Retaining information from multidimensional correlation MRI using a spectral regions of interest generator

Abstract Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensiona...

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Autores principales:	Kristofor Pas, Michal E. Komlosh, Daniel P. Perl, Peter J. Basser, Dan Benjamini
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/81dd5001ccb5418baea0cb303d41b24b
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spelling	oai:doaj.org-article:81dd5001ccb5418baea0cb303d41b24b2021-12-02T16:23:09ZRetaining information from multidimensional correlation MRI using a spectral regions of interest generator10.1038/s41598-020-60092-52045-2322https://doaj.org/article/81dd5001ccb5418baea0cb303d41b24b2020-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-60092-5https://doaj.org/toc/2045-2322Abstract Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensional MR scalar images are replaced with spatially resolved multidimensional spectra. The ensuing abundance in microstructural and chemical information is a blessing that incorporates a real challenge: how does one distill and refine it into images while retaining its significant components? In this paper we introduce a general framework that preserves the spectral information from spatially resolved multidimensional data. Equal weight is given to significant spectral components at the single voxel level, resulting in a summarized image spectrum. This spectrum is then used to define spectral regions of interest that are utilized to reconstruct images of sub-voxel components. Using numerical simulations we first show that, contrary to the conventional approach, the proposed framework preserves spectral resolution, and in turn, sensitivity and specificity of the reconstructed images. The retained spectral resolution allows, for the first time, to observe an array of distinct $${T}_{1}$$ T1 −$${T}_{2}$$ T2 −$$\langle D\rangle $$ ⟨D⟩ components images of the human brain. The robustly generated images of sub-voxel components overcome the limited spatial resolution of MRI, thus advancing multidimensional correlation MRI to fulfilling its full potential.Kristofor PasMichal E. KomloshDaniel P. PerlPeter J. BasserDan BenjaminiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kristofor Pas Michal E. Komlosh Daniel P. Perl Peter J. Basser Dan Benjamini Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
description	Abstract Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensional MR scalar images are replaced with spatially resolved multidimensional spectra. The ensuing abundance in microstructural and chemical information is a blessing that incorporates a real challenge: how does one distill and refine it into images while retaining its significant components? In this paper we introduce a general framework that preserves the spectral information from spatially resolved multidimensional data. Equal weight is given to significant spectral components at the single voxel level, resulting in a summarized image spectrum. This spectrum is then used to define spectral regions of interest that are utilized to reconstruct images of sub-voxel components. Using numerical simulations we first show that, contrary to the conventional approach, the proposed framework preserves spectral resolution, and in turn, sensitivity and specificity of the reconstructed images. The retained spectral resolution allows, for the first time, to observe an array of distinct $${T}_{1}$$ T1 −$${T}_{2}$$ T2 −$$\langle D\rangle $$ ⟨D⟩ components images of the human brain. The robustly generated images of sub-voxel components overcome the limited spatial resolution of MRI, thus advancing multidimensional correlation MRI to fulfilling its full potential.
format	article
author	Kristofor Pas Michal E. Komlosh Daniel P. Perl Peter J. Basser Dan Benjamini
author_facet	Kristofor Pas Michal E. Komlosh Daniel P. Perl Peter J. Basser Dan Benjamini
author_sort	Kristofor Pas
title	Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
title_short	Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
title_full	Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
title_fullStr	Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
title_full_unstemmed	Retaining information from multidimensional correlation MRI using a spectral regions of interest generator
title_sort	retaining information from multidimensional correlation mri using a spectral regions of interest generator
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/81dd5001ccb5418baea0cb303d41b24b
work_keys_str_mv	AT kristoforpas retaininginformationfrommultidimensionalcorrelationmriusingaspectralregionsofinterestgenerator AT michalekomlosh retaininginformationfrommultidimensionalcorrelationmriusingaspectralregionsofinterestgenerator AT danielpperl retaininginformationfrommultidimensionalcorrelationmriusingaspectralregionsofinterestgenerator AT peterjbasser retaininginformationfrommultidimensionalcorrelationmriusingaspectralregionsofinterestgenerator AT danbenjamini retaininginformationfrommultidimensionalcorrelationmriusingaspectralregionsofinterestgenerator
_version_	1718384179557695488

Retaining information from multidimensional correlation MRI using a spectral regions of interest generator

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