Development of cortical microstructure in the preterm human brain

Abstract

Cortical maturation was studied in 65 infants between 27 and 46 wk postconception using structural and diffusion magnetic resonance imaging. Alterations in neural structure and complexity were inferred from changes in mean diffusivity and fractional anisotropy, analyzed by sampling regions of interest and also by a unique whole-cortex mapping approach. Mean diffusivity was higher in gyri than sulci and in frontal compared with occipital lobes, decreasing consistently throughout the study period. Fractional anisotropy declined until 38 wk, with initial values and rates of change higher in gyri, frontal and temporal poles, and parietal cortex; and lower in sulcal, perirolandic, and medial occipital cortex. Neuroanatomical studies and experimental diffusion-anatomic correlations strongly suggested the interpretation that cellular and synaptic complexity and density increased steadily throughout the period, whereas elongation and branching of dendrites orthogonal to cortical columns was later and faster in higher-order association cortex, proceeding rapidly before becoming undetectable after 38 wk. The rate of microstructural maturation correlated locally with cortical growth, and predicted higher neurodevelopmental test scores at 2 y of age. Cortical microstructural development was reduced in a dose-dependent fashion by longer premature exposure to the extrauterine environment, and preterm infants at term-corrected age possessed less mature cortex than term-born infants. The results are compatible with predictions of the tension theory of cortical growth and show that rapidly developing cortical microstructure is vulnerable to the effects of premature birth, suggesting a mechanism for the adverse effects of preterm delivery on cognitive function.

Keywords: DTI; brain development; preterm birth.

Fig. 1.

Regional changes in FA. Change in FA in cortical ROIs demonstrated by piecewise linear regression. ROIs were placed in gyri (black circles) and sulci (white circles) of frontal, parietal, occipital, and temporal cortex, and regression lines are shown for all samples. Note that FA is generally higher in the gyri in all four regions.

Fig. 2.

Regional changes in mean diffusivity. Change in MD in cortical ROIs demonstrated by linear regression. Data labeled as in Fig. 1. Note that MD is generally higher in the gyri in all four regions, and that in contrast to FA, the decline in MD continues after 38 wk of age.

Fig. 3.

FA and MD at term-corrected age. FA and MD extracted from cortical ROIs were compared between all preterm infants imaged at term-corrected age (P; n = 37) and a cohort of healthy, term-born controls (T; n = 10). Cortical FA and MD were both significantly higher in the preterm infants at term in all regions.

Fig. 4.

Global spatiotemporal mapping of changes in FA. (A) Cortical FA at five time-points during the preterm period mapped onto a smoothed isosurface representation of the population-based template image. (B) Cortical voxels were clustered into three groups according to the trajectory of change in FA over time. Kernel regression shows the developmental trajectory of FA in each cluster (thick solid lines) overlaid on 100 randomly sampled voxel time-courses from within each cluster (thin lines). (C) Cluster locations displayed on the same surface as A.

Fig. 5.

Global spatiotemporal mapping of changes in MD. (A) Cortical MD at five time-points during the preterm period. (B) Cortical voxels were clustered into two groups based on the trajectory of MD change over time. Kernel regression shows trajectory of group-average MD in both clusters (thick lines) overlaid onto 100 randomly sampled voxel time courses (thin lines). (C) Cluster locations are displayed as in Fig. 4.

Fig. 6.

Parallel microstructural development and macrostructural growth in the cortex. The relation between increasing cortical volume, represented by the log-Jacobian determinant, and postconceptional age in voxels clustered by spatiotemporal mapping of cortical FA (A, cluster 1; B, cluster 2; C, cluster 3; location of clusters shown in Fig. 4). Rate of change of volume over time was significantly different in each cluster (D).