Abstract
This paper investigates the impact of cell body (namely 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 investigate the ability of dMRI/dMRS to characterize the complex morphology of brain cells focusing on these two distinctive features of brain grey matter.To this end, we employ a recently developed computational framework to create three dimensional meshes of neuron-like structures for Monte Carlo simulations, using diffusion coefficients typical of water and brain metabolites. Modelling the cellular structure as realistically connected spherical soma and cylindrical cellular projections, we cover a wide range of combinations of sphere radii and branching order of cellular projections, characteristic of various grey matter cells. We assess the impact of spherical soma size and branching order on the b-value dependence of the SDE signal as well as the time dependence of the mean diffusivity (MD) and mean kurtosis (MK). Moreover, we also assess the impact of spherical soma size and branching order on the angular modulation of DDE signal at different mixing times, together with the mixing time dependence of the apparent microscopic anisotropy (μA), a promising contrast derived from DDE measurements.The SDE results show that spherical soma size has a measurable impact on both the b-value dependence of the SDE signal and the MD and MK diffusion time dependence for both water and metabolites. On the other hand, we show that branching order has little impact on either, especially for water. In contrast, the DDE results show that spherical soma size has a measurable impact on the DDE signal's angular modulation at short mixing times and the branching order of cellular projections significantly impacts the mixing time dependence of the DDE signal's angular modulation as well as of the derived μA, for both water and metabolites.Our results confirm that SDE based techniques may be sensitive to spherical soma size, and most importantly, show for the first time that DDE measurements may be more sensitive to the dendritic tree complexity (as parametrized by the branching order of cellular projections), paving the way for new ways of characterizing grey matter morphology, non-invasively using dMRS and potentially dMRI.
Highlights
Non-invasive mapping of brain cells morphology is a major focus in biomedical imaging research, as it can play a crucial role in the assessment of neurologic and psychiatric diseases which alter the tissue structure (Uylings and de Brabander, 2002), for studying brain development (Cassey et al, 2005), plasticity (Zatorre et al, 2012) or ageing (Uylings and de Brabander, 2002)
The aim of this study is to systematically investigate the effect of subtle morphological features such as cell soma size and branching order of cellular projections on the diffusion properties measured with water diffusion Magnetic Resonance Imaging (dMRI) and/or metabolite diffusion-weighted MR spectroscopy
Effect of soma size and branching order on double diffusion encoding (DDE) measurements. In this second set of experiments, we study the effect of spherical soma size and branching order on DDE measurements, which have been suggested to provide additional contrast compared to single diffusion encoding (SDE) sequences, especially related to microscopic diffusion anisotropy (Novikov et al, 2019; Shemesh et al, 2010; Shemesh et al, 2015; Finsterbusch, 2011)
Summary
Non-invasive mapping of brain cells morphology is a major focus in biomedical imaging research, as it can play a crucial role in the assessment of neurologic and psychiatric diseases which alter the tissue structure (Uylings and de Brabander, 2002), for studying brain development (Cassey et al, 2005), plasticity (Zatorre et al, 2012) or ageing (Uylings and de Brabander, 2002). Soma size and the tree configuration of cellular projections of neurons and glia are largely plastic properties which are directly affected in various pathologies. Abnormalities and changes in the dendritic tree characterize a wide range of disorders (Kulkarni and Firestein, 2012), including a progressive loss of dendrites and spines in normal aging (Dickstein et al, 2007). Changes in glial cells, such as astrocyte hypertrophy/atrophy characterized by an overall increase/decrease in cell size, accompany various pathologies, from traumatic brain injury (Robinson et al, 2016) to Alzheimer’s disease (De Strooper and Karran, 2016)
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