LAUSR

Magnetic resonance spectroscopic imaging helps to determine abnormal brain tissue conditions by evaluating metabolite concentrations. Although a powerful technique, it is underutilized in routine clinical studies because of its long scan times. In this study, we evaluated the feasibility of scan time reduction in metabolic imaging using compressed-sensing-based MR spectroscopic imaging in pediatric patients undergoing routine brain exams. We retrospectively evaluated compressed-sensing reconstructions in MR spectroscopic imaging datasets from 20 pediatric patients (11 males, 9 females; average age: 5.4±4.5 years; age range: 3 days to 16 years). We performed retrospective under-sampling of the MR spectroscopic imaging datasets to simulate accelerations of 2-, 3-, 4-, 5-, 7- and 10-fold, with subsequent reconstructions in MATLAB. Metabolite maps of N-acetylaspartate, creatine, choline and lactate (where applicable) were quantitatively evaluated in terms of the root-mean-square error (RMSE), peak amplitudes and total scan time. We used the two-tailed paired t-test along with linear regression analysis to statistically compare the compressed-sensing reconstructions at each acceleration with the fully sampled reference dataset. High fidelity was maintained in the compressed-sensing MR spectroscopic imaging reconstructions from 50% to 80% under-sampling, with the RMSE not exceeding 3% in any dataset. Metabolite intensities and ratios evaluated on a voxel-by-voxel basis showed no statistically significant differences and mean metabolite intensities showed high correlation compared to the fully sampled reference dataset up to an acceleration factor of 5. Compressed-sensing MR spectroscopic imaging has the potential to reduce MR spectroscopic imaging scan times for pediatric patients, with negligible information loss.