- Oral presentation
- Open Access
Compressed sensing with synchronized cardio-respiratory sparsity for free-breathing cine MRI: initial comparative study on patients with arrhythmias
© Feng et al.; licensee BioMed Central Ltd. 2014
- Published: 16 January 2014
- Compress Sense
- Respiratory Motion
- Good Image Quality
- Normal Sinus Rhythm
- Free Breathing
Evaluation of myocardial function with MRI is challenging on patients with impaired breath-hold (BH) capabilities or arrhythmias due to the difficulty of respiratory motion suspension and synchronization of cardiac cycles. Compressed sensing (CS) enables free breathing (FB) real-time cine imaging with improved spatiotemporal resolution, but conventional temporal sparsifying transforms do not account for respiratory motion, which limits its performance. In this work, we propose to acquire data continuously in FB using a golden-angle radial sampling scheme and reconstruct images with separated but synchronized cardiac and respiratory motion dimensions using self-detected motion signals. For patients with arrhythmias, both "normal" and "ectopic" cycles are reconstructed by sorting out cardiac cycles with different lengths. The performance of the proposed method was compared to Cartesian BH approach using retrospective ECG-gating in 9 patients.
Image quality comparison between breath-hold and free-breathing cine images.
3.75 ± 0.46
2.0 ± 0.93
3.0 ± 0.53
3.1 ± 0.74
Separation of cardiac and respiratory motion into different dimensions improves compressed sensing reconstruction for free-breathing imaging. Additional physiological information can be obtained by separately reconstructing cardiac cycles of different lengths.
National Institutes of Health: R01 EB000447.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.