UCSF

This thesis developed high signal-to-noise ratio (SNR) yielding magnetic resonance imaging (MRI) methods that require relatively short measurement times. The methods were primarily aimed at addressing existing technical limitations of low SNR and long scan times (~ 20 minutes) in the field of in vivo high resolution (HR) imaging of trabecular bone micro-architecture. HR-MRI of trabecular bone provides a non-invasive way of monitoring trabecular bone structural integrity for assessment of the disease condition, osteoporosis. Osteoporosis is a debilitating skeletal disorder affecting 1 in 3 women and 1 in 12 men over the age of 50 worldwide and is characterized by loss of bone mass and structure leading to atraumatic fractures at the vertebrae, hip, wrists and other sites. SNR limitations in trabecular bone MRI were overcome by incorporating a high magnetization yielding pulse sequence and translating the imaging protocol to the higher field strength of 3 Tesla (T) from the clinical standard of 1.5 T. A simulation model was developed to estimate SNR in bone tissue. The feasibility of imaging trabecular bone structure in vivo at the proximal femur (hip), until then an SNR impeded application, was demonstrated. Next, an autocalibrating parallel imaging (PI) method was implemented to accelerate data acquisition. Using an eight channel coil array, scan time was reduced 2-4 fold without any significant impact on image resolution or edge sharpness; although bone structural measures derived from the accelerated images showed overestimation. Consequently, parallel reconstruction and image processing algorithms were developed to address the causes of overestimation. With the availability of whole body 7 T magnets and the motivation for further improvement in SNR, the PI methods were adapted to the even higher field strength and its performance was found to improve relative to 3 T. To summarize, this thesis developed SNR efficient MR methods that facilitate quantitative HR-MRI of trabecular bone within 2-10 minutes, thus increasing the clinical feasibility of this application. Additionally, the PI methods were applied to diverse applications such as cartilage imaging for osteoarthritis; and susceptibility weighted imaging of brain vasculature and 3D spectroscopic imaging of brain metabolites in brain tumor patients.