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NIHOFFICE OF THE DIRECTOR, NATIONAL INSTITUTES OF HEALTH

High Performance Gradient System for Advanced MRI Neuroimaging

Completed
Institution
INDIANA UNIVERSITY INDIANAPOLIS, IN
Principal investigator
Yu-Chien Wu
Funding
$1.7M
Duration
2025–2026
Open portfolio

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Still being scored

Abstract

Project Abstract We request funds to upgrade our current Siemens MAGNETOM Prisma 3T MRI scanner (installed in 2014) to the Siemens MAGNETOM Cima.X Fit 3T MRI scanner. The Cima.X Fit scanner is a commercialized connectome scanner, designed for advanced neuroimaging, with a gradient system of 200 mT/m, whose prototypes were developed by Siemens Healthineers in collaboration with Massachusetts General Hospital, Cardiff University, and the Max Planck Institute for the human connectome project (HCP). Our request for an MRI system upgrade is driven by the need for advanced diffusion imaging techniques to probe brain and other tissue microstructures with greater detail and specificity and the need to leverage AI-assisted fast imaging. The gradient strength limitations of our current Prisma scanner prevent us from pursuing cutting-edge diffusion microstructural imaging. Over 90% of our projects utilize diffusion-weighted MRI. Building on our strong and well-funded neuroimaging program, the high-performance gradient system will elevate our research capabilities by enabling the bench-to-bedside translation of high-resolution and advanced diffusion MRI technologies that are unavailable to us now. The high-performance gradient system will allow us to move beyond conventional diffusion tensor imaging (DTI) with non-specific metrics and apply biologically specific metrics (e.g., soma fraction, neurite density, and axonal diameter) to our large clinical populations. This will enhance our translational science by further bridging the gap between basic neuroscience research on our preclinical small animal 9.4T MRI scanner and human imaging studies. In addition, the current MRI pulse sequence software has become obsolete, preventing us from applying advanced fast imaging technologies using compressed sensing and AI-assisted reconstruction. Fast imaging improves all our imaging studies (including neuro and body imaging), and shorter scan times, while maintaining image quality, will markedly reduce the participant burden. This is particularly important for neonates, older adults, and other clinical populations who may have difficulty tolerating longer scans.

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OFFICE OF THE DIRECTOR, NATIONAL INSTITUTES OF HEALTHS10Special Emphasis Panel[ZRG1 ISB-Z (31)]scannergradientdiffusionconnectomeai-assistedclinical populationsupgrademri

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