New biomarkers to predict the need for surgery of necrotizing enterocolitis: a study based on abdominal X-ray radiomics and machine learning

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Abstract
Necrotizing enterocolitis (NEC) is an inflammatory intestinal disease that primarily affects premature infants and is a major cause of death in the neonatal period. Approximately half of the affected infants require surgical intervention, but there is no established consensus on the criteria or timing for surgery, making treatment decisions challenging. 291 patients between 2019 and 2023 were categorized into medical group, early surgery group, and late surgery group. The region of interest (ROI) on the abdominal stereotaxic film underwent color-channel transformation, and radiomics features were subsequently extracted. Statistical analysis was then performed using a two-sample independent t test and least absolute shrinkage and selection operator (Lasso) regression to assess the relevant features. By screening and analyzing abdominal X-ray features across different subgroups, three key features-Blue_variance, a_star_variance, and L_star_energy-were identified as common differential markers. These features may serve as imaging biomarkers for predicting the surgical necessity in NEC patients. We identified new parameters of abdominal X-rays in patients with NEC to assess the feasibility of surgical treatment and may provide supporting clinical guidance to clinicians.
Funding Information
  • National Natural Science Foundation of China (82201890)

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