Improved ECG-gated cardiac cine imaging with variable initial value based tiny golden-angle radial trajectory.

Background: Breath-held electrocardiogram-gated cardiac cine imaging (ECG-CINE), as the gold standard for assessing cardiac function in magnetic resonance imaging (MRI), is prone to motion artifacts. Conventional golden-angle (CGA) sampling has emerged as a promising technique for mitigating motion effects in real-time cardiac cine imaging. However, in ECG-CINE, the irregular re-binning of radial k-space profiles based on CGA can exacerbate k-space non-uniformity, resulting in severe streaking artifacts. The recently introduced segmented golden-angle ratio (SGA) scheme aims to solve this problem; nevertheless, it sacrifices the desired motion insensitivity.

Purpose: The study aims to develop a more efficient k-space sampling scheme for ECG-CINE that guarantees both improved motion insensitivity and optimized k-space coverage.

Method: Theoretically, to enhance motion insensitivity, it is essential that the single-frame radial k-space profiles acquired within each heartbeat (HB) span as close to a full 360-degree range as possible. Meanwhile, to ensure uniform data coverage, the sequentially acquired k-space profiles need to be evenly distributed both within each HB and across multiple HBs. In this study, we propose a Variable Initial value-based tiny Golden-Angle radial trajectory (VIGA) to achieve these two goals. Specifically, VIGA is a two-step approach: First, the tiny golden-angle ratio is applied to the k-space profiles within each HB to maintain motion insensitivity and k-space uniformity as in CGA. Second, a golden ratio of the golden angle used within each HB is applied to the initial k-space profiles across adjacent HBs to optimize coverage further. We validated the proposed VIGA method through numerical simulations, phantom experiments, and prospective and retrospective in vivo cardiac cine experiments.

Results: Numerical simulations revealed that the k-space uniformity of CGA is highly dependent on the number of spokes per HB, whereas VIGA and SGA maintained nearly optimal k-space coverage regardless of this parameter. Both phantom and prospective studies demonstrated that VIGA outperforms CGA when the number of spokes per HB is suboptimal, and surpasses SGA in conditions with residual respiratory motion. The standard deviation of gradient scores indicates statistical significance between CGA and VIGA under free-breathing conditions (p = 0.039) and between SGA and VIGA under all conditions tested (Free-breathing, 200 spokes/HB: p = 0.028; Breath-holding, 200 spokes/HB: p = 0.008; Free-breathing, 200 spokes/HB: p = 0.013; Breath-holding, 200 spokes/HB: p = 0.011). Retrospective results demonstrated that doctor ratings for SGA were lower than those for VIGA, and the ratings for systole images using VIGA were significantly higher than those using CGA (2.55 ± 0.45 vs. 3.29 ± 0.52; p = 0.04).

Conclusion: A novel and efficient k-space sampling scheme, named VIGA, was proposed to improve k-space uniformity and motion insensitivity. VIGA facilitates robust image quality in both prospective and retrospective cardiac cine imaging, demonstrating its potential as a clinically viable alternative to CGA and SGA.