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Desynchronization of Cartesian k-space sampling and periodic motion for improved retrospectively self-gated 3D lung MRI using quasi-random numbers

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Ehses,  P
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Weick, S., Völker, M., Hemberger, K., Meyer, C., Ehses, P., Polat, B., et al. (2017). Desynchronization of Cartesian k-space sampling and periodic motion for improved retrospectively self-gated 3D lung MRI using quasi-random numbers. Magnetic Resonance in Medicine, 77(2), 787-793. doi:10.1002/mrm.26159.


Cite as: http://hdl.handle.net/21.11116/0000-0000-C335-8
Abstract
Purpose To demonstrate that desynchronization between Cartesian k-space sampling and periodic motion in free-breathing lung MRI improves the robustness and efficiency of retrospective respiratory self-gating. Methods Desynchronization was accomplished by reordering the phase (ky) and partition (kz) encoding of a three-dimensional FLASH sequence according to two-dimensional, quasi-random (QR) numbers. For retrospective respiratory self-gating, the k-space center signal (DC signal) was acquired separately after each encoded k-space line. QR sampling results in a uniform distribution of k-space lines after gating. Missing lines resulting from the gating process were reconstructed using iterative GRAPPA. Volunteer measurements were performed to compare quasi-random with conventional sampling. Patient measurements were performed to demonstrate the feasibility of QR sampling in a clinical setting. Results The uniformly sampled k-space after retrospective gating allows for a more stable iterative GRAPPA reconstruction and improved ghost artifact reduction compared with conventional sampling. It is shown that this stability can either be used to reduce the total scan time or to reconstruct artifact-free data sets in different respiratory phases, both resulting in an improved efficiency of retrospective respiratory self-gating. Conclusion QR sampling leads to desynchronization between repeated data acquisition and periodic respiratory motion. This results in an improved motion artifact reduction in shorter scan time.