A multivariate surface-based analysis of the putamen in premature newborns: regional differences within the ventral striatum

Abstract

Many children born preterm exhibit frontal executive dysfunction, behavioral problems including attentional deficit/hyperactivity disorder and attention related learning disabilities. Anomalies in regional specificity of cortico-striato-thalamo-cortical circuits may underlie deficits in these disorders. Nonspecific volumetric deficits of striatal structures have been documented in these subjects, but little is known about surface deformation in these structures. For the first time, here we found regional surface morphological differences in the preterm neonatal ventral striatum. We performed regional group comparisons of the surface anatomy of the striatum (putamen and globus pallidus) between 17 preterm and 19 term-born neonates at term-equivalent age. We reconstructed striatal surfaces from manually segmented brain magnetic resonance images and analyzed them using our in-house conformal mapping program. All surfaces were registered to a template with a new surface fluid registration method. Vertex-based statistical comparisons between the two groups were performed via four methods: univariate and multivariate tensor-based morphometry, the commonly used medial axis distance, and a combination of the last two statistics. We found statistically significant differences in regional morphology between the two groups that are consistent across statistics, but more extensive for multivariate measures. Differences were localized to the ventral aspect of the striatum. In particular, we found abnormalities in the preterm anterior/inferior putamen, which is interconnected with the medial orbital/prefrontal cortex and the midline thalamic nuclei including the medial dorsal nucleus and pulvinar. These findings support the hypothesis that the ventral striatum is vulnerable, within the cortico-stiato-thalamo-cortical neural circuitry, which may underlie the risk for long-term development of frontal executive dysfunction, attention deficit hyperactivity disorder and attention-related learning disabilities in preterm neonates.

Figure 1. The proposed system.

(a) The putamen is segmented from T1-weighted images and a conformal grid is built on the surface. Here examples are shown for 2 different subjects (b) Examples of features selected in the image for the two subjects in (a) (c) From left to right: Intensity map on the surface of one of the subjects in (a). Forward map g(x) for the conformal grid fluid registration to a common template. Backward map h(x) from the template to image 1. Intensity map on the surface of the template. (d). Surface mTBM is applied to analyze morphometric changes. Map displays uncorrected p-values on the surface of the putamen from the mTBM analysis.

Figure 2. Putamen segmentation.

While the caudate head is part of the striatum, we chose not to include this structure because of the poor tissue contrast in the anterior limb of the internal capsule in the neonates, which prevented us from obtaining reliable manual contours in this region in neonates. Additionally, our hypothesis testing for this paper included the ventral striatum, which does not contain the caudate head. Note also that the globes palladius, while not part of the putamen, was still included in our segmentation. It is extremely difficult to accurately segment the globus pallidus from the putamen in neonates due to the lack of tissue contrast on volumetric T1 images. However, since our hypothesis is related to the ventral striatal surface, it is not affected by the inclusion of the globus palladius within our putamen contour.

Figure 3. Surface-based statistics.

Top panel: P-values for the comparison of two groups, for 4 different statistics. The meaning of the different colors is shown in the colorbar.

Figure 4. False Discovery Rate Analysis.

This plot shows the CDFs of p-values vs. p-values. Height above the x = y line indicate how powerful a statistic is, while the point at which the data crosses the y = 20× line, if it exists, represents the threshold at which at most 5% of false positives are expected (see section on Multivariate Statistical Analysis). Both mTBM and the combined measure cross the x = 20 y line but the other measures fail to do so.

Figure 5. Comparison of Fluid and constrained harmonic registrations.

Top panel: P-values for the comparison of with the two registration methods. Bottom panel: P-values for the comparison of with the two methods. The left column represents the fluid registration, while the right one is for the constrained harmonic mapping. The meaning of the different colors is shown in the colorbar.