Abstract #0640

Parameter estimation for the GRAMMI (GRAy Matter Microstructure Imaging) model of two exchanging compartments in the rat cortex in vivo

Alexandre de Skowronski¹, Marco Palombo², Dmitry S. Novikov³, and Ileana O. Jelescu⁴

¹Dept. of Physics, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ²Centre for Medical Image Computing and Dept. of Computer Science, University College London, London, United Kingdom, ³Center for Biomedical Imaging, Dept. of Radiology, New York University, New York, NY, United States, ⁴CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

Developing a relevant model for brain gray matter is a complex task. As opposed to white matter, features such as inter-compartment water exchange or soma should likely be modeled. In this work we examine the performance of a variant of the Kärger Model, called GRAMMI, that accounts for exchange, both on synthetic and experimental data. We show q-t coverage is necessary for reliable model parameter estimation at the individual voxel level and compare two regression approaches. Future work includes protocol optimization and the extension of the GRAMMI model to account for soma.

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