Diffusion Magnetic Resonance Imaging in Neurobiology

Diffusion magnetic resonance imaging (MRI) exploits the random motion of water molecules to probe the microstructural architecture of the living brain. By sensitising the MRI signal to molecular displacement, diffusion MRI reveals features of tissue organisation that are invisible to conventional imaging. In white matter, diffusion tensor imaging quantifies the preferred directional movement of water along axonal bundles, enabling tractography and mapping of long-range connectivity. More advanced multi-shell and multi-compartment models separate intra-axonal and extra-axonal contributions, yielding estimates of axon diameter distributions, neurite density and membrane permeability. In grey matter, high gradient strengths and specialised models capture soma size and neurite orientation, offering insights into cortical microstructure. These techniques have been applied to healthy development, ageing and a broad range of neurological disorders, including multiple sclerosis, Alzheimer’s disease and traumatic brain injury. Recent technical innovations—such as oscillating gradient waveforms, ultra-strong gradients and time-dependent diffusion encoding—have extended sensitivity to sub-micrometre structures and refined specificity to biophysical parameters. Together, these advances have established diffusion MRI as an indispensable tool for non-invasive characterisation of brain cytoarchitecture and connectivity, with growing impact on both basic neuroscience and clinical diagnostics.

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Diffusion Magnetic Resonance Imaging in Neurobiology publication trend

The graph below shows the total number of articles in diffusion magnetic resonance imaging in neurobiology across all publications each year (not limited to Nature Index journals).

Technical terms

Diffusion-weighted MRI: An imaging modality that sensitises the MR signal to the Brownian motion of water molecules, revealing tissue microstructure.

b-value: A parameter reflecting the strength and timing of diffusion sensitisation gradients; higher b-values increase sensitivity to restricted diffusion.

Axial and radial diffusivity: Measures of water diffusion parallel and perpendicular to axonal fibres, respectively, indicative of axon integrity and myelination.

Multi-compartment model: A mathematical framework that represents tissue as distinct water pools (e.g., intra-axonal, extra-axonal, soma) to extract specific microstructural parameters.

Spherical mean technique (SMT): A method that computes the orientationally averaged diffusion signal to remove the influence of fibre dispersion and isolate microscopic tissue features.

Soma and Neurite Density Imaging (SANDI): A biophysical model that explicitly includes cell bodies (soma) and neurites to quantify their respective signal fractions in grey matter.

References

1. Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI. Medical Image Analysis (2023).
2. Age‐related alterations in human cortical microstructure across the lifespan: Insights from high‐gradient diffusion MRI. Aging Cell (2024).
3. Multi-compartment microscopic diffusion imaging. NeuroImage (2016).
4. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. NeuroImage (2020).
5. Microstructural imaging of the human brain with a ‘super-scanner’: 10 key advantages of ultra-strong gradients for diffusion MRI. NeuroImage (2018).
6. PGSE, OGSE, and sensitivity to axon diameter in diffusion MRI: Insight from a simulation study. Magnetic Resonance in Medicine (2015).
7. Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications. Frontiers in Physics (2017).