ArticleScientific reports2024
Susceptibility-induced internal gradients reveal axon morphology and cause anisotropic effects in the diffusion-weighted MRI signal.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Axon Diameter Mapping From Myelin Water Diffusion MRI.IEEE transactions on medical imaging · 2026Article
- Axonal microstructure and compartmentalization impact the orientation and time dependence of mesoscopic transverse relaxation.Scientific reports · 2026Article
- Predicting Mesoscopic Larmor Frequency Shifts in White Matter With Diffusion MRI-A Monte Carlo Study in Axonal Phantoms.NMR in biomedicine · 2025Article
- MRI-scale histology validates spatial sensitivity of in-vivo MRI-based axon radius estimation.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- SpinWalk: A Monte Carlo simulator for MR-signal formation in inhomogeneous tissue.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Exploring white matter dynamics and morphology through interactive numerical phantoms: the White Matter Generator.Frontiers in neuroinformatics · 2024Article
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Authors and funding
6 authors.
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Abstract
Diffusion-weighted MRI is our most promising method for estimating microscopic tissue morphology in vivo. The signal acquisition is based on scanner-generated external magnetic gradients. However, it will also be affected by susceptibility-induced internal magnetic gradients caused by interactions between the tissue and the static magnetic field of the scanner. With 3D in silico experiments, we show how internal gradients cause morphology-, compartment-, and orientation-dependence of spin-echo and pulsed-gradient spin-echo experiments in myelinated axons. These effects surpass those observed with previous 2D modelling corresponding to straight cylinders. For an ex vivo monkey brain, we observe the orientation-dependence generated only when including non-circular cross-sections in the in silico morphological configurations, and find orientation-dependent deviation of up to 17% for diffusion tensor metrics. Interestingly, we find that the orientation-dependence not only biases the signal across different brain regions, but also carries a sensitivity to the morphology of axonal cross-sections which is not attainable by the idealised theoretical diffusion-weighted MRI signal.
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