Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detailCitation formats

  • External authors:
  • H. Lundell
  • M. Nilsson
  • T. B. Dyrby
  • F-L Zhou
  • D. Topgaard
  • S. Lasic

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Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail. / Lundell, H.; Nilsson, M.; Dyrby, T. B.; Parker, G. J. M.; Cristinacce, P. L. Hubbard; Zhou, F-L; Topgaard, D.; Lasic, S.

In: Scientific Reports, Vol. 9, 21.06.2019.

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Lundell, H. ; Nilsson, M. ; Dyrby, T. B. ; Parker, G. J. M. ; Cristinacce, P. L. Hubbard ; Zhou, F-L ; Topgaard, D. ; Lasic, S. / Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail. In: Scientific Reports. 2019 ; Vol. 9.

Bibtex

@article{fa1f978a10094a58b0b8785b7455ca5d,
title = "Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail",
abstract = "Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.",
author = "H. Lundell and M. Nilsson and Dyrby, {T. B.} and Parker, {G. J. M.} and Cristinacce, {P. L. Hubbard} and F-L Zhou and D. Topgaard and S. Lasic",
year = "2019",
month = jun,
day = "21",
doi = "10.1038/s41598-019-45235-7",
language = "English",
volume = "9",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail

AU - Lundell, H.

AU - Nilsson, M.

AU - Dyrby, T. B.

AU - Parker, G. J. M.

AU - Cristinacce, P. L. Hubbard

AU - Zhou, F-L

AU - Topgaard, D.

AU - Lasic, S.

PY - 2019/6/21

Y1 - 2019/6/21

N2 - Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

AB - Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

U2 - 10.1038/s41598-019-45235-7

DO - 10.1038/s41598-019-45235-7

M3 - Article

VL - 9

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

ER -