Improved phosphorus MRSI acquisition through compressed sensing acceleration combined with low-rank reconstruction.

Details

Serval ID
serval:BIB_FADBE8F854E9
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Improved phosphorus MRSI acquisition through compressed sensing acceleration combined with low-rank reconstruction.
Journal
Magma
Author(s)
Songeon J., Lazeyras F., Agius T., Dabrowski O., Ruttimann R., Toso C., Longchamp A., Klauser A., Courvoisier S.
ISSN
1352-8661 (Electronic)
ISSN-L
0968-5243
Publication state
In Press
Peer-reviewed
Oui
Language
english
Notes
Publication types: Journal Article
Publication Status: aheadofprint
Abstract
Phosphorus-31 magnetic resonance spectroscopic imaging ( <sup>31</sup> P-MRSI) is a non-invasive tool for assessing cellular high-energy metabolism in-vivo. However, its acquisition suffers from a low sensitivity, which necessitates large voxel sizes or multiple averages to achieve an acceptable signal-to-noise ratio (SNR), resulting in long scan times.
To overcome these limitations, we propose an acquisition and reconstruction scheme for FID-MRSI sequences. Specifically, we employed Compressed Sensing (CS) and Low-Rank (LR) with Total Generalized Variation (TGV) regularization in a combined CS-LR framework. Additionally, we used a novel approach to k-space undersampling that utilizes distinct pseudo-random patterns for each average. To evaluate the proposed method's performance, we performed a retrospective analysis on healthy volunteers' brains and ex-vivo perfused kidneys.
The presented method effectively improves the SNR two-to-threefold while preserving spectral and spatial quality even with threefold acceleration. We were able to recover signal attenuation of anatomical information, and the SNR improvement was obtained while maintaining the metabolites peaks linewidth.
We presented a novel combined CS-LR acceleration and reconstruction method for FID-MRSI sequences, utilizing a unique approach to k-space undersampling. Our proposed method has demonstrated promising results in enhancing the SNR making it applicable for reducing acquisition time.
Keywords
Acceleration, Compressed sensing, Low rank, Phosphorus magnetic resonance spectroscopic imaging (31P-MRSI), Regularization
Pubmed
Web of science
Open Access
Yes
Create date
08/01/2025 14:54
Last modification date
09/01/2025 7:04
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