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Radial Acquisition (radial + acquisition)

Distribution by Scientific Domains

Medical Sciences	100%

Selected Abstracts

3D diffusion tensor MRI with isotropic resolution using a steady-state radial acquisition

JOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 5 2009
Youngkyoo Jung PhD
Abstract Purpose To obtain diffusion tensor images (DTI) over a large image volume rapidly with 3D isotropic spatial resolution, minimal spatial distortions, and reduced motion artifacts, a diffusion-weighted steady-state 3D projection (SS 3DPR) pulse sequence was developed. Materials and Methods A diffusion gradient was inserted in a SS 3DPR pulse sequence. The acquisition was synchronized to the cardiac cycle, linear phase errors were corrected along the readout direction, and each projection was weighted by measures of consistency with other data. A new iterative parallel imaging reconstruction method was also implemented for removing off-resonance and undersampling artifacts simultaneously. Results The contrast and appearance of both the fractional anisotropy and eigenvector color maps were substantially improved after all correction techniques were applied. True 3D DTI datasets were obtained in vivo over the whole brain (240 mm field of view in all directions) with 1.87 mm isotropic spatial resolution, six diffusion encoding directions in under 19 minutes. Conclusion A true 3D DTI pulse sequence with high isotropic spatial resolution was developed for whole brain imaging in under 20 minutes. To minimize the effects of brain motion, a cardiac synchronized, multiecho, DW-SSFP pulse sequence was implemented. Motion artifacts were further reduced by a combination of linear phase correction, corrupt projection detection and rejection, sampling density reweighting, and parallel imaging reconstruction. The combination of these methods greatly improved the quality of 3D DTI in the brain. J. Magn. Reson. Imaging 2009;29:1175,1184. © 2009 Wiley-Liss, Inc. [source]

2D and 3D radial multi-gradient-echo DCE MRI in murine tumor models with dynamic R*2 -corrected R1 mapping

MAGNETIC RESONANCE IN MEDICINE, Issue 1 2010
Julien Vautier
Abstract Dynamic contrast-enhanced MRI is extensively studied to define and evaluate biomarkers for early assessment of vasculature-targeting therapies. In this study, two-dimensional and three-dimensional radial multi-gradient-echo techniques for dynamic R*2 -corrected R1 mapping based on the spoiled gradient recalled signal equation were implemented and validated at 4.7 T. The techniques were evaluated on phantoms and on a respiratory motion animated tumor model. R1 measurements were validated with respect to a standard inversion-recovery spin-echo sequence in a four-compartment phantom covering a range of relaxation rates typically found in tumor tissue. In the range of [0.4, 3] sec,1, R1 differences were less than 10% for both two-dimensional and three-dimensional experiments. A dynamic contrast-enhanced MRI pilot study was performed on a colorectal tumor model subcutaneously implanted in mice at the abdominal level. Low motion sensitivity of radial acquisition allowed image recording without respiratory triggering. Three-dimensional Ktrans maps and significantly different mean Ktrans values were obtained for two contrast agents with different molecular weights. The radial multi-gradient-echo approach should be most useful for preclinical experimental conditions where the tissue of interest experiences physiologic motion, like spontaneous extracerebral tumors developed by transgenic mice, and where dynamic contrast-enhanced MRI is performed with high-relaxivity contrast agents. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc. [source]

Perfusion MRI with radial acquisition for arterial input function assessment,

MAGNETIC RESONANCE IN MEDICINE, Issue 5 2007
Eugene G. Kholmovski
Abstract Quantification of myocardial perfusion critically depends on accurate arterial input function (AIF) and tissue enhancement curves (TECs). Except at low doses, the AIF is inaccurate because of the long saturation recovery time (SRT) of the pulse sequence. The choice of dose and SRT involves a trade-off between the accuracy of the AIF and the signal-to-noise ratio (SNR) of the TEC. Recent methods to resolve this trade-off are based on the acquisition of two data sets: one to accurately estimate the AIF, and one to find the high-SNR TEC. With radial k -space sampling, a set of images with varied SRTs can be reconstructed from the same data set, allowing an accurate assessment of the AIF and TECs, and their conversion to contrast agent (CA) concentration. This study demonstrates the feasibility of using a radial acquisition for quantitative myocardial perfusion imaging. Magn Reson Med 57:821,827, 2007. © 2007 Wiley-Liss, Inc. [source]

RT-GROG: parallelized self-calibrating GROG for real-time MRI

MAGNETIC RESONANCE IN MEDICINE, Issue 1 2010
Haris Saybasili
Abstract A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding's weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two-dimensional gridding weights GG are evaluated for m,n = {,0.5, ,0.4, ,, 0, 0.1, ,, 0.5} and stored in a look-up table. Consequently, the per-sample two-dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look-up table access. In practice, up to 34× faster reconstruction than conventional (parallelized) self-calibrating GRAPPA operator gridding is achieved. On a 32-coil dataset of size 128 × 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps. Magn Reson Med 64:306,312, 2010. © 2010 Wiley-Liss, Inc. [source]