VBM sensitivity to localization and extent of mouse brain lesions: A simulation approach

Voxel-based morphometry (VBM) is a popular neuroimaging technique, used to detect and quantify morphological differences in brain tissues between groups. Widely used in human studies, VBM approaches have tremendous potential for neuroimaging studies in animal models. A significant challenge for applying VBM to small animal studies is the poor understanding of how the design of preprocessing pipelines impacts quantitative results. This is important because the large differences in size, resolution, and imaging parameters implies that human imaging preprocessing pipelines cannot be uncritically applied to small animal studies. In this work, we assessed and validated the performance of different VBM pipelines for the study of the mouse brain.

We applied two pipelines -namely DARTEL VBM and Optimized VBM- by varying spatial normalization used during preprocessing. Using an automatic method, we simulated varying levels of volumetric gray matter (GM) loss and sizes of tissue atrophy on specific areas of the mouse brain. We evaluated the performance of each pipeline by comparing location and extent of the differences detected by them with the simulated ones. Finally, we applied both pipelines on magnetic resonance (MR) images of the brain derived from an experimental model of growth restriction on mice.

Our results demonstrated that some subtle atrophies were detected by the Optimized workflow but not by the DARTEL VBM workflow. Detection of less subtle atrophies was similar for the two workflows, but DARTEL VBM performed better at estimating their size and anatomical location. Both VBM pipelines had difficulties at finding atrophies with a very small level of volumetric loss and, in general, they underestimated the magnitudes of difference between groups. These results also varied across brain regions, with better performance on brain cortex than other regions such as the cerebellum.

The analysis and quantification of VBM pipelines on different areas of the mouse brain allows a better understanding of the advantages and limitations of their results. We performed a controlled and quantitative analysis of the method providing robust evidence to interpret changes in real contexts.