Computed tomography (CT) is widely used in pediatric thoracic imaging but involves ionizing radiation. Zero Echo Time (ZTE) MRI enables silent, free-breathing, non-contrast imaging of short-T2 tissues like lung and bone. We aimed to optimize a 4D ZTE MRI protocol for pediatric chest imaging and evaluate the impact of deep learning (DL) reconstruction on diagnostic image quality. Read More

Meeting name: IPR 2026 Congress , 2026

Authors: Shoaib Navaira, Gee Michael, Sagar Pallavi, Patrick Lenehan, Rigsby Devyn, Clark Kendall, Gallo Sebastian, Harrington Samantha, De Arcos Jose, Milshteyn Eugene, Victoria Teresa

Keywords: Chest MRI, Deep Learning, Free-Breathing MRI

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: IPR 2026 Congress , 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