Accelerated quantification of tissue sodium concentration in skeletal muscle tissue: quantitative capability of dictiona
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RESEARCH ARTICLE
Accelerated quantification of tissue sodium concentration in skeletal muscle tissue: quantitative capability of dictionary learning compressed sensing Matthias Utzschneider1,2 · Nicolas G. R. Behl3 · Sebastian Lachner1 · Lena V. Gast1 · Andreas Maier2 · Michael Uder1 · Armin M. Nagel1,3,4 Received: 18 July 2019 / Revised: 22 November 2019 / Accepted: 17 December 2019 © European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2020, corrected publication 2020
Abstract Objective To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using 23Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS). Materials and methods Simulations and in vivo 23Na MRI examinations of calf muscle were performed with a nominal spatial resolution of Δx = (3.0 × 3.0 × 15.0) mm3 . Fully sampled and three undersampled 23Na MRI data sets (undersampling factors (USF) = 3, 4.4, 6.7) were evaluated. Ten healthy subjects were examined on a 3 Tesla MRI system. Results of the simulation study and the in vivo measurements were compared to the ground truth (GT) and the fully sampled fast Fourier transform (NUFFT) reconstruction, respectively. Results Reconstruction results of simulated data with optimized 3D-DLCS yielded a lower deviation ( 5%) and a lower standard deviation (SD). For in vivo measurements, a TSC of 17 ± 2.7 mMol/l was observed. The mean deviation from the reference is lower for the undersampled 3D-DLCS reconstructions (3.4%) than for NUFFT reconstructions (4.6%). SD is reduced using 3D-DLCS. Compared to a fully sampled NUFFT reconstruction, acquisition time could be reduced by a factor of 4.4 while maintaining similar quantitative accuracy. Discussion The optimized 3D-DLCS reconstruction enables accelerated TSC measurements with high quantification accuracy. Keywords Magnetic resonance imaging · Muscle · Skeletal · Sodium · Image reconstruction · Compressed sensing
Introduction Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10334-019-00819-2) contains supplementary material, which is available to authorized users. * Matthias Utzschneider matthias.utzschneider@uk‑erlangen.de 1
Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Maximiliansplatz 3, 91054 Erlangen, Germany
2
Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
3
Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
4
Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
The muscular sodium concentration has been investigated in several studies [1–6]. In myopathies and muscular channelopathies, an elevated tissue sodium concentration (TSC) seems to play an important role in disease progression [6–8]. In future, the TSC might evolve into an important biomarker to examine pathological processes or p
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