School of Government, Shanghai University of Political Science and Law, Shanghai, China.
Independent Researcher.
Hum Brain Mapp. 2024 Oct 15;45(15):e70055. doi: 10.1002/hbm.70055.
There is still little research on the consistency among the subcortical volume estimates of different software packages. It is also unclear whether there are age-related differences in the inter-software consistency. The current study aimed to examine the consistency of three commonly used automated software packages and the effect of age on inter-software consistency. We analyzed T1-weighted structural images from two public datasets, in which the subjects were divided into four age groups ranging from childhood and adolescence to late adulthood. We chose three mainstream automated software packages including FreeSurfer, CAT, and FSL, to estimate the volumes of seven subcortical structures, including thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens. We used the intraclass correlation coefficient (ICC) and Pearson correlation coefficient (PCC) to quantify inter-software consistency and compared the consistency measures among the age groups. As a measure of validity, we additionally evaluated the predictive power of each software package's estimates for predicting age. The results showed good inter-software consistency in the thalamus, caudate, putamen, and hippocampus, moderate consistency in the pallidum, and poor consistency in the amygdala and accumbens. Significant differences in the inter-software consistency were not observed among the age groups in most cases. FreeSurfer exhibited higher age prediction accuracy than CAT and FSL. The current study showed that the inter-software consistency on the subcortical volume estimation varies with structures but generally not with age groups, which has important implications for the interpretation and reproducibility of neuroimaging findings.
目前关于不同软件包的皮质下体积估计值之间的一致性研究还很少。软件间一致性是否存在与年龄相关的差异也不清楚。本研究旨在检验三种常用的自动化软件包的一致性，以及年龄对软件间一致性的影响。我们分析了两个公共数据集的 T1 加权结构图像，其中将受试者分为从儿童和青少年到老年的四个年龄组。我们选择了三种主流的自动化软件包，包括 FreeSurfer、CAT 和 FSL，来估计七个皮质下结构的体积，包括丘脑、尾状核、壳核、苍白球、海马体、杏仁核和伏隔核。我们使用组内相关系数（ICC）和皮尔逊相关系数（PCC）来量化软件间的一致性，并比较了不同年龄组之间的一致性度量。作为有效性的衡量标准，我们还评估了每个软件包的估计值预测年龄的预测能力。结果表明，在丘脑、尾状核、壳核和海马体中具有良好的软件间一致性，在苍白球中具有中等一致性，而在杏仁核和伏隔核中一致性较差。在大多数情况下，年龄组之间的软件间一致性没有显著差异。FreeSurfer 表现出比 CAT 和 FSL 更高的年龄预测准确性。本研究表明，皮质下体积估计的软件间一致性因结构而异，但通常与年龄组无关，这对神经影像学研究结果的解释和可重复性具有重要意义。
