Research Article
Patient Specific Cardiovascular Disease Modelling Based on the Computational Fluid Dynamics Simulations: Segmentation and Hemodynamic Model of a Thoracic Artery
Abstract
Nowadays cardiovascular diseases (CVDs), mostly
coronary artery diseases become a leading cause of death. Flow dynamics of a
vessel is important to diagnose a CVD in advance. However, hemodynamic
parameters may not be measured directly. Hence, computational methods are
increasingly being used in the fields of neurosurgery and cardiovascular
surgery to obtain realistic physiological simulations. In this study, a patient
specific thoracic artery model is first segmented based on the MRI images and
then a thoracic aneurysm disease model is simulated to assess blood flow
changes under the predefined conditions.
References
- 1) WHO, Fact sheets. Available from: who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds). Revisited: 08.12.2019.
- 2) European Cardiovascular Disease Statistics, CVD Statistics. Available from: ehnheart.org/cvd-statistics.html. Revisited: 08.12.2019.
- 3) American Heart Association, Heart disease and stroke statistics. Available from: heart.org/-/media/data-import/downloadables/heart-disease-and-stroke-statistics-2018---at-a-glance-ucm_498848.pdf. Revisited: 08.12.2019.
- 4) Mohammed Y., “Three dimensional finite-element modeling of blood flow in elastic vessels: effects of arterial geometry and elasticity on aneurysm growth and rupture”, Master thesis, Ryerson University, Toronto, Canada, (2010).
- 5) Canstein C. et al., “3D MR flow analysis in realistic rapid‐prototyping model systems of the thoracic aorta: comparison with in vivo data and computational fluid dynamics in identical vessel geometries”, Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 59(3): 535-546, (2008).
- 6) Van Pelt R., Nguyen H., Ter Haar Romeny B., Vilanova A., “Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements”, International journal of computer assisted radiology and surgery, 7(2): 217-224, (2012).
- 7) Howe G., “Multiphysics simulation of a coronary artery”, Master thesis, Faculty of California Polytechnic State University, San Luis Obispo, (2013).
- 8) Secomb T. W., “Hemodynamics”, Comprehensive physiology, 6(2): 975-1003, (2011).
- 9) Zarandi M. M., Mongrain R., Bertrand O. F., “Non-newtonian hemodynamics and shear stress distribution in three dimensional model of healthy and stented coronary artery bifurcation”, In proceeding of the comsol conference, Boston, 1-5, (2010).
- 10) Tado R., Deoghare A. B., Pandey K. M., “Computational Study of Blood Flow Analysis for Coronary Artery Disease”, In proceeding of the World Academy of Science Engineering and Technology conference, International Journal of Biomedical and Biological Engineering, 12(2), 35-39, (2018).
- 11) Ohhara Y. et al., “Investigation of blood flow in the external carotid artery and its branches with a new 0D peripheral model”, Biomedical engineering online, 15(1): 16, (2016).
- 12) Takizawa K. et al., “Patient-specific computer modeling of blood flow in cerebral arteries with aneurysm and stent”, Computational Mechanics, 50(6): 675-686, (2012).
- 13) Fishman E. K., Kuszyk B. S., Heath D. G., Cabral B., “Surgical planning for liver resection”, Computer, 29(1): 64-72, (1996).
- 14) Taylor C. A., Hughes T. J. R., Zarins C. K., “Finite element modeling of blood flow in arteries”, Computer Methods in Applied Mechanics and Engineering, 158(1-2): 155-196, (1998).
- 15) Bai-Nan X. et al., “Hemodynamics model of fluid–solid interaction in internal carotid artery aneurysms”, Neurosurgical review, 34(1): 39-47, (2011).
- 16) Heart. Understanding Blood Pressure Readings. Healthy and unhealthy blood pressure ranges. Available from: heart.org/en/health-topics/high-blood-pressure/understanding-blood-pressure-readings. Revisited: 08.12.2019.
- 17) Laín S., Caballero A. D., “Simulation of unsteady blood flow dynamics in the thoracic aorta”, Ingeniería e Investigación, 37(3): 92-101, (2017).
- 18) Wain A. J. R. et al., “Blood flow through sutured and coupled microvascular anastomoses: a comparative computational study”, Journal of Plastic, Reconstructive & Aesthetic Surgery, 67(7): 951-959, (2014).
- 19) It Is Foundation. Tissue Properties. Available from: itis.swiss/virtual-population/tissue-properties/database/heat-capacity.Revisited: 08.12.2019.
- 20) It Is Foundation. Tissue Properties. Available from: itis.swiss/virtual-population/tissue-properties/database/thermal-conductivity. Revisited: 08.12.2019.
- 21) Prieto E. S., “Computational fluid dynamics indicators to improve cardiovascular pathologies”, Doctoral thesis, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, (2016).
Patient Specific Cardiovascular Disease Modelling Based on the Computational Fluid Dynamics Simulations: Segmentation and Hemodynamic Model of a Thoracic Artery
Abstract
Nowadays cardiovascular diseases (CVDs), mostly
coronary artery diseases become a leading cause of death. Flow dynamics of a
vessel is important to diagnose a CVD in advance. However, hemodynamic
parameters may not be measured directly. Hence, computational methods are
increasingly being used in the fields of neurosurgery and cardiovascular
surgery to obtain realistic physiological simulations. In this study, a patient
specific thoracic artery model is first segmented based on the MRI images and
then a thoracic aneurysm disease model is simulated to assess blood flow
changes under the predefined conditions.
References
- 1) WHO, Fact sheets. Available from: who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds). Revisited: 08.12.2019.
- 2) European Cardiovascular Disease Statistics, CVD Statistics. Available from: ehnheart.org/cvd-statistics.html. Revisited: 08.12.2019.
- 3) American Heart Association, Heart disease and stroke statistics. Available from: heart.org/-/media/data-import/downloadables/heart-disease-and-stroke-statistics-2018---at-a-glance-ucm_498848.pdf. Revisited: 08.12.2019.
- 4) Mohammed Y., “Three dimensional finite-element modeling of blood flow in elastic vessels: effects of arterial geometry and elasticity on aneurysm growth and rupture”, Master thesis, Ryerson University, Toronto, Canada, (2010).
- 5) Canstein C. et al., “3D MR flow analysis in realistic rapid‐prototyping model systems of the thoracic aorta: comparison with in vivo data and computational fluid dynamics in identical vessel geometries”, Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 59(3): 535-546, (2008).
- 6) Van Pelt R., Nguyen H., Ter Haar Romeny B., Vilanova A., “Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements”, International journal of computer assisted radiology and surgery, 7(2): 217-224, (2012).
- 7) Howe G., “Multiphysics simulation of a coronary artery”, Master thesis, Faculty of California Polytechnic State University, San Luis Obispo, (2013).
- 8) Secomb T. W., “Hemodynamics”, Comprehensive physiology, 6(2): 975-1003, (2011).
- 9) Zarandi M. M., Mongrain R., Bertrand O. F., “Non-newtonian hemodynamics and shear stress distribution in three dimensional model of healthy and stented coronary artery bifurcation”, In proceeding of the comsol conference, Boston, 1-5, (2010).
- 10) Tado R., Deoghare A. B., Pandey K. M., “Computational Study of Blood Flow Analysis for Coronary Artery Disease”, In proceeding of the World Academy of Science Engineering and Technology conference, International Journal of Biomedical and Biological Engineering, 12(2), 35-39, (2018).
- 11) Ohhara Y. et al., “Investigation of blood flow in the external carotid artery and its branches with a new 0D peripheral model”, Biomedical engineering online, 15(1): 16, (2016).
- 12) Takizawa K. et al., “Patient-specific computer modeling of blood flow in cerebral arteries with aneurysm and stent”, Computational Mechanics, 50(6): 675-686, (2012).
- 13) Fishman E. K., Kuszyk B. S., Heath D. G., Cabral B., “Surgical planning for liver resection”, Computer, 29(1): 64-72, (1996).
- 14) Taylor C. A., Hughes T. J. R., Zarins C. K., “Finite element modeling of blood flow in arteries”, Computer Methods in Applied Mechanics and Engineering, 158(1-2): 155-196, (1998).
- 15) Bai-Nan X. et al., “Hemodynamics model of fluid–solid interaction in internal carotid artery aneurysms”, Neurosurgical review, 34(1): 39-47, (2011).
- 16) Heart. Understanding Blood Pressure Readings. Healthy and unhealthy blood pressure ranges. Available from: heart.org/en/health-topics/high-blood-pressure/understanding-blood-pressure-readings. Revisited: 08.12.2019.
- 17) Laín S., Caballero A. D., “Simulation of unsteady blood flow dynamics in the thoracic aorta”, Ingeniería e Investigación, 37(3): 92-101, (2017).
- 18) Wain A. J. R. et al., “Blood flow through sutured and coupled microvascular anastomoses: a comparative computational study”, Journal of Plastic, Reconstructive & Aesthetic Surgery, 67(7): 951-959, (2014).
- 19) It Is Foundation. Tissue Properties. Available from: itis.swiss/virtual-population/tissue-properties/database/heat-capacity.Revisited: 08.12.2019.
- 20) It Is Foundation. Tissue Properties. Available from: itis.swiss/virtual-population/tissue-properties/database/thermal-conductivity. Revisited: 08.12.2019.
- 21) Prieto E. S., “Computational fluid dynamics indicators to improve cardiovascular pathologies”, Doctoral thesis, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, (2016).
There are 21 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 1, 2020 |
| Submission Date | September 6, 2019 |
| Published in Issue | Year 2020 Volume: 23 Issue: 4 |
Cite
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https://doi.org/10.1007/s11831-023-10013-2
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