Flexible and computationally efficient framework for diffusion MRI simulations in realistic neuron morphologies

Motivation: Analytical diffusion models are limited in the complexity of brain tissue they capture, and creating complex numerical phantoms using meshes can be arduous. Goal(s): This work introduces an efficient and user-friendly software for generating realistic neurons using overlapping spheres. Approach: Through Monte-Carlo simulations, we evaluate the impact of sphere overlap, soma-dendrites water exchange, and SNR on dMRI signals. Results: The findings indicate that modest sphere overlap maintains signal quality. Additionally, the soma-dendrites water exchange has a significant impact on the signal, even at realistic SNR. This work has promising implications for non-invasively quantifying gray matter microstructure, especially neuronal packing and cell membrane permeability. Impact: Numerical phantoms of gray matter built with overlapping spheres offer an efficient and flexible way of studying water diffusion. This approach reduces the heavy meshing and cleaning process to trivial building blocks that can be adapted into realistic neuronal substrates.