Cardiac self-gating using blind source separation for 2D cine cardiovascular magnetic resonance imaging

Abstract

Purpose To develop and validate a new cardiac self-gating algorithm using blind source separation for 2D cine steady-state free precession (SSFP) imaging. Methods A standard cine SSFP sequence was modified so that the center point of k-space was sampled with each excitation. The center points of k-space were processed by 4 blind source separation methods, and used to detect heartbeats and assign k-space data to appropriate time points in the cardiac cycle. The proposed self-gating technique was prospectively validated in 8 patients against the standard electrocardiogram (ECG)-gating method by comparing the cardiac cycle lengths, image quality metrics, and ventricular volume measurements. Results There was close agreement between the cardiac cycle length using the ECG- and self-gating methods (bias 0.0 bpm, 95% limits of agreement ±2.1 bpm). The image quality metrics were not significantly different between the ECG- and self-gated images. The ventricular volumes, stroke volumes, and mass measured from self-gated images were all comparable with those from ECG-gated images (all biases <5%). Conclusion The self-gating method yielded comparable cardiac cycle length, image quality, and ventricular measurements compared with standard ECG-gated cine imaging. It may simplify patient preparation, be more robust when there is arrhythmia, and allow cardiac gating at higher field strengths.