Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Mar;89(3):1102-1116.
doi: 10.1002/mrm.29476. Epub 2022 Nov 13.

Influence of image contrasts and reconstruction methods on the classification of multiple sclerosis-like lesions in simulated sodium magnetic resonance imaging

Laurent Ruck  1 , Angelika Mennecke  2 , Tobias Wilferth  1 , Sebastian Lachner  1 , Max Müller  1 , Nico Egger  1 , Arnd Doerfler  2 , Michael Uder  1 , Armin M Nagel  1   3
Affiliations

Influence of image contrasts and reconstruction methods on the classification of multiple sclerosis-like lesions in simulated sodium magnetic resonance imaging

Laurent Ruck et al. Magn Reson Med. 2023 Mar.

Abstract

Purpose: To evaluate the classifiability of small multiple sclerosis (MS)-like lesions in simulated sodium (23 Na) MRI for different 23 Na MRI contrasts and reconstruction methods.

Methods: 23 Na MRI and 23 Na inversion recovery (IR) MRI of a phantom and simulated brain with and without lesions of different volumes (V = 1.3-38.2 nominal voxels) were simulated 100 times by adding Gaussian noise matching the SNR of real 3T measurements. Each simulation was reconstructed with four different reconstruction methods (Gridding without and with Hamming filter, Compressed sensing (CS) reconstruction without and with anatomical 1 H prior information). Based on the mean signals within the lesion volumes of simulations with and without lesions, receiver operating characteristics (ROC) were determined and the area under the curve (AUC) was calculated to assess the classifiability for each lesion volume.

Results: Lesions show higher classifiability in 23 Na MRI than in 23 Na IR MRI. For typical parameters and SNR of a 3T scan, the voxel normed minimal classifiable lesion volume (AUC > 0.9) is 2.8 voxels for 23 Na MRI and 19 voxels for 23 Na IR MRI, respectively. In terms of classifiability, Gridding with Hamming filter and CS without anatomical 1 H prior outperform CS reconstruction with anatomical 1 H prior.

Conclusion: Reliability of lesion classifiability strongly depends on the lesion volume and the 23 Na MRI contrast. Additional incorporation of 1 H prior information in the CS reconstruction was not beneficial for the classification of small MS-like lesions in 23 Na MRI.

Keywords: X-nuclei MRI; anatomical prior information; compressed sensing (CS); lesion classification; multiple sclerosis (MS); sodium (23Na).

PubMed Disclaimer

References

REFERENCES

    1. Madelin G, Regatte RR. Biomedical applications of sodium MRI in vivo. J Magn Reson Imaging. 2013;38:511-529.
    1. Huhn K, Engelhorn T, Linker RA, Nagel AM. Potential of sodium MRI as a biomarker for neurodegeneration and Neuroinflammation in multiple sclerosis. Front Neurol. 2019;10:84.
    1. Gerhalter T, Gast LV, Marty B, et al. 23Na MRI depicts early changes in ion homeostasis in skeletal muscle tissue of patients with duchenne muscular dystrophy. J Magn Reson Imaging. 2019;50:1103-1113.
    1. Grapperon A-M, Ridley B, Verschueren A, et al. Quantitative brain sodium MRI depicts corticospinal impairment in amyotrophic lateral sclerosis. Radiology. 2019;292:422-428.
    1. Hagiwara A, Bydder M, Oughourlian T, et al. Sodium MR Neuroimaging. AJNR Am J Neuroradiol. 2021;42:1920-1926.

Publication types

MeSH terms

LinkOut - more resources