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Pushing boundaries of medical imaging with 10.5 Tesla MR

por Gus Iversen, Editor in Chief | September 10, 2018
From the September 2018 issue of HealthCare Business News magazine

HCB News: Are there specific biomedical applications or indications/diseases for which you can see 10.5 T MR offering clear benefits and perhaps justifying the arrival of such a powerful magnet on the clinical, commercial level?

There are many potential advantages accompanying the increase in static field strength to 10.5 T that justify further developing the technology and assessing its safety for human investigations. First, it has been shown that sensitivity, as measured by the signal-to-noise ratio (SNR), scales supralinearly with the field strength. While acquisition and anatomy-specific relaxation effects need to be accounted for, this underlying increase in SNR plays an important role in the overall benefits expected from 10.5 T compared to lower field strengths.

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Beyond the increase in SNR, other advantages include increasing susceptibility-based contrast for improved anatomic and functional imaging, increased chemical shift dispersion for improved spectroscopic quantification, shifting exchange to faster regimes for improved chemical exchange saturation transfer (CEST) studies, and increased longitudinal relation times for improved non-contrast-enhanced arterial spin-labeled (ASL) perfusion and in-flow angiography.

The passive shielding for the 10.5 Tesla scanner
required 600 tons of iron.
One of the initial motivations pushing the development of the 10.5 T scanner was the drive to image functional structures in the brain with increasing spatial resolution and fidelity. Accomplishing this with functional magnetic resonance imaging (fMRI) would provide unprecedented access to small (submillimeter) organizations critical in function of the brain, such as cortical layers and so called cortical columns that represent elementary computational units. With significant developments in auxiliary technologies that exploit the 10.5 T field strength, which we are currently undertaking, we expect to obtain functional images that span elementary computational units to whole brain coverage.

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