Computational Modeling and Simulation Examples in Bioengineering. Группа авторов

Bohra, A. et al. (2006). A biomechanics‐based rupture potential index for abdominal aortic aneurysm risk assessment. Ann. N. Y. Acad. Sci. 1085: 11–21.

      73 73 Thubrikar, M.J., Labrosse, M., Robicsek, F. et al. (2001). Mechanical properties of abdominal aortic aneurysm wall. J. Med. Eng. Techn. 25 (4): 133–142.

      74 74 Stamatopoulos, C., Mathioulakis, D.S., Papaharilaou, Y., and Katsamouris, A. (2011). Experimental unsteady flow study in a patientspecific abdominal aortic aneurysm model. Exp. Fluids 50 (6): 1695–1709.

      75 75 Holzapfel, G.A. (2006). Determination of material models for arterial walls from uniaxial extension tests and histological structure. J. Theor. Biol. 238 (2): 290–302.

      76 76 Simsek, F.G. and Kwon, Y.W. (2015). Investigation of material modeling in fluid–structure interaction analysis of an idealized three layered abdominal aorta: aneurysm initiation and fully developed aneurysms. J. Biol. Phys. 41 (2): 173–201.

      77 77 Taghizadeh, H., Tafazzoli‐Shadpour, M., Shadmehr, M., and Fatouraee, N. (2015). Evaluation of biaxial mechanical properties of aortic media based on the lamellar microstructure. Materials 8 (1): 302–316.

      78 78 Sokolis, D.P., Kefaloyannis, E.M., Kouloukoussa, M. et al. (2006). A structural basis for the aortic stress–strain relation in uniaxial tension. J. Biomech. 39 (9): 1651–1662.

      79 79 Karimi, A., Navidbakhsh, M., Shojaei, A., and Faghihi, S. (2013). Measurement of the uniaxial mechanical properties of healthy and atherosclerotic human coronary arteries. Mater. Sci. Eng. C 33 (5): 2550–2554.

      80 80 Taylor, C.A. and Humphrey, J.D. (2009). Open problems in computational vascular biomechanics: hemodynamics and arterial wall mechanics. Comput. Methods Appl. Mech. Eng. 198 (45–46): 3514–3523.

      81 81 Raut, S.S., Chandra, S., Shum, J., and Finol, E.A. (2013). The role of geometric and biomechanical factors in abdominal aortic aneurysm rupture risk assessment. Ann. Biomed. Eng. 41 (7): 1459–1477.

      82 82 Stenbaek, J., Kalin, B., and Swedenborg, J. (2000). Growth of thrombus may be a better predictor of rupture than diameter in patients with abdominal aortic aneurysms. Eur. J. Vasc. Endovasc. Surg. 20 (5): 466–469.

      83 83 Li, Z.‐Y., U‐King‐Im, J., Tang, T.Y. et al. (2008). Impact of calcification and intraluminal thrombus on the computed wall stresses of abdominal aortic aneurysm. J. Vasc. Surg. 47 (5): 928–936.

      84 84 Di Martino, E.S. and Vorp, D.A. (2003). Effect of variation in intraluminal thrombus constitutive properties on abdominal aortic aneurysm wall stress. Ann. Biomed. Eng. 31 (7): 804–809.

      85 85 O'Leary, S.A., Kavanagh, E.G., Grace, P.A. et al. (2014). The biaxial mechanical behaviour of abdominal aortic aneurysm intraluminal thrombus: classification of morphology and the determination of layer and region specific properties. J. Biomech. 47 (6): 1430–1437.

      86 86 Tong, J., Schriefl, A.J., Cohnert, T., and Holzapfel, G.A. (2013). Gender differences in biomechanical properties, thrombus age, mass fraction and clinical factors of abdominal aortic aneurysms. Eur. J. Vasc. Endovasc. Surg. 45 (4): 364–372.

      87 87 Speelman, L., Bosboom, E.M.H., Schurink, G.W.H. et al. (2008). Patient‐specific AAA wall stress analysis: 99‐percentile versus peak stress. Eur. J. Vasc. Endovasc. Surg. 36: 668–676.

      88 88 Speelman, L., Bosboom, E.M.H., Schurink, G.W.H., Jacobs, M.J.H.M., and van de Vosse, F.N. (2008). AAA Growth Predicted with Wall Stress. Poster Session Presented at Conference. Mate Poster Award 2008: 13th Annual Poster Contest.

      89 89 Speelman, L., Hellenthal, F.A., Pulinx, B. et al. (2010). The influence of wall stress on AAA growth and biomarkers. Eur. J. Vasc. Surg. 39: 410–416.

      90 90 Kontopodis, N., Metaxa, E., Papaharilaou, Y. et al. (2013). Changes in geometric configuration and biomechanical parameters of a rapidly growing abdominal aortic aneurysm may provide insight in aneurysms natural history and rupture risk. Theor. Biol. Med. Model. 10: 67.

      91 91 Yushkevich, P.A., Piven, J., Hazlett, H.C. et al. (2006). User‐guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31: 1116–1128.

      92 92 Anton, R., Chen, C.Y., Hung, M.Y. et al. (2015). Experimental and computational investigation of the patient‐specific abdominal aortic aneurysm pressure field. Comput. Methods Biomech. Biomed. Eng. 18 (9): 981–992. https://doi.org/10.1080/10255842.2013.865024.

      93 93 Frauenfelder, T., Lotfey, M., Boehm, T., and Wildermuth, S. (2006). Computational fluid dynamics: hemodynamic changes in abdominal aortic aneurysm after stent‐graft implantation. Cardiovasc. Intervent. Radiol. 29: 613–623.

      94 94 Peattie, R.A., Riehle, T.J., and Bluth, E.I. (2004). Pulsatile flow in fusiform models of abdominal aortic aneurysms: flow fields, velocity patterns and flow‐induced wall stresses. J. Biomech. Eng. 126: 438–446.

      95 95 Dorfmann, A., Wilson, C., Edgar, E.S., and Peattie, R.A. (2010). Evaluating patient‐specific abdominal aortic aneurysm wall stress based on flow‐induced loading. Biomech. Model. Mechanobiol. 9: 127–139.

      96 96 Polzer, S., Gasser, T.C., Markert, B. et al. (2012). Impact of poroelasticity of intraluminal thrombus on wall stress of abdominal aortic aneurysms. Biomed. Eng. Online 11: 62.

      97 97 Gasser, T.C., Gorgulu, G., Folkesson, M., and Swedenborg, J. (2008). Failure properties of intraluminal thrombus in abdominal aortic aneurysm under static and pulsating mechanical loads. J. Vasc. Surg. 48: 179–188.

      98 98 Gasser, T.C., Auer, M., Labruto, F. et al. (2010). Biomechanical rupture risk assessment of abdominal aortic aneurysms: model complexity versus predictability of finite element simulations. Eur. J. Vasc. Endovasc. Surg. 40: 176–185.

      99 99 Wang, D.H.J., Makaroun, M.S., Webster, M.W., and Vorp, D.A. (2002). Effect of intraluminal thrombus on wall stress in patient specific models of abdominal aortic aneurysm. J. Vasc. Surg. I36: 598–604.

      100 100 Wang, D.H., Makaroun, M.S., Webster, M.W., and Vorp, D.A. (2001). Mechanical properties and microstructure of intraluminal thrombus from abdominal aortic aneurysm. J. Biomech. Eng. 123: 536–539.

      101 101 Ayyalasomayajula, A., Vande Geest, J.P., and Simon, B.R. (2010). Porohyperelastic finite element modeling of abdominal aortic aneurysms. J. Biomech. Eng. 132: 104502.

      102 102 Baek, S., Zambrano, B.A., Choi, J., and Lim, C.‐Y. (2014). Growth prediction of abdominal aortic aneurysms and its association of intraluminal thrombus. 11th World Congress on Computational Mechanics (WCCM XI); 5th European Conference on Computational Mechanics (ECCM V); 6th European Conference on Computational Fluid Dynamics (ECFD VI), Barcelona, Spain (20–25 July 2014).

      103 103 Zeinali‐Davarani, S. and Baek, S. (2012). Medical image‐based simulation of abdominal aortic aneurysm growth. Mech. Res. Commun. 42: 107–117.

      104 104 Vorp, D.A., Lee, P.C., Wang, D.H. et al. (2001). Association of intraluminal thrombus in abdominal aortic aneurysm with local hypoxia and wall weakening. J. Vasc. Surg. 34: 291–299.

      105 105 Biasetti, J. (2013). Physics of blood flow in arteries and its relation to intra‐luminal thrombus and atherosclerosis. Doctoral dissertation no. 84. KTH School of Engineering Sciences, Department of Solid Mechanics – vascuMECH, KTH Royal Institute of Technology, SE‐100 44 Stockholm, Sweden.

      106 106 Jones, K.C. and Mann, K.G. (1994). A model for the tissue factor pathway to thrombin.II. A mathematical simulation. J. Biol. Chem. 269: 23367–23373.

      107 107 Filipovic, N., Milasinovic, D., Zdravkovic, N. et al. (2011). Impact of aortic repair based on flow field computer simulation within the thoracic aorta. Comput. Methods Prog. Biomed. 101 (3): 243–252.

      108 108 Filipovic, N., Mijailovic, S., Tsuda, A., and Kojic, M. (2006). An implicit algorithm within the arbitrary Lagrangian–Eulerian formulation for solving incompressible fluid flow with large boundary motions. Comp. Meth. Appl. Mech. Engrg. 195: 6347–6361.

      109 109 Filipovic, N., Kojic, M., Ivanovic, M. et al. (2006). MedCFD, Specialized CFD Software for Simulation