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

David A Feinberg*, Alexander J S Beckett, An T Vu, Jason Stockmann, Laurentius Huber, Samantha Ma, Sinyeob Ahn, Kawin Setsompop, Xiaozhi Cao, Suhyung Park, Chunlei Liu, Lawrence L Wald, Jonathan R Polimeni, Azma Mareyam, Bernhard Gruber, Rüdiger Stirnberg, Congyu Liao, Essa Yacoub, Mathias Davids, Paul BellElmar Rummert, Michael Koehler, Andreas Potthast, Ignacio Gonzalez-Insua, Stefan Stocker, Shajan Gunamony, Peter Dietz

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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 , 900?T?m s ) 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.
Original languageEnglish
Pages (from-to)2048–2057
Number of pages10
JournalNature Methods
Volume20
Issue number12
Early online date27 Nov 2023
DOIs
Publication statusPublished - Dec 2023

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