Assessment of cerebral glucose metabolism in cat deafness model: strategies for improving the voxel-based statistical analysis for animal PET studies

Abstract

Purpose: The aim of this study was to establish the procedures for 3D voxel-based statistical analysis of 2-deoxy-2-[(18)F]fluoro-D-glucose-positron emission tomography (FDG-PET) images of a cat's brain obtained using a small animal-dedicated PET system and to assess the utility of this approach in investigating the cerebral glucose metabolism in an animal model of cortical deafness.

Procedures: This study compared several different strategies for the spatial processing of PET data acquired twice from eight cats before and after inducing deafness in terms of the comparability of the statistical analysis results to the established pattern of the cerebral glucose metabolic changes in the deaf animals.

Results: The accuracy of the spatial preprocessing procedures and the statistical significance of the comparison were improved by removing the background activities outside the brain regions. The use of the spatial normalization parameters obtained from the mean image of the realigned data set for individual data also helped improve the statistical significance of the paired t testing. It was also found that an adjustment of the registration options was also important for increasing the precision of the realignment.

Conclusions: A method for voxel-based analysis of the PET data of a cat's brain was optimized. The results demonstrated the high localization accuracy and specificity of this method, which is expected to be useful for examining the brain PET data of medium-sized animals such as cats.