Modeling Flow in Cerebral Aneurysm After Coils Embolization Treatment: A Realistic Patient-Specific Porous Model Approach

Springer Science and Business Media LLC - Tập 14 - Trang 115-128 - 2022
Julia Romero Bhathal1, Fanette Chassagne2, Laurel Marsh3, Michael R. Levitt4, Christian Geindreau1, Alberto Aliseda3,4
13SR, Univ. Grenoble Alpes, CNRS,Grenoble INP, Grenoble, France
2Mines Saint-Etienne, INSERM, UMR1059, SAINBIOSE, CIS-EMSE, Saint-Etienne, France
3Department of Mechanical Engineering, University of Washington, Seattle, USA
4Department of Neurological Surgery, University of Washington, Seattle, USA

Tóm tắt

Computational fluid dynamics (CFD) has been used to evaluate the efficiency of endovascular treatment in coiled cerebral aneurysms. The explicit geometry of the coil mass cannot typically be incorporated into CFD simulations since the coil mass cannot be reconstructed from clinical images due to its small size and beam hardening artifacts. The existing methods use imprecise porous medium representations. We propose a new porous model taking into account the porosity heterogeneity of the coils deployed in the aneurysm. The porosity heterogeneity of the coil mass deployed inside two patients’ cerebral aneurysm phantoms is first quantified based on 3D X-ray synchrotron images. These images are also used to compute the permeability and the inertial factor arising in porous models. A new homogeneous porous model (porous crowns model), considering the coil’s heterogeneity, is proposed to recreate the flow within the coiled aneurysm. Finally, the validity of the model is assessed through comparisons with coil-resolved simulations. The strong porosity gradient of the coil measured close to the aneurysmal wall is well captured by the porous crowns model. The permeability and the inertial factor values involved in this model are closed to the ideal homogeneous porous model leading to a mean velocity in the aneurysmal sac similar as in the coil-resolved model. The porous crowns model allows for an accurate description of the mean flow within the coiled cerebral aneurysm.

Tài liệu tham khảo

Augsburger, L., P. Reymond, D. A. Rufenacht, and N. Stergiopulos. Intracranial stents being modeled as a porous medium: flow simulation in stented cerebral aneurysms. Ann. Biomed. Eng. 39:850–863, 2011. Auriault, J. L., C. Geindreau, and L. Orgéas. Upscaling forchheimer law. Transp. Porous Media 70:213–229, 2007. Auriault, J. L., C. Boutin, and C. Geindreau. Homogenization of Coupled Phenomena in Heterogenous Media. Wiley-ISTE: London, 2009. Barbour, M. Computational and Experimental Investigation into the Hemodynamics of Endovascularly Treated Cerebral Aneurysms, 2018. Boutin, C. Study of permeability by periodic and self-consistent homogenisation. Eur. J. Mech. - A/Solids 19(4):603–632, 2000. Brinkman, H. C. A calculation of the viscosity and the sedimentation constant for solutions of large chain molecules taking into account the hampered flow of the solvent through these molecules. Physica 13(8):447–448, 1947. Chivukula, V. K., M. R., M. R. L., A. Clark, M. C. Barbour, K. Sansom, L. Johnson, C. M. Kelly, C. Geindreau, S. R. du Roscoat, L. J. K., and A. Aliseda. Reconstructing patient-specific cerebral aneurysm vasculature for in vitro investigations and treatment efficacy assessments. J. Clin. Neurosci. 61:153–159, 2019. Chueh, J.-Y., S. Vedantham, A. K. Wakhloo, S. L. Carniato, A. S. Puri, C. Bzura, S. Coffin, A. A. Bogdanov, and M. J. Gounis. Aneurysm permeability following coilembolization: packing density and coil distribution. J. NeuroInterv. Surg. 7(9):676–681, 2015. Crobeddu, E., G. Lanzino, D. F. Kallmes, and H. J. Cloft. Review of 2 decades of aneurysm-recurrence literature, part 1: reducing recurrence after endovascular coiling. Am. J. Neuroradiol. 34(2):266–270, 2013. Damiano, R. J., D. Ma, J. Xiang, H. A. Siddiqui, K. V. Snyder, and H. Meng. Finite element modeling of endovascular coiling and flow diversion enables hemodynamic prediction of complex treatment strategies for intracranial aneurysm. J. Biomech. 48(12):3332–3340, 2015. Guglielmi, G., F. Viñuela, J. Dion, and G. Duckwiler. Electrothrombosis of saccular aneurysms via endovascular approach. J. Neurosurg. 75:1–7, 1991. Kakalis, N. M. P., A. P. Mitsos, J. V. Byrne, and Y. Ventikos. The haemodynamics of endovascular aneurysm treatment: a computational modelling approach for estimating the influence of multiple coil deployment. IEEE Trans. Med. Imaging 27(6):814–824, 2008. Karmonik, C., C. Yen, R. G. Grossman, R. Klucznik, and G. Benndorf. Intra-aneurysmal flow patterns and wall shear stresses calculated with computational flow dynamics in an anterior communicating artery aneurysm depend on knowledge of patient-specific inflow rates. Acta Neurochir. 151:479–485, 2009. Levitt, M. R., P. M. McGah, A. Aliseda, P. D. Mourad, J. D. Nerva, S. S. Vaidya, R. P. Morton, B. V. Ghodke, and L. J. Kim. Cerebral aneurysms treated with flow-diverting stents: computational models with intravascular blood flow measurements. AJNR 35(1):143–148, 2014. Levitt, M. R., M. C. Barbour, S. R. du Roscoat, C. Geindreau, V. K. Chivukula, P. M. McGah, J. D. Nerva, R. P. Morton, L. J. Kim, and A. Aliseda. Computational fluid dynamics of cerebral aneurysm coiling using high-resolution and high-energy synchrotron X-ray microtomography: comparison with the homogeneous porous medium approach. J. NeuroInterv. Surg. 0:1–6, 2016. Luo, B., X. Yang, S. Wang, et al. High shear stress and flow velocity in partially occluded aneurysms prone to recanalization. Stroke 42:745–753, 2011. McGah, P. M., D. F. Leotta, K. W. Beach, J. J. Riley, and A. Aliseda. A longitudinal study of remodeling in a revised peripheral artery bypass graft using 3D ultrasound imaging and computational hemodynamics. J. Biomech. Eng. 133(4):041008, 2011. McGah, P. M., M. R. Levitt, M. C. Barbour, R. P. Morton, J. D. Nerva, P. D. Mourad, B. V. Ghodke, D. K. Hallam, L. N. Sekhar, L. J. Kim, and A. Aliseda. Accuracy of computational cerebral aneurysm hemodynamics using patient-specific endovascular measurements. Ann. Biomed. Eng. 42:503–514, 2014. Meng, H., V. M. Tutino, J. Xiang, and A. Siddiqui. High WSS or low WSS? Complex interactions of hemodynamics with intracranial aneurysm initiation, growth, and rupture: toward a unifying hypothesis. Am. J. Neuroradiol. 35(7):1254–1262, 2014. Mitsos, A. P., N. M. Kakalis, Y. P. Ventiko, and J. V. Byrne. Haemodynamic simulation of aneurysm coiling in an anatomically accurate computational fluid dynamics model: technical note. Neuroradiology 50(4):341–347, 2008. Sadasivan, C., E. Swartwout, A. D. Kappel, H. H. Woo, D. J. Fiorella, and B. B. Lieber. In vitro measurement of the permeability of endovascular coils deployed in cerebral aneurysms. J. Neurointerv. Surg. 10(9):896–900, 2018. Schindelin, J., I. Arganda-Carreras, E. Frise, V. Kaynig, M. Longair, T. Pietzsch, and A. Cardona. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9(7):676–682, 2012. Venkat, K. C., M. R. Levitt, A. Clark, S. R. du Roscoat, L. J. Kim, and A. Aliseda. Reconstructing patient-specific cerebral aneurysm vasculature for in vitro investigations and treatment efficacy assessments. J. Clin. Neurosci. 61:153–159, 2019. Venugopal, P., D. Valentino, H. Schmitt, J. P. Villablanca, F. Viñuela, and G. Duckwiler. Sensitivity of patient-specific numerical simulation of cerebal aneurysm hemodynamics to inflow boundary conditions. J. Neurosurg. 106(6):1051–1060, 2007. Wilm, J. Iterative closest point, MATLAB central file exchange. https://www.mathworks.com/matlabcentral/fileexchange/27804-iterative-closest-point. Yadollahi-Farsani, H., M. Herrmann, D. Frakes, et al. A new method for simulating embolic coils as heterogeneous porous media. Cardiovasc. Eng. Tech. 10:32–45, 2019. Zaripov, S. K., R. F. Mardanov, and V. F. Sharafutdinov. Determination of Brinkman model parameters using stokes flow model. Transp. Porous Media 130:529–557, 2019.