Lorenzo Di Sopra1, Davide Piccini1,2, Simone Coppo1, Matthias Stuber1,3, Jérôme Yerly1,3. 1. Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland. 2. Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland. 3. Center for Biomedical Imaging, Lausanne, Switzerland.
Abstract
PURPOSE: To develop a previously reported, electrocardiogram (ECG)-gated, motion-resolved 5D compressed sensing whole-heart sparse MRI methodology into an automated, optimized, and fully self-gated free-running framework in which external gating or triggering devices are no longer needed. METHODS: Cardiac and respiratory self-gating signals were extracted from raw image data acquired in 12 healthy adult volunteers with a non-ECG-triggered 3D radial golden-angle 1.5 T balanced SSFP sequence. To extract cardiac self-gating signals, central k-space coefficient signal analysis (k0 modulation), as well as independent and principal component analyses were performed on selected k-space profiles. The procedure yielding triggers with the smallest deviation from those of the reference ECG was selected for the automated protocol. Thus, optimized cardiac and respiratory self-gating signals were used for binning in a compressed sensing reconstruction pipeline. Coronary vessel length and sharpness of the resultant 5D images were compared with image reconstructions obtained with ECG-gating. RESULTS: Principal component analysis-derived cardiac self-gating triggers yielded a smaller deviation ( 17.4 ± 6.1 ms ) from the reference ECG counterparts than k0 modulation ( 26 ± 7.5 ms ) or independent component analysis ( 19.8 ± 5.2 ms ). Cardiac and respiratory motion-resolved 5D images were successfully reconstructed with the automated and fully self-gated approach. No significant difference was found for coronary vessel length and sharpness between images reconstructed with the fully self-gated and the ECG-gated approach (all P ≥ . 06 ). CONCLUSION: Motion-resolved 5D compressed sensing whole-heart sparse MRI has successfully been developed into an automated, optimized, and fully self-gated free-running framework in which external gating, triggering devices, or navigators are no longer mandatory. The resultant coronary MRA image quality was equivalent to that obtained with conventional ECG-gating.
PURPOSE: To develop a previously reported, electrocardiogram (ECG)-gated, motion-resolved 5D compressed sensing whole-heart sparse MRI methodology into an automated, optimized, and fully self-gated free-running framework in which external gating or triggering devices are no longer needed. METHODS: Cardiac and respiratory self-gating signals were extracted from raw image data acquired in 12 healthy adult volunteers with a non-ECG-triggered 3D radial golden-angle 1.5 T balanced SSFP sequence. To extract cardiac self-gating signals, central k-space coefficient signal analysis (k0 modulation), as well as independent and principal component analyses were performed on selected k-space profiles. The procedure yielding triggers with the smallest deviation from those of the reference ECG was selected for the automated protocol. Thus, optimized cardiac and respiratory self-gating signals were used for binning in a compressed sensing reconstruction pipeline. Coronary vessel length and sharpness of the resultant 5D images were compared with image reconstructions obtained with ECG-gating. RESULTS: Principal component analysis-derived cardiac self-gating triggers yielded a smaller deviation ( 17.4 ± 6.1 ms ) from the reference ECG counterparts than k0 modulation ( 26 ± 7.5 ms ) or independent component analysis ( 19.8 ± 5.2 ms ). Cardiac and respiratory motion-resolved 5D images were successfully reconstructed with the automated and fully self-gated approach. No significant difference was found for coronary vessel length and sharpness between images reconstructed with the fully self-gated and the ECG-gated approach (all P ≥ . 06 ). CONCLUSION: Motion-resolved 5D compressed sensing whole-heart sparse MRI has successfully been developed into an automated, optimized, and fully self-gated free-running framework in which external gating, triggering devices, or navigators are no longer mandatory. The resultant coronary MRA image quality was equivalent to that obtained with conventional ECG-gating.
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