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Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla

Authors :
Feinberg, David A.
Beckett, Alexander J. S.
Vu, An T.
Stockmann, Jason
Huber, Laurentius
Ma, Samantha
Ahn, Sinyeob
Setsompop, Kawin
Cao, Xiaozhi
Park, Suhyung
Liu, Chunlei
Wald, Lawrence L.
Polimeni, Jonathan R.
Mareyam, Azma
Gruber, Bernhard
Stirnberg, Rüdiger
Liao, Congyu
Yacoub, Essa
Davids, Mathias
Bell, Paul
Rummert, Elmar
Koehler, Michael
Potthast, Andreas
Gonzalez-Insua, Ignacio
Stocker, Stefan
Gunamony, Shajan
Dietz, Peter
Source :
Nature Methods; December 2023, Vol. 20 Issue: 12 p2048-2057, 10p
Publication Year :
2023

Abstract

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m−1, 900 T m−1s−1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35–0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

Details

Language :
English
ISSN :
15487091 and 15487105
Volume :
20
Issue :
12
Database :
Supplemental Index
Journal :
Nature Methods
Publication Type :
Periodical
Accession number :
ejs64712895
Full Text :
https://doi.org/10.1038/s41592-023-02068-7