| Title |
Patient-Specific Modeling of Hemodynamics: Supporting Surgical Planning in a Fontan Circulation Correction
|
|---|---|
| Published in |
Journal of Cardiovascular Translational Research, January 2018
|
| DOI | 10.1007/s12265-017-9781-x |
| Pubmed ID | |
| Authors |
Theodorus M. J. van Bakel, Kevin D. Lau, Jennifer Hirsch-Romano, Santi Trimarchi, Adam L. Dorfman, C. Alberto Figueroa |
| Abstract |
Computational fluid dynamics (CFD) is a modeling technique that enables calculation of the behavior of fluid flows in complex geometries. In cardiovascular medicine, CFD methods are being used to calculate patient-specific hemodynamics for a variety of applications, such as disease research, noninvasive diagnostics, medical device evaluation, and surgical planning. This paper provides a concise overview of the methods to perform patient-specific computational analyses using clinical data, followed by a case study where CFD-supported surgical planning is presented in a patient with Fontan circulation complicated by unilateral pulmonary arteriovenous malformations. In closing, the challenges for implementation and adoption of CFD modeling in clinical practice are discussed. |
X Demographics
The data shown below were collected from the profiles of 9 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 | 3 | 33% |
| Netherlands | 1 | 11% |
| United Kingdom | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 71 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 25% |
| Researcher | 9 | 13% |
| Other | 7 | 10% |
| Student > Master | 7 | 10% |
| Student > Bachelor | 6 | 8% |
| Other | 10 | 14% |
| Unknown | 14 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 29 | 41% |
| Medicine and Dentistry | 11 | 15% |
| Nursing and Health Professions | 4 | 6% |
| Mathematics | 2 | 3% |
| Computer Science | 1 | 1% |
| Other | 6 | 8% |
| Unknown | 18 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 28 September 2022.
All research outputs
#3,636,209
of 25,478,886 outputs
Outputs from Journal of Cardiovascular Translational Research
#70
of 664 outputs
Outputs of similar age
#77,044
of 450,488 outputs
Outputs of similar age from Journal of Cardiovascular Translational Research
#2
of 16 outputs
Altmetric has tracked 25,478,886 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 664 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 89% 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 450,488 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 16 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 93% of its contemporaries.