New coil to make magnetic resonance (MR) imaging easier

Oxford University researchers have devised a novel coil design for magnetic resonance (MR) application, devised specifically for deep organ MR where sensitive imaging and spectroscopy have been previously difficult.

Deep organ magnetic resonance requires maximised sensitivity and magnetic field homogeneity over a relatively large field of view (FOV). However, it is difficult to maximise both sensitivity and magnetic field homogeneity simultaneously. The sensitivity can be maximised by reducing the coil volume, but this minimises the magnetic field homogeneity. Conversely, the magnetic field homogeneity can be maximised by increasing the coil volume, but this minimises sensitivity.

The conventional approach to addressing the problem of sensitivity and homogeneity balance utilises the Phased-Coil array. The Phased-Coil array consists of closely packed surface coils that offer both the sensitivity of a surface coil and the large FOV benefit of a volume coil. This approach, however, requires a separate RF transmitter coil and MR scanner with multiple receiver channels, thereby significantly increasing both the complexity and cost of use.

The Oxford researchers have addressed these problems by designing an RF coil that is appropriate for deep organ applications like cardiac MR without greatly increasing the complexity and cost of the MR scanner itself. The coil has been devised to increase the available ‘sweet spot’ of the coil to deep-lying regions of interest, facilitating imaging and spectroscopy of elements deep within the subject of interest. The coil can be used in MR scanners that are only equipped to use a single coil, and because the coil is suitable for both imaging and spectroscopy, the dual functionality makes its use more cost effective.

Isis Innovation, Oxford University’s technology transfer company, has filed a patent application for this technology and welcomes contact from companies interested in commercially developing this novel coil design in MR applications.

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