A Multiplanar Radiomics Model Based on Cranial Ultrasound to Predict the White Matter Injury in Premature Infants and an Analysis of its Correlation With Neurodevelopment

Abstract

ObjectivesTo develop and evaluate a multiplanar radiomics model based on cranial ultrasound (CUS) to predict white matter injury (WMI) in premature infants and explore its correlation with neurodevelopment.MethodsWe retrospectively reviewed 267 premature infants. The radiomics features were extracted from five standard sections of CUS. The Spearman's correlation coefficient combined with the least absolute shrinkage and selection operator (LASSO) was applied to select features and build radiomics signature, and a multiplanar radiomics model was constructed based on the radiomics signature of five planes. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC). Infants with WMI were re‐examined by ultrasound at 2 and 4 weeks after birth, and the recovery degree of WMI was evaluated using multiplanar radiomics. The relationship between WMI and the recovery degree and neurodevelopment was analyzed.ResultsThe AUC of the multiplanar radiomics in the training and validation sets were 0.94 and 0.91, respectively. The neurodevelopmental function scores in infants with WMI were significantly lower than those in healthy preterm infants and full‐term newborns (P < .001). There were statistically significant differences in the neurodevelopmental function scores of infants between the 2‐ and 4‐week lesion disappearance and 4‐week lesion persistence (P < .001).ConclusionsThe multiplanar radiomics model showed a good performance in predicting the WMI of premature infants. It can not only provide objective and accurate results but also dynamically monitor the degree of recovery of WMI to predict the prognosis of premature infants.