Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model

Robust cardiorespiratory motion correction is critical for high-quality ultra-high-field (UHF) preclinical cardiac magnetic resonance imaging (MRI). Whereas radial tiny golden angle (tyGA) sampling, data-driven self-gating (sg), compressed sensing (CS), and ultrashort echo time (UTE) are individually well-established techniques, their integration into a unified acquisition and reconstruction pipeline, together with systematic validation at 11.7 T remains insufficiently explored. This study presents and validates a UHF-optimized tyGA-based UTE workflow that enables high-temporal-resolution sliding-window dynamic imaging (SW-tyGA-UTE) and high-spatial-resolution cardiorespiratory self-gated cine imaging (Gated-tyGA-UTE) from a single continuous acquired tyGA acquisition. All experiments were performed on an 11.7-T small-animal MRI system in 16 healthy wild-type mice. Cardiac functional parameters, image quality metrics (signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]), and inter-/intra-observer reproducibility were systematically compared between the proposed tyGA-UTE pipeline and two navigator-gated reference techniques: retrospectively gated FLASH and UTE methodologies. SW-tyGA-UTE and Gated-tyGA-UTE reconstructions yielded global left ventricular functional parameters comparable to those obtained with the reference methods (all p > 0.05). All functional metrics showed excellent intra-observer (ICC = 0.94-0.99) and inter-observer (ICC = 0.90-0.98) reproducibility, with ejection fraction showing the highest measurement consistency. Image quality was evaluated using an image-based within-ROI noise quantification approach that captures both thermal noise and reconstruction-related artifacts. In this analysis, the Gated-tyGA-UTE protocol showed no statistically significant differences in left ventricular blood-pool SNR, myocardial SNR, or CNR relative to the reference sequences. In contrast, the high-temporal-resolution sliding-window reconstruction showed significantly reduced image quality across all three metrics, consistent with the expected spatiotemporal trade-off of undersampled dynamic imaging. This study validates a robust, UHF-optimized tyGA-UTE imaging workflow that generates both high-fidelity quantitative cine data and ultra-fast dynamic cardiac images from a single acquisition. The unified pipeline eliminates the need for sequential repeated scans, minimizes anesthesia-related physiological variability, and improves experimental efficiency, providing a practical tool for preclinical cardiac phenotyping, longitudinal studies, and drug screening.