Background and objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

背景与目的：基于体素的形态计量学（VBM）是一种流行的神经成像技术，用于检测和量化各组之间脑组织的形态学差异。VBM方法广泛用于人体研究，在动物模型的神经影像研究中具有巨大潜力。将VBM应用于小型动物研究的一个重大挑战是对预处理管道的设计如何影响定量结果的了解不足。这一点很重要，因为尺寸，分辨率和成像参数的巨大差异暗示着人类成像预处理管道不能无限制地应用于小型动物研究。在这项工作中，我们评估和验证了不同VBM管线用于研究小鼠大脑的性能。

方法：通过改变预处理过程中使用的空间归一化，我们应用了两条管道-DARTEL VBM和Optimized VBM-。使用一种自动方法，我们模拟了小鼠大脑特定区域的体积变化的灰质（GM）损失水平和组织萎缩的大小。我们通过将它们检测到的差异的位置和范围与模拟的管线进行比较来评估每个管线的性能。最后，我们将两条管道应用到大脑的磁共振（MR）图像上，该图像来自小鼠生长受限的实验模型。

结果：我们的结果表明，Optimized工作流程检测到了一些细微的萎缩，而DARTEL VBM工作流程未检测到。在这两个工作流程中，检测到较小的萎缩程度相似，但是DARTEL VBM在估计其大小和解剖位置方面表现更好。两条VBM管道都很难找到体积损失很小的萎缩症，而且总的来说，它们低估了两组之间的差异幅度。这些结果在整个大脑区域也各不相同，在大脑皮质上的表现要比其他区域（例如小脑）更好。

结论：对小鼠大脑不同区域的VBM管线的分析和定量可以更好地了解其结果的优缺点。我们对该方法进行了控制和定量分析，为解释实际情况下的变化提供了有力的证据。