ArticleFrontiers in neuroscience2022
A radiomics-based study of deep medullary veins in infants: Evaluation of neonatal brain injury with hypoxic-ischemic encephalopathy
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Magnesium Sulfate in Neonatal Hypoxic-Ischemic Encephalopathy: Bridging the Gap Between Molecular Neuroprotection and Clinical Outcomes.Current issues in molecular biology · 2026Review
- MRI evaluation of ADC values and venous variations in fetal cerebral white matter with T2WI signal hyperintensity in late gestation.Frontiers in medicine · 2026Article
- Radiographic Severity of Neonatal Deep Medullary Venous Thrombosis is Associated with Neurodevelopmental Impairment.The Journal of pediatrics · 2025Article
- Prediction of feeding difficulties in neonates with hypoxic-ischemic encephalopathy using magnetic resonance imaging-derived radiomics features.Pediatric radiology · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The deep medullary veins (DMVs) can be evaluated using susceptibility-weighted imaging (SWI). This study aimed to apply radiomic analysis of the DMVs to evaluate brain injury in neonatal patients with hypoxic-ischemic encephalopathy (HIE) using SWI. Methods: This study included brain magnetic resonance imaging of 190 infants with HIE and 89 controls. All neonates were born at full-term (37+ weeks gestation). To include the DMVs in the regions of interest, manual drawings were performed. A Rad-score was constructed using least absolute shrinkage and selection operator (LASSO) regression to identify the optimal radiomic features. Nomograms were constructed by combining the Rad-score with a clinically independent factor. Receiver operating characteristic curve analysis was applied to evaluate the performance of the different models. Clinical utility was evaluated using a decision curve analysis. Results: The combined nomogram model incorporating the Rad-score and clinical independent predictors, was better in predicting HIE (in the training cohort, the area under the curve was 0.97, and in the validation cohort, it was 0.95) and the neurologic outcomes after hypoxic-ischemic (in the training cohort, the area under the curve was 0.91, and in the validation cohort, it was 0.88). Conclusion: Based on radiomic signatures and clinical indicators, we developed a combined nomogram model for evaluating neonatal brain injury associated with perinatal asphyxia.
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