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Patient-specific hemodynamics and stress-strain state of cerebral aneurysms

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Approximately 5% of the adult population has one or more cerebral aneurysm. Aneurysms are one of the most dangerous cerebral vascular pathologies. Aneurysm rupture leads to a subarachnoid hemorrhage with a very high mortality rate of 45–50%. Despite the high importance of this disease there are no criteria for assessing the probability of aneurysm rupture. Moreover, mechanisms of aneurysm development and rupture are not fully understood until now. Methods: Biomechanical and numerical computer simulations allow us to estimate the behavior of vessels in normal state and under pathological conditions as well as to make a prediction of their postoperative state. Biomechanical studies may help clinicians to find and investigate mechanical factors which are responsible for the initiation, growth and rupture of the cerebral aneurysms. Results: In this work, biomechanical and numerical modeling of healthy and pathological cerebral arteries was conducted. Patient-specific models of the basilar and posterior cerebral arteries and patient-specific boundary conditions at the inlet were used in numerical simulations. A comparative analysis of the three vascular wall models (rigid, perfectly elastic, hyperelastic) was performed. Blood flow and stress-strain state of the two posterior cerebral artery aneurysm models was compared. Conclusions: Numerical simulations revealed that hyperelastic material most adequately and realistically describes the behavior of the cerebral vascular walls. The size and shape of the aneurysm have a significant impact on the blood flow through the affected vessel and on the effective stress distribution in the aneurysm dome. It was shown that large aneurysm is more likely to rupture than small aneurysm.
Rocznik
Strony
9--17
Opis fizyczny
Bibliogr. 24 poz., rys., wykr.
Twórcy
autor
  • Saratov State University, Educational-Research Institute of Nanostructures and Biosystems, Saratov, Russia
autor
  • Saratov State University, Educational-Research Institute of Nanostructures and Biosystems, Saratov, Russia
autor
  • Saratov State University, Educational-Research Institute of Nanostructures and Biosystems, Saratov, Russia
Bibliografia
  • [1] BAZILEVS Y., HSU M.C., ZHANG Y., WANG W., KVAMSDAL T., HENTSCHEL S., ISAKSEN J.G., Computational vascular fluidstructure interaction: methodology and application to cerebral aneurysms, Biomech. Model Mechanobiol., 2010, Vol. 9(4), 481–498.
  • [2] BEDERSON J.B., CONNOLLY E.S., BATJER H.H., DACEY R.G., DION J.E., DIRINGER M.N., DULDNER J.E., HARBAUGH R.E., PATEL A.B., ROSENWASSER R.H., Guidelines for the management of aneurysmal subarachnoid hemorrhage: a statement for healthcare professionals from a special writing group of the stroke council, Stroke, 2009, Vol. 40(3), 994–1025.
  • [3] BONNEVILLE F., SOUROUR N., BIONDI A., Intracranial aneurysms: an overview, Neuroimaging Clin. N. Am., 2006, Vol. 16(3), 371–382.
  • [4] CASTRO M.A., PUTMAN C.M., CEBRAL J.R., Patient-specific computational fluid dynamics modeling of anterior communicating artery aneurysms: a study of the sensitivity of intraaneurysmal flow patterns to flow conditions in thecarotidarteries, Am. J. Neuroradiol., 2006, Vol. 27(10), 2061–2068.
  • [5] CEBRAL J.R., MUT F., RASCHI M., SCRIVANO E., CERATTO R., LYLYK P., PUTMAN C.M., Aneurysm rupture following treatment with flow-diverting stents: computational hemodynamics analysis of treatment, AJNR Am. J. Neuroradiol., 2011, Vol. 32(1), 27–33.
  • [6] CURTIS S.L., BRADLEY M., WILDE P., AW J., CHAKRABARTI S., HAMILTON M., MARTIN R., TURNER M., STUART A.G., Results of screening for intracranial aneurysms in patients with coarctation of the aorta, AJNR Am. J. Neuroradiol., 2012, Vol. 33(6), 1182–1186.
  • [7] IVANOV D., DOL A., PAVLOVA O., ARISTAMBEKOVA A., Modeling of human circle of Willis with and without aneurisms, Acta Bioeng. Biomech., 2014, Vol. 16(2), 121–129.
  • [8] JANIGA G., BERG P., SUGIYAMA S., KONO K., STEINMAN D.A., The computational fluid dynamics rupture challenge 2013 – phase I: prediction of rupture status in intracranial aneurysms, AJNR Am. J. Neuroradiol., 2015, Vol. 36(3), 530–536.
  • [9] JANSEN I.G., SCHNEIDERS J.J., POTTERS W.V., VAN OOIJ P., VAN DEN BERG R., VAN BAVEL E., MARQUERING H.A., MAJOIE C.B., Generalized versus patient-specific inflow boundary conditions in computational fluid dynamics simulations of cerebral aneurysmal hemodynamics, AJNR Am. J. Neuroradiol., 2014, Vol. 35(8), 1543–1548.
  • [10] KROON M., Simulation of cerebral aneurysm growth and prediction of evolving rupture risk, Modelling and Simulation in Engineering, 2011. DOI: 10.1155/2011/289523
  • [11] KU J.P., ELKINS C.J., TAYLOR C.A., Comparison of CFD and MRI flow and velocities in an in vitro large artery bypass graft model, Ann. Biomed. Eng., 2005, Vol. 33(3), 257–269.
  • [12] LEE C.J., ZHANG Y., TAKAO H., MURAYAMA Y., QIAN Y., A fluid–structure interaction study using patient-specific ruptured and unruptured aneurysm: The effect of aneurysm morphology, hypertension and elasticity, J. Biomech., 2013, Vol. 46(14), 2402–2410.
  • [13] LEHOUX S., TRONC F., TEDGUI A., Mechanisms of blood flowinduced vascular enlargement, Biorheology, 2002, Vol. 39(3–4), 319–324.
  • [14] MARZO A., SINGH P., REYMOND P., STERGIOPULOS N., PATEL U., HOSE R., Influence of inlet boundary conditions on the local haemodynamics of intracranial aneurysms, Computer Methods in Biomechanics and Biomedical Engineering, 2009, Vol. 12(4), 431–444.
  • [15] SADASIVAN C., FIORELLA D.J., WOO H.H., LIEBER B.B., Physical factors effecting cerebral aneurysm pathophysiology, Ann. Biomed. Eng., 2013, Vol. 41(7), 1347–1365.
  • [16] SHOJIMA M., OSHIMA M., TAKAGI K., TORII R., NAGATA K., SHIROUZU I., MORITA A., KIRINO T., Role of the bloodstream impacting force and the local pressure elevation in the rupture of cerebral aneurysms, Stroke, 2005, Vol. 36(9), 1933–1938.
  • [17] TEUNISSEN L.L., RINKEL G.J.E., ALGRA A., VAN GIJN J., Risk factors for subarachnoid hemorrhage – a systematic review, Stroke, 1996, Vol. 27(3), 544–549.
  • [18] TORII R., OSHIMA M., An integrated geometric modelling framework for patient-specific computational haemodynamic study on wide-ranged vascular network, Comput. Methods Biomech. Biomed. Engin., 2012, Vol. 15(6), 615–625.
  • [19] TORII R., OSHIMA M., KOBAYASHI T., TAKAGI K., TEZDUYAR T.E., Fluid–structure interaction modeling of blood flow and cerebral aneurysm: significance of artery and aneurysm shapes, Comput. Methods Appl. Mech. Eng., 2009, Vol. 198(45–46), 3613–3621.
  • [20] TURJMAN A.S., TURJMAN F., EDELMAN E.R., Role of fluid dynamics and inflammation in intracranial aneurysm formation, Circulation, 2014, Vol. 129(3), 373–382.
  • [21] VALENCIA A., BURDILES P., IGNAT M., MURA J., BRAVO E., RIVERA R., SORDO J., Fluid structural analysis of human cerebral aneurysm using their own wall mechanical properties, Comput. Math. Methods Med., 2013, 2013, 293128, DOI: 10.1155/2013/293128.
  • [22] VALENCIA A., LEDERMANN D., RIVERA R., BRAVO E., GALVEZ M., Blood flow dynamics and fluid–structure interaction in patient-specific bifurcating cerebral aneurysms, Int. J. Numer Method Biomed. Eng., 2008, Vol. 58(10), 1081–1100.
  • [23] WANG S., DING G., ZHANG Y., YANG X., Computational haemodynamics in two idealised cerebral wide-necked aneurysms after stent placement, Comput. Methods Biomech. Biomed. Engin., 2011, Vol. 14, 927–937.
  • [24] WANG X., LI X., Biomechanical behaviour of cerebral aneurysm and its relation with the formation of intraluminal thrombus: a patient-specific modelling study, Comput. Methods Biomech. Biomed. Engin., 2013, Vol. 16(11), 1127–1134, DOI: 10.1080/10255842.2011.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b73bdd6b-f715-42c3-9766-19ba83cf1633
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