Nature Methods
Nature Methods
10 months ago

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

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 Bell, Elmar Rummert, Michael Koehler, Andreas Potthast, Ignacio Gonzalez-Insua, Stefan Stocker, Shajan Gunamony, Peter Dietz
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.

Publisher URL: https://www.nature.com/articles/s41592-023-02068-7

Open URL: https://www.nature.com/articles/s41592-023-02068-7.pdf

DOI: 10.1038/s41592-023-02068-7

Open access
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