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Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics

Overview of attention for article published in Cardiovascular Engineering and Technology, July 2017
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81 Mendeley
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Article details
Title
Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics
Published in
Cardiovascular Engineering and Technology, July 2017
DOI 10.1007/s13239-017-0324-z
Pubmed ID
Authors
Abstract

This study aims to investigate the capability of smoothed particle hydrodynamics (SPH), a fully Lagrangian mesh-free method, to simulate the bulk blood flow dynamics in two realistic left ventricular (LV) models. Three dimensional geometries and motion of the LV, proximal left atrium and aortic root are extracted from cardiac magnetic resonance imaging and multi-slice computed tomography imaging data. SPH simulation results are analyzed and compared with those obtained using a traditional finite volume-based numerical method, and to in vivo phase contrast magnetic resonance imaging and echocardiography data, in terms of the large-scale blood flow phenomena usually clinically measured. A quantitative comparison of the velocity fields and global flow parameters between the in silico models and the in vivo data shows a reasonable agreement, given the inherent uncertainties and limitations in the modeling and imaging techniques. The results indicate the capability of SPH as a promising tool for predicting clinically relevant large-scale LV flow information.

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X Demographics

X Demographics

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

Mendeley demographics

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 14 17%
Researcher 9 11%
Student > Master 8 10%
Other 5 6%
Student > Bachelor 5 6%
Other 12 15%
Unknown 28 35%
Readers by discipline
Readers by discipline Count As %
Engineering 24 30%
Medicine and Dentistry 4 5%
Chemical Engineering 3 4%
Mathematics 3 4%
Computer Science 3 4%
Other 5 6%
Unknown 39 48%
Attention Score in Context

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 17 July 2021.
All research outputs
#17,306,843
of 26,367,288 outputs
Outputs from Cardiovascular Engineering and Technology
#117
of 211 outputs
Outputs of similar age
#201,596
of 332,678 outputs
Outputs of similar age from Cardiovascular Engineering and Technology
#7
of 9 outputs
Altmetric has tracked 26,367,288 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 211 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 332,678 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.