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Heart blood flow simulation: a perspective review

Overview of attention for article published in BioMedical Engineering OnLine, August 2016
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Mentioned by

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2 tweeters

Citations

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66 Dimensions

Readers on

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287 Mendeley
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Title
Heart blood flow simulation: a perspective review
Published in
BioMedical Engineering OnLine, August 2016
DOI 10.1186/s12938-016-0224-8
Pubmed ID
Authors

Siamak N. Doost, Dhanjoo Ghista, Boyang Su, Liang Zhong, Yosry S. Morsi

Abstract

Cardiovascular disease (CVD), the leading cause of death today, incorporates a wide range of cardiovascular system malfunctions that affect heart functionality. It is believed that the hemodynamic loads exerted on the cardiovascular system, the left ventricle (LV) in particular, are the leading cause of CVD initiation and propagation. Moreover, it is believed that the diagnosis and prognosis of CVD at an early stage could reduce its high mortality and morbidity rate. Therefore, a set of robust clinical cardiovascular assessment tools has been introduced to compute the cardiovascular hemodynamics in order to provide useful insights to physicians to recognize indicators leading to CVD and also to aid the diagnosis of CVD. Recently, a combination of computational fluid dynamics (CFD) and different medical imaging tools, image-based CFD (IB-CFD), has been widely employed for cardiovascular functional assessment by providing reliable hemodynamic parameters. Even though the capability of CFD to provide reliable flow dynamics in general fluid mechanics problems has been widely demonstrated for many years, up to now, the clinical implications of the IB-CFD patient-specific LVs have not been applicable due to its limitations and complications. In this paper, we review investigations conducted to numerically simulate patient-specific human LV over the past 15 years using IB-CFD methods. Firstly, we divide different studies according to the different LV types (physiological and different pathological conditions) that have been chosen to reconstruct the geometry, and then discuss their contributions, methodologies, limitations, and findings. In this regard, we have studied CFD simulations of intraventricular flows and related cardiology insights, for (i) Physiological patient-specific LV models, (ii) Pathological heart patient-specific models, including myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy and hypoplastic left heart syndrome. Finally, we discuss the current stage of the IB-CFD LV simulations in order to mimic realistic hemodynamics of patient-specific LVs. We can conclude that heart flow simulation is on the right track for developing into a useful clinical tool for heart function assessment, by (i) incorporating most of heart structures' (such as heart valves) operations, and (ii) providing useful diagnostic indices based hemodynamic parameters, for routine adoption in clinical usage.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 287 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Belgium 1 <1%
Unknown 285 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 63 22%
Researcher 46 16%
Student > Bachelor 35 12%
Student > Master 32 11%
Student > Doctoral Student 15 5%
Other 40 14%
Unknown 56 20%
Readers by discipline Count As %
Engineering 132 46%
Medicine and Dentistry 30 10%
Mathematics 10 3%
Agricultural and Biological Sciences 10 3%
Computer Science 10 3%
Other 30 10%
Unknown 65 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 03 November 2016.
All research outputs
#13,304,212
of 21,346,066 outputs
Outputs from BioMedical Engineering OnLine
#351
of 787 outputs
Outputs of similar age
#154,068
of 286,578 outputs
Outputs of similar age from BioMedical Engineering OnLine
#4
of 7 outputs
Altmetric has tracked 21,346,066 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 787 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 52% 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 286,578 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.