The NODDI-DTI signal model is a modification of the NODDI signal model that formally allows interpretation of standard single-shell DTI data in terms of biophysical parameters in healthy human white matter (WM). The NODDI-DTI signal model contains no CSF compartment, restricting application to voxels without CSF partial-volume contamination. This modification allowed derivation of analytical re...

Discussion: The correlation between the DTIand NODDI-based FVF was relatively high in the skeleton of the corpus callosum, where the voxels are expected to contain relatively straight, parallel white matter fibers, as required by the DTI-based FVF model (Fig.s 1 and 2). The DTI-based FVF is, however, lower than that from NODDI even in the corpus callosum, probably due to partial volume averagin...

This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI), "Hybrid diffusion imaging"[1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI) model, "NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brai...

Here we present the application of neurite orientation dispersion and density imaging (NODDI) to the healthy spinal cord in vivo. NODDI provides maps such as the intra-neurite tissue volume fraction (vin), the orientation dispersion index (ODI) and the isotropic volume fraction (viso), and here we investigate their potential for spinal cord imaging. We scanned five healthy volunteers, four of w...

INTRODUCTION There is a need to develop imaging methods sensitive to axonal injury in multiple sclerosis (MS), given the prominent impact of axonal pathology on disability and outcome. Advanced multi-compartmental diffusion models offer novel indices sensitive to white matter microstructure. One such model, neurite orientation dispersion and density imaging (NODDI), is sensitive to neurite morp...

Increased hyperphosphorylated tau and the formation of intracellular neurofibrillary tangles are associated with the loss of neurons and cognitive decline in Alzheimer's disease, and related neurodegenerative conditions. We applied two diffusion models, diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to in vivo diffusion magnetic resonance images (...

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 disp...

In diffusion MRI (dMRI), microscopic diffusion anisotropy can be obscured by orientation dispersion. Separation of these properties is of high importance, since it could allow dMRI to non-invasively probe elongated structures such as neurites (axons and dendrites). However, conventional dMRI, based on single diffusion encoding (SDE), entangles microscopic anisotropy and orientation dispersion w...

Diffusion Magnetic Resonance Imaging (DMRI) is the only non-invasive imaging technique which is able to detect the principal directions of water diffusion as well as neurites density in the human brain. Exploiting the ability of Spherical Harmonics (SH) to model spherical functions, we propose a new reconstruction model for DMRI data which is able to estimate both the fiber Orientation Distribu...

Neurite orientation dispersion and density imaging (NODDI) enables more specific characterization of tissue microstructure by estimating neurite density (NDI) and orientation dispersion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. ...