Thalamic alterations in preterm neonates and their relation to ventral striatum disturbances revealed by a combined shape and pose analysis

Abstract

Finding the neuroanatomical correlates of prematurity is vital to understanding which structures are affected, and to designing efficient prevention and treatment strategies. Converging results reveal that thalamic abnormalities are important indicators of prematurity. However, little is known about the localization of the abnormalities within the subnuclei of the thalamus, or on the association of altered thalamic development with other deep gray matter disturbances. Here, we aim to investigate the effect of prematurity on the thalamus and the putamen in the neonatal brain, and further investigate the associated abnormalities between these two structures. Using brain structural magnetic resonance imaging, we perform a novel combined shape and pose analysis of the thalamus and putamen between 17 preterm (41.12 ± 5.08 weeks) and 19 term-born (45.51 ± 5.40 weeks) neonates at term equivalent age. We also perform a set of correlation analyses between the thalamus and the putamen, based on the surface and pose results. We locate significant alterations on specific surface regions such as the anterior and ventral anterior (VA) thalamic nuclei, and significant relative pose changes of the left thalamus and the right putamen. In addition, we detect significant association between the thalamus and the putamen for both surface and pose parameters. The regions that are significantly associated include the VA, and the anterior and inferior putamen. We detect statistically significant surface deformations and pose changes on the thalamus and putamen, and for the first time, demonstrate the feasibility of using relative pose parameters as indicators for prematurity in neonates. Our methods show that regional abnormalities of the thalamus are associated with alterations of the putamen, possibly due to disturbed development of shared pre-frontal connectivity. More specifically, the significantly correlated regions in these two structures point to frontal-subcortical pathways including the dorsolateral prefrontal-subcortical circuit, the lateral orbitofrontal-subcortical circuit, the motor circuit, and the oculomotor circuit. These findings reveal new insight into potential subcortical structural covariates for poor neurodevelopmental outcomes in the preterm population.

Keywords: Frontal-subcortical circuits; Pose; Prematurity; Subcortical structures; Tensor-based morphometry.

Fig. 1

Diagram of the combined shape and relative pose analysis. For simplicity, only the surfaces of thalamus are used for illustration. Top Row: the subcortical structures are first segmented from T1 images, and then reconstructed to 3D surface models; Middle Row: surface based morphometry and correlation analysis; Bottom Row: relative pose based statistics and correlation analysis

Fig. 2

Distribution of scale parameter in log-Euclidean space (logS) for the left thalamus, right thalamus, left putamen, and right putamen. Scatter points in the figure represent observed results from the Procrustes alignment, while lines represent their corresponding linear regressions. In all the figures above, data from the preterm group are marked in red(circles and dash lines), and while that from the term group are marked in blue (x symbles and dash-dot lines). Note that the logS for the preterm group are distributed lower in the graphs, compared to that from the term controls, indicating a smaller size of structures in the preterm group. When very preterm subjects are removed from the sample (gestational age at birth < 31 weeks), the downward trends of linear regression (shown in solid cyan lines) for preterm subjects disappears, indicating a closer size compared to the term born subjects.

Fig. 3

Thalamus statistical p-maps: Overall p-values are p=0.0901 for MAD(a), p=0.0077 for mTBM(b), p=0.0035 for MAD + mTBM(c) and p=0.0683 for detJ(d)

Fig. 4

Vertex-wise ratio determinant (a) and radial distance (b) maps of the thalamus. Widespread shrinkage of preterm group is present in both thalami, and the clusters with significant preterm vs. term differences (seen in Fig. 3) all fall on the preterm < term areas

Fig. 5

Vertex-wise ratio determinant (a) and radial distance (b) maps of putamen. Widespread shrinkage of preterm group is present in both putamen, and the clusters with significant preterm vs. term differences (seen in our previous publication (Shi et al., 2013)) mostly fall on the preterm < term areas

Fig. 6

3D visualization of the pose of mean shapes averaged from the preterm (red) and term groups (blue). Areas where the mean shapes of two groups overlaid appear in purple. To better visualize the pose changes, enlargements of locations A, B, C at the bottom right figure are presented in top left, bottom left, and top right figures, respectively. Note the borders of these two structures: shift of pose are evident on the left putamen (A), left thalamus (B), and right putamen (C), but are quite small the right thalamus

Fig. 7

Vertex-wise correlation coefficient maps have been generated based on determinant (left) and radius (right), respectively. The upper row are displayed in a superior view, while the bottom ones are seen from the inferior brain surface

Fig. 8

P-maps of the corresponding to the correlation coefficients, derived from the determinant map (left), and radius maps (right). The upper row are displayed in a superior view, while the bottom are seen from the inferior brain surface

Fig. 9

The correlation between the thalamus and the putamen in the left (upper row) and right (bottom row) hemispheres, tested using pose parameters: logS (left column), ‖logR‖(middle column), ‖logd‖(right column). More details, such as correlation coefficients and p-values, are presented in Table 2