Computational Modeling Approach to Profile Hemodynamical Behavior in a Healthy Aorta

Overview

Journal Bioengineering (Basel)

Date 2024 Sep 27

PMID 39329656

Authors

Ahmed M Al-Jumaily

Mohammad Al-Rawi

Djelloul Belkacemi

Radu Andy Sascau

Cristian Statescu

Florin-Emilian Turcanu

Larisa Anghel

Affiliations

Soon will be listed here.

Abstract

Cardiovascular diseases (CVD) remain the leading cause of mortality among older adults. Early detection is critical as the prognosis for advanced-stage CVD is often poor. Consequently, non-invasive diagnostic tools that can assess hemodynamic function, particularly of the aorta, are essential. Computational fluid dynamics (CFD) has emerged as a promising method for simulating cardiovascular dynamics efficiently and cost-effectively, using increasingly accessible computational resources. This study developed a CFD model to assess the aorta geometry using tetrahedral and polyhedral meshes. A healthy aorta was modeled with mesh sizes ranging from 0.2 to 1 mm. Key hemodynamic parameters, including blood pressure waveform, pressure difference, wall shear stress (WSS), and associated wall parameters like relative residence time (RRT), oscillatory shear index (OSI), and endothelial cell activation potential (ECAP) were evaluated. The performance of the CFD simulations, focusing on accuracy and processing time, was assessed to determine clinical viability. The CFD model demonstrated clinically acceptable results, achieving over 95% accuracy while reducing simulation time by up to 54%. The entire simulation process, from image construction to the post-processing of results, was completed in under 120 min. Both mesh types (tetrahedral and polyhedral) provided reliable outputs for hemodynamic analysis. This study provides a novel demonstration of the impact of mesh type in obtaining accurate hemodynamic data, quickly and efficiently, using CFD simulations for non-invasive aortic assessments. The method is particularly beneficial for routine check-ups, offering improved diagnostics for populations with limited healthcare access or higher cardiovascular disease risk.

References

Timmis A, Vardas P, Townsend N, Torbica A, Katus H, De Smedt D . European Society of Cardiology: cardiovascular disease statistics 2021. Eur Heart J. 2022; 43(8):716-799. DOI: 10.1093/eurheartj/ehab892. View

He Y, Northrup H, Le H, Cheung A, Berceli S, Shiu Y . Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases. Front Bioeng Biotechnol. 2022; 10:855791. PMC: 9091352. DOI: 10.3389/fbioe.2022.855791. View

Hashemi J, Patel B, Chatzizisis Y, Kassab G . Study of Coronary Atherosclerosis Using Blood Residence Time. Front Physiol. 2021; 12:625420. PMC: 8128163. DOI: 10.3389/fphys.2021.625420. View

Wang X, Shen Y, Shang M, Liu X, Munn L . Endothelial mechanobiology in atherosclerosis. Cardiovasc Res. 2023; 119(8):1656-1675. PMC: 10325702. DOI: 10.1093/cvr/cvad076. View

Curta A, Jaber A, Rieber J, Hetterich H . Estimation of endothelial shear stress in atherosclerotic lesions detected by intravascular ultrasound using computational fluid dynamics from coronary CT scans with a pulsatile blood flow and an individualized blood viscosity. Clin Hemorheol Microcirc. 2021; 79(4):505-518. DOI: 10.3233/CH-201025. View

Qu W, Li X, Huang H, Xie C, Song H . Mechanisms of the ascites volume differences between patients receiving a left or right hemi-liver graft liver transplantation: From biofluidic analysis. Comput Methods Programs Biomed. 2022; 226:107196. DOI: 10.1016/j.cmpb.2022.107196. View

Soudah E, Ng E, Loong T, Bordone M, Pua U, Narayanan S . CFD modelling of abdominal aortic aneurysm on hemodynamic loads using a realistic geometry with CT. Comput Math Methods Med. 2013; 2013:472564. PMC: 3707263. DOI: 10.1155/2013/472564. View

Martin S, Aday A, Almarzooq Z, Anderson C, Arora P, Avery C . 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation. 2024; 149(8):e347-e913. DOI: 10.1161/CIR.0000000000001209. View

Cilla M, Casales M, Pena E, Martinez M, Malve M . A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics. J Biomech. 2020; 103:109691. DOI: 10.1016/j.jbiomech.2020.109691. View

10.

Cheng H, Zhong W, Wang L, Zhang Q, Ma X, Wang Y . Effects of shear stress on vascular endothelial functions in atherosclerosis and potential therapeutic approaches. Biomed Pharmacother. 2023; 158:114198. DOI: 10.1016/j.biopha.2022.114198. View

11.

Etli M, Canbolat G, Karahan O, Koru M . Numerical investigation of patient-specific thoracic aortic aneurysms and comparison with normal subject via computational fluid dynamics (CFD). Med Biol Eng Comput. 2020; 59(1):71-84. DOI: 10.1007/s11517-020-02287-6. View

12.

Spiegel M, Redel T, Zhang Y, Struffert T, Hornegger J, Grossman R . Tetrahedral and polyhedral mesh evaluation for cerebral hemodynamic simulation--a comparison. Annu Int Conf IEEE Eng Med Biol Soc. 2009; 2009:2787-90. DOI: 10.1109/IEMBS.2009.5333829. View

13.

Trenti C, Ziegler M, Bjarnegard N, Ebbers T, Lindenberger M, Dyverfeldt P . Wall shear stress and relative residence time as potential risk factors for abdominal aortic aneurysms in males: a 4D flow cardiovascular magnetic resonance case-control study. J Cardiovasc Magn Reson. 2022; 24(1):18. PMC: 8932193. DOI: 10.1186/s12968-022-00848-2. View

14.

Al-Rawi M, Al-Jumaily A, Belkacemi D . Non-invasive diagnostics of blockage growth in the descending aorta-computational approach. Med Biol Eng Comput. 2022; 60(11):3265-3279. PMC: 9537206. DOI: 10.1007/s11517-022-02665-2. View

15.

Numata S, Itatani K, Kanda K, Doi K, Yamazaki S, Morimoto K . Blood flow analysis of the aortic arch using computational fluid dynamics. Eur J Cardiothorac Surg. 2016; 49(6):1578-85. DOI: 10.1093/ejcts/ezv459. View

16.

Xiao M, Wu J, Chen D, Wang C, Wu Y, Sun T . Ascending aortic volume: A feasible indicator for ascending aortic aneurysm elective surgery?. Acta Biomater. 2023; 167:100-108. DOI: 10.1016/j.actbio.2023.06.026. View

17.

Minderhoud S, Arrouby A, van den Hoven A, Bons L, Chelu R, Kardys I . Regional aortic wall shear stress increases over time in patients with a bicuspid aortic valve. J Cardiovasc Magn Reson. 2024; 26(2):101070. PMC: 11417319. DOI: 10.1016/j.jocmr.2024.101070. View

18.

Osswald A, Karmonik C, ANDERSON J, Rengier F, Karck M, Engelke J . Elevated Wall Shear Stress in Aortic Type B Dissection May Relate to Retrograde Aortic Type A Dissection: A Computational Fluid Dynamics Pilot Study. Eur J Vasc Endovasc Surg. 2017; 54(3):324-330. DOI: 10.1016/j.ejvs.2017.06.012. View

19.

Alkhatib F, Wittek A, Zwick B, Bourantas G, Miller K . Computation for biomechanical analysis of aortic aneurysms: the importance of computational grid. Comput Methods Biomech Biomed Engin. 2023; 27(8):994-1010. DOI: 10.1080/10255842.2023.2218521. View

20.

Wellnhofer E, Goubergrits L, Kertzscher U, Affeld K, Fleck E . Novel non-dimensional approach to comparison of wall shear stress distributions in coronary arteries of different groups of patients. Atherosclerosis. 2008; 202(2):483-90. DOI: 10.1016/j.atherosclerosis.2008.05.044. View