ArticleScientific reports2022
MRI based radiomics enhances prediction of neurodevelopmental outcome in very preterm neonates.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Machine learning techniques for predicting neurodevelopmental impairments in premature infants: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Article
- Analysis of fetal MRI data reveals no effect on liver maturation following prenatal alcohol exposure.European radiology · 2026Article
- Emerging Applications of Artificial Intelligence in Pediatric Care.Indian journal of pediatrics · 2026Review
- Prediction of motor developmental outcomes based on MRI radiomics in premature infants.Pediatric research · 2026Article
- Structuro-Functional Differentiation and Coupling of Gyri and Sulci in the Neonatal Cortex.Human brain mapping · 2026Article
- Radiomics in fetal brain MRI: a narrative review.European radiology experimental · 2026Review
- Neurodevelopmental disorders in children: the role of MRI in early detection and intervention planning.Frontiers in neuroscience · 2026Review
- 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
- Radiomics models predict early neurodevelopment in infants with congenital cardiac septal defects.Quantitative imaging in medicine and surgery · 2025Article
- Automated Neuroprognostication Via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy.Annals of neurology · 2025Article
- 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To predict adverse neurodevelopmental outcome of very preterm neonates. A total of 166 preterm neonates born between 24-32 weeks' gestation underwent brain MRI early in life. Radiomics features were extracted from T1- and T2- weighted images. Motor, cognitive, and language outcomes were assessed at a corrected age of 18 and 33 months and 4.5 years. Elastic Net was implemented to select the clinical and radiomic features that best predicted outcome. The area under the receiver operating characteristic (AUROC) curve was used to determine the predictive ability of each feature set. Clinical variables predicted cognitive outcome at 18 months with AUROC 0.76 and motor outcome at 4.5 years with AUROC 0.78. T1-radiomics features showed better prediction than T2-radiomics on the total motor outcome at 18 months and gross motor outcome at 33 months (AUROC: 0.81 vs 0.66 and 0.77 vs 0.7). T2-radiomics features were superior in two 4.5-year motor outcomes (AUROC: 0.78 vs 0.64 and 0.8 vs 0.57). Combining clinical parameters and radiomics features improved model performance in motor outcome at 4.5 years (AUROC: 0.84 vs 0.8). Radiomic features outperformed clinical variables for the prediction of adverse motor outcomes. Adding clinical variables to the radiomics model enhanced predictive performance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.