Abstract
Near-wall transport is of utmost importance in connecting blood flow mechanics with cardiovascular disease progression. The near-wall region is the interface for biologic and pathophysiologic processes such as thrombosis and atherosclerosis. Most computational and experimental investigations of blood flow implicitly or explicitly seek to quantify hemodynamics at the vessel wall (or lumen surface), with wall shear stress (WSS) quantities being the most common descriptors. Most WSS measures are meant to quantify the frictional force of blood flow on the vessel lumen. However, WSS also provides an approximation to the near-wall blood flow velocity. We herein leverage this fact to compute a wall shear stress exposure time (WSSET) measure that is derived from Lagrangian processing of the WSS vector field. We compare WSSET against the more common relative residence time (RRT) measure, as well as a WSS divergence measure, in several applications where hemodynamics are known to be important to disease progression. Because these measures seek to quantify near-wall transport and because near-wall transport is important in several cardiovascular pathologies, surface concentration computed from a continuum transport model is used as a reference. The results show that compared to RRT, WSSET is able to better approximate the locations of near-wall stagnation and concentration build-up of chemical species, particularly in complex flows. For example, the correlation to surface concentration increased on average from 0.51 (RRT) to 0.79 (WSSET) in abdominal aortic aneurysm flow. Because WSSET considers integrated transport behavior, it can be more suitable in regions of complex hemodynamics that are traditionally difficult to quantify, yet encountered in many disease scenarios.
Similar content being viewed by others
References
Arzani A, Gambaruto AM, Chen G, Shadden SC (2016) Lagrangian wall shear stress structures and near-wall transport in high-Schmidt-number aneurysmal flows. J Fluid Mech 790:158–172
Arzani A, Les AS, Dalman RL, Shadden SC (2014) Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing. Int J Numer Methods Biomed Eng 30(2):280–295
Arzani A, Shadden SC (2012) Characterization of the transport topology in patient-specific abdominal aortic aneurysm models. Phys Fluids 24(8):081901
Arzani A, Shadden SC (2016) Characterizations and correlations of wall shear stress in aneurysmal flow. J Biomech Eng 138(1):014503
Arzani A, Suh GY, Dalman RL, Shadden SC (2014) A longitudinal comparison of hemodynamics and intraluminal thrombus deposition in abdominal aortic aneurysms. Am J Physiol Heart Circ Physiol 307(12):H1786–H1795
Barakat AI, Lieu DK (2003) Differential responsiveness of vascular endothelial cells to different types of fluid mechanical shear stress. Cell Biochem Biophys 38(3):323–343
Basmadjian D (1990) The effect of flow and mass transport in thrombogenesis. Ann Biomed Eng 18(6):685–709
Boileau E, Bevan RLT, Sazonov I, Rees MI, Nithiarasu P (2013) Flow-induced ATP release in patient-specific arterial geometries-a comparative study of computational models. Int J Numer Methods Biomed Eng 29(10):1038–1056
Caro CG, Fitz-Gerald JM, Schroter RC (1969) Arterial wall shear and distribution of early atheroma in man. Nature 223:1159–1161
Chen G, Mischaikow K, Laramee RS, Pilarczyk P, Zhang E (2007) Vector field editing and periodic orbit extraction using morse decomposition. Vis Comput Graph IEEE Trans 13(4):769–785
Chien S (2007) Mechanotransduction and endothelial cell homeostasis: the wisdom of the cell. Am J Physiol Heart Circ Physiol 292(3):H1209–H1224
Chiu JJ, Chen CN, Lee PL, Yang CT, Chuang HS, Chien S, Usami S (2003) Analysis of the effect of disturbed flow on monocytic adhesion to endothelial cells. J Biomech 36(12):1883–1895
Choi HW, Ferrara KW, Barakat AI (2007) Modulation of ATP/ADP concentration at the endothelial surface by shear stress: effect of flow recirculation. Ann Biomed Eng 35(4):505–516
Cilla M, Peña E, Martínez MA (2013) Mathematical modelling of atheroma plaque formation and development in coronary arteries. J R Soc Interface 11(90):20130866
Comerford A, Plank MJ, David T (2008) Endothelial nitric oxide synthase and calcium production in arterial geometries: an integrated fluid mechanics/cell model. J Biomech Eng 130(1):011010
Coppola G, Caro C (2008) Oxygen mass transfer in a model three-dimensional artery. J R Soc Interface 5(26):1067–1075
Dabagh M, Jalali P, Tarbell JM (2009) The transport of LDL across the deformable arterial wall: the effect of endothelial cell turnover and intimal deformation under hypertension. Am J Physiol Heart Circ Physiol 297(3):H983–H996
Davies PF (1995) Flow-mediated endothelial mechanotransduction. Physiol Rev 75(3):519–560
Ethier CR (2002) Computational modeling of mass transfer and links to atherosclerosis. Ann Biomed Eng 30(4):461–471
Fazli S, Shirani E, Sadeghi MR (2011) Numerical simulation of LDL mass transfer in a common carotid artery under pulsatile flows. J Biomech 44(1):68–76
Gambaruto AM, Doorly DJ, Yamaguchi T (2010) Wall shear stress and near-wall convective transport: comparisons with vascular remodelling in a peripheral graft anastomosis. J Comput Phys 229(14):5339–5356
Gambaruto AM, João AJ (2012) Flow structures in cerebral aneurysms. Comput Fluids 65:56–65
Hansen KB, Shadden SC (2016) A reduced-dimensional model for near-wall transport in cardiovascular flows. Biomech Model Mechanobiol 15(3):713–722
Hao W, Friedman A (2014) The LDL-HDL profile determines the risk of atherosclerosis: a mathematical model. PLoS ONE 9(3):e90497
Hathcock JJ (2006) Flow effects on coagulation and thrombosis. Arterioscler Thromb Vasc Biol 26(8):1729–1737
Himburg HA, Grzybowski DM, Hazel AL, LaMack JA, Li XM, Friedman MH (2004) Spatial comparison between wall shear stress measures and porcine arterial endothelial permeability. Am J Physiol Heart Circ Physiol 286(5):H1916–H1922
Iori F, Grechy L, Corbett R W, Gedroyc W, Duncan N, Caro C G, Vincent P E (2015) The effect of in-plane arterial curvature on blood flow and oxygen transport in arterio-venous fistulae. Phys Fluids (1994-present) 27(3):031903
Jiménez JM, Prasad V, Yu MD, Kampmeyer CP, Kaakour AH, Wang PJ, Maloney SF, Wright N, Johnston I, Jiang YZ, Davies PF (2014) Macro- and microscale variables regulate stent haemodynamics, fibrin deposition and thrombomodulin expression. J R Soc Interface 11(94):20131079
Ku DN, Giddens DP, Zarins CK, Glagov S (1985) Pulsatile flow and atherosclerosis in the human carotid bifurcation. positive correlation between plaque location and low oscillating shear stress. Arterioscler Thromb Vasc Biol 5(3):293–302
Lantz J, Karlsson M (2012) Large eddy simulation of LDL surface concentration in a subject specific human aorta. J Biomech 45(3):537–542
Lee SW, Antiga L, Spence JD, Steinman DA (2008) Geometry of the carotid bifurcation predicts its exposure to disturbed flow. Stroke 39(8):2341–2347
Lee SW, Antiga L, Steinman DA (2009) Correlations among indicators of disturbed flow at the normal carotid bifurcation. J Biomech Eng 131(6):061013
Les AS, Shadden SC, Figueroa CA, Park JM, Tedesco MM, Herfkens RJ, Dalman RL, Taylor CA (2010) Quantification of hemodynamics in abdominal aortic aneurysms during rest and exercise using magnetic resonance imaging and computational fluid dynamics. Ann Biomed Eng 38:1288–1313
Lévêque M (1928) Les lois de la transmission de chaleur par convection. Ann Mines 13:201–239
Liu X, Fan Y, Xu XY, Deng X (2012) Nitric oxide transport in an axisymmetric stenosis. J R Soc Interface 9(75):2468–2478
Logg A, Mardal KA, Wells G (2012) Automated solution of differential equations by the finite element method, vol 84. Springer, Berlin
Longest PW, Kleinstreuer C (2003) Numerical simulation of wall shear stress conditions and platelet localization in realistic end-to-side arterial anastomoses. J Biomech Eng 125(5):671–681
Marrero VL, Tichy JA, Sahni O, Jansen KE (2014) Numerical study of purely viscous non-Newtonian flow in an abdominal aortic aneurysm. J Biomech Eng 136(10):101001
McIlhany K L, Wiggins S (2012) Eulerian indicators under continuously varying conditions. Phys Fluids (1994-present) 24(7):073601
Meng W, Yu F, Chen H, Zhang J, Zhang E, Dian K, Shi Y (2009) Concentration polarization of high-density lipoprotein and its relation with shear stress in an in vitro model. BioMed Research International 695838–695838:2009
Menichini C, Xu XY (2016) Mathematical modeling of thrombus formation in idealized models of aortic dissection: initial findings and potential applications. J Math Biol 73(5):1205–1226
Papadopoulos KP, Gavaises M, Atkin C (2014) A simplified mathematical model for thrombin generation. Med Eng Phys 36(2):196–204
Peach TW, Ngoepe M, Spranger K, Zajarias-Fainsod D, Ventikos Y (2014) Personalizing flow-diverter intervention for cerebral aneurysms: from computational hemodynamics to biochemical modeling. Int J Numer Methods Biomed Eng 30(11):1387–1407
Peiffer V, Sherwin SJ, Weinberg PD (2013) Does low and oscillatory wall shear stress correlate spatially with early atherosclerosis? A systematic review. Cardiovasc Res 99(2):242–250
Plata AM, Sherwin SJ, Krams R (2010) Endothelial nitric oxide production and transport in flow chambers: the importance of convection. Ann Biomed Eng 38(9):2805–2816
Poelma C, Watton PN, Ventikos Y (2015) Transitional flow in aneurysms and the computation of haemodynamic parameters. J R Soc Interface 12(105):20141394
Schwartz CJ, Valente AJ, Sprague EA, Kelley JL, Nerem RM (1991) The pathogenesis of atherosclerosis: an overview. Clin Cardiol 14(S1):1–16
Sengupta D, Kahn AM, Burns JC, Sankaran S, Shadden SC, Marsden AL (2012) Image-based modeling of hemodynamics in coronary artery aneurysms caused by kawasaki disease. Biomech Model Mechanobiol 11(6):915–932
Seo JH, Abd T, George RT, Mittal R (2016) A coupled chemo-fluidic computational model for thrombogenesis in infarcted left ventricles. Am J Physiol-Heart Circ Physiol. 10.1152/ajpheart.00855.2015
Shadden SC, Arzani A (2015) Lagrangian postprocessing of computational hemodynamics. Ann Biomed Eng 43(1):41–58
Shadden SC, Taylor CA (2008) Characterization of coherent structures in the cardiovascular system. Ann Biomed Eng 36:1152–1162
Sorensen EN, Burgreen GW, Wagner WR, Antaki JF (1999) Computational simulation of platelet deposition and activation: I. Model development and properties. Ann Biomed Eng 27(4):436–448
Tarbell JM (2003) Mass transport in arteries and the localization of atherosclerosis. Annu Rev Biomed Eng 5(1):79–118
Tong J, Holzapfel GA (2015) Structure, mechanics, and histology of intraluminal thrombi in abdominal aortic aneurysms. Ann Biomed Eng 43(7):1488–1501
Tricoche X, Scheuermann G, Hagen H (2001) Continuous topology simplification of planar vector fields. In: Proceedings of the conference on Visualization’01, pp 159–166
Updegrove A, Wilson NM, Merkow J, Lan H, Marsden AL, Shadden SC (2016) Simvascular—an open source pipeline for cardiovascular simulation. Ann Biomed Eng (in press)
Vincent PE, Weinberg PD (2014) Flow-dependent concentration polarization and the endothelial glycocalyx layer: multi-scale aspects of arterial mass transport and their implications for atherosclerosis. Biomech Model Mechanobiol 13(2):313–326
Wilson JS, Virag L, Di Achille P, Karšaj I, Humphrey JD (2013) Biochemomechanics of intraluminal thrombus in abdominal aortic aneurysms. J Biomech Eng 135(2):021011
Zhang E, Mischaikow K, Turk G (2006) Vector field design on surfaces. ACM Trans Graph (TOG) 25(4):1294–1326
Acknowledgements
The authors are thankful to Nathan M. Wilson for providing the coronary aneurysm data. This work was supported by the National Science Foundation (Grant No. 1354541).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no conflict of interest.
Rights and permissions
About this article
Cite this article
Arzani, A., Gambaruto, A.M., Chen, G. et al. Wall shear stress exposure time: a Lagrangian measure of near-wall stagnation and concentration in cardiovascular flows. Biomech Model Mechanobiol 16, 787–803 (2017). https://doi.org/10.1007/s10237-016-0853-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10237-016-0853-7