Temporal SNR optimization through RF coil combination in fMRI: The more, the better?

For functional MRI with a multi-channel receiver RF coil, images are often reconstructed channel by channel, resulting into multiple images per time frame. The final image to analyze usually is the result of the covariance Sum-of-Squares (covSoS) combination across these channels. Although this reco...

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Autores principales:	Redouane Jamil, Franck Mauconduit, Caroline Le Ster, Philipp Ehses, Benedikt A Poser, Alexandre Vignaud, Nicolas Boulant
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a7bdddb9e6754565bdf0b345cf64cad3
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spelling	oai:doaj.org-article:a7bdddb9e6754565bdf0b345cf64cad32021-12-02T20:05:58ZTemporal SNR optimization through RF coil combination in fMRI: The more, the better?1932-620310.1371/journal.pone.0259592https://doaj.org/article/a7bdddb9e6754565bdf0b345cf64cad32021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0259592https://doaj.org/toc/1932-6203For functional MRI with a multi-channel receiver RF coil, images are often reconstructed channel by channel, resulting into multiple images per time frame. The final image to analyze usually is the result of the covariance Sum-of-Squares (covSoS) combination across these channels. Although this reconstruction is quasi-optimal in SNR, it is not necessarily the case in terms of temporal SNR (tSNR) of the time series, which is yet a more relevant metric for fMRI data quality. In this work, we investigated tSNR optimality through voxel-wise RF coil combination and its effects on BOLD sensitivity. An analytical solution for an optimal RF coil combination is described, which is somewhat tied to the extended Krueger-Glover model involving both thermal and physiological noise covariance matrices. Compared experimentally to covSOS on four volunteers at 7T, the method yielded great improvement of tSNR but, surprisingly, did not result into higher BOLD sensitivity. Solutions to improve the method such as for example the t-score for the mean recently proposed are also explored, but result into similar observations once the statistics are corrected properly. Overall, the work shows that data-driven RF coil combinations based on tSNR considerations alone should be avoided unless additional and unbiased assumptions can be made.Redouane JamilFranck MauconduitCaroline Le SterPhilipp EhsesBenedikt A PoserAlexandre VignaudNicolas BoulantPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0259592 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Redouane Jamil Franck Mauconduit Caroline Le Ster Philipp Ehses Benedikt A Poser Alexandre Vignaud Nicolas Boulant Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
description	For functional MRI with a multi-channel receiver RF coil, images are often reconstructed channel by channel, resulting into multiple images per time frame. The final image to analyze usually is the result of the covariance Sum-of-Squares (covSoS) combination across these channels. Although this reconstruction is quasi-optimal in SNR, it is not necessarily the case in terms of temporal SNR (tSNR) of the time series, which is yet a more relevant metric for fMRI data quality. In this work, we investigated tSNR optimality through voxel-wise RF coil combination and its effects on BOLD sensitivity. An analytical solution for an optimal RF coil combination is described, which is somewhat tied to the extended Krueger-Glover model involving both thermal and physiological noise covariance matrices. Compared experimentally to covSOS on four volunteers at 7T, the method yielded great improvement of tSNR but, surprisingly, did not result into higher BOLD sensitivity. Solutions to improve the method such as for example the t-score for the mean recently proposed are also explored, but result into similar observations once the statistics are corrected properly. Overall, the work shows that data-driven RF coil combinations based on tSNR considerations alone should be avoided unless additional and unbiased assumptions can be made.
format	article
author	Redouane Jamil Franck Mauconduit Caroline Le Ster Philipp Ehses Benedikt A Poser Alexandre Vignaud Nicolas Boulant
author_facet	Redouane Jamil Franck Mauconduit Caroline Le Ster Philipp Ehses Benedikt A Poser Alexandre Vignaud Nicolas Boulant
author_sort	Redouane Jamil
title	Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
title_short	Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
title_full	Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
title_fullStr	Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
title_full_unstemmed	Temporal SNR optimization through RF coil combination in fMRI: The more, the better?
title_sort	temporal snr optimization through rf coil combination in fmri: the more, the better?
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a7bdddb9e6754565bdf0b345cf64cad3
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Temporal SNR optimization through RF coil combination in fMRI: The more, the better?

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