ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2023
Free-breathing simultaneous native myocardial T1, T2 and T1ρ mapping with Cartesian acquisition and dictionary matching.
Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Dark-Blood AdiabaticBioengineering (Basel, Switzerland) · 2026Article
- Free-Running Three-Dimensional Cardiac Extracellular Volume Mapping in a Single Scan With Mid-Scan Contrast Injection.Magnetic resonance in medicine · 2026Article
- Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint TJournal of magnetic resonance imaging : JMRI · 2026Article
- Navigator-gated free-breathing joint TMagma (New York, N.Y.) · 2026Article
- Non-invasive Evaluation of Myocardial Fibrosis Using T1 and T2 Mapping by Cardiac Magnetic Resonance Imaging.Cureus · 2026Review
- Clinical evaluation of free-breathing cardiac multi-parametric mapping using dictionary-based motion correction.Quantitative imaging in medicine and surgery · 2026Article
- 3D Whole-Heart Joint TNMR in biomedicine · 2026Article
- Fine-Tuning Deep Learning Model for Quantitative Knee Joint Mapping With MR Fingerprinting and Its Comparison to Dictionary Matching Method: Fine-Tuning Deep Learning Model for Quantitative MRF.NMR in biomedicine · 2025Article
- Simultaneous free-breathing T1, T2, and T1ρ mapping for myocardial fibrosis detection in non-ischemic cardiomyopathy: A comparative study with conventional techniques.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Article
- Simultaneous multislice cardiac multimapping based on locally low-rank and sparsity constraints.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024Article
- Simultaneous myocardial T1, T2, T1ρ and fat fraction mapping with hybrid dual-echo cartesian acquisition and dictionary matching.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundT1, T2 and T1ρ are well-recognized parameters for quantitative cardiac MRI. Simultaneous estimation of these parameters allows for comprehensive myocardial tissue characterization, such as myocardial fibrosis and edema. However, conventional techniques either quantify the parameters individually with separate breath-hold acquisitions, which may result in unregistered parameter maps, or estimate multiple parameters in a prolonged breath-hold acquisition, which may be intolerable to patients. We propose a free-breathing multi-parametric mapping (FB-MultiMap) technique that provides co-registered myocardial T1, T2 and T1ρ maps in a single efficient acquisition.
methodsThe proposed FB-MultiMap performs electrocardiogram-triggered single-shot Cartesian acquisition over 16 consecutive cardiac cycles, where inversion, T2 and T1ρ preparations are introduced for varying contrasts. A diaphragmatic navigator was used for prospective through-plane motion correction and the in-plane motion was corrected retrospectively with a group-wise image registration method. Quantitative mapping was conducted through dictionary matching of the motion corrected images, where the subject-specific dictionary was created using Bloch simulations for a range of T1, T2 and T1ρ values, as well as B1 factors to account for B1 inhomogeneities. The FB-MultiMap was optimized and validated in numerical simulations, phantom experiments, and in vivo imaging of 15 healthy subjects and six patients with suspected cardiac diseases.
resultsThe phantom T1, T2 and T1ρ values estimated with FB-MultiMap agreed well with reference measurements with no dependency on heart rate. In healthy subjects, FB-MultiMap T1 was higher than MOLLI T1 mapping (1218 ± 50 ms vs. 1166 ± 38 ms, p < 0.001). The myocardial T2 and T1ρ estimated with FB-MultiMap were lower compared to the mapping with T2- or T1ρ-prepared 2D balanced steady-state free precession (T2: 41.2 ± 2.8 ms vs. 42.5 ± 3.1 ms, p = 0.06; T1ρ: 45.3 ± 4.4 ms vs. 50.2 ± 4.0, p < 0.001). The pathological changes in myocardial parameters measured with FB-MultiMap were consistent with conventional techniques in all patients.
conclusionThe proposed free-breathing multi-parametric mapping technique provides co-registered myocardial T1, T2 and T1ρ maps in 16 heartbeats, achieving similar mapping quality to conventional breath-hold mapping methods.
Indexed as
Identifiers
What OpenQuestion holds
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.