{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiology, the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.",
    "Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, Shandong, China.",
    "Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.",
    "Department of Radiology, the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.",
    "Ulm University, Core Facility Small Animal Imaging, Ulm, Germany."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Hao Li",
      "orcid": "0000-0002-8644-0263"
    },
    {
      "affs": [
        2
      ],
      "name": "Patrick Metze"
    },
    {
      "affs": [
        3
      ],
      "name": "Pengxi Han"
    },
    {
      "affs": [
        1
      ],
      "name": "Benzheng Wei",
      "orcid": "0000-0001-9640-4947"
    },
    {
      "affs": [
        2,
        4
      ],
      "name": "Volker Rasche",
      "orcid": "0000-0001-8844-3583"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bv4nz8am50wvn.bib",
  "cited_by": 0,
  "doi": "10.1002/nbm.70418",
  "fulltext_url": "https://europepmc.org/articles/PMC13669412",
  "id": "bv4nz8am50wvn",
  "issns": [
    "0952-3480",
    "1099-1492"
  ],
  "landing_url": "https://europepmc.org/article/MED/42875891",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2741|Advanced MRI Techniques and Applications"
    ]
  ],
  "openalex": "W7222074669",
  "pdf_url": "https://europepmc.org/articles/PMC13669412?pdf=render",
  "pmcid": "PMC13669412",
  "pmid": "42875891",
  "published": "2026-10-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bv4nz8am50wvn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:46Z",
      "native_id": "MED:42875891",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42875891"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Advanced MRI Techniques and Applications",
      "subfield": "imaging"
    }
  ],
  "title": "Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model.",
  "title_text": "Radial Tiny Golden Angle UTE (tyGA-UTE) for Cardiac MRI in the Small Animal Model.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:46Z",
  "url": "https://research.draconitic.com/paper/bv4nz8am50wvn",
  "venue": "NMR in biomedicine",
  "versions": []
}