Skip to main content
Log in

Numerical investigation of patient-specific thoracic aortic aneurysms and comparison with normal subject via computational fluid dynamics (CFD)

Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Vascular hemodynamics play an important role in cardiovascular diseases. This work aimed to investigate the effects of an increase in ascending aortic diameter (AAD) on hemodynamics throughout a cardiac cycle for real patients. In this study, two scans of thoracic aortic aneurysm (TAA) subject with different AADs (42.94 mm and 48.01 mm) and a scan of a normal subject (19.81 mm) were analyzed to assess the effects of hemodynamics on the progression of TAA with the same flow rate. Real-patient aortic geometries were scanned by computed tomography angiography (CTA), and steady and pulsatile flow conditions were used to simulate real patient aortic geometries. Aortic arches were obtained from routine clinical scans. Computational fluid dynamics (CFD) simulations were performed with in vivo boundary conditions, and 3D Navier-Stokes equations were solved by a UDF (user-defined function) code defining a real cardiac cycle of one patient using Fourier series (FS). Wall shear stress (WSS) and pressure distributions were presented from normal subject to TAA cases. The results show that during the peak systolic phase pressure load increased by 18.56% from normal subject to TAA case 1 and by 23.8% from normal subject to TAA case 2 in the aneurysm region. It is concluded that although overall WSS increased in aneurysm cases but was low in dilatation areas. As a result, abnormal changes in WSS and higher pressure load may lead to rupture and risk of further dilatation. CFD simulations were highly effective to guide clinical predictions and assess the progress of aneurysm regions in case of early surgical intervention.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Valen-Sendstad K, Piccinelli M, KrishnankuttyRema R, Steinman DA (2015) Estimation of inlet flow rates for image-based aneurysm CFD models: where and how to begin? Ann Biomed Eng 43:1422–1431. https://doi.org/10.1007/s10439-015-1288-5

    Article  PubMed  Google Scholar 

  2. Caballero AD, Laín S (2015) Numerical simulation of non-Newtonian blood flow dynamics in human thoracic aorta. Comput Methods Biomech Biomed Engin 18:1200–1216. https://doi.org/10.1080/10255842.2014.887698

    Article  CAS  PubMed  Google Scholar 

  3. Vinoth R, Kumar D, Adhikari R et al (2019) Steady and transient flow CFD simulations in an aorta model of normal and aortic aneurysm subjects. Lect Notes Electr Eng 506:29–43. https://doi.org/10.1007/978-3-319-91659-0_3

    Article  Google Scholar 

  4. Wen CY, Yang AS, Tseng LY, Chai JW (2010) Investigation of pulsatile flowfield in healthy thoracic aorta models. Ann Biomed Eng 38:391–402. https://doi.org/10.1007/s10439-009-9835-6

    Article  PubMed  Google Scholar 

  5. Sonesson B, Sandgren T, Länne T (1999) Abdominal aortic aneurysm wall mechanics and their relation to risk of rupture. Eur J Vasc Endovasc Surg 18:487–493. https://doi.org/10.1053/ejvs.1999.0872

    Article  CAS  PubMed  Google Scholar 

  6. Rizzo JA, Coady MA, Elefteriades JA (1998) Procedures for estimating growth rates in thoracic aortic aneurysms. J Clin Epidemiol 51:747–754. https://doi.org/10.1016/S0895-4356(98)00050-X

    Article  CAS  PubMed  Google Scholar 

  7. Metaxa E, Iordanov I, Maravelakis E, Papaharilaou Y (2017) A novel approach for local abdominal aortic aneurysm growth quantification. Med Biol Eng Comput 55:1277–1286. https://doi.org/10.1007/s11517-016-1592-8

    Article  PubMed  Google Scholar 

  8. Cheng CP (2019) Handbook of vascular motion. Elsevier Science Publishing Co Inc, San Diego

    Google Scholar 

  9. Dabagh M, Vasava P, Jalali P (2015) Effects of severity and location of stenosis on the hemodynamics in human aorta and its branches. Med Biol Eng Comput 53:463–476. https://doi.org/10.1007/s11517-015-1253-3

    Article  PubMed  Google Scholar 

  10. Salsac A-V, SPARKS SR, J-M CHOMAZ, LASHERAS JC (2006) Evolution of the wall shear stresses during the progressive enlargement of symmetric abdominal aortic aneurysms. J Fluid Mech 560:19. https://doi.org/10.1017/S002211200600036X

    Article  Google Scholar 

  11. Morris L, Delassus P, Callanan A, Walsh M, Wallis F, Grace P, McGloughlin T (2005) 3-D numerical simulation of blood flow through models of the human aorta. J Biomech Eng 127:767–775. https://doi.org/10.1115/1.1992521

    Article  CAS  PubMed  Google Scholar 

  12. Qian Y, Liu JL, Itatani K, Miyaji K, Umezu M (2010) Computational hemodynamic analysis in congenital heart disease: simulation of the Norwood procedure. Ann Biomed Eng 38:2302–2313. https://doi.org/10.1007/s10439-010-9978-5

    Article  CAS  PubMed  Google Scholar 

  13. Gallo D, De Santis G, Negri F et al (2012) On the use of in vivo measured flow rates as boundary conditions for image-based hemodynamic models of the human aorta: implications for indicators of abnormal flow. Ann Biomed Eng 40:729–741. https://doi.org/10.1007/s10439-011-0431-1

    Article  CAS  PubMed  Google Scholar 

  14. Fan Y, Jiang W, Zou Y, Li J, Chen J, Deng X (2009) Numerical simulation of pulsatile non-Newtonian flow in the carotid artery bifurcation. Acta Mech Sin Xuebao 25:249–255. https://doi.org/10.1007/s10409-009-0227-9

    Article  Google Scholar 

  15. Olufsen MS, Peskin CS, Kim WY, Pedersen EM, Nadim A, Larsen J (2000) Numerical simulation and experimental validation of blood flow in arteries with structured-tree outflow conditions. Ann Biomed Eng 28:1281–1299. https://doi.org/10.1114/1.1326031

    Article  CAS  PubMed  Google Scholar 

  16. Kamangar S, Badruddin IA, Govindaraju K, Nik-Ghazali N, Badarudin A, Viswanathan GN, Ahmed NJS, Khan TMY (2017) Patient-specific 3D hemodynamics modelling of left coronary artery under hyperemic conditions. Med Biol Eng Comput 55:1451–1461. https://doi.org/10.1007/s11517-016-1604-8

    Article  PubMed  Google Scholar 

  17. Tang BT, Cheng CP, Draney MT, Wilson NM, Tsao PS, Herfkens RJ, Taylor CA (2006) Abdominal aortic hemodynamics in young healthy adults at rest and during lower limb exercise: quantification using image-based computer modeling. Am J Physiol Heart Circ Physiol 291:668–676. https://doi.org/10.1152/ajpheart.01301.2005

    Article  CAS  Google Scholar 

  18. Castro MA, Olivares MCA, Putman CM, Cebral JR (2014) Unsteady wall shear stress analysis from image-based computational fluid dynamic aneurysm models under Newtonian and Casson rheological models. Med Biol Eng Comput 52:827–839. https://doi.org/10.1007/s11517-014-1189-z

    Article  PubMed  Google Scholar 

  19. Arzani A, Dyverfeldt P, Ebbers T, Shadden SC (2012) In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation. Ann Biomed Eng 40:860–870. https://doi.org/10.1007/s10439-011-0447-6

    Article  PubMed  Google Scholar 

  20. Edelhoff D, Walczak L, Henning S, Weichert F, Suter D (2013) High-resolution MRI velocimetry compared with numerical simulations. J Magn Reson 235:42–49. https://doi.org/10.1016/j.jmr.2013.07.002

    Article  CAS  PubMed  Google Scholar 

  21. Goubergrits L, Mevert R, Yevtushenko P, Schaller J, Kertzscher U, Meier S, Schubert S, Riesenkampff E, Kuehne T (2013) The impact of MRI-based inflow for the hemodynamic evaluation of aortic coarctation. Ann Biomed Eng 41:2575–2587. https://doi.org/10.1007/s10439-013-0879-2

    Article  CAS  PubMed  Google Scholar 

  22. Ladisa JF, Alberto Figueroa C, Vignon-Clementel IE et al (2011) Computational simulations for aortic coarctation: representative results from a sampling of patients. J Biomech Eng 133:091008. https://doi.org/10.1115/1.4004996

    Article  PubMed  Google Scholar 

  23. Numata S, Itatani K, Kanda K, Doi K, Yamazaki S, Morimoto K, Manabe K, Ikemoto K, Yaku H (2016) Blood flow analysis of the aortic arch using computational fluid dynamics. Eur J Cardio-thoracic Surg 49:1578–1585. https://doi.org/10.1093/ejcts/ezv459

    Article  Google Scholar 

  24. Taylor CA, Hughes TJR, Zarins CK (1998) Finite element modeling of three-dimensional pulsatile flow in the abdominal aorta: relevance to atherosclerosis. Ann Biomed Eng 26:975–987. https://doi.org/10.1114/1.140

    Article  CAS  PubMed  Google Scholar 

  25. Zaotis LB, Chiang VW (2007) Comprehensive pediatric hospital 798 medicine, 6th edn. Philadelphiahttps. https://doi.org/10.1016/B978-0-323-03004-5.X5001-7

  26. Berger SA, Jou L (2000) Flows in stenotic vessels. Annu Rewiev Fluid Mech 32:347–382

    Article  Google Scholar 

  27. Pedley TJ (1980) The fluid mechanics of large blood vessels. Cambridge University Press, Cambridge

    Book  Google Scholar 

  28. Alimohammadi M, Agu O, Balabani S, Díaz-Zuccarini V (2014) Development of a patient-specific simulation tool to analyse aortic dissections: assessment of mixed patient-specific flow and pressure boundary conditions. Med Eng Phys 36:275–284. https://doi.org/10.1016/j.medengphy.2013.11.003

    Article  PubMed  Google Scholar 

  29. Brown AG, Shi Y, Marzo A, Staicu C, Valverde I, Beerbaum P, Lawford PV, Hose DR (2012) Accuracy vs. computational time: translating aortic simulations to the clinic. J Biomech 45:516–523. https://doi.org/10.1016/j.jbiomech.2011.11.041

    Article  PubMed  Google Scholar 

  30. Shahcheranhi N, Dwyer HA, Cheer AY et al (2002) Unsteady and three-dimensional simulation of blood flow in the human aortic arch. J Biomech Eng 124:378–387. https://doi.org/10.1115/1.1487357

    Article  Google Scholar 

  31. Youssefi P, Gomez A, Arthurs C, Sharma R, Jahangiri M, Alberto Figueroa C (2018) Impact of patient-specific inflow velocity profile on hemodynamics of the thoracic aorta. J Biomech Eng 140:1–14. https://doi.org/10.1115/1.4037857

    Article  Google Scholar 

  32. Tse KM, Chang R, Lee HP, Lim SP, Venkatesh SK, Ho P (2013) A computational fluid dynamics study on geometrical influence of the aorta on haemodynamics. Eur J Cardio-thoracic Surg 43:829–838. https://doi.org/10.1093/ejcts/ezs388

    Article  Google Scholar 

  33. Myers JG, Moore JA, Ojha M, Johnston KW, Ethier CR (2001) Factors influencing blood flow patterns in the human right coronary artery. Ann Biomed Eng 29:109–120. https://doi.org/10.1114/1.1349703

    Article  CAS  PubMed  Google Scholar 

  34. Lam SK, Fung GSK, Cheng SWK, Chow KW (2008) A computational study on the biomechanical factors related to stent-graft models in the thoracic aorta. Med Biol Eng Comput 46:1129–1138. https://doi.org/10.1007/s11517-008-0361-8

    Article  CAS  PubMed  Google Scholar 

  35. Nichols WW, O’Rourke MF (2005) McDonald’s blood flow in arteries, 5th edn. Taylor & Francis Ltd, London

    Google Scholar 

  36. Chandran KB, Yoganathan AP, Rittgers SE (2012) Biofluid mechanics, 2. CRC Press, Edition

    Book  Google Scholar 

  37. ANSYS (2013) ANSYS fluent theory guide. ANSYS, Inc., 275 Technology Drive Canonsburg, PA 15317

  38. Febina J, Sikkandar MY, Sudharsan NM (2018) Wall shear stress estimation of thoracic aortic aneurysm using computational fluid dynamics. Comput Math Methods Med 2018: https://doi.org/10.1155/2018/7126532

  39. Munarriz PM, Gómez PA, Paredes I, Castaño-Leon AM, Cepeda S, Lagares A (2016) Basic principles of hemodynamics and cerebral aneurysms. World Neurosurg 88:311–319. https://doi.org/10.1016/j.wneu.2016.01.031

    Article  PubMed  Google Scholar 

  40. Malek AM, Alper SL, Izumo S (1999) Hemodynamic shear stress and its role in atherosclerosis. J Am Med Assoc 282:2035–2042

    Article  CAS  Google Scholar 

  41. Shojima M (2004) Magnitude and role of wall shear stress on cerebral aneurysm. Computational fluid dynamic study of 20 middle cerebral artery aneurysms. Stroke:2500–2505. https://doi.org/10.1161/01.str.0000144648.89172.of

  42. Palmer RF, Wheat MW (1967) Treatment of dissecting aneurysms of the aorta. Ann Thorac Surg 4:38–52. https://doi.org/10.1016/S0003-4975(10)66476-4

    Article  CAS  PubMed  Google Scholar 

  43. Davies PF, Remuzzi A, Gordon EJ, Dewey CF, Gimbrone MA (1986) Turbulent fluid shear stress induces vascular endothelial cell turnover in vitro. Proc Natl Acad Sci U S A 83:2114–2117. https://doi.org/10.1073/pnas.83.7.2114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Chen D, Müller-Eschner M, von Tengg-Kobligk H, Barber D, Böckler D, Hose R, Ventikos Y (2013) A patient-specific study of type-B aortic dissection: evaluation of true-false lumen blood exchange. Biomed Eng Online 12:1–16. https://doi.org/10.1186/1475-925X-12-65

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Materialise for providing a trial version of Mimics software package in the use of segmentation process. The authors also acknowledge taking advantages of the Alanya Aladdin Keykubat University hospital’s facilities. All invasive measurement techniques have been approved by the Ethics Committee of Alanya Alaaddin Keykubat University, Turkey.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gokhan Canbolat.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Etli, M., Canbolat, G., Karahan, O. et al. Numerical investigation of patient-specific thoracic aortic aneurysms and comparison with normal subject via computational fluid dynamics (CFD). Med Biol Eng Comput 59, 71–84 (2021). https://doi.org/10.1007/s11517-020-02287-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-020-02287-6

Keywords

Navigation