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Abstract #3486

Linking sub-diffusion model parameters and brain cell morphometrics

Qianqian Yang1,2,3, Megan Farquhar1, Viktor Vegh4,5, and Marco Palombo6,7
1School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia, 2Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Australia, 3Centre for Data Science, Queensland University of Technology, Brisbane, Australia, 4Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 5ARC Training Centre for Innovation in Biomedical Imaging Technology, Brisbane, Australia, 6Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom, 7School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

Synopsis

Keywords: Simulation/Validation, Signal Representations, sub-diffusion model, brain cell morphology

Motivation: The diffusion MRI signal in brain tissues can be modelled as a sub-diffusion process. The connection between sub-diffusion model parameters and microstructure of brain cells is yet to be explored.

Goal(s): The research aims to investigate the link between sub-diffusion model parameters and brain cell morphometrics.

Approach: Monte Carlo simulations are performed for representative brain cell types. The sub-diffusion model are then fitted to the simulated diffusion MRI data for each cell type.

Results: Results reveal that the sub-diffusion model parameters are sensitive to the branch order of the cell, with higher parameter values indicating higher branch order.

Impact: This is the first study to investigate how the sub-diffusion model parameters link to brain cell morphometrics. Our findings may provide new opportunities in diffusion MRI, where cell morphology and potentially cell type are of interest.

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Keywords

diffusioncellbetamodelbraindelta