Orientationally invariant indices of axon diameter and density from diffusion MRI

By Daniel C. Alexander, Penny L. Hubbard Cristinacce, Matt G. Hall, Elizabeth A. Moore, Maurice Ptito, G. Parker, Tim Bjørn Dyrby. NeuroImage, 2010

749 citations recorded by the source corpus.

Subfields: Orthopedics and Sports Medicine, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/e7b8534aafff0d84ad9eafe54c04e9284b7220df

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In Orthopedics and Sports Medicine

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Citations in the corpus

Advances in diffusion MRI acquisition and processing in the Human Connectome Project (2013, methodology): “Furthermore, we focused on schemes optimised for angular coverage, which is important for fibre orientation estimation and the connectome reconstruction; rather than considering more specialised schemes that are used, for instance, in microstructure imaging (Alexander et al., 2010).”
White matter characterization with diffusional kurtosis imaging (2011, methodology): “This is in contrast to other advanced diffusion models, based on high b-value and/or many gradient directions, aiming to characterize the axon diameter, diameter distribution or fiber orientation distribution (Alexander et al., 2010; Assaf et al., 2008; Barazany et al., 2009; Jespersen et al., 2010)”
Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data (2015, methodology): “…the estimated coef ﬁ cients x into [ x r | x h | x i ], the intra-axonal volume fraction ν ′ and the indices of axon diameter a ′ and density ρ ′ , de ﬁ ned in Alexander et al. (2010), can be expressed as: where, for j ∈ {1, … , N r }, we denote with R j the radius of the cylinders…”
Multi-compartment microscopic diffusion imaging (2016, background): “Further, in contrast to the in-vivo human data sets, we observe, at a b-value of 6000 s/mm2, a relatively high diffusion signal for gradient directions parallel to the main fibre orientation in the corpus callosum and other white matter regions, suggesting the presence of a signal component of very ”
Imaging brain microstructure with diffusion MRI: practicality and applications (2019, background): “alternative, for example, regarding axon diameter estimation in humans.(11) Resections in patients with e.”
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain (2012, methodology): “Although important for estimating weak parameters like the axon diameter index in (Alexander et al., 2010), for the NODDI model, the MCMC has a negligible effect on the accuracy of our fitted model parameters.”
Apparent Fibre Density: A novel measure for the analysis of diffusion-weighted magnetic resonance images (2012, methodology): “The AFD is based on the widely-used assumption that intra-axonal water is restricted in the radial direction (Stanisz et al., Jan., 1997; Alexander, Aug., 2008; Alexander et al., 2010; Assaf and Basser, 2005; Assaf et al., 2008; Barazany et al., May, 2009).”
Model-based analysis of multi-shell diffusion MR data for tractography: How to get over fitting problems (2012, neutral): “This model has been suggested previously to account for physical compartments where water is trapped so the diffusion coefficient is effectively zero [21].”
Investigating white matter fibre density and morphology using fixel-based analysis (2017, methodology): “…volume would provide additional information and potentially more biologically meaningful metrics, however current approaches to estimate axon diameters using DWI are not able to assign estimates to individual fixels in crossing fibre regions (Alexander et al., 2010; Assaf et al., 2008).”
Compartment models of the diffusion MR signal in brain white matter: A taxonomy and comparison (2012, positive): “This supports observations in both Stanisz et al. (1997) and Alexander et al. (2010).”
The Human Connectome Project and Beyond: Initial Applications of 300 mT/m Gradients (2013, methodology): “Despite this, at least one group has now demonstrated estimation of an axon diameter index, a′, in the in vivo human brain using a standard clinical gradient strength of 40–60 mT/m (Alexander et al., 2010; Zhang et al., 2011).”
Graph analysis of the human connectome: Promise, progress, and pitfalls (2013, positive): “, 2010) or diffusion-based estimates of axonal structure (Alexander et al., 2010; Assaf et al., 2008).”