ArticleEuropean radiology2021
Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.Biological psychiatry · 2023Pooled it
- Structuro-Functional Differentiation and Coupling of Gyri and Sulci in the Neonatal Cortex.Human brain mapping · 2026Article
- Combined model of radiomics and clinical features for predicting prognosis of term neonatal hypoxic-ischemic encephalopathy after one year: an exploratory study.BMC medical imaging · 2025Article
- SEPoolConvNeXt: A Deep Learning Framework for Automated Classification of Neonatal Brain Development Using T1- and T2-Weighted MRI.Journal of clinical medicine · 2025Article
- Radiomics-based correlation analysis of fetal brain MRI features and children's neurodevelopmental outcomes in monochorionic twins.BMC pregnancy and childbirth · 2025Article
- Radiomics models predict early neurodevelopment in infants with congenital cardiac septal defects.Quantitative imaging in medicine and surgery · 2025Article
- Development and Validation of an MRI-Based Brain Volumetry Model Predicting Poor Psychomotor Outcomes in Preterm Neonates.Journal of clinical medicine · 2025Article
- Prediction of feeding difficulties in neonates with hypoxic-ischemic encephalopathy using magnetic resonance imaging-derived radiomics features.Pediatric radiology · 2024Article
- Predicting long-term outcomes in patients with classical trigeminal neuralgia following microvascular decompression with an MRI-based radiomics nomogram: a multicentre study.European radiology · 2024Article
- Radiomics with structural magnetic resonance imaging, surface morphometry features, neurology scales, and clinical metrics to evaluate the neurodevelopment of preschool children with corrected tetralogy of Fallot.Translational pediatrics · 2024Article
- Diagnostic performance of synthetic relaxometry for predicting neurodevelopmental outcomes in premature infants: a feasibility study.European radiology · 2023Article
- Term equivalent age brain MRI of preterm newborns: gathering the pieces for prognostication.European radiology · 2023Article
- Promoting the application of pediatric radiomics via an integrated medical engineering approach.Cancer innovation · 2023Review
- Multi-algorithms analysis for pre-treatment prediction of response to transarterial chemoembolization in hepatocellular carcinoma on multiphase MRI.Insights into imaging · 2023Article
- MRI based radiomics enhances prediction of neurodevelopmental outcome in very preterm neonates.Scientific reports · 2022Article
- Article
- Development and validation of a pyradiomics signature to predict initial treatment response and prognosis during transarterial chemoembolization in hepatocellular carcinoma.Frontiers in oncology · 2022Article
- Radiomics analysis of MR neonatal brain: will it be the Rosetta stone for predicting the poor psychomotor outcome in preterm newborns?European radiology · 2021Article
- Predicting the Initial Treatment Response to Transarterial Chemoembolization in Intermediate-Stage Hepatocellular Carcinoma by the Integration of Radiomics and Deep Learning.Frontiers in oncology · 2021Article
- Brain MRI Radiomics Analysis of School-Aged Children with Tetralogy of Fallot.Computational and mathematical methods in medicine · 2021Article
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
objectivesThis study aimed to apply a radiomics approach to predict poor psychomotor development in preterm neonates using brain MRI.
methodsProspectively enrolled preterm neonates underwent brain MRI near or at term-equivalent age and neurodevelopment was assessed at a corrected age of 12 months. Two radiologists visually assessed the degree of white matter injury. The radiomics analysis on white matter was performed using T1-weighted images (T1WI) and T2-weighted images (T2WI). A total of 1906 features were extracted from the images and the minimum redundancy maximum relevance algorithm was used to select features. A prediction model for the binary classification of the psychomotor developmental index was developed and eightfold cross-validation was performed. The diagnostic performance of the model was evaluated using the AUC with and without including significant clinical and DTI parameters.
resultsA total of 46 preterm neonates (median gestational age, 29 weeks; 26 males) underwent brain MRI (median corrected gestational age, 37 weeks). Thirteen of 46 (28.3%) neonates showed poor psychomotor outcomes. There was one neonate among 46 with moderate to severe white matter injury on visual assessment. For the radiomics analysis, twenty features were selected for each analysis. The AUCs of prediction models based on T1WI, T2WI, and both T1WI and T2WI were 0.925, 0.834, and 0.902. Including gestational age or DTI parameters did not improve the prediction performance of T1WI.
conclusionsA radiomics analysis of white matter using early T1WI or T2WI could predict poor psychomotor outcomes in preterm neonates. KEY POINTS: • Radiomics analysis on T1-weighted images of preterm neonates showed the highest diagnostic performance (AUC, 0.925) for predicting poor psychomotor outcomes. • In spite of 45 of 46 neonates having no significant white matter injury on visual assessment, the radiomics analysis of early brain MRI showed good diagnostic performance (sensitivity, 84.6%; specificity, 78.8%) for predicting poor psychomotor outcomes. • Radiomics analysis on early brain MRI can help to predict poor neurodevelopmental outcomes in preterm neonates.
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