Topology preserving embedded network for PICC segmentation in pediatric X ray images

Peripherally inserted central catheters (PICCs) are essential for long-term infusion in vulnerable pediatric patients. Optimal tip placement in the lower third of the superior vena cava or at the cavoatrial junction is critical to prevent serious complications. Verifying correct tip position in infants and toddlers is challenging because of very small anatomic target zones, non-standard radiograph acquisition, interference from other devices, low contrast, and high risk of catheter migration. Existing automated segmentation methods, mostly developed for adults, perform poorly on pediatric images. We retrospectively collected 1184 PICC patients from three medical centers, including 280 pediatric cases (210 neonates, 46 infants, 24 toddlers), with appropriate ethical approval. We introduce TopNet, a topology-preserving embedded network designed for automated PICC segmentation in pediatric patients. TopNet maintains catheter continuity and enables precise tip localization under difficult conditions. Quantitative and qualitative evaluations show superior segmentation and tip localization on both internal and external validation.