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Description
Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality.
ContributorsBhavsar, Payal (Author) / Pipe, James G (Thesis advisor) / Frakes, David (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2013
Description
The aim of this study was to investigate the microstructural sensitivity of the statistical distribution and diffusion kurtosis (DKI) models of non-monoexponential signal attenuation in the brain using diffusion-weighted MRI (DWI). We first developed a simulation of 2-D water diffusion inside simulated tissue consisting of semi-permeable cells and a variable cell size. We simulated a DWI acquisition using a pulsed gradient spin echo (PGSE) pulse sequence, and fitted the models to the simulated DWI signals using b-values up to 2500 s/mm2. For comparison, we calculated the apparent diffusion coefficient (ADC) of the monoexponential model (b-value = 1000 s/mm2). In separate experiments, we varied the cell size (5-10-15 μ), cell volume fraction (0.50-0.65-0.80), and membrane permeability (0.001-0.01-0.1 mm/s) to study how the fitted parameters tracked simulated microstructural changes. The ADC was sensitive to all the simulated microstructural changes except the decrease in membrane permeability. The σstat of the statistical distribution model increased exclusively with a decrease in cell volume fraction. The Kapp of the DKI model increased exclusively with decreased cell size and decreased with increasing membrane permeability. These results suggest that the non-monoexponential models have different, specific microstructural sensitivity, and a combination of the models may give insights into the microstructural underpinning of tissue pathology. Faster PROPELLER DWI acquisitions, such as Turboprop and X-prop, remain subject to phase errors inherent to a gradient echo readout, which ultimately limits the applied turbo factor and thus scan time reductions. This study introduces a new phase correction to Turboprop, called Turboprop+. This technique employs calibration blades, which generate 2-D phase error maps and are rotated in accordance with the data blades, to correct phase errors arising from off-resonance and system imperfections. The results demonstrate that with a small increase in scan time for collecting calibration blades, Turboprop+ had a superior immunity to the off-resonance related artifacts when compared to standard Turboprop and recently proposed X-prop with the high turbo factor (turbo factor = 7). Thus, low specific absorption rate (SAR) and short scan time can be achieved in Turboprop+ using a high turbo factor, while off-resonance related artifacts are minimized.
ContributorsLee, Chu-Yu (Author) / Debbins, Josef P (Thesis advisor) / Bennett, Kevin M (Thesis advisor) / Karam, Lina (Committee member) / Pipe, James G (Committee member) / Arizona State University (Publisher)
Created2012
Description
Magnetic resonance (MR) imaging with data acquisition on a non-rectangular grid permits a variety of approaches to cover k-space. This flexibility can be exploited to achieve clinically relevant characteristics -- fast yet full coverage for short scan times, center out schemes for short Te, over-sampled k-space for robustness to motion, long acquisition time for improved signal-to-noise (SNR) performance and benign under-sampling (aliasing) artifact. This dissertation presents advances in Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) trajectory design and improved reconstruction for spiral imaging. Scan time in PROPELLER imaging can be reduced by tailoring the trajectory to the required Field-Of-View (FOV). A technique to design the PROPELLER trajectory for an elliptical FOV is described. The proposed solution is a set of empirically derived closed form equations that preserve the standard PROPELLER geometry and specify the minimum number of blades necessary. Reconstructing spiral scans requires accurate trajectory information. A simple method to measure the deviation from the designed trajectory due to gradient coupling is presented. A line phantom is used to force a uniform structure in a predetermined orientation in k-space. This uniformity permits measurements of zeroth order trajectory deviations due to gradient coupling. Spiral reconstruction is also sensitive to B0 inhomogeneities (variations in the external magnetic field). This sensitivity manifests itself as a spatially varying blur. An algorithm to correct for concomitant field and first order B0 inhomogeneity effects is developed based on de-blurring via convolution by separable kernels. To reduce computation time, an empirical equation for sufficient kernel length is derived. It is also necessary to know the noise characteristics of the proposed algorithm; this is investigated via Monte-Carlo simulations. The algorithm is further extended to correct for concomitant field artifacts by modeling these artifacts as blurring due to a temporally static field map. This approach has the potential for further reduction in computational cost by combining the B0 map with the concomitant field map to simultaneously correct for artifacts resulting from both field inhomogeneities and concomitant field map.
ContributorsDevaraj, Ajit (Author) / Pipe, James G (Thesis advisor) / Karam, Lina J (Thesis advisor) / Frakes, David H (Committee member) / Aberle, James T (Committee member) / Arizona State University (Publisher)
Created2010