Early childhood is an important period of sensory, motor, cognitive and socio-emotional maturation, yet relatively little is known about the brain changes specific to this period. Voxel-based morphometry (VBM) is a technique to estimate regional brain volumes from magnetic resonance (MR) images. The default VBM processing pipeline can be customized to increase accuracy of segmentation and normalization, yet the impact of customizations on analyses in young children are not clear. Here, we assessed the impact of different preprocessing steps on T1-weighted MR images from typically developing children in two separate cohorts. Data were processed with the Computational Anatomy Toolbox (CAT12), using seven different VBM pipelines with distinct combinations of tissue probability maps (TPMs) and DARTEL templates created using the Template-O-Matic, and CerebroMatic. The first cohort comprised female children aged 3.9–7.9 years (N = 62) and the second included boys and girls aged 2.7–8 years (N = 74). We found that pipelines differed significantly in their tendency to classify voxels as grey or white matter and the conclusions about some age effects were pipeline-dependent. Our study helps to both understand age-associations in grey and white matter volume across early childhood and elucidate the impact of VBM customization on brain volumes in this age range.

幼儿期是感觉，运动，认知和社会情感成熟的重要时期，但对该时期特有的大脑变化知之甚少。基于体素的形态计量学（VBM）是一种从磁共振（MR）图像估算区域性大脑体积的技术。可以自定义默认的VBM处理管道，以提高分割和归一化的准确性，但是自定义对幼儿分析的影响尚不清楚。在这里，我们评估了不同预处理步骤对来自两个不同队列中典型发育儿童的T1加权MR图像的影响。使用7个不同的VBM管道，使用具有组织概率图（TPM）和使用Template-O-Matic创建的DARTEL模板的不同组合，通过计算解剖工具箱（CAT12）处理数据，和CerebroMatic。第一组包括3.9–7.9岁的女童（N = 62），第二组包括2.7–8岁的男孩和女孩（N = 74）。我们发现管线将体素归类为灰色或白色物质的趋势存在显着差异，并且有关某些年龄影响的结论与管线有关。我们的研究有助于了解儿童早期灰色和白色物质数量的年龄相关性，并阐明VBM定制对这一年龄段的大脑容量的影响。