Elsevier

NeuroImage

Volume 133, June 2016, Pages 207-223
NeuroImage

Bingham–NODDI: Mapping anisotropic orientation dispersion of neurites using diffusion MRI

https://doi.org/10.1016/j.neuroimage.2016.01.046Get rights and content
Under a Creative Commons license
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Highlights

  • We propose a method to estimate anisotropic orientation dispersion of neurites.

  • Estimation of this anisotropy enhances tractography and is a potential marker of disease.

  • The method uses NODDI, a clinically feasible technique to estimate neurite morphology.

  • We show that the estimation of indices of the proposed model is clinically feasible.

  • The new model explains the data better in white matter compared to the original model.

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.

Keywords

Anisotropic orientation dispersion
NODDI
Diffusion MRI
Bingham distribution
Neurite morphology

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