Genetic burden and multidimensional predictors in prenatal diagnosis of fetal congenital diaphragmatic hernia.

Abstract

This study aims to assess the genetic burden of fetal congenital diaphragmatic hernia (CDH) and identify prenatal, perinatal, and postnatal predictors to improve early diagnosis, monitoring, and intervention. This study included 130 CDH fetuses who underwent invasive prenatal diagnosis, with fetal prognosis evaluated using imaging parameters such as observed-to-expected lung-to-head ratio (o/e LHR), observed-to-expected total lung volume (o/e TLV), and percent predicted lung volume (PPLV). Clinical outcomes included neonatal outcomes, extracorporeal membrane oxygenation (ECMO) requirement, and post-neonatal prognosis. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to evaluate prognostic indicators and construct predictive models. Chromosomal microarray analysis (CMA) and exome sequencing (ES) yielded diagnostic rates of 7.7% and 8.7%, respectively, identifying a wide spectrum of pathogenic variants and highlighting the genetic heterogeneity of CDH. Among imaging parameters, o/e LHR, o/e TLV, and PPLV were significantly associated with neonatal outcomes, ECMO requirement, and post-neonatal prognosis. Multivariable models incorporating these parameters achieved high predictive accuracy (AUCs > 0.85), with the neonatal outcomes model reaching an AUC of 0.929, sensitivity of 93.2%, and specificity of 78.6%. By integrating genetic, imaging and clinical outcome data, this study identified CMA and ES as key tools for detecting genetic burden in CDH fetuses, and confirmed o/e LHR, o/e TLV, PPLV, and liver herniation as reliable prognostic indicators. Multivariable models based on these parameters showed strong predictive performance. A combined genetic-imaging approach is recommended to support individualized risk assessment and guide perinatal management.