  This paper investigates the impact of cell body (soma) size and branching of
cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS)
signals for both standard single diffusion encoding (SDE) and more advanced
double diffusion encoding (DDE) measurements using numerical simulations. The
aim is to study the ability of dMRI/dMRS to characterize the complex morphology
of brain grey matter, focusing on these two distinctive features. To this end,
we employ a recently developed framework to create realistic meshes for Monte
Carlo simulations, covering a wide range of soma sizes and branching orders of
cellular projections, for diffusivities reflecting both water and metabolites.
For SDE sequences, we assess the impact of soma size and branching order on the
signal b-value dependence as well as the time dependence of the apparent
diffusion coefficient (ADC). For DDE sequences, we assess their impact on the
mixing time dependence of the signal angular modulation and of the estimated
microscopic anisotropy, a promising contrast derived from DDE measurements. The
SDE results show that soma size has a measurable impact on both the b-value and
diffusion time dependence, for both water and metabolites. On the other hand,
branching order has little impact on either, especially for water. In contrast,
the DDE results show that soma size has a measurable impact on the signal
angular modulation at short mixing times and the branching order significantly
impacts the mixing time dependence of the signal angular modulation as well as
of the derived microscopic anisotropy, for both water and metabolites. Our
results confirm that soma size can be estimated from SDE based techniques, and
most importantly, show for the first time that DDE measurements show
sensitivity to the branching of cellular projections, paving the way for
non-invasive characterization of grey matter morphology.
