Ani Eloyan (Brown University)
Title: Imaging and Clinical Biomarker Estimation in Alzheimer’s Disease
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Abstract:
Estimation of biomarkers related to disease classification and modeling of its progression is essential for treatment development for Alzheimer’s Disease (AD). The task is more daunting for characterizing relatively rare AD subtypes such as the early-onset AD. In this talk, I will describe the Longitudinal Alzheimer’s Disease Study (LEADS) intending to collect and publicly distribute clinical, imaging, genetic, and other types of data from people with EOAD, as well as cognitively normal (CN) controls and people with early-onset non-amyloid positive (EOnonAD) dementias. I will discuss manifold estimation methods for estimation of surfaces of shapes in the brain using data clouds, longitudinal manifold learning methods for modeling trajectories of shape changes in the brain over time. Finally, I will discuss our work in leveraging magnetic resonance imaging and positron emission tomography data to characterize distributions of white matter hyperintensities in people with EOAD and to obtain imaging-based biomarkers of disease trajectories of AD subtypes.
Speaker
Dr. Ani Eloyan is associate professor and vice chair of Biostatistics at Brown University. Before joining the faculty at Brown, she was a postdoctoral fellow and faculty member in the Department of Biostatistics at the Bloomberg School of Public Health, at Johns Hopkins University. Dr. Eloyan works on developing statistical methods for analyzing medical imaging data. She received her PhD in Statistics from North Carolina State University in 2010, where she worked on the development of likelihood-based semi-parametric models for independent component analysis, including a density estimation method with moment constraints. She served on editorial boards of the Journal of American Statistical Association and Biostatistics as Associate Editor.