Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders

Tax, Chantal M. W.; Genc, Sila; MacIver, Claire; Nilsson, Markus; Wardle, Mark; Szczepankiewicz, Filip; Jones, Derek K.; Peall, Kathryn J.

doi:10.1016/j.nicl.2023.103419

Cited by 2 publications

(1 citation statement)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that this difference could also be attributed to the differences between the spinal cord and the rest of the brain. Other recent diffusion studies conducted with high b -values diffusion weighting 89,90 also highlight a very low diffusivity compartment especially present in the gray matter human cerebellum with a proportion of up to 15 % 90,91 which was attributed to cell bodies and thus intracellular water pools. Additional works demonstrate that such contrast can also be achieved with b-values up to 4 ms/µm 2 only.…”

Section: Discussionmentioning

confidence: 88%

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

Yon,

Narvaez,

Topgaard

et al. 2024

Preprint

View full text Add to dashboard Cite

Massively Multidimensional Diffusion MRI combines tensor-valued encoding, oscillating gradients, and diffusion-relaxation correlation to provide multicomponent sub-voxel parameters depicting the tissue microstructure. This method was successfully implementedex vivoin micro-imaging systems and in clinical conditions but with a reduced diffusion frequency (ω) range due to the use of classical tensor-valued encoding. We demonstrate here its preclinicalin vivoimplementation with a protocol of 389 contrast images probing a wide diffusion frequency range of 18 to 92 Hz atb-values up to 2.1 ms/µm2enabled by the use of modulated gradient waveforms and combined with multislice high-resolution and low-distortion EPI acquisition with segmented and full reversed phase-encode acquisition. This framework allows the identification of diffusionω-dependence in the rat cerebellum and olfactory bulb gray matter (GM) and the parameter distributions are shown to resolve two water pools in GM with different diffusion coefficients, shapes,ω-dependence, relaxation rates, and spatial repartition whose attribution to specific microstructure could modify the current understanding of the origin of restriction in GM.

show abstract

Section: Discussionmentioning

confidence: 88%

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

Yon,

Narvaez,

Topgaard

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R₁‐R₂ distributions MRI

Yon,

Narvaez,

Topgaard

et al. 2024

NMR in Biomedicine

View full text Add to dashboard Cite

Massively multidimensional diffusion magnetic resonance imaging combines tensor‐valued encoding, oscillating gradients, and diffusion‐relaxation correlation to provide multicomponent subvoxel parameters depicting some tissue microstructural features. This method was successfully implemented ex vivo in microimaging systems and clinical conditions with tensor‐valued gradient waveform of variable duration giving access to a narrow diffusion frequency (ω) range. We demonstrate here its preclinical in vivo implementation with a protocol of 389 contrast images probing a wide diffusion frequency range of 18 to 92 Hz at b‐values up to 2.1 ms/μm2 enabled by the use of modulated gradient waveforms and combined with multislice high‐resolution and low‐distortion echo planar imaging acquisition with segmented and full reversed phase‐encode acquisition. This framework allows the identification of diffusion ω‐dependence in the rat cerebellum and olfactory bulb gray matter (GM), and the parameter distributions are shown to resolve two water pools in the cerebellum GM with different diffusion coefficients, shapes, ω‐dependence, relaxation rates, and spatial repartition whose attribution to specific microstructure could modify the current understanding of the origin of restriction in GM.

show abstract

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders

Cited by 2 publications

References 49 publications

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R₁‐R₂ distributions MRI

Contact Info

Product

Resources

About

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders

Cited by 2 publications

References 49 publications

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

In vivorat-brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI

In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R1‐R2 distributions MRI

Contact Info

Product

Resources

About

In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)‐R₁‐R₂ distributions MRI