Magnetic resonance imaging (MRI) is a unique technique for studying the human body since it is non-invasive, does not require ionizing radiation and offers a multiplicity of complementary tissue contrasts. My research seeks to explore the potential of MRI for clinical and pre-clinical imaging and to provide new and improved MRI technology.

The goal of this endeavor is twofold: 1.) to contribute deeper insight into the etiology, pathogenesis and potential treatment of neurodegenerative diseases, and 2.) to give clinicians the ability to diagnose diseases earlier and monitor them more accurately.

I am currently focusing on understanding MRI contrast mechanisms as well as on developing innovative imaging and reconstruction techniques that improve the sensitivity and specificity of MRI with respect to biophysical properties of brain tissue. Advancements in this field promise to have a substantial impact on our understanding of biophysical and morphological tissue alterations associated with neurological diseases and their treatment.

We recently pioneered quantitative susceptibility mapping (QSM), a breakthrough in quantitative MRI. This technique allows for unique assessment of endogenous and exogenous magnetic particles in the human brain such as iron, calcium, myelin or contrast agents. The concept of QSM is fundamentally different from conventional MRI techniques as it involves solving for all imaging voxels simultaneously in large physically motivated equations, a so-called inverse problem. At the Buffalo Neuroimaging Analysis Center (BNAC), we use QSM to explore whether brain iron may serve as an early biomarker for diseases of the central nervous system such as multiple sclerosis and Parkinson’s disease. Other interesting applications of this technique we are investigating include differentiation between hemorrhages and calcifications, detection of demyelination and quantification of tissue oxygenation.

I am fascinated by the synergies from combining physical expertise with high-level mathematical, numerical and engineering concepts to advance our understanding of the human brain. Consequently, my research activities are generally interdisciplinary and involve collaboration with clinicians, physicists, computer scientists, technicians and engineers. Student projects typically focus either on the application of techniques or on technical developments. Undergraduate, graduate and doctoral candidates from a variety of disciplines such as neuroscience, physics and mathematics work collaboratively in my lab.