Abstract
Four-dimensional (4D) Magnetic Resonance Spectroscopic Imaging (MRSI) data combining 2 spatial and 2 spectral dimensions provides valuable biochemical information in vivo; however, its 20–40 min acquisition time is too long to be used for a clinical protocol. Data acquisition can be accelerated by non-uniformly under-sampling (NUS) the ky− t1 plane, but this causes artifacts in the spatial-spectral domain that must be removed by non-linear, iterative reconstruction. Previous work has demonstrated the feasibility of accelerating 4D MRSI data acquisition through NUS and iterative reconstruction using Compressed Sensing (CS), Total Variation (TV), and Maximum Entropy (MaxEnt) reconstruction. Group Sparse (GS) reconstruction is a variant of CS that exploits the structural sparsity of transform coefficients to achieve higher acceleration factors than traditional CS. In this article, we derive a solution to the GS reconstruction problem within the Split Bregman iterative framework that uses arbitrary transform grouping patterns of overlapping or non-overlapping groups. The 4D Echo-Planar Correlated Spectroscopic Imaging (EP-COSI) gray matter brain phantom and in vivo brain data are retrospectively under-sampled 2×, 4×, 6×, 8×, and 10___ and reconstructed using CS, TV, MaxEnt, and GS with overlapping or non-overlapping groups. Results show that GS reconstruction with overlapping groups outperformed the other reconstruction methods at each NUS rate for both phantom and in vivo data. These results can potentially reduce the scan time of a 4D EP-COSI brain scan from 40 min to under 5 min in vivo.
Highlights
Magnetic Resonance Imaging (MRI) exploits the resonant frequency of 1 H protons within water in vivo to generate anatomical images of the human body
Because of the homogeneity of the phantom spectra, a single representative 2D spectrum was chosen to illustrate the qualitative effectiveness of each reconstruction method
The spectrum from the fully sampled phantom scan is shown in the top left of the figure and the 8× non-uniformly under-sampling (NUS) spectrum with zeros in place of missing samples is shown to its right
Summary
Magnetic Resonance Imaging (MRI) exploits the resonant frequency of 1 H protons within water in vivo to generate anatomical images of the human body. Magnetic Resonance Spectroscopic Imaging (MRSI) is a similar imaging technique to MRI; in lieu of the resonant frequency of 1 H protons in water, the resonant frequencies of 1 H protons in metabolites including, but not limited to, creatine (Cr), choline (Cho), glutamate (Glu), glutamine (Gln), lactate (Lac), aspartate (Asp), and N-acetyl-aspartate (NAA) are used to generate a metabolic image instead [1,2] Each of these metabolites has a unique resonance spectrum in vivo caused by their chemical environment and covalent bonding structure that can be used to identify and quantify their concentrations within each voxel [3]. 4D EP-COSI acquisitions are slow compared with most MRI sequences and can require up to 40 min for a typical scan, which is too long to be used on a routine clinical basis
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