Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model.
5 affiliations
- 1Department of Cardiology, the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
- 2Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, Shandong, China.
- 3Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
- 4Department of Radiology, the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
- 5Ulm University, Core Facility Small Animal Imaging, Ulm, Germany.
Abstract
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.
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BibTeX
@article{li2026radial,
title = {{Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model.}},
author = {Hao Li and Patrick Metze and Pengxi Han and Benzheng Wei and Volker Rasche},
journal = {NMR in biomedicine},
year = {2026},
month = oct,
doi = {10.1002/nbm.70418},
url = {https://europepmc.org/article/MED/42875891},
note = {CC BY},
}
RIS
TY - JOUR
TI - Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model.
AU - Hao Li
AU - Patrick Metze
AU - Pengxi Han
AU - Benzheng Wei
AU - Volker Rasche
PY - 2026
DA - 2026/10/30
JO - NMR in biomedicine
DO - 10.1002/nbm.70418
UR - https://europepmc.org/article/MED/42875891
AB - 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.
SN - 0952-3480
SN - 1099-1492
ER -