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Abstract #1336

Imaging at 400 mT/m with next-generation gradient driver technology on a high-performance gradient platform.

Nastaren Abad1, Eric Fiveland1, John Hotaling1, Anil Kumar Reddy Siddavatam1, Rohail Hassan1, Seung-Kyun Lee1, Eric Budesheim1, Ante Zhu1, Justin Ricci1, Melissa Freeman2, Jason Stich2, Andrew Panos2, Saban Kurucay2, Logan Snow3, Teck Beng Desmond Yeo1, and Thomas K.F. Foo1
1GE HealthCare, Technology & Innovation Center, Niskayuna, NY, United States, 2GE HealthCare, Waukesha, WI, United States, 3Advanced Research, GE Vernova, Niskayuna, NY, United States

Synopsis

Keywords: Hybrid & Novel Systems Technology, Gradients, Gradient Driver Technology, High performance MRI gradients, High performance Neuroimaging, Neuroimaging

Motivation: To push the technology envelope in advanced brain structural and functional imaging by increasing the performance of an investigational MAGNUS platform to ≥400 mT/m with a 3-MVA SiC gradient driver.

Goal(s): To demonstrate the technical feasibility of improving gradient performance using advanced SiC semiconductor MOSFET gradient driver architecture, without any gradient coil redesign.

Approach: Integrate the high efficiency head only MAGNUS gradient with next generation SiC advanced gradient driver topology and evaluate technical performance.

Results: Demonstration of high command waveform fidelity, quality assurance phantom testing and in-vivo human scanning with diffusion MRI at high resolution (0.8-mm) and ultra-high b-values (30,000 s/mm2) with TE(s)<50ms.

Impact: Cumulative gains from gradient coil design and gradient driver topology enable imaging of the mesoscale, with increased sensitivity in estimation of elusive contrasts such as slow-flow characterization of neuro-fluids, effective intra-axonal radii, and time-dependent diffusivities.

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Keywords