Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

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.

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.

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SENSE: Sensitivity Encoding for fast MRI

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

Over the past few decades, daily exposure to radiofrequency (RF) fields has been increasing due to the rapid development of wireless and medical imaging technologies. Under extreme circumstances, exposure to very strong RF energy can lead to heating of body tissue, even resulting in tissue injury. The presence of implanted devices, moreover, can amplify RF effects on surrounding tissue. Therefore, it is important to understand the interactions of RF fields with tissue in the presence of implants, in order to establish appropriate wireless safety protocols, and also to extend the benefits of medical imaging to increasing numbers of people with implanted medical devices. This study explored the neurological effects of RF exposure in rodents implanted with neuronal recording electrodes. We exposed freely moving and anesthetized rats and mice to 950 MHz RF energy while monitoring their brain activity, temperature, and behavior. We found that RF exposure could induce fast onset firing of single neurons without heat injury. In addition, brain implants enhanced the effect of RF stimulation resulting in reversible behavioral changes. Using an optical temperature measurement system, we found greater than tenfold increase in brain temperature in the vicinity of the implant. On the one hand, our results underline the importance of careful safety assessment for brain implanted devices, but on the other hand, we also show that metal implants may be used for neurostimulation if brain temperature can be kept within safe limits.

Brain-implanted conductors amplify radiofrequency fields in rodents: advantages and risks

In accordance with certain exemplary embodiments of the present disclosure, provided herein are apparatus, systems and methods for, e.g., facilitating signal excitation and/or reception in a magnetic resonance system, such as, e.g., a system configured for magnetic resonance imaging (MRI) and/or spectroscopy. For example, exemplary embodiments of a method for traveling wave imaging in an MRI system can include, e.g., a circular conductive structure lying in a transverse plane within the scanner bore. The exemplary structure can be concentric with the center of the scanner RF shield. The structure can be arranged to have a resonant mode at the MR frequency characterized by a current pattern which can be configured to excite and receive an exemplary waveguide mode. The exemplary current pattern can be further configured to facilitate traveling wave imaging, for example.

Apparatus, systems and methods for facilitating signal excitation and/or reception in a magnetic resonance system

Compressed sensing (CS) requires undersampled projection data, but CT x-ray tubes cannot be pulsed quickly enough to achieve reduced-view undersampling. We propose an alternative within-view undersampling strategy, named SparseCT, as a practical CS technique to reduce CT radiation dose. SparseCT uses a multi-slit collimator (MSC) to interrupt the x-ray beam, thus acquiring undersampled projection data directly. This study evaluated the feasibility of SparseCT via simulations using a standardized patient dataset. Because the projection data in the dataset are fully sampled, we retrospectively undersample the projection data to simulate SparseCT acquisitions in three steps. First, two photon distributions were simulated, representing the cases with and without the MSC. Second, by comparing the two distributions, detector regions with more than 80% of x-ray blocked by the MSC were identified and the corresponding projection data were not used. Third, noise was inserted into the rest of the projection data to account for the increase in quantum noise due to reduced flux (partial MSC blockage). The undersampled projection data were then reconstructed iteratively using a penalized weighted least squares cost function with the conjugate gradient algorithm. The image reconstruction problem promotes sparsity in the solution and incorporates the undersampling model. Weighting factors were applied to the projection data during the reconstruction to account for the noise variation in the undersampled projection. Compared to images acquired with reduced tube current (provided in the standardized patient dataset), SparseCT undersampling presented less image noise while preserving pathologies and fine structures such as vessels in the reconstructed images.

Evaluation of SparseCT on patient data using realistic undersampling models

Introduction Whole heart coronary MRA (CMRA) is typically performed with navigator gating because of the extensive data acquisition needed to achieve an isotropic spatial resolution on the order of 1-2 mm3 with full anatomic coverage (10-16 cm). Previous studies have shown that whole heart CMRA can be performed with either a single [1] or double [2,3] breath-hold (BH) approach using highlyaccelerated parallel imaging. The single breath-hold approach [1] acquires the coil sensitivity data immediately before and after the coronary MRA data within the same cardiac cycle, whereas the double BH approach acquires coil sensitivity data in a separate BH. The single BH approach lengthens the time between the T2 and fat suppression pulses to the image acquisition, and the double BH approach may suffer from misregistration. We propose to acquire the coil sensitivity and coronary MRA data in two separate cardiac phases (early systole and mid diastole, respectively) both within a single BH, in order to circumvent the aforementioned problems.

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Single breath-hold whole heart coronary MRA with isotropic spatial resolution using highly-accelerated parallel imaging with a 32-element coil array

Introduction Imaging of the carotid artery with black-blood MRI can be used to identify plaques that are vulnerable for rupture [1,2] 3D imaging is particularly interesting to overcome the SNR and volumetric coverage limitations of 2D multislice techniques However, 3D scans are more susceptible to motion artifacts, particularly swallowing-related artifacts, due to the longer acquisition times [3] Parallel imaging can be used to accelerate the acquisition, but acceleration is limited by noise amplification An alternative acceleration technique is compressed sensing (CS) [4], where image compressibility can be exploited to undersample k-space without losing image information 3D imaging is a natural candidate for CS, since higher dimensional data sets increase sparsity We propose to combine CS and parallel imaging to increase the acceleration rate for 3D carotid imaging

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Daniel K. Sodickson

Papers

Brain-implanted conductors amplify radiofrequency fields in rodents: advantages and risks

Apparatus, systems and methods for facilitating signal excitation and/or reception in a magnetic resonance system

Evaluation of SparseCT on patient data using realistic undersampling models

Single breath-hold whole heart coronary MRA with isotropic spatial resolution using highly-accelerated parallel imaging with a 32-element coil array

Accelerated 3D carotid MRI using compressed sensing and parallel imaging