ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2024
Image navigator-based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis.
Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05473117 (iNav-based, Automated Coronary Magnetic Resonance Angiography for the Detection of Coronary Artery Stenosis), which is not on this map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
iNav-based, Automated Coronary Magnetic Resonance Angiography for the Detection of Coronary Artery Stenosis (iNav-AUTO CMRA)
Who cites it
4 citing papers in PubMed.
- MRCA Combined With Zero-Contrast IVUS-Guided PCI in a Patient With NSTE-ACS and Severe Contrast Allergy.JACC. Case reports · 2026Article
- Improvements in the spatial resolution of coronary magnetic resonance angiography enhance the diagnostic performance in comparison to quantitative coronary angiography.European heart journal. Imaging methods and practice · 2026Article
- Development and validation of a novel coronary artery disease risk prediction model.Journal of translational medicine · 2025Review
- An explainable dual-modal diagnostic model for coronary artery disease: a feature-gated approach using tongue and facial image features.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoronary computed tomography angiography (CCTA) is recommended as the first-line diagnostic imaging modality in low-to-intermediate-risk individuals suspected of stable coronary artery disease (CAD). However, CCTA exposes patients to ionizing radiation and potentially nephrotoxic contrast agents. Invasive coronary angiography is the gold-standard investigation to guide coronary revascularisation strategy; however, invasive procedures incur an inherent risk to the patient. Coronary magnetic resonance angiography (CMRA) avoids these issues. Nevertheless, clinical implementation is currently limited due to extended scanning durations, inconsistent image quality, and consequent lack of diagnostic accuracy. Several technical CMRA innovations, including advanced respiratory motion correction with 100% scan efficiency (no data rejection), fast image acquisition with motion-corrected undersampled image reconstruction, and deep-learning-based automated planning, have been implemented and now await clinical validation in multi-center trials.
methodsThe objective of the image navigator-based, automated CMRA prospective multi-center study is to evaluate the diagnostic accuracy of a newly developed, state-of-the-art, standardized, and automated CMRA framework compared to CCTA in 201 patients undergoing clinical investigation for CAD. The study protocol mandates the administration of oral beta-blockers to decrease heart rate to below 60 bpm and the use of sublingual nitroglycerine spray to induce vasodilation. Additionally, the study incorporates the utilization of standardized postprocessing with sliding-thin-slab multiplanar reformatting, in combination with evaluation of the source images, to optimize the visualization of coronary artery stenosis. DISCUSSION: If proven effective, CMRA could provide a non-invasive, needle-free, yet also clinically viable, alternative to CCTA.
trial registrationThis study is registered at ClinicalTrials.gov (NCT05473117).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.