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Mikrodamarların Sertliğinin Hemodinamik Üzerine Etkisi, bir FSI Analizi

Year 2020, Volume: 13 Issue: 3, 1271 - 1280, 31.12.2020
https://doi.org/10.18185/erzifbed.794261

Abstract

Kardiyovasküler hastalıkların araştırmasında bilgisayarla modelleme son zamanlarda önemli ilerleme kaydetmiştir. Bu çalışmada; mikrodamar sertliğinin kan basıncı ve kan akışından kaynaklanan çeper kayma gerilmesi (WSS) üzerindeki etkisi, sayısal yöntemle analiz edilmiştir. Çalışmada üç mikrodamar tasarlanmıştır. Tasarlanan bu üç mikrodamar 100, 200 ve 300 mikron çaplarında ve sırasıyla 10, 20 ve 30 mikron kalınlıkta tasarlanmıştır. Daha sonra her mikrodamar için malzeme özelliği olarak 0.4, 0.6 ve 0.8 MPa’lık üç farklı elastisite modülü uygulanmıştır. Mikrodamarlarda ki kan akışı, CFD yöntemi ile analiz edilmiştir. Damar sertliğindeki değişimin kanın uyguladığı basınç üzerindeki etkisini ve ayrıca kan akışının damarın deformasyonu üzerindeki etkisini incelemek için bir sıvı-yapı etkileşimli (FSI) analizi gerçekleştirilmiştir. Analizler sonucunda: Damar sertliğinin artmasının kan basıncını ve WSS'i artırdığını ayrıca mikrodamarın deformasyon kabiliyetini düşürdüğünü göstermiştir. Bu çalışmanın sonuçları, kardiyovasküler hastalıkların özellikle mikron boyutlu damarlarda incelenmelerine ışık tutmuştur.

References

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  • Ali, D., & Önel, S. (2018). Effect of Blood Viscosity on Pressure and Shear Stress on the Walls of an Artery with Stenosis. Paper presented at the 2018 Medical Technologies National Congress (TIPTEKNO-Cyprus).
  • Amiri, M. H., Keshavarzi, A., Karimipour, A., Bahiraei, M., Goodarzi, M., & Esfahani, J. A. (2019). A 3-D numerical simulation of non-Newtonian blood flow through femoral artery bifurcation with a moderate arteriosclerosis: investigating Newtonian/non-Newtonian flow and its effects on elastic vessel walls. Heat and Mass Transfer, 55(7), 2037-2047. doi:10.1007/s00231-019-02583-4
  • Boari, G. E., Rizzardi, N., de Ciuceis, C., Platto, C., Paiardi, S., Porteri, E., . . . Rosei, E. A. (2008). Determinants of the structure of resistance-sized arteries in hypertensive patients. Blood Press, 17(4), 204-211. doi:10.1080/08037050802433735
  • Borén, J., Chapman, M. J., Krauss, R. M., Packard, C. J., Bentzon, J. F., Binder, C. J., . . . Ginsberg, H. N. (2020). Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel. European Heart Journal, 41(24), 2313-2330. doi:10.1093/eurheartj/ehz962
  • Casas, R., Castro-Barquero, S., Estruch, R., & Sacanella, E. (2018). Nutrition and Cardiovascular Health. International journal of molecular sciences, 19(12), 3988. doi:10.3390/ijms19123988
  • Chong, A. Y., Doyle, B. J., Jansen, S., Ponosh, S., Cisonni, J., & Sun, Z. (2017). Blood flow velocity prediction in aorto-iliac stent grafts using computational fluid dynamics and Taguchi method. Computers in Biology and Medicine, 84, 235-246. doi:https://doi.org/10.1016/j.compbiomed.2017.03.015
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  • Ebrahimi, A. P. (2009). Mechanical properties of normal and diseased cerebrovascular system. Journal of vascular and interventional neurology, 2(2), 155-162.
  • Flora, G. D., & Nayak, M. K. (2019). A Brief Review of Cardiovascular Diseases, Associated Risk Factors and Current Treatment Regimes. Curr Pharm Des, 25(38), 4063-4084. doi:10.2174/1381612825666190925163827
  • Franklin, S. S., & Wong, N. D. (2013). Hypertension and Cardiovascular Disease: Contributions of the Framingham Heart Study. Global Heart, 8(1), 49-57. doi:https://doi.org/10.1016/j.gheart.2012.12.004
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  • Hoi, Y., Woodward, S. H., Kim, M., Taulbee, D. B., & Meng, H. (2006). Validation of CFD simulations of cerebral aneurysms with implication of geometric variations. Journal of Biomechanical Engineering, 128(6), 844-851. doi:10.1115/1.2354209
  • Kallekar, L., Viswanath, C., & Anand, M. (2017). Effect of Wall Flexibility on the Deformation during Flow in a Stenosed Coronary Artery. Fluids, 2(2). doi:10.3390/fluids2020016
  • Katt, M. E., Linville, R. M., Mayo, L. N., Xu, Z. S., & Searson, P. C. (2018). Functional brain-specific microvessels from iPSC-derived human brain microvascular endothelial cells: the role of matrix composition on monolayer formation. Fluids and Barriers of the CNS, 15(1), 7. doi:10.1186/s12987-018-0092-7
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  • Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., . . . Memish, Z. A. (2012). Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet, 380(9859), 2095-2128. doi:10.1016/s0140-6736(12)61728-0
  • Luo, K., Jiang, W., Yu, C., Tian, X., Zhou, Z., & Ding, Y. (2019). Fluid–Solid Interaction Analysis on Iliac Bifurcation Artery: A Numerical Study. International Journal of Computational Methods, 16(07), 1850112. doi:10.1142/s0219876218501128 Markwald, R. R., Norris, R. A., Moreno-Rodriguez, R., & Levine, R. A. (2010). Developmental basis of adult cardiovascular diseases: valvular heart diseases. Annals of the New York Academy of Sciences, 1188, 177-183. doi:10.1111/j.1749-6632.2009.05098.x
  • Miller, M. R., & Newby, D. E. (2019). Air pollution and cardiovascular disease: car sick. Cardiovascular Research, 116(2), 279-294. doi:10.1093/cvr/cvz228
  • Mittal, R., Seo, J. H., Vedula, V., Choi, Y. J., Liu, H., Huang, H. H., . . . George, R. T. (2016). Computational modeling of cardiac hemodynamics: Current status and future outlook. Journal of Computational Physics, 305, 1065-1082. doi:https://doi.org/10.1016/j.jcp.2015.11.022
  • Nilsson, K. F., Gozdzik, W., Zielinski, S., Ratajczak, K., Goranson, S. P., Rodziewicz, S., . . . Frostell, C. (2020). Pulmonary Vasodilation by Intravenous Infusion of Organic Mononitrites Of 1,2-Propanediol in Acute Pulmonary Hypertension Induced by Aortic Cross Clamping and Reperfusion: A Comparison With Nitroglycerin in Anesthetized Pigs. Shock, 54(1), 119-127. doi:10.1097/shk.0000000000001436
  • O'Donnell, M. J., Xavier, D., Liu, L., Zhang, H., Chin, S. L., Rao-Melacini, P., . . . Yusuf, S. (2010). Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet, 376(9735), 112-123. doi:10.1016/s0140-6736(10)60834-3
  • Okada, S., Fukunaga, S., Ohta, H., Furuta, T., Hirano, R., Motonaga, T., & Ishikawa, Y. (2020). Cerebral Insufficiency Caused by Diazoxide in a Premature Neonate with Congenital Hyperinsulinism. Neuropediatrics, 51(03), 211-214. doi:10.1055/s-0039-3400975
  • Rapsomaniki, E., Timmis, A., George, J., Pujades-Rodriguez, M., Shah, A. D., Denaxas, S., . . . Hemingway, H. (2014). Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people. Lancet, 383(9932), 1899-1911. doi:10.1016/S0140-6736(14)60685-1
  • Ren, R., Covassin, N., Yang, L., Li, Y., Zhang, Y., Zhou, J., . . . Tang, X. (2018). Objective but Not Subjective Short Sleep Duration Is Associated With Hypertension in Obstructive Sleep Apnea. Hypertension, 72(3), 610-617. doi:10.1161/HYPERTENSIONAHA.118.11027
  • Selmi, M., Belmabrouk, H., & Bajahzar, A. (2019). Numerical Study of the Blood Flow in a Deformable Human Aorta. Applied Sciences-Basel, 9(6), 11. doi:10.3390/app9061216
  • Shibeshi, S. S., & Collins, W. E. (2005). The Rheology of Blood Flow in a Branched Arterial System. Appl Rheol, 15(6), 398-405. doi:10.1901/jaba.2005.15-398
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  • Soltani, M., & Chen, P. (2013). Numerical Modeling of Interstitial Fluid Flow Coupled with Blood Flow through a Remodeled Solid Tumor Microvascular Network. Plos One, 8(6), e67025. doi:10.1371/journal.pone.0067025
  • Urquiza, S. A., Blanco, P. J., Vénere, M. J., & Feijóo, R. A. (2006). Multidimensional modelling for the carotid artery blood flow. Computer Methods in Applied Mechanics and Engineering, 195(33), 4002-4017. doi:https://doi.org/10.1016/j.cma.2005.07.014
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  • Vardhan, M., Gounley, J., Chen, S. J., Kahn, A. M., Leopold, J. A., & Randles, A. (2019). The importance of side branches in modeling 3D hemodynamics from angiograms for patients with coronary artery disease. Scientific Reports, 9(1), 8854. doi:10.1038/s41598-019-45342-5
  • Wang, Y. F., Quaini, A., & Canic, S. (2018). A Higher-Order Discontinuous Galerkin/Arbitrary Lagrangian Eulerian Partitioned Approach to Solving Fluid-Structure Interaction Problems with Incompressible, Viscous Fluids and Elastic Structures. Journal of Scientific Computing, 76(1), 481-520. doi:10.1007/s10915-017-0629-y
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Effect Of Microvessels Stiffness on Hemodynamic; an FSI Analysis

Year 2020, Volume: 13 Issue: 3, 1271 - 1280, 31.12.2020
https://doi.org/10.18185/erzifbed.794261

Abstract

The exploits of computer modelling in the study of cardiovascular disease have recently gained significant progress. In this study, the effect of microvessels stiffness on blood pressure and blood flow-induced wall shear stress (WSS) was analysed numerically. Three microvessels in diameters of 100, 200 and 300 microns with respectively media thicknesses of 10, 20 and 30 microns, were designed. Then for each model as material properties, the elastic modulus of 0.4, 0.6 and 0.8 MPa was applied. The blood flow within the microvessels was investigated using CFD analysis. A fluid-structure interaction (FSI) multiphysics analysis was performed to observe the effect of vascular stiffness on blood pressure and vice versa the effect of blood flow on the microvessel deformation. The result of the analysis showed that increasing the stiffness of the vessel increases blood pressure and WSS, and as well as causes a decline in its deformation capability. The outcome of this theoretical study shed more light on understanding cardiovascular diseases roots and origin, especially in micron-sized vessels.

References

  • Abdul Khader, S. M., Ayachit, A., Pai, B. R., Rao, V. R. K., & Kamath, S. G. (2012). FSI Simulation of Common Carotid under Normal and High Blood Pressures. Advances in Mechanical Engineering, 4, 140579. doi:10.1155/2012/140579
  • Ali, D., & Önel, S. (2018). Effect of Blood Viscosity on Pressure and Shear Stress on the Walls of an Artery with Stenosis. Paper presented at the 2018 Medical Technologies National Congress (TIPTEKNO-Cyprus).
  • Amiri, M. H., Keshavarzi, A., Karimipour, A., Bahiraei, M., Goodarzi, M., & Esfahani, J. A. (2019). A 3-D numerical simulation of non-Newtonian blood flow through femoral artery bifurcation with a moderate arteriosclerosis: investigating Newtonian/non-Newtonian flow and its effects on elastic vessel walls. Heat and Mass Transfer, 55(7), 2037-2047. doi:10.1007/s00231-019-02583-4
  • Boari, G. E., Rizzardi, N., de Ciuceis, C., Platto, C., Paiardi, S., Porteri, E., . . . Rosei, E. A. (2008). Determinants of the structure of resistance-sized arteries in hypertensive patients. Blood Press, 17(4), 204-211. doi:10.1080/08037050802433735
  • Borén, J., Chapman, M. J., Krauss, R. M., Packard, C. J., Bentzon, J. F., Binder, C. J., . . . Ginsberg, H. N. (2020). Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel. European Heart Journal, 41(24), 2313-2330. doi:10.1093/eurheartj/ehz962
  • Casas, R., Castro-Barquero, S., Estruch, R., & Sacanella, E. (2018). Nutrition and Cardiovascular Health. International journal of molecular sciences, 19(12), 3988. doi:10.3390/ijms19123988
  • Chong, A. Y., Doyle, B. J., Jansen, S., Ponosh, S., Cisonni, J., & Sun, Z. (2017). Blood flow velocity prediction in aorto-iliac stent grafts using computational fluid dynamics and Taguchi method. Computers in Biology and Medicine, 84, 235-246. doi:https://doi.org/10.1016/j.compbiomed.2017.03.015
  • Dash, D. (2013). Stenting of left main coronary artery stenosis: A to Z. Heart Asia, 5(1), 18-27. doi:10.1136/heartasia-2012-010218
  • de Simone, G., Devereux, R. B., Chinali, M., Best, L. G., Lee, E. T., Welty, T. K., & Stong Heart Study, I. (2005). Association of blood pressure with blood viscosity in American Indians - The Strong Heart Study. Hypertension, 45(4), 625-630. doi:10.1161/01.HYP.0000157526.07977.ec
  • Ebrahimi, A. P. (2009). Mechanical properties of normal and diseased cerebrovascular system. Journal of vascular and interventional neurology, 2(2), 155-162.
  • Flora, G. D., & Nayak, M. K. (2019). A Brief Review of Cardiovascular Diseases, Associated Risk Factors and Current Treatment Regimes. Curr Pharm Des, 25(38), 4063-4084. doi:10.2174/1381612825666190925163827
  • Franklin, S. S., & Wong, N. D. (2013). Hypertension and Cardiovascular Disease: Contributions of the Framingham Heart Study. Global Heart, 8(1), 49-57. doi:https://doi.org/10.1016/j.gheart.2012.12.004
  • Fraser, K. H., Meagher, S., Blake, J. R., Easson, W. J., & Hoskins, P. R. (2008). Characterization of an Abdominal Aortic Velocity Waveform in Patients with Abdominal Aortic Aneurysm. Ultrasound in Medicine & Biology, 34(1), 73-80. doi:https://doi.org/10.1016/j.ultrasmedbio.2007.06.015
  • Fuchs, F. D., & Whelton, P. K. (2020). High Blood Pressure and Cardiovascular Disease. Hypertension, 75(2), 285-292. doi:doi:10.1161/HYPERTENSIONAHA.119.14240
  • Giles, T. D., Sander, G. E., Nossaman, B. D., & Kadowitz, P. J. (2012). Impaired Vasodilation in the Pathogenesis of Hypertension: Focus on Nitric Oxide, Endothelial-Derived Hyperpolarizing Factors, and Prostaglandins. The Journal of Clinical Hypertension, 14(4), 198-205. doi:10.1111/j.1751-7176.2012.00606.x
  • Gómez, S., Vlad, M. D., López, J., & Fernández, E. (2016). Design and properties of 3D scaffolds for bone tissue engineering. Acta Biomaterialia, 42, 341-350. doi:http://dx.doi.org/10.1016/j.actbio.2016.06.032
  • Hoi, Y., Woodward, S. H., Kim, M., Taulbee, D. B., & Meng, H. (2006). Validation of CFD simulations of cerebral aneurysms with implication of geometric variations. Journal of Biomechanical Engineering, 128(6), 844-851. doi:10.1115/1.2354209
  • Kallekar, L., Viswanath, C., & Anand, M. (2017). Effect of Wall Flexibility on the Deformation during Flow in a Stenosed Coronary Artery. Fluids, 2(2). doi:10.3390/fluids2020016
  • Katt, M. E., Linville, R. M., Mayo, L. N., Xu, Z. S., & Searson, P. C. (2018). Functional brain-specific microvessels from iPSC-derived human brain microvascular endothelial cells: the role of matrix composition on monolayer formation. Fluids and Barriers of the CNS, 15(1), 7. doi:10.1186/s12987-018-0092-7
  • Lipp, S. N., Niedert, E. E., Cebull, H. L., Diorio, T. C., Ma, J. L., Rothenberger, S. M., . . . Goergen, C. J. (2020). Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review. Frontiers in Physiology, 11, 454-454. doi:10.3389/fphys.2020.00454
  • Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., . . . Memish, Z. A. (2012). Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet, 380(9859), 2095-2128. doi:10.1016/s0140-6736(12)61728-0
  • Luo, K., Jiang, W., Yu, C., Tian, X., Zhou, Z., & Ding, Y. (2019). Fluid–Solid Interaction Analysis on Iliac Bifurcation Artery: A Numerical Study. International Journal of Computational Methods, 16(07), 1850112. doi:10.1142/s0219876218501128 Markwald, R. R., Norris, R. A., Moreno-Rodriguez, R., & Levine, R. A. (2010). Developmental basis of adult cardiovascular diseases: valvular heart diseases. Annals of the New York Academy of Sciences, 1188, 177-183. doi:10.1111/j.1749-6632.2009.05098.x
  • Miller, M. R., & Newby, D. E. (2019). Air pollution and cardiovascular disease: car sick. Cardiovascular Research, 116(2), 279-294. doi:10.1093/cvr/cvz228
  • Mittal, R., Seo, J. H., Vedula, V., Choi, Y. J., Liu, H., Huang, H. H., . . . George, R. T. (2016). Computational modeling of cardiac hemodynamics: Current status and future outlook. Journal of Computational Physics, 305, 1065-1082. doi:https://doi.org/10.1016/j.jcp.2015.11.022
  • Nilsson, K. F., Gozdzik, W., Zielinski, S., Ratajczak, K., Goranson, S. P., Rodziewicz, S., . . . Frostell, C. (2020). Pulmonary Vasodilation by Intravenous Infusion of Organic Mononitrites Of 1,2-Propanediol in Acute Pulmonary Hypertension Induced by Aortic Cross Clamping and Reperfusion: A Comparison With Nitroglycerin in Anesthetized Pigs. Shock, 54(1), 119-127. doi:10.1097/shk.0000000000001436
  • O'Donnell, M. J., Xavier, D., Liu, L., Zhang, H., Chin, S. L., Rao-Melacini, P., . . . Yusuf, S. (2010). Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet, 376(9735), 112-123. doi:10.1016/s0140-6736(10)60834-3
  • Okada, S., Fukunaga, S., Ohta, H., Furuta, T., Hirano, R., Motonaga, T., & Ishikawa, Y. (2020). Cerebral Insufficiency Caused by Diazoxide in a Premature Neonate with Congenital Hyperinsulinism. Neuropediatrics, 51(03), 211-214. doi:10.1055/s-0039-3400975
  • Rapsomaniki, E., Timmis, A., George, J., Pujades-Rodriguez, M., Shah, A. D., Denaxas, S., . . . Hemingway, H. (2014). Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people. Lancet, 383(9932), 1899-1911. doi:10.1016/S0140-6736(14)60685-1
  • Ren, R., Covassin, N., Yang, L., Li, Y., Zhang, Y., Zhou, J., . . . Tang, X. (2018). Objective but Not Subjective Short Sleep Duration Is Associated With Hypertension in Obstructive Sleep Apnea. Hypertension, 72(3), 610-617. doi:10.1161/HYPERTENSIONAHA.118.11027
  • Selmi, M., Belmabrouk, H., & Bajahzar, A. (2019). Numerical Study of the Blood Flow in a Deformable Human Aorta. Applied Sciences-Basel, 9(6), 11. doi:10.3390/app9061216
  • Shibeshi, S. S., & Collins, W. E. (2005). The Rheology of Blood Flow in a Branched Arterial System. Appl Rheol, 15(6), 398-405. doi:10.1901/jaba.2005.15-398
  • Siogkas, P. K., Papafaklis, M. I., Sakellarios, A. I., Stefanou, K. A., Bourantas, C. V., Athanasiou, L. S., . . . Fotiadis, D. I. (2015). Patient-specific simulation of coronary artery pressure measurements: an in vivo three-dimensional validation study in humans. Biomed Research International, 2015, 628416-628416. doi:10.1155/2015/628416
  • Soltani, M., & Chen, P. (2013). Numerical Modeling of Interstitial Fluid Flow Coupled with Blood Flow through a Remodeled Solid Tumor Microvascular Network. Plos One, 8(6), e67025. doi:10.1371/journal.pone.0067025
  • Urquiza, S. A., Blanco, P. J., Vénere, M. J., & Feijóo, R. A. (2006). Multidimensional modelling for the carotid artery blood flow. Computer Methods in Applied Mechanics and Engineering, 195(33), 4002-4017. doi:https://doi.org/10.1016/j.cma.2005.07.014
  • Valencia, A., Ledermann, D., Rivera, R., Bravo, E., & Galvez, M. (2008). Blood flow dynamics and fluid-structure interaction in patient-specific bifurcating cerebral aneurysms. International Journal for Numerical Methods in Fluids, 58(10), 1081-1100. doi:10.1002/fld.1786
  • Vardhan, M., Gounley, J., Chen, S. J., Kahn, A. M., Leopold, J. A., & Randles, A. (2019). The importance of side branches in modeling 3D hemodynamics from angiograms for patients with coronary artery disease. Scientific Reports, 9(1), 8854. doi:10.1038/s41598-019-45342-5
  • Wang, Y. F., Quaini, A., & Canic, S. (2018). A Higher-Order Discontinuous Galerkin/Arbitrary Lagrangian Eulerian Partitioned Approach to Solving Fluid-Structure Interaction Problems with Incompressible, Viscous Fluids and Elastic Structures. Journal of Scientific Computing, 76(1), 481-520. doi:10.1007/s10915-017-0629-y
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There are 42 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Makaleler
Authors

Daver Ali 0000-0002-8500-7820

Publication Date December 31, 2020
Published in Issue Year 2020 Volume: 13 Issue: 3

Cite

APA Ali, D. (2020). Effect Of Microvessels Stiffness on Hemodynamic; an FSI Analysis. Erzincan University Journal of Science and Technology, 13(3), 1271-1280. https://doi.org/10.18185/erzifbed.794261