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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 goal of the works presented in this volume is to develop a magnetic resonance imaging (MRI) probe for non-invasive detection of extracellular matrix (ECM) underlying fenestrated endothelia. The ECM is the scaffold that supports tissue structure in all organs. In fenestrated structures the such as the kidney glomerulus and the hepatic sinusoid the ECM serves a unique role in blood filtration and is directly exposed to blood plasma. An assessment of the ECM in fenestrated organs such as the kidney and liver reports on the organ's ability to filter blood - a process critical to maintaining homeostasis. Unfortunately, clinical assessment of the ECM in most organs requires biopsy, which is focal and invasive. This work will focus on visualizing the ECM underlying fenestrated endothelia with natural nanoparticles and MRI. The superparamagnetic ferritin protein has been proposed as a useful naturally-derived, MRI-detectable nanoparticle due to its biocompatibility, ease of functionalization, and modifiable metallic core. We will show that cationized ferritin (CF) specifically binds to the anionic proteoglycans of the ECM underlying fenestrated endothelia and that its accumulation is MRI-detectable. We will then demonstrate the use of CF and MRI in identifying and measuring all glomeruli in the kidney. We will also explore the toxicity of intravenously injected CF and consider other avenues for its application, including detection of microstructural changes in the liver due to chronic liver disease. This work will show that CF is useful in detected fenestrated microstructures in small animals and humans alike, indicating that CF may find broad application in detecting and monitoring disease in both preclinical and clinical settings.
ContributorsBeeman, Scott (Author) / Bennett, Kevin M (Thesis advisor) / Kodibagkar, Vikram D (Committee member) / Fayad, Zahi A (Committee member) / Pizziconi, Vincent B (Committee member) / Pipe, James G (Committee member) / Arizona State University (Publisher)
Created2012
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