Inter-Software Consistency on the Estimation of Subcortical Structure Volume in Different Age Groups

Abstract

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.