Abstract #0661

Linear Multi-scale Modeling of diffusion MRI data: A framework for characterization of orientational structures across length scales

Barbara Wichtmann^1,2, Susie Huang¹, Qiuyun Fan¹, Thomas Witzel¹, Elizabeth Gerstner³, Bruce Rosen¹, Lothar Schad², Lawrence Wald^1,4, and Aapo Nummenmaa¹

¹A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States, ²Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ³Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, ⁴Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

We propose a new analysis technique called Linear Multi-scale Modeling (LMM) for diffusion MRI data that enables detailed microstructural tissue characterization by separating orientation distributions of restricted and hindered diffusion water compartments over a range of length scales. We demonstrate the ability of LMM to estimate volume fractions, compartment sizes and orientation distributions utilizing both simulations as well as empirical data from one healthy subject and one tumor patient acquired using a human 3T MRI scanner equipped with a 300mT/m gradient system. Possible applications of our modeling framework include characterization of diffusion microstructural signatures of pathological vs. healthy tissue.

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