Technical Note: Swing golden angle – A navigator‐interleaved golden angle trajectory with eddy current suppression – Application in free‐running cardiac MRI

Abstract Background Golden angle (GA) radial trajectory is advantageous for dynamic magnetic resonance imaging (MRI). Recently, several advanced algorithms have been developed based on navigator‐interleaved GA trajectory to realize free‐running cardiac MRI. However, navigator‐interleaved GA trajectory suffers from the eddy‐current effect, which reduces the image quality. Purpose This work aims to integrate the navigator‐interleaved GA trajectory with clinical cardiac MRI acquisition, with the minimum eddy‐current artifacts. The ultimate goal is to realize a high‐quality free‐running cardiac imaging technique. Methods In this paper, we propose a new “swing golden angle” (swingGA) radial profile order. SwingGA samples the k‐space by rotating back and forth at the generalized golden ratio interval, with smoothly interleaved navigator readouts. The sampling efficiency and angle increment distributions were investigated by numerical simulations. Static phantom imaging experiments were conducted to evaluate the eddy current effect, compared with cartesian, golden angle radial (GA), and tiny golden angle (tGA) trajectories. Furthermore, 12 heart‐healthy subjects (aged 21–25 years) were recruited for free‐running cardiac imaging with different sampling trajectories. Dynamic images were reconstructed by a low‐rank subspace‐constrained algorithm. The image quality was evaluated by signal‐to‐noise‐ratio and spectrum analysis in the heart region, and compared with traditional clinical cardiac MRI images. Results SwingGA pattern achieves the highest sampling efficiency (mSE > 0.925) and the minimum azimuthal angle increment (mAD < 1.05). SwingGA can effectively suppress eddy currents in static phantom images, with the lowest normalized root mean square error (nRMSE) values among radial trajectories. For the in‐vivo cardiac images, swingGA enjoys the highest SNR both in the blood pool and myocardium, and contains the minimum level of high‐frequency artifacts. The free‐running cardiac images have good consistency with traditional clinical cardiac MRI, and the swingGA sampling pattern achieves the best image quality among all sampling patterns. Conclusions The proposed swingGA sampling pattern can effectively improve the sampling efficiency and reduce the eddy currents for the navigator‐interleaved GA sequence. SwingGA is a promising sampling pattern for free‐running cardiac MRI.