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Register a new userActive split-ring metamaterial slabs for magnetic resonance imaging
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In this work, it is analyzed the ability of split-ring metamaterial slabs with zero/high permeability to reject/confine the radiofrequency magnetic field in magnetic resonance imaging systems. Using an homogenization procedure, split-ring slabs have been designed and fabricated to work in a 1.5T system. Active elements consisting of pairs of crossed diodes are inserted in the split-rings. With these elements, the permeability of the slabs can be automatically switched between a unity value when interacting with the strong excitation field of the transmitting body coil, and zero or high values when interacting with the weak field produced by protons in tissue. Experiments are shown for different configurations where these slabs can help to locally increase the signal-to-noise-ratio.
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Parallel magnetic resonance imaging (MRI) is a technique of image acceleration which takes advantage of the localization of the field of view (FOV) of coils in an array. In this letter we show that metamaterial lenses based on capacitively-loaded rings can provide higher localization of the FOV. Several lens designs are systematically analyzed in order to find the structure providing higher signal-to-noise-ratio. The magnetoinductive (MI) lens is find to be the optimum structure and an experiment is developed to show it. The ability of the fabricated MI lenses to accelerate the image is quantified by means of the parameter known in the MRI community as g-factor.
Auxetics refers to structures or materials with a negative Poissons ratio, thereby capable of exhibiting counter-intuitive behaviors. Herein, auxetic structures are exploited to design mechanically tunable metamaterials in both planar and hemispherical configurations operating at megahertz (MHz) frequencies, optimized for their application to magnetic resonance imaging (MRI). Specially, the reported tunable metamaterials are composed of arrays of inter-jointed unit cells featuring metallic helices, enabling auxetic patterns with a negative Poissons ratio. The deployable deformation of the metamaterials yields an added degree of freedom with respect to frequency tunability through the resultant modification of the electromagnetic interactions between unit cells. The metamaterials are fabricated using 3D printing technology and a ~20 MHz frequency shift of the resonance mode is enabled during deformation. Experimental validation is performed in a clinical (3.0 Tesla) MRI, demonstrating that the metamaterials enable a marked boost in radiofrequency (RF) field strength under resonance matched conditions, ultimately yielding a dramatic increase in the signal-to-noise ratio (SNR) (~ 4.5X) of MRI. The tunable metamaterials presented herein offer a novel pathway towards the practical utilization of metamaterials in MRI, as well as a range of other emerging applications.
Over almost five decades of development and improvement, Magnetic Resonance Imaging (MRI) has become a rich and powerful, non-invasive technique in medical imaging, yet not reaching its physical limits. Technical and physiological restrictions constrain physically feasible developments. A common solution to improve imaging speed and resolution is to use higher field strengths, which also has subtle and potentially harmful implications. However, patient safety is to be considered utterly important at all stages of research and clinical routine. Here we show that dynamic metamaterials are a promising solution to expand the potential of MRI and to overcome some limitations. A thin, smart, non-linear metamaterial is presented that enhances the imaging performance and increases the signal-to-noise ratio in 3T MRI significantly (up to eightfold), whilst the transmit field is not affected due to self-detuning and, thus, patient safety is also assured. This self-detuning works without introducing any additional overhead related to MRI-compatible electronic control components or active (de-)tuning mechanisms. The design paradigm, simulation results, on-bench characterization, and MRI experiments using homogeneous and structural phantoms are described. The suggested single-layer metasurface paves the way for conformal and patient-specific manufacturing, which was not possible before due to typically bulky and rigid metamaterial structures.
Nuclear magnetic resonance (NMR) diffusion measurements are widely used to derive parameters indirectly related to the microstructure of biological tissues and porous media. However, a direct imaging of cell or pore shapes and sizes would be of high interest. For a long time, determining pore shapes by NMR diffusion acquisitions seemed impossible, because the necessary phase information could not be preserved. Here we demonstrate experimentally using the measurement technique which we have recently proposed theoretically that the shape of arbitrary closed pores can be imaged by diffusion acquisitions, which yield the phase information. For this purpose, we use hyperpolarized xenon gas in well-defined geometries. The signal can be collected from the whole sample which mainly eliminates the problem of vanishing signal at increasing resolution of conventional NMR imaging. This could be used to non-invasively gain structural information inaccessible so far such as pore or cell shapes, cell density or axon integrity.
Modern reconstruction methods for magnetic resonance imaging (MRI) exploit the spatially varying sensitivity profiles of receive-coil arrays as additional source of information. This allows to reduce the number of time-consuming Fourier-encoding steps by undersampling. The receive sensitivities are a priori unknown and influenced by geometry and electric properties of the (moving) subject. For optimal results, they need to be estimated jointly with the image from the same undersampled measurement data. Formulated as an inverse problem, this leads to a bilinear reconstruction problem related to multi-channel blind deconvolution. In this work, we will discuss some recently developed approaches for the solution of this problem.
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