NMR in biomedicine
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In MRI, structurally aligned molecular or micro-organization (e.g. axonal fibers) can be a source of substantial signal variations that depend on the structural orientation and the applied magnetic field. This signal anisotropy gives us a unique opportunity to explore information that exists at a resolution several orders of magnitude smaller than that of typical MRI. In this review, one of the signal anisotropies, T2 * anisotropy in white matter, and a related imaging method, gradient echo myelin water imaging (GRE-MWI), are explored. ⋯ The GRE-MWI method has been further improved by signal compensation techniques including physiological noise compensation schemes. The T2 * anisotropy and GRE-MWI provide microstructural information on a voxel (e.g. fiber orientation and tissue composition), and may serve as sensitive biomarkers for microstructural changes in the brain. Copyright © 2016 John Wiley & Sons, Ltd.
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Sophisticated harmonic artifact reduction for phase data (SHARP) is a method to remove background field contributions in MRI phase images, which is an essential processing step for quantitative susceptibility mapping (QSM). To perform SHARP, a spherical kernel radius and a regularization parameter need to be defined. In this study, we carried out an extensive analysis of the effect of these two parameters on the corrected phase images and on the reconstructed susceptibility maps. ⋯ We demonstrated and confirmed the new parameter scheme in vivo. The novel regularization scheme allows the use of the same regularization parameter irrespective of other imaging parameters, such as image resolution. Copyright © 2016 John Wiley & Sons, Ltd.
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Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. ⋯ In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.
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The magnetism of hemoglobin - being paramagnetic in its deoxy and diamagnetic in its oxy state - offers unique opportunities to probe oxygen metabolism in blood and tissues. The magnetic susceptibility χ of blood scales linearly with blood oxygen saturation, which can be obtained by measuring the magnetic field ΔB of the intravascular MR signal relative to tissue. In contrast to χ, the induced field ΔB is non-local. ⋯ Applications of susceptometry-based oximetry to studies of metabolic and degenerative disorders of the brain are reviewed. Lastly, the technique is shown to be applicable to other organ systems such as the extremities using SvO2 as a dynamic tracer to monitor the kinetics of the microvascular response to induced ischemia. Copyright © 2016 John Wiley & Sons, Ltd.
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Review Comparative Study
Computational methods for image reconstruction.
Reconstructing images from indirect measurements is a central problem in many applications, including the subject of this special issue, quantitative susceptibility mapping (QSM). The process of image reconstruction typically requires solving an inverse problem that is ill-posed and large-scale and thus challenging to solve. Although the research field of inverse problems is thriving and very active with diverse applications, in this part of the special issue we will focus on recent advances in inverse problems that are specific to deconvolution problems, the class of problems to which QSM belongs. ⋯ We will discuss state-of-the-art computational tools and methods for image reconstruction, including regularization approaches and regularization parameter selection methods. We finish by outlining some of the current trends and future challenges. Copyright © 2016 John Wiley & Sons, Ltd.