Sairam Geethanath 1 , Hyeon-Man Baek , Sandeep K Ganji , Yao Ding , Elizabeth A Maher , Robert D Sims , Changho Choi , Matthew A Lewis , Vikram D Kodibagkar . Show Affiliations »
Abstract
PURPOSE: To retrospectively evaluate the fidelity of magnetic resonance (MR) spectroscopic imaging data preservation at a range of accelerations by using compressed sensing. MATERIALS AND 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. CONCLUSION: 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. © RSNA, 2012.
PURPOSE: To retrospectively evaluate the fidelity of magnetic resonance (MR) spectroscopic imaging data preservation at a range of accelerations by using compressed sensing. MATERIALS AND 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. CONCLUSION: 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. © RSNA, 2012.
Entities: Chemical
Disease
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Year: 2012
PMID: 22357898 PMCID: PMC3285227 DOI: 10.1148/radiol.11111098
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105