Combining parallel detection of proton echo planar spectroscopic imaging (PEPSI) measurements with a data-consistency constraint improves SNR.
One major challenge of MRSI is the poor signal-to-noise ratio (SNR), which can be improved by using a surface coil array. Here we propose to exploit the spatial sensitivity of different channels of a coil array to enforce the k-space data consistency (DC) in order to suppress noise and consequently to improve MRSI SNR. MRSI data were collected using a proton echo planar spectroscopic imaging (PEPSI) sequence at 3 T using a 32-channel coil array and were averaged with one, two and eight measurements (avg-1, avg-2 and avg-8). The DC constraint was applied using a regularization parameter λ of 1, 2, 3, 5 or 10. Metabolite concentrations were quantified using LCModel. Our results show that the suppression of noise by applying the DC constraint to PEPSI reconstruction yields up to 32% and 27% SNR gain for avg-1 and avg-2 data with λ = 5, respectively. According to the reported Cramer-Rao lower bounds, the improvement in metabolic fitting was significant (p < 0.01) when the DC constraint was applied with λ ≥ 2. Using the DC constraint with λ = 3 or 5 can minimize both root-mean-square errors and spatial variation for all subjects using the avg-8 data set as reference values. Our results suggest that MRSI reconstructed with a DC constraint can save around 70% of scanning time to obtain images and spectra with similar SNRs using λ = 5.
Graduate Institute of Applied Physics, National Chengchi University, Taipei, Taiwan.|Research Center for Mind, Brain and Learning, National Chengchi University, Taipei, Taiwan.
Shang-Yueh
SY
Tsai
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.
Yi-Cheng
YC
Hsu
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.
Ying-Hua
YH
Chu
Institute of Neuroscience, National Yang Ming University, Taipei, Taiwan.
Wen-Jui
WJ
Kuo
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.|Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland.
Fa-Hsuan
FH
Lin
D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000378:metabolism*; D017352:Echo-Planar Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008297:Male; D057054:Molecular Imaging / Q000379:methods*; D066244:Proton Magnetic Resonance Spectroscopy / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio
SNR; data consistency; proton echo planar spectroscopy imaging; regularization