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The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity
Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) frame...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619933/ https://www.ncbi.nlm.nih.gov/pubmed/37910622 http://dx.doi.org/10.1126/sciadv.adh9853 |
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author | Dvorak, Adam V. Kumar, Dushyant Zhang, Jing Gilbert, Guillaume Balaji, Sharada Wiley, Neale Laule, Cornelia Moore, G.R. Wayne MacKay, Alex L. Kolind, Shannon H. |
author_facet | Dvorak, Adam V. Kumar, Dushyant Zhang, Jing Gilbert, Guillaume Balaji, Sharada Wiley, Neale Laule, Cornelia Moore, G.R. Wayne MacKay, Alex L. Kolind, Shannon H. |
author_sort | Dvorak, Adam V. |
collection | PubMed |
description | Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications. |
format | Online Article Text |
id | pubmed-10619933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-106199332023-11-02 The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity Dvorak, Adam V. Kumar, Dushyant Zhang, Jing Gilbert, Guillaume Balaji, Sharada Wiley, Neale Laule, Cornelia Moore, G.R. Wayne MacKay, Alex L. Kolind, Shannon H. Sci Adv Physical and Materials Sciences Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications. American Association for the Advancement of Science 2023-11-01 /pmc/articles/PMC10619933/ /pubmed/37910622 http://dx.doi.org/10.1126/sciadv.adh9853 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Dvorak, Adam V. Kumar, Dushyant Zhang, Jing Gilbert, Guillaume Balaji, Sharada Wiley, Neale Laule, Cornelia Moore, G.R. Wayne MacKay, Alex L. Kolind, Shannon H. The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title | The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title_full | The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title_fullStr | The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title_full_unstemmed | The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title_short | The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity |
title_sort | calipr framework for highly accelerated myelin water imaging with improved precision and sensitivity |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619933/ https://www.ncbi.nlm.nih.gov/pubmed/37910622 http://dx.doi.org/10.1126/sciadv.adh9853 |
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