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Motion robust high resolution 3D free‐breathing pulmonary MRI using dynamic 3D image self‐navigator
Author(s) -
Jiang Wenwen,
Ong Frank,
Johnson Kevin M.,
Nagle Scott K.,
Hope Thomas A.,
Lustig Michael,
Larson Peder E.Z.
Publication year - 2018
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26958
Subject(s) - computer science , computer vision , motion compensation , artificial intelligence , image quality , breathing , magnetic resonance imaging , motion (physics) , motion estimation , temporal resolution , image (mathematics) , medicine , physics , radiology , anatomy , optics
Purpose To achieve motion robust high resolution 3D free‐breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data. Methods Five‐minute free‐breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self‐navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft‐gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion‐resolved technique to provide images of all respiratory motion states. Results Respiratory motion estimation derived from the proposed dynamic 3D self‐navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC‐based navigators. Respiratory motion compensation with soft‐gating and respiratory motion‐resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients. Conclusion An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high‐resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954–2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine.