/j.photonics.2021.100988
Raolison Z, Dubois M, Luong M, et al. Evaluation of new MR invisible silicon carbide based dielectric pads for 7 T MRI. Magn Reson Imaging. 2022;90:37-43. doi:10.1016/j.mri.2022.04.002
Knowles. Non-magnetic capacitors, 1111 series. https://www.knowlescapacitors.com/getattachment/70d267f3-1950-40f6-8a8c-6aa7b1594725/High-Q (accessed February 01, 2023)
Hoult DI. The principle of reciprocity in signal strength calculations-a mathematical guide. Concepts Magn Res. 2000;12:173-187. doi:10.1002/1099-0534(2000)12:4<173::AID-CMR1>3.0.CO;2-Q
Neiman MS. The principle of reciprocity in antenna theory. Proc IRE. 1943;31:666-671. doi:10.1109/JRPROC.1943.233683
Bosma H. On the theory of linear noisy systems. Eindhoven University of Technology. 1967. doi:10.6100/IR109175
Findeklee C. Array noise matching via the scattering matrix. IEEE Trans Antennas Propag. 2019;67:2344-2353. doi:10.1109/TAP.2019.2893229
Seeber DA, Jevtic J, Menon A. A floating shield current suppression trap. Concepts Magn Reson Part B Magn Reson Eng. 2004;21B:26-31. doi:10.1002/cmr.b.20008
Mispelter J. NMR Probeheads for Biophysical and Biomedical Experiments: Theoretical Principles & Practical Guidelines. Imperial College Press; 2006.
United States National Bureau of Standards. Copper wire tables. Government Printing Office, Washington DC. 1914.
Ianniello C, de Zwart JA, Duan Q, et al. Synthesized tissue-equivalent dielectric phantoms using salt and polyvinylpyrrolidone solutions. Magn Reson Med. 2018;80:413-419. doi:10.1002/mrm.27005
Amadon A, Mauconduit F, Vignaud A, Boulant N. Slice profile corrections in the XFL (magnetization-prepared turbo-FLASH) B1-mapping sequence. Proceedings of the 23rd Annual Meeting of ISMRM, Toronto, Canada. 2015. Abstract #2377
Kellman P, McVeigh ER. Image reconstruction in SNR units: a general method for SNR measurement. Magn Reson Med. 2005;54:1439-1447. doi:10.1002/mrm.20713
Vignaud A, Mauconduit F, Gras V, et al. Fast and unconditionally safe in vivo MR head protocol for home-made coil prototype assessment at 7T. J Phys Conf Ser. 2018;1092:012159. doi:10.1088/1742-6596/1092/1/012159
Dudysheva N, Boulant N, Vignaud A, Mauconduit F. New “restricted SAR mode” definition based on a thermal conservative model for relaxed unconditional safe in vivo experiments. In: Proceedings of the 31st Annual Meeting of ISMRM, London, UK. 2022 Abstract #2550.
Redpath TW. Noise correlation in multicoil receiver systems. Magn Reson Med. 1992;24:85-89. doi:10.1002/mrm.1910240109
Brown R, Wang Y, Spincemaille P, Lee RF. On the noise correlation matrix for multiple radio frequency coils. Magn Reson Med. 2007;58:213-437. doi:10.1002/mrm.21324
Maunder A, Fallone BG, Daneshmand M, De Zanche N. Experimental verification of SNR and parallel imaging improvements using composite arrays. NMR Biomed. 2015;28:141-153. doi:10.1002/nbm.3230
Findeklee C, Oliver L, Peter V, Christoph L, Randy D. Preamp decoupling improves SNR and the earth is flat. In: Proceedings of the 27th Annual Conference of ISMRM. Montréal, Canada 2019. Abstract #0563
Ohliger MA, Ledden P, McKenzie CA, Sodickson DK. Effects of inductive coupling on parallel MR image reconstructions. Magn Reson Med. 2004;52:628-639. doi:10.1002/mrm.20195

Auteurs

Paul-François Gapais (PF)

Université Paris-Saclay, CEA, CNRS, Joliot, NeuroSpin, BAOBAB, Gif-sur-Yvette, France.
Multiwave Imaging SAS, Marseille, France.

Michel Luong (M)

Université Paris-Saclay, CEA, Irfu, DACM, Gif-sur-Yvette, France.

François Nizery (F)

Université Paris-Saclay, CEA, Irfu, LCAP, Gif-sur-Yvette, France.

Gabriel Maitre (G)

Université Paris-Saclay, CEA, Irfu, LCAP, Gif-sur-Yvette, France.

Eric Giacomini (E)

Université Paris-Saclay, CEA, CNRS, Joliot, NeuroSpin, BAOBAB, Gif-sur-Yvette, France.

Jules Guillot (J)

Université Paris-Saclay, CEA, CNRS, Joliot, NeuroSpin, BAOBAB, Gif-sur-Yvette, France.

Alexandre Vignaud (A)

Université Paris-Saclay, CEA, CNRS, Joliot, NeuroSpin, BAOBAB, Gif-sur-Yvette, France.

Djamel Berrahou (D)

Multiwave Imaging SAS, Marseille, France.

Marc Dubois (M)

Multiwave Imaging SAS, Marseille, France.

Redha Abdeddaim (R)

Aix-Marseille Université, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France.

Elodie Georget (E)

Multiwave Imaging SAS, Marseille, France.

Sajad Hosseinnezhadian (S)

Multiwave Imaging SAS, Marseille, France.

Alexis Amadon (A)

Université Paris-Saclay, CEA, CNRS, Joliot, NeuroSpin, BAOBAB, Gif-sur-Yvette, France.

Classifications MeSH