Accelerated quantification of tissue sodium concentration in skeletal muscle tissue: quantitative capability of dictionary learning compressed sensing
Objective To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using 23 Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS). Materials and methods Simulations and in vivo 23 Na MRI examinations of calf muscle were performed with a nominal spatial resolution of...
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| Veröffentlicht in: | Magma (New York, N.Y.) Jg. 33; H. 4; S. 495 - 505 |
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01.08.2020
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| ISSN: | 0968-5243, 1352-8661, 1352-8661 |
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| Abstract | Objective
To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using
23
Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS).
Materials and methods
Simulations and in vivo
23
Na MRI examinations of calf muscle were performed with a nominal spatial resolution of
Δ
x
=
3.0
×
3.0
×
15.0
mm
3
. Fully sampled and three undersampled
23
Na 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 (< 4%) from the GT than results of the NUFFT reconstruction (> 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. |
|---|---|
| AbstractList | Objective
To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using
23
Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS).
Materials and methods
Simulations and in vivo
23
Na MRI examinations of calf muscle were performed with a nominal spatial resolution of
Δ
x
=
3.0
×
3.0
×
15.0
mm
3
. Fully sampled and three undersampled
23
Na 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 (< 4%) from the GT than results of the NUFFT reconstruction (> 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. To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using 23Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS).OBJECTIVETo accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using 23Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS).Simulations and in vivo 23Na MRI examinations of calf muscle were performed with a nominal spatial resolution of [Formula: see text]. 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.MATERIALS AND METHODSSimulations and in vivo 23Na MRI examinations of calf muscle were performed with a nominal spatial resolution of [Formula: see text]. 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.Reconstruction results of simulated data with optimized 3D-DLCS yielded a lower deviation (< 4%) from the GT than results of the NUFFT reconstruction (> 5%) and a lower standard deviation (SD). For in vivo measurements, a TSC of [Formula: see text] 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.RESULTSReconstruction results of simulated data with optimized 3D-DLCS yielded a lower deviation (< 4%) from the GT than results of the NUFFT reconstruction (> 5%) and a lower standard deviation (SD). For in vivo measurements, a TSC of [Formula: see text] 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.The optimized 3D-DLCS reconstruction enables accelerated TSC measurements with high quantification accuracy.DISCUSSIONThe optimized 3D-DLCS reconstruction enables accelerated TSC measurements with high quantification accuracy. To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS). Simulations and in vivo Na MRI examinations of calf muscle were performed with a nominal spatial resolution of [Formula: see text]. Fully sampled and three undersampled Na 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. Reconstruction results of simulated data with optimized 3D-DLCS yielded a lower deviation (< 4%) from the GT than results of the NUFFT reconstruction (> 5%) and a lower standard deviation (SD). For in vivo measurements, a TSC of [Formula: see text] 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. The optimized 3D-DLCS reconstruction enables accelerated TSC measurements with high quantification accuracy. |
| Author | Lachner, Sebastian Maier, Andreas Nagel, Armin M. Uder, Michael Gast, Lena V. Utzschneider, Matthias Behl, Nicolas G. R. |
| Author_xml | – sequence: 1 givenname: Matthias orcidid: 0000-0002-2242-4707 surname: Utzschneider fullname: Utzschneider, Matthias email: matthias.utzschneider@uk-erlangen.de organization: Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) – sequence: 2 givenname: Nicolas G. R. surname: Behl fullname: Behl, Nicolas G. R. organization: Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ) – sequence: 3 givenname: Sebastian surname: Lachner fullname: Lachner, Sebastian organization: Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) – sequence: 4 givenname: Lena V. surname: Gast fullname: Gast, Lena V. organization: Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) – sequence: 5 givenname: Andreas surname: Maier fullname: Maier, Andreas organization: Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) – sequence: 6 givenname: Michael surname: Uder fullname: Uder, Michael organization: Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) – sequence: 7 givenname: Armin M. surname: Nagel fullname: Nagel, Armin M. organization: Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31950390$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1016_j_zemedi_2020_10_003 crossref_primary_10_1002_jmri_27326 crossref_primary_10_1002_mrm_28428 crossref_primary_10_1016_j_mri_2023_12_011 crossref_primary_10_1002_mrm_29841 crossref_primary_10_1016_j_mri_2024_04_027 crossref_primary_10_1002_mrm_29721 crossref_primary_10_1016_j_pnmrs_2023_04_002 crossref_primary_10_1002_jmri_28029 crossref_primary_10_1186_s12891_022_05879_5 |
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| Keywords | Muscle Magnetic resonance imaging Sodium Skeletal Image reconstruction Compressed sensing |
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To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using
23
Na MRI and 3D dictionary-learning compressed sensing... To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using Na MRI and 3D dictionary-learning compressed sensing (3D-DLCS).... To accelerate tissue sodium concentration (TSC) quantification of skeletal muscle using 23Na MRI and 3D dictionary-learning compressed sensing... |
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| SubjectTerms | Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Computer Appl. in Life Sciences Health Informatics Imaging Medicine Medicine & Public Health Radiology Research Article Solid State Physics |
| Title | Accelerated quantification of tissue sodium concentration in skeletal muscle tissue: quantitative capability of dictionary learning compressed sensing |
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