Qualitative scores of parenchymal disease severity from 3D lung MRI predict clinical outcomes such as duration of respiratory support in infants with BPD. However, current methods suffer from low signal-to-noise ratio (SNR) and motion-related blurring, reducing interpretability and diagnostic confidence. The inherently quiet zero echo time (ZTE) MRI with deep learning reconstruction (DLR) may improve diagnostic reliability but has not been evaluated in infants. This study assessed the feasibility of ZTE MRI and image quality improvements with DLR in infants with BPD. Read More

Meeting name: SPR 2026 Annual Meeting , 2026

Authors: Munidasa Samal, Bates Alister, Kingma Paul, Hysinger Erik, Woods Jason, Willmering Matthew, Muslu Yavuz, De Arcos Jose, Morin Cara, Kocaoglu Murat, Fleck Robert, Pednekar Amol, Tanimoto Aki, Higano Nara

Keywords: Neonatal, Deep Learning, Pulmonary