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Home arrow Computer Science arrow Computational Diffusion MRI: MICCAI Workshop, Athens, Greece, October 2016

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Comparison of Biomarkers in Transgenic Alzheimer Rats Using Multi-Shell Diffusion MRI

Rutger H.J. Fick, Madelaine Daianu, Marco Pizzolato, Demian Wassermann, Russell E. Jacobs, Paul M. Thompson, Terrence Town, and Rachid Deriche

Abstract In this study, we assessed the evolution of diffusion MRI (dMRI) derived markers from different white matter models as progressive neurodegeneration occurs in transgenic Alzheimer rats (TgF344-AD) at 10, 15 and 24 months. We compared biomarkers reconstructed from Diffusion Tensor Imaging (DTI), Neurite Orientation Dispersion and Density Imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI in the hippocampus, cingulate cortex and corpus callosum using multi-shell dMRI. We found that NODDI’s dispersion and MAP-MRI’s anisotropy markers consistently changed over time, possibly indicating that these measures are sensitive to age-dependent neuronal demise due to amyloid accumulation. Conversely, we found that DTI’s mean diffusivity, NODDI’s isotropic volume fraction and MAP-MRI’s restriction-related metrics all followed a two-step progression from 10 to 15 months, and from 15 to 24 months. This two-step pattern might be linked with a neuroinflammatory response that may be occurring prior to, or during microstructural breakdown. Using our approach, we are able to provide— for the first time—preliminary and valuable insight on relevant biomarkers that may directly describe the underlying pathophysiology in Alzheimer’s disease.

R.H.J. Fick (H) • M. Pizzolato • D. Wassermann (H) • R. Deriche

Universite Cote d’Azur, Inria, Valbonne, France

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M. Daianu • P.M. Thompson

Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA

R.E. Jacobs

Division of Biology and Biological Engineering, Beckman Institute, California Institute of Technology, Pasadena, CA, USA

T. Town

Department of Physiology & Biophysics, Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA, USA

© Springer International Publishing AG 2017

A. Fuster et al. (eds.), Computational Diffusion MRI, Mathematics

and Visualization, DOI 10.1007/978-3-319-54130-3_16

 
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