In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.
Compressed sensing (CS) holds considerable promise to accelerate the data acquisition in magnetic resonance imaging by exploiting signal sparsity. Prior knowledge about the signal can be exploited in some applications to choose an appropriate sparsifying transform. This work presents a CS reconstruction for magnetic resonance (MR) parameter mapping, which applies an overcomplete dictionary, learned from the data model to sparsify the signal. The approach is presented and evaluated in simulations and in in vivo T 1 and T 2 mapping experiments in the brain. Accurate A major concern in MR parameter mapping is the often long scan time. This has led to an estimation of T 1 and T 2 relaxation times from three or even only two data points, which entails poor accuracy and does not give any indication of multicompartmental signal behavior. Higher numbers of measurements are necessary to cover a large dynamic range of tissue parameters relevant in clinical applications (4) and also to improve the accuracy of the fit and SNR. Multiexponential fits can be applied to decrease partial volume effects and to characterize multicompartmental relaxation curves (5). Several works consider measurements of T 2 distributions in tissue acquiring several thousand echoes (6,7).This article presents a technique for reducing the acquisition time in multipoint MR parameter mapping experiments, which is inspired by the theory of compressed
In this work, a new two-point method for water-fat imaging is described and explored. It generalizes existing two-point methods by eliminating some of the restrictions that these methods impose on the choice of echo times. Thus, the new two-point method promises to provide more freedom in the selection of protocol parameters and to reach higher scan efficiency. Its performance was studied theoretically and was evaluated experimentally in abdominal imaging with a multigradient-echo sequence. While depending on the choice of echo times, it is generally found to be favorable compared to existing two-point methods. Notably, water images with higher spatial resolution and better signal-to-noise ratio were attained with it in single breathholds at 3.0 T and 1.5 T, respectively. The use of more accurate spectral models of fat is shown to substantially reduce observed variations in the extent of fat suppression. The acquisition of in-and opposedphase images is demonstrated to be replaceable by a synthesis from water and fat images. The new two-point method is finally also applied to autocalibrate a multidimensional eddy current correction and to enhance the fat suppression achieved with three-point methods in this way, especially toward the edges of larger field of views. Magn Reson Med 65:96-107, 2011. V C 2010 Wiley-Liss, Inc. Key words: water-fat separation; fat suppression; Dixon methods; multiecho acquisitions; abdominal imaging; eddy currentsAs hyperintense signal from fat may obscure underlying pathology, its partial or complete suppression is a basic requirement in various applications of magnetic resonance imaging. Its characteristics result from the comparatively short relaxation times and large chemical shifts of the dominant methylene protons and serve as the basis for its elimination.Fat suppression is often an integral part of the acquisition. Popular methods include short-tau inversion recovery, which exploits the specific relaxation times, and selective saturation, which relies on the specific chemical shifts (1,2). However, these methods all have individual drawbacks, such as longer scan times, lower signalto-noise ratio (SNR), higher specific absorption rate, or less tolerance to field inhomogeneities. Postponing the separation of water and fat signals until the reconstruction allows avoiding most of these disadvantages. So-called Dixon methods perform for this purpose measurements at different echo times to encode the chemical shift (3). Besides fat suppression, they also permit efficient water-fat imaging, providing additional diagnostic information of relevance to selected applications.Several Dixon methods have been proposed over the last two decades (4). Apart from different strategies for the separation, they are mainly characterized by the number of echoes, or points, that they sample, and by the constraints that they impose on the echo times. We focus in this work on two-and three-point methods, as multipoint methods are usually very similar to threepoint methods, and one-point methods are gene...
Respiratory motion is a major source of artifacts in cardiac magnetic resonance imaging (MRI). Free-breathing techniques with pencil-beam navigators efficiently suppress respiratory motion and minimize the need for patient cooperation. However, the correlation between the measured navigator position and the actual position of the heart may be adversely affected by hysteretic effects, navigator position, and temporal delays between the navigators and the image acquisition. In addition, irregular breathing patterns during navigator-gated scanning may result in low scan efficiency and prolonged scan time. The purpose of this study was to develop and implement a selfnavigated, free-breathing, whole-heart 3D coronary MRI technique that would overcome these shortcomings and improve the ease-of-use of coronary MRI. A signal synchronous with respiration was extracted directly from the echoes acquired for imaging, and the motion information was used for retrospective, rigid-body, through-plane motion correction. The images obtained from the self-navigated reconstruction were compared with the results from conventional, prospective, pencilbeam navigator tracking. Image quality was improved in phantom studies using self-navigation, while equivalent results were Key words: 3D radial; motion detection; self-navigation; wholeheart MRI; coronary angiography Free-breathing, three-dimensional (3D) cardiac MRI has received considerable attention because it enables highresolution imaging and, in contrast to breath-held imaging, does not require patient cooperation. For data acquisition during free breathing with the use of navigator technology (1), an end-expiratory gating window is defined prior to image acquisition, and data that were acquired outside the predefined respiratory gating window are rejected and remeasured in the next RR interval.However, fluctuations of the breathing pattern during prolonged scans may adversely affect the scan efficiency and prolong the scan time. Furthermore, the correlation between the navigator information and the actual position of the heart may be compromised by temporal delays (2) between the navigator signal and the actual image acquisition, which may arise from magnetization preparation pulses and the startup cycles necessary to approach the steady state. Also, the 2D-selective navigator pulses ("pencil beams") are preferably localized at the dome of the right hemidiaphragm to avoid contamination of the magnetization in the region of interest (ROI). While a stable correlation between the superior-inferior (SI) displacement of the diaphragm and the heart over a large number of subjects has been reported (3), hysteretic effects may occur (4), such as those induced by the difference in relative displacement between the diaphragm and the heart that reduce the precision of the motion estimation. Finally, the localization of the navigator beam requires special attention (5), which may decrease the utility and reproducibility of coronary MRI.To address these shortcomings, a self-navigated, 3D radi...
For certain medical applications resampling of data is required. In magnetic resonance tomography (MRT) or computer tomography (CT), e.g., data may be sampled on nonrectilinear grids in the Fourier domain. For the image reconstruction a convolution-interpolation algorithm, often called gridding, can be applied for resampling of the data onto a rectilinear grid. Resampling of data from a rectilinear onto a nonrectilinear grid are needed, e.g., if projections of a given rectilinear data set are to be obtained. In this paper we introduce the application of the convolution interpolation for resampling of data from one arbitrary grid onto another. The basic algorithm can be split into two steps. First, the data are resampled from the arbitrary input grid onto a rectilinear grid and second, the rectilinear data is resampled onto the arbitrary output grid. Furthermore, we like to introduce a new technique to derive the sampling density function needed for the first step of our algorithm. For fast, sampling-pattern-independent determination of the sampling density function the Voronoi diagram of the sample distribution is calculated. The volume of the Voronoi cell around each sample is used as a measure for the sampling density. It is shown that the introduced resampling technique allows fast resampling of data between arbitrary grids. Furthermore, it is shown that the suggested approach to derive the sampling density function is suitable even for arbitrary sampling patterns. Examples are given in which the proposed technique has been applied for the reconstruction of data acquired along spiral, radial, and arbitrary trajectories and for the fast calculation of projections of a given rectilinearly sampled image.
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