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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
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.
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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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