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Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance
Nuclear magnetic resonance is a powerful tool for probing the structures of chemical and biological systems. Combined with field gradients it leads to NMR imaging (MRI), a widespread tool in non-invasive examinations. Sensitivity usually limits MRI’s spatial resolution to tens of micrometers, but ot...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468317/ https://www.ncbi.nlm.nih.gov/pubmed/28607445 http://dx.doi.org/10.1038/s41598-017-03277-9 |
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author | Álvarez, Gonzalo A. Shemesh, Noam Frydman, Lucio |
author_facet | Álvarez, Gonzalo A. Shemesh, Noam Frydman, Lucio |
author_sort | Álvarez, Gonzalo A. |
collection | PubMed |
description | Nuclear magnetic resonance is a powerful tool for probing the structures of chemical and biological systems. Combined with field gradients it leads to NMR imaging (MRI), a widespread tool in non-invasive examinations. Sensitivity usually limits MRI’s spatial resolution to tens of micrometers, but other sources of information like those delivered by constrained diffusion processes, enable one extract morphological information down to micron and sub-micron scales. We report here on a new method that also exploits diffusion – isotropic or anisotropic– to sense morphological parameters in the nm-mm range, based on distributions of susceptibility-induced magnetic field gradients. A theoretical framework is developed to define this source of information, leading to the proposition of internal gradient-distribution tensors. Gradient-based spin-echo sequences are designed to measure these new observables. These methods can be used to map orientations even when dealing with unconstrained diffusion, as is here demonstrated with studies of structured systems, including tissues. |
format | Online Article Text |
id | pubmed-5468317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54683172017-06-14 Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance Álvarez, Gonzalo A. Shemesh, Noam Frydman, Lucio Sci Rep Article Nuclear magnetic resonance is a powerful tool for probing the structures of chemical and biological systems. Combined with field gradients it leads to NMR imaging (MRI), a widespread tool in non-invasive examinations. Sensitivity usually limits MRI’s spatial resolution to tens of micrometers, but other sources of information like those delivered by constrained diffusion processes, enable one extract morphological information down to micron and sub-micron scales. We report here on a new method that also exploits diffusion – isotropic or anisotropic– to sense morphological parameters in the nm-mm range, based on distributions of susceptibility-induced magnetic field gradients. A theoretical framework is developed to define this source of information, leading to the proposition of internal gradient-distribution tensors. Gradient-based spin-echo sequences are designed to measure these new observables. These methods can be used to map orientations even when dealing with unconstrained diffusion, as is here demonstrated with studies of structured systems, including tissues. Nature Publishing Group UK 2017-06-12 /pmc/articles/PMC5468317/ /pubmed/28607445 http://dx.doi.org/10.1038/s41598-017-03277-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Álvarez, Gonzalo A. Shemesh, Noam Frydman, Lucio Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title | Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title_full | Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title_fullStr | Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title_full_unstemmed | Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title_short | Internal gradient distributions: A susceptibility-derived tensor delivering morphologies by magnetic resonance |
title_sort | internal gradient distributions: a susceptibility-derived tensor delivering morphologies by magnetic resonance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468317/ https://www.ncbi.nlm.nih.gov/pubmed/28607445 http://dx.doi.org/10.1038/s41598-017-03277-9 |
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