• Magn Reson Med · Apr 2020

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

    • Xucheng Zhu, Marilynn Chan, Michael Lustig, Kevin M Johnson, and LarsonPeder E ZPEZ0000-0003-4183-3634UCSF/UC Berkeley Graduate Program in Bioengineering, University of California, San Francisco, California.Department of Radiology and Biomedical Imaging, University of California, San Francisco, California..
    • UCSF/UC Berkeley Graduate Program in Bioengineering, University of California, San Francisco, California.
    • Magn Reson Med. 2020 Apr 1; 83 (4): 1208-1221.

    PurposeTo 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.MethodsAn 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.ResultsThe 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.ConclusionThe 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.© 2019 International Society for Magnetic Resonance in Medicine.

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