Iterative motion‐compensation reconstruction ultra‐short TE (iMoCo UTE) for high‐resolution free‐breathing pulmonary MRI

Purpose To develop a high‐scanning efficiency, motion‐corrected imaging strategy for free‐breathing pulmonary MRI by combining an iterative motion‐compensation reconstruction with a ultrashort echo time (UTE) acquisition called iMoCo UTE. Methods An optimized golden‐angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self‐navigator signals, and then motion‐resolved data was reconstructed by XD golden‐angle radial sparse parallel reconstruction. One state from the motion‐resolved images was selected as a reference, and then motion fields from the other states to the reference were derived via nonrigid registration. Finally, all motion‐resolved data and motion fields were reconstructed by using an iterative motion‐compensation (MoCo) reconstruction with a total generalized variation sparse constraint. Results The iMoCo UTE strategy was evaluated in volunteers and nonsedated pediatric patient (4‐6 years old) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures and higher apparent SNR and contrast‐to‐noise ratio compared to using other motion‐correction strategies, such as soft‐gating, motion‐resolved reconstruction, and nonrigid MoCo. iMoCo UTE also showed promising results in an infant study. Conclusion The proposed iMoCo UTE combines self‐navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency and SNR and to reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free‐breathing lung MRI scans, especially in very challenging application situations such as pediatric MRI studies.