Braggio Delfina, Barbeito-Andrés Jimena, Gonzalez Paula, Hallgrímsson Benedikt, Larrabide Ignacio
Instituto Pladema, Facultad de Ciencias Exactas, UNCPBA, Argentina.
Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos, CONICET, UNAJ, Hospital El Cruce, Argentina.
Comput Methods Programs Biomed. 2020 Nov;196:105636. doi: 10.1016/j.cmpb.2020.105636. Epub 2020 Jul 4.
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.
基于体素的形态学测量（VBM）是一种常用的神经成像技术，用于检测和量化不同组之间脑组织的形态差异。VBM方法在人体研究中广泛应用，在动物模型的神经成像研究中具有巨大潜力。将VBM应用于小动物研究的一个重大挑战是对预处理流程的设计如何影响定量结果了解不足。这一点很重要，因为大小、分辨率和成像参数的巨大差异意味着不能不加批判地将人类成像预处理流程应用于小动物研究。在这项工作中，我们评估并验证了不同VBM流程用于小鼠脑研究的性能。
我们应用了两种流程——即DARTEL VBM和优化VBM——通过改变预处理过程中使用的空间归一化方法。使用一种自动方法，我们在小鼠脑的特定区域模拟了不同程度的体积灰质（GM）损失和组织萎缩大小。我们通过比较它们检测到的差异的位置和范围与模拟的差异来评估每个流程的性能。最后，我们将这两种流程应用于源自小鼠生长受限实验模型的脑磁共振（MR）图像。
我们的结果表明，优化工作流程检测到了一些细微萎缩，而DARTEL VBM工作流程未检测到。对于不太细微的萎缩，两种工作流程的检测相似，但DARTEL VBM在估计其大小和解剖位置方面表现更好。两种VBM流程在发现体积损失水平非常小的萎缩方面都有困难，总体而言，它们低估了组间差异的程度。这些结果在不同脑区也有所不同，在大脑皮层上的表现优于小脑等其他区域。
对小鼠脑不同区域的VBM流程进行分析和量化，可以更好地理解其结果的优缺点。我们对该方法进行了可控的定量分析，为在实际情况下解释变化提供了有力证据。
