RESUMO
In this work, we introduce a super-resolution method that generates a high-resolution (HR) sodium (23 Na) image from simultaneously acquired low-resolution (LR) 23 Na density-weighted MRI and HR proton density, T1 , and T2 maps from proton (1 H) MR fingerprinting in the brain at 7 T. The core of our method is a partial least squares regression between the HR (1 H) images and the LR (23 Na) image. An iterative loop and deconvolution with the point spread function of each acquired image were included in the algorithm to generate a final HR 23 Na image without losing features from the LR 23 Na image. The method was applied to simultaneously acquired HR proton and LR sodium data with in-plane resolution ratios between sodium and proton data of 3.8 and 1.9 and the same slice thickness. Four volunteers were scanned to evaluate the method's performance. For the data with a resolution ratio of 3.8, the mean absolute difference between the generated and ground truth HR 23 Na images was in the range of 1.5%-7.2% of the ground truth with a multiscale structural similarity index (M-SSIM) of 0.93 ± 0.03. For the data with a resolution ratio of 1.9, the mean absolute difference was in the range of 4.8%-6.3% with an M-SSIM of 0.95 ± 0.01.
