| Abstract |
In contrast to traditional magnetic resonance imaging (MRI) that produces weighted images contaminated by experiment- and/or scanner-specific parameters (e.g., receive coil sensitivity, receiver gain, and image scaling), quantitative MRI (qMRI) has the potential to provide maps whose intensities represent one of the biophysical parameters (e.g., T1, T2, T2* relaxation times, magnetization transfer, proton density, mean/radial/axial diffusivity, and cerebral blood flow). To obtain a meaningful quantitative map, measurements need to be both accurate and precise. However, numerous factors could compromise the accuracy and/or precision of the measurement. This includes gradient nonlinearities, eddy currents, gradient heating, radiofrequency transmit field (B1+) inhomogeneity, thermal noise, subject motion, physiologically-induced field fluctuations, to name a few. In light of these challenges in qMRI, this thesis aimed to evaluate and improve the accuracy and/or precision of qMRI measurements. From a wide range of available qMRI measures, diffusion MRI and T1 relaxation time mapping were the focus of this thesis.
In diffusion MRI, the actual b-value played out on the scanner may deviate from the nominal value due to magnetic field imperfections (e.g., gradient nonlinearities, imaging gradient interactions, concomitant fields, eddy currents, and gradient miscalibration). In Chapter 2 of this thesis, an image-based approach for correcting voxel-wise b-value errors in diffusion MRI is proposed. This method acquires diffusion MRI data from a water phantom while monitoring the temperature of the phantom to estimate the effective b-value map for a specific sequence. Subsequently, this effective b-value map is used in the diffusion analysis to obtain more reliable diffusion-related parameters. The proposed method was tested in both phantom and in vivo experiments. The apparent diffusion coefficient maps of the homogeneous water phantom estimated using the effective b-value map showed the expected spatial uniformity as ...
|
