Developmental changes in hippocampal shape among preadolescent children

Abstract

It is known that the largest developmental changes in the hippocampus take place during the prenatal period and during the first two years of postnatal life. Few studies have been conducted to address the normal developmental trajectory of the hippocampus during childhood. In this study shape analysis was applied to study the normal developing hippocampus in a group of 103 typically developing 6- to 10-year-old preadolescent children. The individual brain was normalized to a template, and then the hippocampus was manually segmented and further divided into the head, body, and tail sub-regions. Three different methods were applied for hippocampal shape analysis: radial distance mapping, surface-based template registration using the robust point matching (RPM) algorithm, and volume-based template registration using the Demons algorithm. All three methods show that the older children have bilateral expanded head segments compared to the younger children. The results analyzed based on radial distance to the centerline were consistent with those analyzed using template-based registration methods. In analyses stratified by sex, it was found that the age-associated anatomical changes were similar in boys and girls, but the age-association was strongest in girls. Total hippocampal volume and sub-regional volumes analyzed using manual segmentation did not show a significant age-association. Our results suggest that shape analysis is sensitive to detect sub-regional differences that are not revealed in volumetric analysis. The three methods presented in this study may be applied in future studies to investigate the normal developmental trajectory of the hippocampus in children. They may be further applied to detect early deviations from the normal developmental trajectory in young children for evaluating susceptibility for psychopathological disorders involving hippocampus.

Keywords: AD; Alzheimer's disease; CT; Demons algorithm; FDR; Hippocampal shape analysis; ICBM; IR-SPGR; International Consortium for Brain Mapping; LDDMM; Large Deformation Diffeomorphic Metric Mapping; MNI; MRI; Montreal Neurological Institute; Non-rigid registration; PET; Positron emission tomography; RDD; RDM; ROI; RPM; Radial distance mapping; Robust point matching algorithm; TE; TFE; TI; TR; computed tomography; echo time; false discovery rate; inversion time; inversion-recovery spoiled gradient recalled acquisition; magnetic resonance imaging; radial distance difference; radial distance mapping; region of interest; repetition time; robust point matching; turbo field echo.

Figure 1

Example of six hippocampi showing heterogeneous shapes. The centerline and 11 perpendicular cross-sectional planes are marked.

Figure 2

The correlation between child age and volume of the left hippocampus. Plots show the association between child age and the volume of the head, body, tail, and the whole left hippocampus, with the correlation coefficient r and the p value indicated in each figure for the whole group. All p values are > 0.05. Different symbols and fitting lines are used for males and females, respectively.

Figure 3

The correlation between child age and volume of the right hippocampus. Plots show the association between child age and the volume of the head, body, tail, and the whole right hippocampus, with the correlation coefficient r and the p value for the whole group indicated in each figure. All p values are > 0.05. The volume of the tail segment is negatively correlated with age with p = 0.06 approaching the significance level. Different symbols and fitting lines are used for males and females, respectively.

Figure 4

The uncorrected p-value maps of the correlation between the Radial Distance Difference (RDD) value analyzed using the RDM method, the surface-based RPM registration, and the volume-based Demons registration with age in the male group(a); the female group(b); and the whole group combining males and females(c). All 3 analytic methods reveal significant correlations with child age mainly in the head segment, particularly in the bottom view. In separate sex analyses in males and females, both show significant results in the head region, but the effect is stronger in females than in males.

Figure 4

The uncorrected p-value maps of the correlation between the Radial Distance Difference (RDD) value analyzed using the RDM method, the surface-based RPM registration, and the volume-based Demons registration with age in the male group(a); the female group(b); and the whole group combining males and females(c). All 3 analytic methods reveal significant correlations with child age mainly in the head segment, particularly in the bottom view. In separate sex analyses in males and females, both show significant results in the head region, but the effect is stronger in females than in males.

Figure 4

The uncorrected p-value maps of the correlation between the Radial Distance Difference (RDD) value analyzed using the RDM method, the surface-based RPM registration, and the volume-based Demons registration with age in the male group(a); the female group(b); and the whole group combining males and females(c). All 3 analytic methods reveal significant correlations with child age mainly in the head segment, particularly in the bottom view. In separate sex analyses in males and females, both show significant results in the head region, but the effect is stronger in females than in males.

Figure 5

The p-value maps after applying the FDR correction for multiple comparisons in the whole group combining males and females. It can be seen that a substantial cluster of pixels in the head segment of the bottom view survive the FDR correction with p<0.05 (showing green, yellow to red color).

Figure 6

The age correlation of the mean RDD value analyzed in a selected ROI (approximately 7.1 mm²) placed over the 3-dimensional surface of the head region on the left hippocampus. For each method using RDM, RPM and Demons registration, a mean RDD value was calculated by averaging over all pixels contained within the ROI, and used in the plot. The Pearson’s correlation coefficient r and the p values analyzed using the whole group are indicated in each figure, which are significant for all 3 methods. The older subjects are more likely to have positive RDD, indicating expanded hippocampus compared to the template in the head region of the left hippocampus. Different symbols and fitting lines are used for males and females, respectively.

Figure 7

The age correlation of the mean RDD value analyzed in a selected ROI (approximately 7.1 mm²) placed over the 3-dimensional surface of the head region on the right hippocampus. The Pearson’s correlation coefficient r and the p values analyzed using the whole group are indicated in each figure, which are significant for all 3 methods. The older subjects are more likely to have positive RDD, indicating expanded hippocampus compared to the template in the head region of the right hippocampus. Different symbols and fitting lines are used for males and females, respectively.