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Enhancing the spatial resolution of hyperpolarized carbonā€13 MRI of human brain metabolism using structure guidance

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Peer-reviewed

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Article

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Authors

Ehrhardt, Matthias J.  ORCID logo  https://orcid.org/0000-0001-8523-353X
Gallagher, Ferdia A. 
McLean, Mary A. 
Schƶnlieb, Carolaā€Bibiane 

Abstract

Purpose: Dynamic nuclear polarization is an emerging imaging method that allows noninvasive investigation of tissue metabolism. However, the relatively low metabolic spatial resolution that can be achieved limits some applications, and improving this resolution could have important implications for the technique. Methods: We propose to enhance the 3D resolution of carbonā€13 magnetic resonance imaging (13Cā€MRI) using the structural information provided by hydrogenā€1 MRI (1Hā€MRI). The proposed approach relies on variational regularization in 3D with a directional total variation regularizer, resulting in a convex optimization problem which is robust with respect to the parameters and can efficiently be solved by many standard optimization algorithms. Validation was carried out using an in silico phantom, an in vitro phantom and in vivo data from four human volunteers. Results: The clinical data used in this study were upsampled by a factor of 4 inā€plane and by a factor of 15 outā€ofā€plane, thereby revealing occult information. A key finding is that 3D superā€resolution shows superior performance compared to several 2D superā€resolution approaches: for example, for the in silico data, the meanā€squaredā€error was reduced by around 40% and for all data produced increased anatomical definition of the metabolic imaging. Conclusion: The proposed approach generates images with enhanced anatomical resolution while largely preserving the quantitative measurements of metabolism. Although the work requires clinical validation against tissue measures of metabolism, it offers great potential in the field of 13Cā€MRI and could significantly improve image quality in the future.

Description

Funder: Mark Foundation Institute for Cancer Research


Funder: Cambridge Experimental Cancer Medicine Centre


Funder: Alan Turing Institute; Id: http://dx.doi.org/10.13039/100012338


Funder: Cantab Capital Institute for the Mathematics of Information

Keywords

RESEARCH ARTICLE, RESEARCH ARTICLES, human brain, hyperpolarized 13C, magnetic resonance imaging, superā€resolution, variational regularization

Journal Title

Magnetic Resonance in Medicine

Conference Name

Journal ISSN

0740-3194
1522-2594

Volume Title

Publisher

Sponsorship
Leverhulme Trust (ECFā€2019ā€478, Philip Leverhulme Prize)
Wellcome Trust (RG98755)
Royal Society (Wolfson Fellowship)
H2020 European Research Council (777826)
National Institute for Health Research (Cambridge Biomedical Research Centre)
Cancer Research UK (C19212/A16628, C19212/A911376, C19212/A27150, C968)
Engineering and Physical Sciences Research Council (EP/S026045/1, EP/T026693/1, EP/T007745/1, EP/T0035)