Abstract
This paper presents Bingham–NODDI, a clinically-feasible technique for estimating the anisotropic orientation dispersion of neurites. Direct quantification of neurite morphology on clinical scanners was recently realised by a diffusion MRI technique known as neurite orientation dispersion and density imaging (NODDI). However in its current form NODDI cannot estimate anisotropic orientation dispersion, which is widespread in the brain due to common fanning and bending of neurites. This work proposes Bingham–NODDI that extends the NODDI formalism to address this limitation. Bingham–NODDI characterises anisotropic orientation dispersion by utilising the Bingham distribution to model neurite orientation distribution. The new model estimates the extent of dispersion about the dominant orientation, separately along the primary and secondary dispersion orientations. These estimates are subsequently used to estimate the overall dispersion about the dominant orientation and the dispersion anisotropy. We systematically evaluate the ability of the new model to recover these key parameters of anisotropic orientation dispersion with standard NODDI protocol, both in silico and in vivo. The results demonstrate that the parameters of the proposed model can be estimated without additional acquisition requirements over the standard NODDI protocol. Thus anisotropic dispersion can be determined and has the potential to be used as a marker for normal brain development and ageing or in pathology. We additionally find that the original NODDI model is robust to the effects of anisotropic orientation dispersion, when the quantification of anisotropic dispersion is not of interest.
Highlights
Axons and dendrites, collectively known as neurites, are the projections from the cell body of a neuron; they are the structural underpinnings of brain functions
We model the effect of orientationally dispersed neurites on Aen by taking into account the following two observations: a) the dispersion of neurites has an effect on the diffusion in the extra-neurite space, with the diffusion perpendicular to the dominant orientation of neurites being greater if they have high dispersion, b) neurites hinder the diffusion in the surrounding space and this hindrance is greater if the neurite density in that space is greater
Protocol comparison We carry out a protocol comparison, similar to that for synthetic data, to establish if the Bingham–neurite orientation dispersion and density imaging (NODDI) parameters can be estimated in vivo with the standard NODDI protocol, N1, and if the protocol can be further reduced without impacting the accuracy and precision of the estimates
Summary
Collectively known as neurites, are the projections from the cell body of a neuron; they are the structural underpinnings of brain functions. Neurite morphology, quantified using histological analysis of postmortem tissue, is the most accurate and reliable means for understanding the development (Conel, 1939), ageing (Jacobs et al, 1997), function (Jacobs et al, 2001) and pathology (Fiala et al, 2002) of the brain. Accessing such information in vivo in humans has been of great interest as it can enable a dynamic view of the brain function and development, in health and disease. Diffusion tensor imaging (DTI) (Basser et al, 1994), the standard diffusion MRI technique in neuroimaging, provides sensitivity to neurite morphology but cannot quantify neurite-specific measures such as their density and orientation dispersion. Jespersen et al (2007) proposed the first direct technique to estimate these features using diffusion MRI, with subsequent validation against detailed histology in Jespersen et al (2010, 2012). Zhang et al (2012) enabled the in vivo mapping of these measures with the development of the neurite orientation dispersion and density imaging (NODDI)
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