ArticleNeuroImage. Clinical2020
Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants.
Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- Pooled it
- Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Associations between neonatal brain structure and neurodevelopmental outcomes following very preterm birth.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- Postnatal dexamethasone treatment for preterm infants at high risk for bronchopulmonary dysplasia is associated with improved regional brain volumes: a prospective cohort study.Archives of disease in childhood. Fetal and neonatal edition · 2025Article
- The Impacts of Enlarged Subarachnoid Space on Brain Growth and Cortex Maturation in Very Preterm Infants.Diagnostics (Basel, Switzerland) · 2025Article
- Application of machine learning in early childhood development research: a scoping review.BMJ open · 2025Article
- Brain MRI before and at term equivalent age predicts motor and cognitive outcomes in very preterm infants.Neuroimage. Reports · 2025Article
- Imaging biomarkers for detection and longitudinal monitoring of ventricular abnormalities from birth to childhood.World journal of radiology · 2025Review
- DFC-Igloo: A dynamic functional connectome learning framework for identifying neurodevelopmental biomarkers in very preterm infants.Computer methods and programs in biomedicine · 2024Article
- The developmental phenotype of motor delay in extremely preterm infants following early-life respiratory adversity is influenced by brain dysmaturation in the parietal lobe.Journal of neurodevelopmental disorders · 2024Article
- Extremely Preterm Infants with a Near-total Absence of Cerebellum: Usefulness of Quantitative Magnetic Resonance in Predicting the Motor Outcome.Cerebellum (London, England) · 2024Article
- Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity.Scientific reports · 2024Article
- Prenatal Opioid Exposure and Risk for Adverse Brain and Motor Outcomes in Infants Born Premature.The Journal of pediatrics · 2024Article
- Multilabel SegSRGAN-A framework for parcellation and morphometry of preterm brain in MRI.PloS one · 2024Article
- Thalamic volume in very preterm infants: associations with severe brain injury and neurodevelopmental outcome at two years.Frontiers in neurology · 2024Article
- Structural connectivity at term equivalent age and language in preterm children at 2 years corrected.Brain communications · 2024Article
- A Semi-Supervised Graph Convolutional Network for Early Prediction of Motor Abnormalities in Very Preterm Infants.Diagnostics (Basel, Switzerland) · 2023Article
- Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology.NeuroImage · 2022Article
- Article
- Altered Cerebral Curvature in Preterm Infants Is Associated with the Common Genetic Variation Related to Autism Spectrum Disorder and Lipid Metabolism.Journal of clinical medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Very preterm infants are at high risk for motor impairments. Early interventions can improve outcomes in this cohort, but they would be most effective if clinicians could accurately identify the highest-risk infants early. A number of biomarkers for motor development exist, but currently none are sufficiently accurate for early risk-stratification. We prospectively enrolled very preterm (gestational age ≤31 weeks) infants from four level-III NICUs. Structural brain MRI was performed at term-equivalent age. We used a established pipeline to automatically derive brain volumetrics and cortical morphometrics - cortical surface area, sulcal depth, gyrification index, and inner cortical curvature - from structural MRI. We related these objective measures to Bayley-III motor scores (overall, gross, and fine) at two-years corrected age. Lasso regression identified the three best predictive biomarkers for each motor scale from our initial feature set. In multivariable regression, we assessed the independent value of these brain biomarkers, over-and-above known predictors of motor development, to predict motor scores. 75 very preterm infants had high-quality T2-weighted MRI and completed Bayley-III motor testing. All three motor scores were positively associated with regional cortical surface area and subcortical volumes and negatively associated with cortical curvature throughout the majority of brain regions. In multivariable regression modeling, thalamic volume, curvature of the temporal lobe, and curvature of the insula were significant predictors of overall motor development on the Bayley-III, independent of known predictors. Objective brain morphometric biomarkers at term show promise in predicting motor development in very preterm infants.
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