Whenever a linear gradient is activated, concomitant magnetic fields with non-linear spatial dependence result. This is a consequence of Maxwell's equations, i.e., within the imaging volume the magnetic field must have zero divergence, and has negligible curl. The concomitant, or Maxwell field has been described in the MRI literature for over 10 years. In this paper, we theoretically and experimentally show the existence of two additional lowest-order terms in the concomitant field, which we call cross-terms. The concomitant gradient cross-terms only arise when the longitudinal gradient Gz is simultaneously active with a transverse gradient (Gx or Gy). The effect of all of the concomitant gradient terms on phase contrast imaging is examined in detail. Several methods for reducing or eliminating phase errors arising from the concomitant magnetic field are described. The feasibility of a joint pulse sequence-reconstruction method, which requires no increase in minimum TE, is demonstrated. Since the lowest-order terms of the concomitant field are proportional to G2/B0, the importance of concomitant gradient terms is expected to increase given the current interest in systems with stronger gradients and/or weaker main magnetic fields.

The recently developed multi-acquisition with variable resonance image combination (MAVRIC) and slice-encoding metal artifact correction (SEMAC) techniques can significantly reduce image artifacts commonly encountered near embedded metal hardware. These artifact reductions are enabled by applying alternative spectral and spatial-encoding schemes to conventional spin-echo imaging techniques. Here, the MAVRIC and SEMAC concepts are connected and discussed. The development of a hybrid technique that utilizes strengths of both methods is then introduced. The presented technique is shown capable of producing minimal artifact, high-resolution images near total joint replacements in a clinical setting. Magn Reson Med 65:71-82, 2011.

Metallic implants used in bone and joint arthroplasty induce severe spatial perturbations to the B 0 magnetic field used for high-field clinical magnetic resonance. These perturbations distort slice-selection and frequency encoding processes applied in conventional two-dimensional MRI techniques and hinder the diagnosis of complications from arthroplasty. Here, a method is presented whereby multiple three-dimensional fast-spin-echo images are collected using discrete offsets in RF transmission and reception frequency. It is demonstrated that this multi acquisition variable-resonance image combination technique can be used to generate a composite image that is devoid of slice-plane distortion and possesses greatly reduced distortions in the readout direction, even in the immediate vicinity of metallic implants.Magn Reson Med 61:381-390, 2009.

This paper deals with methods of reducing the total time required to acquire the projection data for a set of contiguous computed tomography (CT) images. Normally during the acquisition of a set of slices, the patient is held stationary during data collection and translated to the next axial location during an interscan delay. We demonstrate using computer simulations and scans of volunteers on a modified scanner how acceptable image quality is achieved if the patient translation time is overlapped with data acquisition. If the concurrent patient translation is ignored, structured artifacts significantly degrade resulting reconstructions. We present a number of weighting schemes for use with the conventional convolution/backprojection algorithm to reduce the structured artifacts through the use of projection modulation using the data from individual and multiple slices. We compare the methods with respect to structured artifacts, noise, resolution and to patient motion. Review of preliminary results by a panel of radiologists indicates that the residual image degradation is tolerable for selected applications when it is critical to acquire more slices in a patient breathing cycle than is possible with conventional scanning.

We developed a novel method to accelerate diffusion spectrum imaging using compressed sensing. The method can be applied to either reduce acquisition time of diffusion spectrum imaging acquisition without losing critical information or to improve the resolution in diffusion space without increasing scan time. Unlike parallel imaging, compressed sensing can be applied to reconstruct a sub-Nyquist sampled dataset in domains other than the spatial one. Simulations of fiber crossings in 2D and 3D were performed to systematically evaluate the effect of compressed sensing reconstruction with different types of undersampling patterns (random, gaussian, Poisson disk) and different acceleration factors on radial and axial diffusion information. Experiments in brains of healthy volunteers were performed, where diffusion space was undersampled with different sampling patterns and reconstructed using compressed sensing. Essential information on diffusion properties, such as orientation distribution function, diffusion coefficient, and kurtosis is preserved up to an acceleration factor of R Key words: compressed sensing; q-space; diffusion spectrum imaging; kurtosis; undersampling; orientation distribution function Over the last decade the application of diffusionweighted MR imaging to the central nervous system has gained significant attention. Recently, Inglese and Bester (1) reviewed the importance of diffusion in clinical evaluation of multiple sclerosis. Similarly, earlier studies indicated that diffusion tensor imaging could be used to detect evidence of traumatic brain injury (2). Diffusion tensor imaging samples only a very small subset of the full diffusion information encoded in q-space and describes diffusion as single compartment gaussian (3). This assumption however falls short for instance in fiber crossings or in biological tissue (4), which may exhibit restricted, non-gaussian diffusion. The concept of full qspace imaging to study molecular diffusion and tissue microstructure was introduced by Callaghan et al. (5) and first applied to brain tissue by King et al. (6); its modulus Fourier transform variant using finite gradient pulse widths is known as diffusion spectrum MR imaging (DSI) (7). DSI samples the full q-space and can be related to a center-of-mass weighted displacement space (8) by Fourier transform. Despite the large information content of DSI, its high dimensionality (three dimensions in the spatial domain [k-space] and three dimensions in the q-space) leading to very long acquisition times, severely limited its clinical application in vivo. And indeed the application of DSI has been reported only a few times in biological systems (6,9), although the nonlocalized analysis of q-space is commonly used in porous media (10). It can however be envisioned that using the full potential of diffusion information of full q-space to derive and evaluate surrogate markers for multiple sclerosis (MS) and traumatic brain injury would add significant clinical benefit and indeed more extended sampling of diffusion...