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Neonatal brain-age models in full- and preterm infants.

Howard Chiu¹, Adam C Richie-Halford², Molly F Lazarus³

¹Graduate School of Education, Stanford University, Stanford, CA, USA.

Developmental Cognitive Neuroscience

|July 4, 2026

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This summary is machine-generated.

Brain age models using white matter MRI accurately predict maturation in preterm infants. However, the brain-age gap did not correlate with health complications, suggesting limited sensitivity to prematurity

Area of Science:

Neuroimaging
Developmental Neuroscience
Biomarker Discovery

Background:

Prematurity poses significant risks to infant brain development and neurodevelopmental outcomes.
Current biomarkers for identifying at-risk infants are limited.
Diffusion magnetic resonance imaging (dMRI) offers insights into white matter development.

Purpose of the Study:

To develop and validate brain-age prediction models using white matter features from dMRI.
To assess the model's performance in both healthy and high-risk preterm infant cohorts.
To determine if brain-age gap predicts health complications in preterm infants.

Main Methods:

Tractometry-based brain-age models were constructed using white matter features from dMRI data.
Models were trained and validated on two datasets: the developing Human Connectome Project (dHCP) and a clinical cohort (LPCH).

Keywords:

Brain development Brain-age Diffusion imaging Neonatal Prematurity Tractometry White matter

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Model accuracy was evaluated by comparing predicted brain age to chronological age, and the brain-age gap was assessed against clinical complication scores.

Main Results:

White matter features demonstrated high predictive accuracy for brain age in both dHCP (within 3.9 days) and LPCH (within 6.6 days) datasets.
The brain-age gap, derived from white matter maturation, showed no significant association with a composite score of common prematurity complications.
Tractometry-derived brain-age models accurately reflect neonatal brain maturation but appear limited in detecting clinical complications.

Conclusions:

Brain-age models based on white matter maturation are effective in characterizing neonatal brain development.
Current white matter maturation metrics may lack the sensitivity to capture the cumulative impact of prematurity-related health issues.
Multimodal or longitudinal biomarkers may be necessary to better assess health outcomes in high-risk preterm infants.