An automated approach to fully self-gated free-running cardiac and respiratory motion-resolved 5D whole-heart MRI.

Abstract

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. 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 1.5T 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. Principal component analysis-derived cardiac self-gating triggers yielded a smaller deviation ( ) from the reference ECG counterparts than k0 modulation ( ) or independent component analysis ( ). 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 ). 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.