Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise

Research output: Contribution to journalArticlepeer-review

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Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise. / Bahraseman, Hamidreza Ghasemi; Hassani, Kamran; khosravi, Arezoo ; Navidbakhsh, Mahdi; Espino, Daniel; Fatouraee, Naser; Kazemi-Saleh, Davood .

In: Perfusion, Vol. 29, No. 4, 07.2014, p. 340-350.

Research output: Contribution to journalArticlepeer-review

Harvard

Bahraseman, HG, Hassani, K, khosravi, A, Navidbakhsh, M, Espino, D, Fatouraee, N & Kazemi-Saleh, D 2014, 'Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise', Perfusion, vol. 29, no. 4, pp. 340-350. https://doi.org/10.1177/0267659114521103

APA

Bahraseman, H. G., Hassani, K., khosravi, A., Navidbakhsh, M., Espino, D., Fatouraee, N., & Kazemi-Saleh, D. (2014). Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise. Perfusion, 29(4), 340-350. https://doi.org/10.1177/0267659114521103

Vancouver

Author

Bahraseman, Hamidreza Ghasemi ; Hassani, Kamran ; khosravi, Arezoo ; Navidbakhsh, Mahdi ; Espino, Daniel ; Fatouraee, Naser ; Kazemi-Saleh, Davood . / Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise. In: Perfusion. 2014 ; Vol. 29, No. 4. pp. 340-350.

Bibtex

@article{4afa3da55bd94eb5b1e61d5e161477ab,
title = "Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise",
abstract = "Computational simulations have the potential to aid understanding of cardiovascular hemodynamics under physiological conditions, including exercise. Therefore, blood hemodynamic parameters during different heart rates, rest and exercise have been investigated, using a numerical method. A model was developed for a healthy subject. Using geometrical data acquired by echo-Doppler, a two-dimensional model of the chamber of aortic sinus valsalva and aortic root was created. Systolic ventricular and aortic pressures were applied as boundary conditions computationally. These pressures were the initial physical conditions applied to the model to predict valve deformation and changes in hemodynamics. They were the clinically measured brachial pressures plus differences between brachial, central and left ventricular pressures. Echocardiographic imaging was also used to acquire different ejection times, necessary for pressure waveform equations of blood flow during exercise. A fluid-structure interaction simulation was performed, using an arbitrary Lagrangian-Eulerian mesh. During exercise, peak vorticity increased by 14.8%, peak shear rate by 15.8%, peak cell Reynolds number by 20%, peak leaflet tip velocity increased by 47% and the blood velocity increased by 3% through the leaflets, whereas full opening time decreased by 11%. Our results show that numerical methods can be combined with clinical measurements to provide good estimates of patient-specific hemodynamics at different heart rates.",
author = "Bahraseman, {Hamidreza Ghasemi} and Kamran Hassani and Arezoo khosravi and Mahdi Navidbakhsh and Daniel Espino and Naser Fatouraee and Davood Kazemi-Saleh",
year = "2014",
month = jul,
doi = "10.1177/0267659114521103",
language = "English",
volume = "29",
pages = "340--350",
journal = "Perfusion",
issn = "0267-6591",
publisher = "SAGE Publications",
number = "4",

}

RIS

TY - JOUR

T1 - Combining numerical and clinical methods to assess aortic valve hemodynamics during exercise

AU - Bahraseman, Hamidreza Ghasemi

AU - Hassani, Kamran

AU - khosravi, Arezoo

AU - Navidbakhsh, Mahdi

AU - Espino, Daniel

AU - Fatouraee, Naser

AU - Kazemi-Saleh, Davood

PY - 2014/7

Y1 - 2014/7

N2 - Computational simulations have the potential to aid understanding of cardiovascular hemodynamics under physiological conditions, including exercise. Therefore, blood hemodynamic parameters during different heart rates, rest and exercise have been investigated, using a numerical method. A model was developed for a healthy subject. Using geometrical data acquired by echo-Doppler, a two-dimensional model of the chamber of aortic sinus valsalva and aortic root was created. Systolic ventricular and aortic pressures were applied as boundary conditions computationally. These pressures were the initial physical conditions applied to the model to predict valve deformation and changes in hemodynamics. They were the clinically measured brachial pressures plus differences between brachial, central and left ventricular pressures. Echocardiographic imaging was also used to acquire different ejection times, necessary for pressure waveform equations of blood flow during exercise. A fluid-structure interaction simulation was performed, using an arbitrary Lagrangian-Eulerian mesh. During exercise, peak vorticity increased by 14.8%, peak shear rate by 15.8%, peak cell Reynolds number by 20%, peak leaflet tip velocity increased by 47% and the blood velocity increased by 3% through the leaflets, whereas full opening time decreased by 11%. Our results show that numerical methods can be combined with clinical measurements to provide good estimates of patient-specific hemodynamics at different heart rates.

AB - Computational simulations have the potential to aid understanding of cardiovascular hemodynamics under physiological conditions, including exercise. Therefore, blood hemodynamic parameters during different heart rates, rest and exercise have been investigated, using a numerical method. A model was developed for a healthy subject. Using geometrical data acquired by echo-Doppler, a two-dimensional model of the chamber of aortic sinus valsalva and aortic root was created. Systolic ventricular and aortic pressures were applied as boundary conditions computationally. These pressures were the initial physical conditions applied to the model to predict valve deformation and changes in hemodynamics. They were the clinically measured brachial pressures plus differences between brachial, central and left ventricular pressures. Echocardiographic imaging was also used to acquire different ejection times, necessary for pressure waveform equations of blood flow during exercise. A fluid-structure interaction simulation was performed, using an arbitrary Lagrangian-Eulerian mesh. During exercise, peak vorticity increased by 14.8%, peak shear rate by 15.8%, peak cell Reynolds number by 20%, peak leaflet tip velocity increased by 47% and the blood velocity increased by 3% through the leaflets, whereas full opening time decreased by 11%. Our results show that numerical methods can be combined with clinical measurements to provide good estimates of patient-specific hemodynamics at different heart rates.

U2 - 10.1177/0267659114521103

DO - 10.1177/0267659114521103

M3 - Article

VL - 29

SP - 340

EP - 350

JO - Perfusion

JF - Perfusion

SN - 0267-6591

IS - 4

ER -