1. Self-navigated 4D cartesian imaging of periodic motion in the body trunk using partial k-space compressed sensing.
- Author
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Küstner T, Würslin C, Schwartz M, Martirosian P, Gatidis S, Brendle C, Seith F, Schick F, Schwenzer NF, Yang B, and Schmidt H
- Subjects
- Algorithms, Humans, Respiration, Retrospective Studies, Imaging, Three-Dimensional methods, Magnetic Resonance Imaging methods, Movement physiology, Torso diagnostic imaging
- Abstract
Purpose: To enable fast and flexible high-resolution four-dimensional (4D) MRI of periodic thoracic/abdominal motion for motion visualization or motion-corrected imaging., Methods: We proposed a Cartesian three-dimensional k-space sampling scheme that acquires a random combination of k-space lines in the ky/kz plane. A partial Fourier-like constraint compacts the sampling space to one half of k-space. The central k-space line is periodically acquired to allow an extraction of a self-navigated respiration signal used to populate a k-space of multiple breathing positions. The randomness of the acquisition (induced by periodic breathing pattern) yields a subsampled k-space that is reconstructed using compressed sensing. Local image evaluations (coefficient of variation and slope steepness through organs) reveal information about motion resolvability. Image quality is inspected by a blinded reading. Sequence and reconstruction method are made publicly available., Results: The method is able to capture and reconstruct 4D images with high image quality and motion resolution within a short scan time of less than 2 min. These findings are supported by restricted-isometry-property analysis, local image evaluation, and blinded reading., Conclusion: The proposed method provides a clinical feasible setup to capture periodic respiratory motion with a fast acquisition protocol and can be extended by further surrogate signals to capture additional periodic motions. Retrospective parametrization allows for flexible tuning toward the targeted applications. Magn Reson Med 78:632-644, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)
- Published
- 2017
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