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Multiparametric imaging with heterogeneous radiofrequency fields
Magnetic resonance imaging (MRI) has become an unrivalled medical diagnostic technique able to map tissue anatomy and physiology non-invasively. MRI measurements are meticulously engineered to control experimental conditions across the sample. However, residual radiofrequency (RF) field inhomogeneit...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990694/ https://www.ncbi.nlm.nih.gov/pubmed/27526996 http://dx.doi.org/10.1038/ncomms12445 |
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author | Cloos, Martijn A. Knoll, Florian Zhao, Tiejun Block, Kai T. Bruno, Mary Wiggins, Graham C. Sodickson, Daniel K. |
author_facet | Cloos, Martijn A. Knoll, Florian Zhao, Tiejun Block, Kai T. Bruno, Mary Wiggins, Graham C. Sodickson, Daniel K. |
author_sort | Cloos, Martijn A. |
collection | PubMed |
description | Magnetic resonance imaging (MRI) has become an unrivalled medical diagnostic technique able to map tissue anatomy and physiology non-invasively. MRI measurements are meticulously engineered to control experimental conditions across the sample. However, residual radiofrequency (RF) field inhomogeneities are often unavoidable, leading to artefacts that degrade the diagnostic and scientific value of the images. Here we show that, paradoxically, these artefacts can be eliminated by deliberately interweaving freely varying heterogeneous RF fields into a magnetic resonance fingerprinting data-acquisition process. Observations made based on simulations are experimentally confirmed at 7 Tesla (T), and the clinical implications of this new paradigm are illustrated with in vivo measurements near an orthopaedic implant at 3T. These results show that it is possible to perform quantitative multiparametric imaging with heterogeneous RF fields, and to liberate MRI from the traditional struggle for control over the RF field uniformity. |
format | Online Article Text |
id | pubmed-4990694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49906942016-09-01 Multiparametric imaging with heterogeneous radiofrequency fields Cloos, Martijn A. Knoll, Florian Zhao, Tiejun Block, Kai T. Bruno, Mary Wiggins, Graham C. Sodickson, Daniel K. Nat Commun Article Magnetic resonance imaging (MRI) has become an unrivalled medical diagnostic technique able to map tissue anatomy and physiology non-invasively. MRI measurements are meticulously engineered to control experimental conditions across the sample. However, residual radiofrequency (RF) field inhomogeneities are often unavoidable, leading to artefacts that degrade the diagnostic and scientific value of the images. Here we show that, paradoxically, these artefacts can be eliminated by deliberately interweaving freely varying heterogeneous RF fields into a magnetic resonance fingerprinting data-acquisition process. Observations made based on simulations are experimentally confirmed at 7 Tesla (T), and the clinical implications of this new paradigm are illustrated with in vivo measurements near an orthopaedic implant at 3T. These results show that it is possible to perform quantitative multiparametric imaging with heterogeneous RF fields, and to liberate MRI from the traditional struggle for control over the RF field uniformity. Nature Publishing Group 2016-08-16 /pmc/articles/PMC4990694/ /pubmed/27526996 http://dx.doi.org/10.1038/ncomms12445 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Cloos, Martijn A. Knoll, Florian Zhao, Tiejun Block, Kai T. Bruno, Mary Wiggins, Graham C. Sodickson, Daniel K. Multiparametric imaging with heterogeneous radiofrequency fields |
title | Multiparametric imaging with heterogeneous radiofrequency fields |
title_full | Multiparametric imaging with heterogeneous radiofrequency fields |
title_fullStr | Multiparametric imaging with heterogeneous radiofrequency fields |
title_full_unstemmed | Multiparametric imaging with heterogeneous radiofrequency fields |
title_short | Multiparametric imaging with heterogeneous radiofrequency fields |
title_sort | multiparametric imaging with heterogeneous radiofrequency fields |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990694/ https://www.ncbi.nlm.nih.gov/pubmed/27526996 http://dx.doi.org/10.1038/ncomms12445 |
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