The DOI matches its Crossref record.
Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance
Open accessAbstract
BACKGROUND: Phase contrast cardiovascular magnetic resonance (CMR) is able to measure all three directional components of the velocities of blood flow relative to the three spatial dimensions and the time course of the heart cycle. In this article, methods used for the acquisition, visualization, and quantification of such datasets are reviewed and illustrated. METHODS: Currently, the acquisition of 3D cine (4D) phase contrast velocity data, synchronized relative to both cardiac and respiratory movements takes about ten minutes or more, even when using parallel imaging and optimized pulse sequence design. The large resulting datasets need appropriate post processing for the visualization of multidirectional flow, for example as vector fields, pathlines or streamlines, or for retrospective volumetric quantification. APPLICATIONS: Multidirectional velocity acquisitions have provided 3D visualization of large scale flow features of the healthy heart and great vessels, and have shown altered patterns of flow in abnormal chambers and vessels. Clinically relevant examples include retrograde streams in atheromatous descending aortas as potential thrombo-embolic pathways in patients with cryptogenic stroke and marked variations of flow visualized in common aortic pathologies. Compared to standard clinical tools, 4D velocity mapping offers the potential for retrospective quantification of flow and other hemodynamic parameters. CONCLUSIONS: Multidirectional, 3D cine velocity acquisitions are contributing to the understanding of normal and pathologically altered blood flow features. Although more rapid and user-friendly strategies for acquisition and analysis may be needed before 4D velocity acquisitions come to be adopted in routine clinical CMR, their capacity to measure multidirectional flows throughout a study volume has contributed novel insights into cardiovascular fluid dynamics in health and disease.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Markl, M., Frydrychowicz, A., Kozerke, S., Hope, M., & Wieben, O. (2012) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.23632 · Cited by 788
Self-citationDeshmane, A., Gulani, V., Griswold, M. A., & Seiberlich, N. (2012) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.23639 · Cited by 606
SCMR Position Paper (2020) on clinical indications for cardiovascular magnetic resonance
Leiner, T., Bogaert, J., Friedrich, M. G., Mohiaddin, R., Muthurangu, V., Myerson, S., Powell, A. J., Raman, S. V., & Pennell, D. J. (2020) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-020-00682-4 · Cited by 328
The vortex—an early predictor of cardiovascular outcome?
Pedrizzetti, G., La Canna, G., Alfieri, O., & Tonti, G. (2014) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2014.75 · Cited by 284
Emerging Trends in CV Flow Visualization
Sengupta, P. P., Pedrizzetti, G., Kilner, P. J., Kheradvar, A., Ebbers, T., Tonti, G., Fraser, A. G., & Narula, J. (2012) · JACC: Cardiovascular Imaging · doi:10.1016/j.jcmg.2012.01.003 · Cited by 254
Self-citation
Metadata
- Authors
- Markl, M., Kilner, P. J., & Ebbers, T.
- Venue
- Journal of Cardiovascular Magnetic Resonance
- Publisher
- Elsevier BV
- Published
- 2011-01
- Volume
- 13
- Issue
- 1
- Pages
- 7
- ISSN
- 1097-6647 (ISSN-L)
- OpenAlex
- W1968464116
- Cited by
- 463
- References
- 0
- FWCI
- 36.31
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. https://app.cochat.ai/papers/10.1186/1532-429x-13-7
- The paper
- Markl, M., Kilner, P. J., & Ebbers, T. (2011). Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. https://doi.org/10.1186/1532-429x-13-7
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.