The sparsity which is implicit in MR images is exploited to significantly undersample k -space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial finite-differences or their wavelet coefficients. According to the recently developed mathematical theory of compressedsensing, images with a sparse representation can be recovered from randomly undersampled k -space data, provided an appropriate nonlinear recovery scheme is used. Intuitively, artifacts due to random undersampling add as noise-like interference. In the sparse transform domain the significant coefficients stand out above the interference. A nonlinear thresholding scheme can recover the sparse coefficients, effectively recovering the image itself. In this article, practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference. Incoherence is introduced by pseudo-random variable-density undersampling of phase-encodes. The reconstruction is performed by minimizing the 1 norm of a transformed image, subject to data

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Sparse MRI: The application of compressed sensing for rapid MR imaging.

In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique.

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Generalized autocalibrating partially parallel acquisitions (GRAPPA).

Functional magnetic resonance imaging (fMRI) is currently the mainstay of neuroimaging in cognitive neuroscience. Advances in scanner technology, image acquisition protocols, experimental design, and analysis methods promise to push forward fMRI from mere cartography to the true study of brain organization. However, fundamental questions concerning the interpretation of fMRI data abound, as the conclusions drawn often ignore the actual limitations of the methodology. Here I give an overview of the current state of fMRI, and draw on neuroimaging and physiological data to present the current understanding of the haemodynamic signals and the constraints they impose on neuroimaging data interpretation.

What we can do and what we cannot do with fMRI

http://pages.stat.wisc.edu/~mchung/teaching/MIA/reading/DTI.alexander.2007.pdf

Diffusion Tensor Imaging of the Brain

This article reviews the requirements for successful compressed sensing (CS), describes their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The authors emphasize on an intuitive understanding of CS by describing the CS reconstruction as a process of interference cancellation. There is also an emphasis on the understanding of the driving factors in applications, including limitations imposed by MRI hardware, by the characteristics of different types of images, and by clinical concerns.

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Compressed Sensing MRI

The invention relates to a method of parallel imaging for obtaining images by means of magnetic resonance (MR). The method includes the simultaneous measurement of sets of MR singals by an array of receiver coils, and the reconstruction of individual receiver coil images from the sets of MR signals. In order to reduce the acquisition time, the distance between adjacent phase encoding lines in k-space is increased, compared to standard Fourier imaging, by a non-integer factor smaller than the number of receiver coils. This undersampling gives rise to aliasing artifacts in the individual receiver coil images. An unaliased final image with the same field of view as in standard Fourier imaging is formed from a combination of the individual receiver coil images whereby account is taken of the mutually different spatial sensitivities of the receiver coils at the positions of voxels which in the receiver coil images become superimposed by aliasing. This requires the solution of a linear equation by means of the generalised inverse of a sensitivity matrix. The reduction of the number of phase encoding lines by a non-integer factor compared to standard Fourier imaging provides that different numbers of voxels become superimposed (by aliasing) in different regions of the receiver coil images. This effect can be exploited to shift residual aliasing artifacts outside the area of interest.

/pdf/sense-sensitivity-encoding-for-fast-mri-3f84cqy5tp.pdf

SENSE: Sensitivity Encoding for fast MRI

Background—MR tissue tagging allows the noninvasive assessment of the locally and temporally resolved motion pattern of the left ventricle. Alterations in cardiac torsion and diastolic relaxation of the left ventricle were studied in patients with aortic stenosis and were compared with those of healthy control subjects and championship rowers with physiological volume-overload hypertrophy. Methods and Results—Twelve aortic stenosis patients, 11 healthy control subjects with normal left ventricular function, and 11 world-championship rowers were investigated for systolic and diastolic heart wall motion on a basal and an apical level of the myocardium. Systolic torsion and untwisting during diastole were examined by use of a novel tagging technique (CSPAMM) that provides access to systolic and diastolic motion data. In the healthy heart, the left ventricle performs a systolic wringing motion, with a counterclockwise rotation at the apex and a clockwise rotation at the base. Apical untwisting precedes diasto...

Alterations in the Local Myocardial Motion Pattern in Patients Suffering From Pressure Overload Due to Aortic Stenosis

Background Diastolic dysfunction with delayed relaxation and abnormal passive elastic properties has been described in patients with severe pressure overload hypertrophy. The purpose of this study was to evaluate the time course of rotational motion of the left ventricle in patients with aortic valve stenosis using myocardial tagging.

Methods Myocardial tagging is a non-invasive method based on magnetic resonance which makes it possible to label (‘tag’) specific myocardial regions. From the motion of the tag’s cardiac rotation, radial displacement and translational motion can be determined. In 12 controls and 13 patients with severe aortic valve stenosis systolic and diastolic wall motion was assessed in an apical and basal short axis plane.

Results The normal left ventricle performs a systolic wringing motion around the ventricular long axis with clockwise rotation at the base (−4·4±1·6°) and counterclockwise rotation at the apex (+6·8±2·5°) when viewed from the apex. During early diastole an untwisting motion can be observed which precedes diastolic filling. In patients with aortic valve stenosis systolic rotation is reduced at the base (−2·4±2·0°; P <0·01) but increased at the apex (+12·0±6·0°; P <0·05). Diastolic untwisting is delayed and prolonged with a decrease in normalized rotation velocity (−6·9±1·1s−1) when compared to controls (−10·7±2·2s−1; P <0·001). Maximal systolic torsion is 8·0±2·1° in controls and 14·1±6·4° ( P <0·01) in patients with aortic valve stenosis.

Conclusions Left ventricular pressure overload hypertrophy is associated with a reduction in basal and an increase in apical rotation resulting in increased torsion of the ventricle. Diastolic untwisting is delayed and prolonged. This may explain the occurrence of diastolic dysfunction in patients with severe pressure overload hypertrophy.

/pdf/cardiac-rotation-and-relaxation-in-patients-with-aortic-6xl80f2qww.pdf

Cardiac rotation and relaxation in patients with aortic valve stenosis

Hemodynamics in the carotid artery bifurcation: a comparison between numerical simulations and in vitro MRI measurements.

LUECHINGER, R., et al.: Force and Torque Effects of a 1.5-Tesla MRI Scanner on Cardiac Pacemakers and ICDs. Magnetic resonance imaging (MRI) is a widely accepted tool for the diagnosis of a variety of disease states. However, the presence of an implanted pacemaker is considered to be a strict contraindication to MRI in a vast majority of centers due to safety concerns. In phantom studies, the authors investigated the force and torque effects of the static magnetic field of MRI on pacemakers and ICDs. Thirty-one pacemakers (15 dual chamber and 16 single chamber units) from eight manufacturers and 13 ICDs from four manufacturers were exposed to the static magnetic field of a 1.5-Tesla MRI scanner. Magnetic force and acceleration measurements were obtained quantitatively, and torque measurements were made qualitatively. For pacemakers, the measured magnetic force was in the range of 0.05–3.60 N. Pacemakers released after 1995 had low magnetic force values as compared to the older devices. For these devices, the measured acceleration was even lower than the gravity of the earth (< 9.81 N/kg). Likewise, the torque levels were significantly reduced in newer generation pacemakers (≤ 2 from a scale of 6). ICD devices, except for one recent model, showed higher force (1.03–5.85 N), acceleration 9.5–34.2 N/kg), and torque (5–6 out of 6) levels. In conclusion, modern pacemakers present no safety risk with respect to magnetic force and torque induced by the static magnetic field of a 1.5-Tesla MRI scanner. However, ICD devices, despite considerable reduction in size and weight, may still pose problems due to strong magnetic force and torque.

Markus B. Scheidegger

Papers

SENSE: Sensitivity Encoding for fast MRI

Alterations in the Local Myocardial Motion Pattern in Patients Suffering From Pressure Overload Due to Aortic Stenosis

Cardiac rotation and relaxation in patients with aortic valve stenosis

Hemodynamics in the carotid artery bifurcation: a comparison between numerical simulations and in vitro MRI measurements.

Force and torque effects of a 1.5-Tesla MRI scanner on cardiac pacemakers and ICDs.