Development of a new toolbox for mouse PET–CT brain image analysis fully based on CT images and validation in a PD mouse model

Abstract

Abstract Automatic analysis toolboxes are popular in brain image analysis, both in clinical and in preclinical practices. In this regard, we proposed a new toolbox for mouse PET–CT brain image analysis including a new Statistical Parametric Mapping-based template and a pipeline for image registration of PET–CT images based on CT images. The new templates is compatible with the common coordinate framework (CCFv3) of the Allen Reference Atlas (ARA) while the CT based registration step allows to facilitate the analysis of mouse PET–CT brain images. From the ARA template, we identified 27 volumes of interest that are relevant for in vivo imaging studies and provided binary atlas to describe them. We acquired 20 C57BL/6 mice with [18F]FDG PET–CT, and 12 of them underwent 3D T2-weighted high-resolution MR scans. All images were elastically registered to the ARA atlas and then averaged. High-resolution MR images were used to validate a CT-based registration pipeline. The resulting method was applied to a mouse model of Parkinson’s disease subjected to a test–retest study (n = 6) with the TSPO-specific radioligand [18F]VC701. The identification of regions of microglia/macrophage activation was performed in comparison to the Ma and Mirrione template. The new toolbox identified 11 (6 after false discovery rate adjustment, FDR) brain sub-areas of significant [18F]VC701 uptake increase versus the 4 (3 after FDR) macro-regions identified by the Ma and Mirrione template. Moreover, these 11 areas are functionally connected as found by applying the Mouse Connectivity tool of ARA. In conclusion, we developed a mouse brain atlas tool optimized for PET–CT imaging analysis that does not require MR. This tool conforms to the CCFv3 of ARA and could be applied to the analysis of mouse brain disease models.