Literature DB >> 16140309

Numerical simulation of cardiovascular dynamics with healthy and diseased heart valves.

Theodosios Korakianitis1, Yubing Shi.   

Abstract

This paper presents a new concentrated parameter model for cardiovascular dynamics that includes an innovative model of heart valve dynamics, which is embedded in the overall model of the four chambers of the heart and the systemic and pulmonary circulation loops. The heart chambers are described with a variable elastance model, and the systemic and pulmonary loops are described with modified Windkessel models. In modelling the heart valve dynamics, the various factors that influence the valve motion are examined, and the governing differential equation for valve motion is derived. The heart valve model includes the influence of the blood pressure effect, the friction effect from the tissue, and from blood motion. As improvement from previous works, the contribution of the blood vortex effect in the vicinity of the valve leaflets to valve motion is specially considered. The proposed model is then used in simulation of healthy and certain pathological conditions such as mitral valve stenosis and aortic regurgitation. The predicted results agree well with results illustrated in cardiology textbooks.

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Year:  2005        PMID: 16140309     DOI: 10.1016/j.jbiomech.2005.06.016

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  20 in total

1.  Computational modelling and evaluation of cardiovascular response under pulsatile impeller pump support.

Authors:  Yubing Shi; Alistair G Brown; Patricia V Lawford; Andreas Arndt; Peter Nuesser; D Rodney Hose
Journal:  Interface Focus       Date:  2011-03-02       Impact factor: 3.906

2.  Boundary conditions of patient-specific fluid dynamics modelling of cavopulmonary connections: possible adaptation of pulmonary resistances results in a critical issue for a virtual surgical planning.

Authors:  Giancarlo Pennati; Chiara Corsini; Daria Cosentino; Tain-Yen Hsia; Vincenzo S Luisi; Gabriele Dubini; Francesco Migliavacca
Journal:  Interface Focus       Date:  2011-03-09       Impact factor: 3.906

3.  Alteration of cerebrovascular haemodynamic patterns due to atrial fibrillation: an in silico investigation.

Authors:  S Scarsoglio; A Saglietto; M Anselmino; F Gaita; L Ridolfi
Journal:  J R Soc Interface       Date:  2017-04       Impact factor: 4.118

4.  Patient-Specific Modelling and Parameter Optimisation to Simulate Dilated Cardiomyopathy in Children.

Authors:  Selim Bozkurt; Waleed Paracha; Kaushiki Bakaya; Silvia Schievano
Journal:  Cardiovasc Eng Technol       Date:  2022-02-22       Impact factor: 2.495

5.  Simulated Performance of the Cleveland Clinic Continuous-Flow Total Artificial Heart Using the Virtual Mock Loop.

Authors:  Takuma Miyamoto; David J Horvath; Dennis W Horvath; Jamshid H Karimov; Nicole Byram; Barry D Kuban; Kiyotaka Fukamachi
Journal:  ASAIO J       Date:  2019-08       Impact factor: 2.872

6.  Impact of atrial fibrillation on the cardiovascular system through a lumped-parameter approach.

Authors:  Stefania Scarsoglio; Andrea Guala; Carlo Camporeale; Luca Ridolfi
Journal:  Med Biol Eng Comput       Date:  2014-09-06       Impact factor: 2.602

Review 7.  Review of zero-D and 1-D models of blood flow in the cardiovascular system.

Authors:  Yubing Shi; Patricia Lawford; Rodney Hose
Journal:  Biomed Eng Online       Date:  2011-04-26       Impact factor: 2.819

8.  Compensatory Effect between Aortic Stiffening and Remodelling during Ageing.

Authors:  Andrea Guala; Carlo Camporeale; Luca Ridolfi
Journal:  PLoS One       Date:  2015-10-01       Impact factor: 3.240

9.  Simulation of the Frank-Starling Law of the Heart.

Authors:  Samo Ribarič; Marjan Kordaš
Journal:  Comput Math Methods Med       Date:  2012-11-29       Impact factor: 2.238

10.  A 1D pulse wave propagation model of the hemodynamics of calf muscle pump function.

Authors:  J M T Keijsers; C A D Leguy; W Huberts; A J Narracott; J Rittweger; F N van de Vosse
Journal:  Int J Numer Method Biomed Eng       Date:  2015-04-21       Impact factor: 2.747

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