Three-dimensional inversion recovery manganese-enhanced MRI of mouse brain using super-resolution reconstruction to visualize nuclei involved in higher brain function

The visualization of activity in mouse brain using inversion recovery spin echo (IR‐SE) manganese‐enhanced MRI (MEMRI) provides unique contrast, but suffers from poor resolution in the slice‐encoding direction. Super‐resolution reconstruction (SRR) is a resolution‐enhancing post‐processing technique in which multiple low‐resolution slice stacks are combined into a single volume of high isotropic resolution using computational methods. In this study, we investigated, first, whether SRR can improve the three‐dimensional resolution of IR‐SE MEMRI in the slice selection direction, whilst maintaining or improving the contrast‐to‐noise ratio of the two‐dimensional slice stacks. Second, the contrast‐to‐noise ratio of SRR IR‐SE MEMRI was compared with a conventional three‐dimensional gradient echo (GE) acquisition. Quantitative experiments were performed on a phantom containing compartments of various manganese concentrations. The results showed that, with comparable scan times, the signal‐to‐noise ratio of three‐dimensional GE acquisition is higher than that of SRR IR‐SE MEMRI. However, the contrast‐to‐noise ratio between different compartments can be superior with SRR IR‐SE MEMRI, depending on the chosen inversion time. In vivo experiments were performed in mice receiving manganese using an implanted osmotic pump. The results showed that SRR works well as a resolution‐enhancing technique in IR‐SE MEMRI experiments. In addition, the SRR image also shows a number of brain structures that are more clearly discernible from the surrounding tissues than in three‐dimensional GE acquisition, including a number of nuclei with specific higher brain functions, such as memory, stress, anxiety and reward behavior. Copyright © 2014 John Wiley & Sons, Ltd. Visualization of mouse brain using manganese‐enhanced inversion recovery spin echo (IR‐SE) MRI provides unique contrast, but is hampered by time and resolution constraints. We apply computational super‐resolution reconstruction to overcome this problem, introducing a new tool for brain nuclei visualization. We validate our method quantitatively and qualitatively, and recommend it as a complementary technique to conventional visualization using three‐dimensional gradient echo or spin echo imaging.