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Gradient echo (GRE) imaging, a magnetic resonance imaging (MRI) technique that is sensitive to changes in the magnetic susceptibility property of tissues, has recently revealed significant signal heterogeneity in white matter (WM) at high magnetic field B0 ≥ 3T. Various aspects of the underlying white matter microstructure have been linked to the observed contrast between white matter regions. This thesis investigates the origins of the observed differences in GRE signal behaviour. We proposed an explicit multi-compartmental model of WM that incorporates realistic representation of the geometry and magnetic susceptibility of the underlying microstructure that can be used to study the effects of WM microstructural changes on GRE signal characteristics. In particular, we looked at the apparent transverse relaxation rate (R2*) and the resonance frequency, as well as their respective deviations from mono-exponential decay and linear phase evolution. Next, we investigated the effect of WM fiber orientation on GRE signal using healthy human volunteers at 3T by correlating the GRE signal from different WM regions with WM fiber orientation information. Using literature-based parameters, we demonstrated that the geometric model predicted similar trends. Lastly, we studied the effect of myelin on GRE signal using a cuprizone mouse model at 7T . An ex vivo study was used to correlate GRE signal in fixed mouse brain with normalized myelin stain intensity. Simulated GRE signal from hypothetical scenarios of demyelination were then compared with the experimental results. R2* and resonance frequency were then used in an in vivo longitudinal study to track myelin changes during demyelination and subsequent remyelination.

Data from the Louisiana Tumor Registry for the years 1988-1992 were used to describe the relationship between the rates of five selected cancer sites (leukemia, non-Hodgkin's lymphoma, breast cancer, prostate cancer and cervical cancer) and urbanization status while controlling for the effects of age, race, sex and socioeconomic status. Population density measurements for each of Louisiana's 64 parishes were used to define urbanization status. The census derived percent of the population below poverty level (SES) was used to define socioeconomic status. The SES variable is race-specific. For each race-sex combination, multiple regression analysis was performed in order to describe the relationship between each selected cancer site and the log of the population density while controlling for the effect of SES. The incidence of non-Hodgkin's lymphoma increased with increasing population density in white males. Breast cancer incidence increased with increasing population density in white and black females. Prostate cancer incidence increased with increasing population density in white males. The rates of leukemia and cervical cancer were not associated with population density. However, the rate of cervical cancer increased with increasing percent poverty in white females even after adjusting for population density. SES was associated with breast cancer in white females, but not after adjusting for population density. It is hypothesized that SES was not statistically significant in black females for breast or cervical cancer because the prevalence of poverty was above the threshold for which the rates of these cancers may be constant / acase@tulane.edu