Objective: To develop a prospective cardiac motion self-gating method that provides robust and accurate cardiac triggers in real time. Methods: The proposed self-gating method consists of an “imaging mode” that acquires the k-space segments and a “self-gating mode” that captures the cardiac motion by repeatedly sampling the k-space centerline. A training based principal component analysis algorithm is utilized to process the self-gating data where the projection onto the first principal component was used as the self-gating signal. Retrospective studies using a sequence with self-gating mode only was performed on 8 healthy subjects to validate the accuracy and reliability of the self-gating triggers. Prospective studies using both ECG-gated and self-gated cardiac CINE sequences were conducted on 6 healthy subjects to compare the image quality. Results: Using the ECG as the reference, the proposed method was able to detect self-gating triggers within ±10ms accuracy on all 8 subjects in the retrospective study. The prospectively self-gated CINE sequence successfully detected 100% of the cardiac triggers and provided excellent CINE image quality without using ECG signals. Conclusions: The proposed cardiac self-gating method is a robust and accurate alternative to conventional ECG-based gating method for a number of cardiac MRI applications.
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