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AZTEK: Adaptive zero TE k‐space trajectories.

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Title: AZTEK: Adaptive zero TE k‐space trajectories.
Authors: Boucneau, Tanguy1 (AUTHOR), Fernandez, Brice2 (AUTHOR), Besson, Florent L.1,3 (AUTHOR), Menini, Anne4 (AUTHOR), Wiesinger, Florian5 (AUTHOR), Durand, Emmanuel1,3 (AUTHOR), Caramella, Caroline1 (AUTHOR), Darrasse, Luc1 (AUTHOR), Maître, Xavier1 (AUTHOR) xavier.maitre@universite-paris-saclay.fr
Source: Magnetic Resonance in Medicine. Feb2021, Vol. 85 Issue 2, p926-935. 10p.
Subjects: Lung cancer, Quality standards
Abstract: Purpose: Because of short signal lifetimes and respiratory motion, 3D lung MRI is still challenging today. Zero‐TE (ZTE) pulse sequences offer promising solutions as they overcome the issue of short T2∗. Nevertheless, as they rely on continuous readout gradients, the trajectories they follow in k‐space are not adapted to retrospective gating and inferred motion correction. Theory and methods: We propose AZTEK (adaptive ZTE k‐space trajectories), a set of 3D radial trajectories featuring three tuning parameters, to adapt the acquisition to any moving organ while keeping seamless transitions between consecutive spokes. Standard ZTE and AZTEK trajectories were compared for static and moving phantom acquisitions as well as for human thoracic imaging performed on 3 volunteers (1 healthy and 2 patients with lung cancer). Results: For the static phantom, we observe comparable image qualities with standard and AZTEK trajectories. For the moving phantom, spatially coherent undersampling artifacts observed on gated images with the standard trajectory are alleviated with AZTEK. The same improvement in image quality is obtained in human, so details are more delineated in the lung with the use of the adaptive trajectory. Conclusion: The AZTEK technique opens the possibility for 3D dynamic ZTE lung imaging with retrospective gating. It enables us to uniformly sample the k‐space for any arbitrary respiratory motion gate, while preserving static image quality, improving dynamic image quality and guaranteeing continuous readout gradient transitions between spokes, which makes it appropriate to ZTE. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: AZTEK: Adaptive zero TE k‐space trajectories.
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Feb2021, Vol. 85 Issue 2, p926-935. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Lung+cancer%22">Lung cancer</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+standards%22">Quality standards</searchLink>
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  Data: Purpose: Because of short signal lifetimes and respiratory motion, 3D lung MRI is still challenging today. Zero‐TE (ZTE) pulse sequences offer promising solutions as they overcome the issue of short T2∗. Nevertheless, as they rely on continuous readout gradients, the trajectories they follow in k‐space are not adapted to retrospective gating and inferred motion correction. Theory and methods: We propose AZTEK (adaptive ZTE k‐space trajectories), a set of 3D radial trajectories featuring three tuning parameters, to adapt the acquisition to any moving organ while keeping seamless transitions between consecutive spokes. Standard ZTE and AZTEK trajectories were compared for static and moving phantom acquisitions as well as for human thoracic imaging performed on 3 volunteers (1 healthy and 2 patients with lung cancer). Results: For the static phantom, we observe comparable image qualities with standard and AZTEK trajectories. For the moving phantom, spatially coherent undersampling artifacts observed on gated images with the standard trajectory are alleviated with AZTEK. The same improvement in image quality is obtained in human, so details are more delineated in the lung with the use of the adaptive trajectory. Conclusion: The AZTEK technique opens the possibility for 3D dynamic ZTE lung imaging with retrospective gating. It enables us to uniformly sample the k‐space for any arbitrary respiratory motion gate, while preserving static image quality, improving dynamic image quality and guaranteeing continuous readout gradient transitions between spokes, which makes it appropriate to ZTE. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/mrm.28483
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              Text: Feb2021
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              Y: 2021
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