Volumetric Patch-Based Super-Resolution Reconstruction of Hyperpolarized C Cardiac MRI.

The achievable spatial resolution of C metabolic images acquired with hyperpolarized C-pyruvate is worse than H images typically by an order of magnitude due to the rapidly decaying hyperpolarized signals and the low gyromagnetic ratio of C. This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution C cardiac MRI by utilizing structural information from H MRI. The reconstruction procedure comprises anatomical segmentation from high-resolution H MRI, calculation of a patch-based weight matrix, and iterative reconstruction of high-resolution multi-slice C MRI. The method was tested with a multi-compartmental digital phantom for optimizing the patch size and an anthropomorphic cardiac MR phantom for validating the performance. Finally, the method was applied to human cardiac C images, acquired with an injection of hyperpolarized [1-C]pyruvate. The phantom studies demonstrated that high-resolution multi-slice C images, reconstructed from a single-slice low-resolution input C image, retained the signal intensity range. The reconstruction accuracy was asymptotically improved as the patch size increased whereas intra-segmental spatial fluctuations were preserved better with smaller patches. However, a structurally non-identified tissue region was not restored regardless of the patch size. The cardiac MR phantom and the human cardiac images demonstrated improved spatial resolutions in the reconstructed images (10 × 10 × 30 mm/voxel to 2 × 2 × 5 mm/voxel). The volumetric patch-based super-resolution method reconstructs multi-slice high-resolution of C images, enhancing the cardiac structure, while preserving the quantitative accuracy. The proposed method is applicable to other multi-modal images that suffer from limited spatial resolution.