This observational study analyzed 1056 structural MRI scans from six datasets in Zurich, Shanghai, and the Developing Human Connectome Project. The population included preterm neonates (n=90) and neonates with congenital heart disease (CHD), with fetal (n=50) and postnatal (n=110) cohorts. The study used a deep learning-based brain age estimation framework to quantify the brain age gap (BAG) compared to term-born or center-matched controls.
In preterm neonates, BAG was progressively more negative with lower gestational age at birth, with an effect size of -0.7 to -0.8 weeks. In the CHD fetal period, brain age did not differ from center-matched controls. However, in the CHD postnatal period before surgery, significant negative BAGs of -1.3 to -1.8 weeks were observed (p<0.05). After cardiac surgery, BAGs increased significantly, reaching up to -3 weeks (p<0.05), indicating a widening maturational gap.
Safety and tolerability data were not reported. Key limitations include the limited generalizability of the methods and the need for cross-center calibration to minimize systematic bias. The study supports a continuous fetal-neonatal brain age metric as a sensitive marker of global neurological maturational timing. However, the observational design and methodological constraints mean these findings should be interpreted as preliminary associations requiring validation in broader, calibrated cohorts before clinical application.
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Brain development follows a precisely regulated biological timetable, with defined periods of vulnerability increasingly recognized in congenital disorders affecting early brain development. This biological timing can be captured by the emerging concept of brain age, a measure of brain maturation, enabling the detection of deviation from normative developmental trajectories. Clinical conditions affect the degree of brain development during this critical period, including preterm birth and congenital heart disease (CHD). We developed a deep learning-based brain age estimation framework across the fetal-neonatal period (21-44 gestational weeks) to quantify neurodevelopment from structural MRI. Using 1056 scans from six datasets acquired at three centers, Zurich, Shanghai, and the Developing Human Connectome Project, we trained models on normative fetal and neonatal MRI data. Both structural MRI-based and segmentation-derived cortical morphology-based models were implemented to assess representation effects and cross-center generalisability. The framework was applied to two clinically relevant conditions, preterm birth and CHD, to estimate the brain age gap (BAG), defined as the difference between predicted brain age and chronological age. In preterm neonates scanned at term-equivalent age (n=90, 37-44 weeks), BAG was progressively more negative with lower gestational age at birth. Neonates born before 28 weeks showed delays of -0.7 to -0.8 weeks relative to term-born controls. In CHD (n=50, 22-34 weeks), fetal brain age did not differ from center-matched controls and no association with cardiac defect severity was observed. After birth, neonates with CHD (n=110, 37-44 weeks) showed significant (p<0.05) negative BAGs before surgery (-1.3 to -1.8 weeks) and BAGs increased significantly (p<0.05) after surgery (up to -3 weeks in center-specific analyses), indicating a delay in brain maturation from postnatal stage, but not in prenatal stage in CHD patients. These patterns were found across both structural MRI-based models and cortical morphology-based models, despite the need for cross-center calibration to minimize systematic bias. Voxel-based morphometry showed that a larger BAG was associated with regional contraction in deep frontal and peri-Rolandic white matter in preterm neonates, and perioperative spatial shifts in neonates with CHD. Saliency maps converged on deep white matter and periventricular regions, highlighting a potential link between BAG and delayed maturation of rapidly developing projection pathways. These findings may indicate neurodevelopmental delays in preterm birth and a postnatally emerging maturational gap in CHD that increases following cardiac intervention. Despite limited generalisability of our methods, these results support a continuous fetal-neonatal brain age metric as a sensitive marker of global neurological maturational timing.