Evren Ozarslan1, 2, Cheng Guan Koay3, Timothy M. Shepherd4, Michal E. Komlosh2, 5, Mustafa Okan Irfanoglu2, 5, Carlo Pierpaoli2, Peter J. Basser2
1Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; 2STBB, PPITS, NICHD, National Institutes of Health, Bethesda, MD, United States; 3Department of Medical Physics, University of Wisconsin, Madison, WI, United States; 4Department of Radiology, New York University Langone Medical Center, New York, NY, United States; 5Center for Neuroscience and Regenerative Medicine, USUHS, Bethesda, MD, United States
We propose a quantitative, efficient, and robust framework for representing diffusion-weighted MRI data obtained in q-space, and the corresponding mean apparent propagator (MAP) describing molecular displacements in r-space. We also define and map novel quantitative descriptors of diffusion that can be computed robustly using this MAP-MRI framework. Our approach employs a series expansion of basis functions with anisotropic scale parameters. Consequently, the technique subsumes DTI and reconstructions are performed in an anatomically consistent reference frame. Experiments on excised marmoset brain specimens demonstrate that MAP-MRI provides several novel, quantifiable parameters that capture previously obscured intrinsic features of nervous tissue microstructure.