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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

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
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Description
Among electrical properties of living tissues, the differentiation of tissues or organs provided by electrical conductivity is superior. The pathological condition of living tissues is inferred from the spatial distribution of conductivity. Magnetic Resonance Electrical Impedance Tomography (MREIT) is a relatively new non-invasive conductivity imaging technique. The majority of

Among electrical properties of living tissues, the differentiation of tissues or organs provided by electrical conductivity is superior. The pathological condition of living tissues is inferred from the spatial distribution of conductivity. Magnetic Resonance Electrical Impedance Tomography (MREIT) is a relatively new non-invasive conductivity imaging technique. The majority of conductivity reconstruction algorithms are suitable for isotropic conductivity distributions. However, tissues such as cardiac muscle and white matter in the brain are highly anisotropic. Until recently, the conductivity distributions of anisotropic samples were solved using isotropic conductivity reconstruction algorithms. First and second spatial derivatives of conductivity (∇σ and ∇2σ ) are integrated to obtain the conductivity distribution. Existing algorithms estimate a scalar conductivity instead of a tensor in anisotropic samples.

Accurate determination of the spatial distribution of a conductivity tensor in an anisotropic sample necessitates the development of anisotropic conductivity tensor image reconstruction techniques. Therefore, experimental studies investigating the effect of ∇2σ on degree of anisotropy is necessary. The purpose of the thesis is to compare the influence of ∇2σ on the degree of anisotropy under two different orthogonal current injection pairs.

The anisotropic property of tissues such as white matter is investigated by constructing stable TX-151 gel layer phantoms with varying degrees of anisotropy. MREIT and Diffusion Magnetic Resonance Imaging (DWI) experiments were conducted to probe the conductivity and diffusion properties of phantoms. MREIT involved current injection synchronized to a spin-echo pulse sequence. Similarities and differences in the divergence of the vector field of ∇σ (∇2σ) among anisotropic samples subjected to two different current injection pairs were studied. DWI of anisotropic phantoms involved the application of diffusion-weighted magnetic field gradients with a spin-echo pulse sequence. Eigenvalues and eigenvectors of diffusion tensors were compared to characterize diffusion properties of anisotropic phantoms.

The orientation of current injection electrode pair and degree of anisotropy influence the spatial distribution of ∇2σ. Anisotropy in conductivity is preserved in ∇2σ subjected to non-symmetric electric fields. Non-symmetry in electric field is observed in current injections parallel and perpendicular to the orientation of gel layers. The principal eigenvalue and eigenvector in the phantom with maximum anisotropy display diffusion anisotropy.
ContributorsAshok Kumar, Neeta (Author) / Sadleir, Rosalind J (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2015