Early cortical maturation predicts neurodevelopment in very preterm infants

Abstract

Objective: To evaluate the ability of four objectively defined, cortical maturation features-surface area, gyrification index, sulcal depth and curvature-from structural MRI at term-equivalent age (TEA) to independently predict cognitive and language development at 2 years corrected age in very preterm (VPT) infants.

Design: Population-based, prospective cohort study. Structural brain MRI was performed at term, between 40 and 44 weeks postmenstrual age and processed using the developing Human Connectome Project pipeline.

Setting: Multicentre study comprising four regional level III neonatal intensive care units in the Columbus, Ohio region.

Patients: 110 VPT infants (gestational age (GA) ≤ 31 weeks).

Main outcome measures: Cognitive and language scores at 2 years corrected age on the Bayley Scales of Infant and Toddler Development, Third Edition.

Results: Of the 94 VPT infants with high-quality T2-weighted MRI scans, 75 infants (80%) returned for Bayley-III testing. Cortical surface area was positively correlated with cognitive and language scores in nearly every brain region. Curvature of the inner cortex was negatively correlated with Bayley scores in the frontal, parietal and temporal lobes. In multivariable regression models, adjusting for GA, sex, socioeconomic status, and injury score on MRI, regional measures of surface area and curvature independently explained more than one-third of the variance in cognitive and language scores at 2 years corrected age in our cohort.

Conclusions: We identified increased cortical curvature at TEA as a new prognostic biomarker of adverse neurodevelopment in very premature infants. When combined with cortical surface area, it enhanced prediction of cognitive and language development. Larger studies are needed to externally validate our findings.

Keywords: neonatology; neurodevelopment; neurodisability; neurology; outcomes research.

Figure 1

Pearson correlations with Bayley-III cognitive score are displayed for surface area (top left), curvature (top right), sulcal depth (bottom left) and gyrification index (bottom right) on a representative subject brain. The magnitude of correlation is displayed only for regions that were significant at p<0.05. The colour bar represents the magnitude of the Pearson correlation (R value).

Figure 2

Pearson correlations with Bayley-III language score are displayed for surface area (top left), curvature (top right), sulcal depth (bottom left) and gyrification index (bottom right) on a representative subject brain. The magnitude of correlation is displayed only for regions that were significant at p<0.05. The colour bar represents the magnitude of the Pearson correlation (R value).

Figure 3

Measured Bayley-III scores versus predicted Bayley-III scores (left: cognitive model, right: language model). The predicted scores were calculated using our final fitted models, which included sex, gestational age, global injury score on structural MRI and maternal socioeconomic status as covariates.