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X Demographics
Mendeley readers
Attention Score in Context
| Title |
4D flow cardiovascular magnetic resonance consensus statement
|
|---|---|
| Published in |
Critical Reviews in Diagnostic Imaging, August 2015
|
| DOI | 10.1186/s12968-015-0174-5 |
| Pubmed ID | |
| Authors |
Petter Dyverfeldt, Malenka Bissell, Alex J. Barker, Ann F. Bolger, Carl-Johan Carlhäll, Tino Ebbers, Christopher J. Francios, Alex Frydrychowicz, Julia Geiger, Daniel Giese, Michael D. Hope, Philip J. Kilner, Sebastian Kozerke, Saul Myerson, Stefan Neubauer, Oliver Wieben, Michael Markl |
| Abstract |
Pulsatile blood flow through the cavities of the heart and great vessels is time-varying and multidirectional. Access to all regions, phases and directions of cardiovascular flows has formerly been limited. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has enabled more comprehensive access to such flows, with typical spatial resolution of 1.5×1.5×1.5 - 3×3×3 mm(3), typical temporal resolution of 30-40 ms, and acquisition times in the order of 5 to 25 min. This consensus paper is the work of physicists, physicians and biomedical engineers, active in the development and implementation of 4D Flow CMR, who have repeatedly met to share experience and ideas. The paper aims to assist understanding of acquisition and analysis methods, and their potential clinical applications with a focus on the heart and greater vessels. We describe that 4D Flow CMR can be clinically advantageous because placement of a single acquisition volume is straightforward and enables flow through any plane across it to be calculated retrospectively and with good accuracy. We also specify research and development goals that have yet to be satisfactorily achieved. Derived flow parameters, generally needing further development or validation for clinical use, include measurements of wall shear stress, pressure difference, turbulent kinetic energy, and intracardiac flow components. The dependence of measurement accuracy on acquisition parameters is considered, as are the uses of different visualization strategies for appropriate representation of time-varying multidirectional flow fields. Finally, we offer suggestions for more consistent, user-friendly implementation of 4D Flow CMR acquisition and data handling with a view to multicenter studies and more widespread adoption of the approach in routine clinical investigations. |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 40% |
| Germany | 1 | 5% |
| Saudi Arabia | 1 | 5% |
| New Zealand | 1 | 5% |
| Netherlands | 1 | 5% |
| United Kingdom | 1 | 5% |
| Unknown | 7 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 65% |
| Practitioners (doctors, other healthcare professionals) | 4 | 20% |
| Science communicators (journalists, bloggers, editors) | 2 | 10% |
| Scientists | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 617 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | <1% |
| Spain | 2 | <1% |
| Sweden | 1 | <1% |
| United Kingdom | 1 | <1% |
| Belgium | 1 | <1% |
| Germany | 1 | <1% |
| Japan | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 605 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 107 | 17% |
| Researcher | 103 | 17% |
| Student > Master | 68 | 11% |
| Student > Bachelor | 47 | 8% |
| Student > Doctoral Student | 45 | 7% |
| Other | 110 | 18% |
| Unknown | 137 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 193 | 31% |
| Engineering | 150 | 24% |
| Physics and Astronomy | 21 | 3% |
| Computer Science | 15 | 2% |
| Agricultural and Biological Sciences | 13 | 2% |
| Other | 48 | 8% |
| Unknown | 177 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 40. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2024.
All research outputs
#1,026,829
of 25,578,098 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#27
of 1,380 outputs
Outputs of similar age
#12,888
of 275,558 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#1
of 33 outputs
Altmetric has tracked 25,578,098 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,558 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.