My research focuses on developing magnetic resonance imaging techniques and processing methods to improve the robustness and interpretation of MR measures by reducing artifacts. I am currently concentrating on studying diseases, disorders and healthy processes in the abdomen and pelvis. This research is very translational in nature and is driven by clinical questions. The artifacts I address arise from various sources, such as: 1) technical sources – as in hardware acquisition artifacts, 2) biological sources – as in respiratory motion artifacts, 3) physiological sources – as in the impact of feeding history, and 4) pathological sources – as in tissue heterogeneity and the difficulty in discriminating among different tissue types and cancer grades. I am currently focused on prostate cancer and fatty liver disease.

In my prostate cancer research, I am focused on building tools to evaluate DCE MRI and other MR metrics obtained in men with prostate cancer to help identify cancer and to help discriminate among cancers with different degrees of aggressiveness. This work entails obtaining detailed histopathology, careful alignment of pathology to MR data, mathematical modeling of the MRI data and statistical modeling of the combinations of MR data. Preliminary data has been very promising for detecting differences in aggressiveness in prostate cancer, which is extremely important clinically.

I strive to find more robust ways to measure the diffuse liver in my liver research. I investigate changes due to diet and disease. Primarily I use MR spectroscopy to study changes in steatosis but also utilize diffusion weighted MR and other MR metrics to attempt to discriminate among grades of inflammation and stages of fibrosis. We have shown dramatic changes in MR-measured metabolism with short-term changes in diet.