UCSF

Magnetic resonance imaging (MRI) tools have been commonly utilized in the management of patients diagnosed with gliomas. Functional and metabolic MRI techniques have been proposed to add information regarding the tissue characteristics and biochemistry for better tumor localization, treatment planning and follow up of the disease. Magnetic resonance spectroscopic imaging (MRSI) is a metabolic imaging technique used to analyze brain tissue chemistry.

MR spectroscopic and diffusion imaging were utilized to study the spatial characteristics of grade 3 gliomas. The contrast enhancing regions appeared to be the most malignant tumor area in contrast enhancing patients, and choline to NAA index (CNI) greater than four regions appeared to be the most malignant focus in the non-enhancing patients.

The presence of lipids within MR spectra in sub-regions of tumor may indicate cellular membrane breakdown due to cell death. Another potential source of lipids is from subcutaneous fat that may be aliased into the spectral field of view due to chemical shift artifact and low bandwidth of the selection pulses. It is therefore important to identify the origins of lipid resonances, either artifact or from pathologic state, for accurate assessment of the disease state. A post-processing method based on the sensitivity encoding (SENSE) technique was developed to reduce lipid contamination in the spectra to increase the spectral quantification accuracy.

The major limitation of acquiring spectral data for gliomas is the long data acquisition time. The possibility of combining ellipsoidal sampling with two parallel imaging techniques, SENSE and generalized autocalibrating partially parallel acquisitions (GRAPPA), was investigated using simulations. Two fast data acquisition schemes, SENSE and ellipsoidal SENSE, were developed to scan patients at 3T within 9 and 4.5 minutes, respectively. Both SENSE and ellipsoidal SENSE sampling resulted in clinically interpretable spectra with high correlation to the ellipsoidal sampling.

The results of this dissertation suggest that magnetic resonance spectroscopic imaging is an important technique for spatially characterizing brain tumors that can be acquired in a shorter time to obtain equivalent disease related information. It is expected that shorter scan times will result in less patient discomfort and motion artifacts, and will increase the scanner throughput.