Cortical Morphology and Morphometric Similarity Network Topology Alterations in Preterm Neonates: Insights From an East Asian Cohort

Abstract

The early postnatal period is critical for cortical development, with prematurity disrupting neurodevelopmental trajectories and increasing long-term vulnerability. However, cortical morphological and morphometric similarity network (MSN) research in East Asian preterm neonates is limited. Using structural MRI in 159 Chinese neonates (109 preterm [median GA at birth: 34.6 weeks], 50 term [median GA at birth: 38.8 weeks]) scanned at near-term equivalent PMA (36-42 weeks), we analyzed cortical morphometry and constructed individualized MSNs. Compared to term neonates, preterm neonates exhibited significant region-specific morphological alterations: reduced surface area in the left precuneus and supramarginal gyrus, decreased mean curvature in the left inferior parietal, parahippocampal, and right superior temporal cortices, and increased cortical thickness in the right caudal middle frontal gyrus (FDR-corrected p < 0.05). Within preterm neonates, surface area and gray matter volume showed widespread positive correlations with PMA at scan (FDR-corrected p < 0.05 in multiple regions). Regional MSN analysis revealed significantly increased morphometric similarity in the right medial orbitofrontal cortex (FDR-corrected p = 0.026). Although global MSN topology showed no statistically significant group differences, preterm neonates displayed trends suggesting reduced MSN-based integration and segregation, reflecting less coordinated cortical morphological patterns across distant and local regions. Within the preterm group, developmental analysis indicated progressive trends toward enhanced global MSN integration and segregation with increasing PMA, alongside a significant decrease in betweenness centrality within the right precuneus (Spearman's ρ = -0.337). This study comprehensively characterizes cortical morphology and MSN development in East Asian preterm neonates, identifying region-specific disruptions and dynamic postnatal cortical morphological and network maturation trajectories.

Keywords: brain development; cortical morphology; graph theory; morphometric similarity network; preterm neonates.

FIGURE 1

Flowchart of study population selection and distribution of postmenstrual age at scan. (a) Stepwise illustration of the inclusion and exclusion criteria applied to the study cohort. (b) Distribution of PMA at scan for all included neonates (preterm and term groups).

FIGURE 2

Group differences in morphometric features between preterm and term neonates. Region‐wise comparison of five morphometric features (SA, MC, SD, CT, GMV) between term and preterm neonates, visualized as t‐maps (p < 0.05, uncorrected). Analyses were adjusted for PMA at scan, sex, and eTIV. The color bar represents t‐values, with warm colors indicating higher values in term neonates and cool colors indicating higher values in preterm neonates.

FIGURE 3

Association between morphometric features and PMA at scan in preterm neonates. Partial Spearman correlation analysis was performed to assess the relationship between morphometric features and PMA at scan, adjusting for GA at birth, sex, and eTIV. The color bar represents Spearman's ρ values, where red indicates a positive correlation and blue indicates a negative correlation. Results are presented without correction for multiple comparisons.

FIGURE 4

Group differences in regional MSN between preterm and term neonates. (a, b) Mean regional MSN values in term and preterm neonates, with warm and cool colors representing higher and lower morphometric similarity, respectively. (c) Region‐wise t‐map comparing regional MSN values between groups (p < 0.05, uncorrected), adjusted for PMA at scan and sex.

FIGURE 5

Group differences in global network metrics between preterm and term neonates. Comparison of area under the curve (AUC) values for global topological metrics—including Sigma, characteristic path length (Lp), global efficiency (Eg), clustering coefficient (Cp), and local efficiency (Eloc)—between the two groups, adjusted for PMA at scan and sex. Arrow annotations (“↑” or “↓”) highlight the direction of group differences for preterm neonates relative to term neonates.

FIGURE 6

Associations between global network metrics and PMA at scan in preterm neonates. Partial Spearman correlation analyses assessing relationships between AUC‐based global network metrics and PMA at scan, controlling for GA at birth and sex.

FIGURE 7

Associations between nodal network metrics and PMA at scan in preterm neonates. Partial Spearman correlation analyses of nodal network metrics and PMA at scan, adjusted for GA at birth and sex. The color bar represents Spearman's ρ values, with red indicating positive and blue indicating negative correlations. Results are presented without correction for multiple comparisons.