Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T

TitleConsiderations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T
Publication TypeJournal Article
Year of Publication2017
AuthorsHatay, GH, Yildirim, M, Ozturk-Isik, E
JournalMed Biol Eng ComputMed Biol Eng ComputMed Biol Eng Comput
Volume55
Issue8
Pagination1303-1315
ISBN Number1741-0444 (Electronic)<br/>0140-0118 (Linking)
Accession Number27826817
Abstract

The purpose of this study was to apply compressed sensing method for accelerated phosphorus MR spectroscopic imaging (31P-MRSI) of human brain in vivo at 3T. Fast 31P-MRSI data of five volunteers were acquired on a 3T clinical MR scanner using pulse-acquire sequence with a pseudorandom undersampling pattern for a data reduction factor of 5.33 and were reconstructed using compressed sensing. Additionally, simulated 31P-MRSI human brain tumor datasets were created to analyze the effects of k-space sampling pattern, data matrix size, regularization parameters of the reconstruction, and noise on the compressed sensing accelerated 31P-MRSI data. The 31P metabolite peak ratios of the full and compressed sensing accelerated datasets of healthy volunteers in vivo were similar according to the results of a Bland-Altman test. The estimated effective spatial resolution increased with reduction factor and sampling more at the k-space center. A lower regularization parameter for both total variation and L1-norm penalties resulted in a better compressed sensing reconstruction of 31P-MRSI. Although the root-mean-square error increased with noise levels, the compressed sensing reconstruction was robust for up to a reduction factor of 10 for the simulated data that had sharply defined tumor borders. As a result, compressed sensing was successfully applied to accelerate 31P-MRSI of human brain in vivo at 3T.

Short TitleMedical & biological engineering & computingMedical & biological engineering & computing
Alternate JournalMedical & biological engineering & computing