UCSF

Pediatric magnetic resonance imaging (MRI) emerged as an independent research area from adult MRI, due to distinct brain structure and development trajectory, and different responses to brain injuries or diseases in pediatric subjects. This dissertation discussed a few unexplored but important areas in pediatric brain MRI, including diffusion tensor imaging (DTI) and hyperpolarized 13C spectroscopic imaging.

DTI is adversely affected by subject motion, which is a common problem among unsedated pediatric subjects. It is necessary to discard the corrupted images before diffusion parameter estimation. However, the consequences of rejecting those images were not well understood. We investigated the effects of excluding one or more volumes of diffusion weighted images by analyzing the changes in diffusion parameters. Based on the full set of diffusion images, we generated incomplete sets in three different ways: random, uniform and clustered rejections. Different rejection methods resulted in very different variations in DTI parameters, and sometimes the resulting accuracy depended on the relative orientation of the underlying fibers with respect to the excluded directions. In practice, if diffusion data is excluded, it is important to note the number and location of directions rejected, in order to make a more precise analysis of the results.

Structural changes during early brain development have been studied using conventional MRI methods, but metabolic changes remain unrevealed. Hyperpolarized 13C spectroscopic imaging has recently been used to dynamically image metabolism in vivo. This technique provides the capability to investigate metabolic changes in mouse brain development over multiple time points. We used hyperpolarized 13C-1 labeled pyruvate to analyze its conversion into lactate during early brain development in normal and hypoxic-ischemic (HI) injured brains. The produced lactate level decreased linearly with increasing age in normal brains, but no pattern was observed in HI brains. This technique was also able to detect HI injury at a very early stage within a very short amount of time, which was hardly discovered otherwise. It can be a potential marker for HI diagnosis and progression tracking.