title: Compressive sensing could accelerate 1H MR metabolic imaging in the clinic.
abstract: OBJECTIVE
  To retrospectively evaluate the fidelity of magnetic resonance (MR) spectroscopic imaging data preservation at a range of accelerations by using compressed sensing.
  
  
  METHODS
  The protocols were approved by the institutional review board of the university, and written informed consent to acquire and analyze MR spectroscopic imaging data was obtained from the subjects prior to the acquisitions. This study was HIPAA compliant. Retrospective application of compressed sensing was performed on 10 clinical MR spectroscopic imaging data sets, yielding 600 voxels from six normal brain data sets, 163 voxels from two brain tumor data sets, and 36 voxels from two prostate cancer data sets for analysis. The reconstructions were performed at acceleration factors of two, three, four, five, and 10 and were evaluated by using the root mean square error (RMSE) metric, metabolite maps (choline, creatine, N-acetylaspartate [NAA], and/or citrate), and statistical analysis involving a voxelwise paired t test and one-way analysis of variance for metabolite maps and ratios for comparison of the accelerated reconstruction with the original case.
  
  
  RESULTS
  The reconstructions showed high fidelity for accelerations up to 10 as determined by the low RMSE (< 0.05). Similar means of the metabolite intensities and hot-spot localization on metabolite maps were observed up to a factor of five, with lack of statistically significant differences compared with the original data. The metabolite ratios of choline to NAA and choline plus creatine to citrate did not show significant differences from the original data for up to an acceleration factor of five in all cases and up to that of 10 for some cases.
  
  
  CONCLUSIONS
  A reduction of acquisition time by up to 80%, with negligible loss of information as evaluated with clinically relevant metrics, has been successfully demonstrated for hydrogen 1 MR spectroscopic imaging.
authors.affiliation: Joint Graduate Program in Biomedical Engineering, UT Arlington and UT Southwestern Medical Center, Dallas, Tex, USA.
authors.forename: Sairam
authors.initials: S
authors.lastname: Geethanath
authors.forename: Hyeon-Man
authors.initials: HM
authors.lastname: Baek
authors.forename: Sandeep K
authors.initials: SK
authors.lastname: Ganji
authors.forename: Yao
authors.initials: Y
authors.lastname: Ding
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Maher
authors.forename: Robert D
authors.initials: RD
authors.lastname: Sims
authors.forename: Changho
authors.initials: C
authors.lastname: Choi
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Lewis
authors.forename: Vikram D
authors.initials: VD
authors.lastname: Kodibagkar
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001224:Aspartic Acid / Q000031:analogs & derivatives / Q000378:metabolism; D001932:Brain Neoplasms / Q000378:metabolism*; D002794:Choline / Q000378:metabolism; D019343:Citric Acid / Q000378:metabolism; D003401:Creatine / Q000378:metabolism; D044962:Data Compression; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008297:Male; D011471:Prostatic Neoplasms / Q000378:metabolism*; D012189:Retrospective Studies
chemical_list: D019343:Citric Acid; D001224:Aspartic Acid; C000179:N-acetylaspartate; D003401:Creatine; D002794:Choline