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Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding

Diffusion tensor distribution (DTD) imaging builds on principles from diffusion, solid‐state and low‐field NMR spectroscopies, to quantify the contents of heterogeneous voxels as nonparametric distributions, with tensor “size”, “shape” and orientation having direct relations to corresponding microst...

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Autores principales: Yon, Maxime, de Almeida Martins, João P., Bao, Qingjia, Budde, Matthew D., Frydman, Lucio, Topgaard, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583469/
https://www.ncbi.nlm.nih.gov/pubmed/32812669
http://dx.doi.org/10.1002/nbm.4355
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author Yon, Maxime
de Almeida Martins, João P.
Bao, Qingjia
Budde, Matthew D.
Frydman, Lucio
Topgaard, Daniel
author_facet Yon, Maxime
de Almeida Martins, João P.
Bao, Qingjia
Budde, Matthew D.
Frydman, Lucio
Topgaard, Daniel
author_sort Yon, Maxime
collection PubMed
description Diffusion tensor distribution (DTD) imaging builds on principles from diffusion, solid‐state and low‐field NMR spectroscopies, to quantify the contents of heterogeneous voxels as nonparametric distributions, with tensor “size”, “shape” and orientation having direct relations to corresponding microstructural properties of biological tissues. The approach requires the acquisition of multiple images as a function of the magnitude, shape and direction of the diffusion‐encoding gradients, leading to long acquisition times unless fast image read‐out techniques like EPI are employed. While in previous in vivo human brain studies performed at 3 T this proved a viable option, porting these measurements to very high magnetic fields and/or to heterogeneous organs induces B (0)‐ and B (1)‐inhomogeneity artifacts that challenge the limits of EPI. To overcome such challenges, we demonstrate here that high spatial resolution DTD of mouse brain can be carried out at 15.2 T with a surface‐cryoprobe, by relying on SPatiotemporal ENcoding (SPEN) imaging sequences. These new acquisition and data‐processing protocols are demonstrated with measurements on in vivo mouse brain, and validated with synthetic phantoms designed to mimic the diffusion properties of white matter, gray matter and cerebrospinal fluid. While still in need of full extensions to 3D mappings and of scanning additional animals to extract more general physiological conclusions, this work represents another step towards the model‐free, noninvasive in vivo characterization of tissue microstructure and heterogeneity in animal models, at ≈0.1 mm resolutions.
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spelling pubmed-75834692020-10-29 Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding Yon, Maxime de Almeida Martins, João P. Bao, Qingjia Budde, Matthew D. Frydman, Lucio Topgaard, Daniel NMR Biomed Research Articles Diffusion tensor distribution (DTD) imaging builds on principles from diffusion, solid‐state and low‐field NMR spectroscopies, to quantify the contents of heterogeneous voxels as nonparametric distributions, with tensor “size”, “shape” and orientation having direct relations to corresponding microstructural properties of biological tissues. The approach requires the acquisition of multiple images as a function of the magnitude, shape and direction of the diffusion‐encoding gradients, leading to long acquisition times unless fast image read‐out techniques like EPI are employed. While in previous in vivo human brain studies performed at 3 T this proved a viable option, porting these measurements to very high magnetic fields and/or to heterogeneous organs induces B (0)‐ and B (1)‐inhomogeneity artifacts that challenge the limits of EPI. To overcome such challenges, we demonstrate here that high spatial resolution DTD of mouse brain can be carried out at 15.2 T with a surface‐cryoprobe, by relying on SPatiotemporal ENcoding (SPEN) imaging sequences. These new acquisition and data‐processing protocols are demonstrated with measurements on in vivo mouse brain, and validated with synthetic phantoms designed to mimic the diffusion properties of white matter, gray matter and cerebrospinal fluid. While still in need of full extensions to 3D mappings and of scanning additional animals to extract more general physiological conclusions, this work represents another step towards the model‐free, noninvasive in vivo characterization of tissue microstructure and heterogeneity in animal models, at ≈0.1 mm resolutions. John Wiley and Sons Inc. 2020-08-19 2020-11 /pmc/articles/PMC7583469/ /pubmed/32812669 http://dx.doi.org/10.1002/nbm.4355 Text en © 2020 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Yon, Maxime
de Almeida Martins, João P.
Bao, Qingjia
Budde, Matthew D.
Frydman, Lucio
Topgaard, Daniel
Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title_full Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title_fullStr Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title_full_unstemmed Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title_short Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
title_sort diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583469/
https://www.ncbi.nlm.nih.gov/pubmed/32812669
http://dx.doi.org/10.1002/nbm.4355
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