بررسی روش‌های شبیه‌سازی عددی جریان خون در ناهنجاری شریانی وریدی

نوع مقاله : علمی ترویجی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران

2 استادیار مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران

چکیده

بدشکلی شریانی وریدی، نوعی بیماری از سیستم عروقی بدن انسان است که عمدتاً در عروق مغزی و ستون فقرات رخ می‌دهد. در این بیماری جریان خون برخلاف حالت طبیعی به جای عبور از بخش مویرگی، به صورت مستقیم از شریان به ورید منتقل می‌شود و در صورت پیشرفت می‌تواند منجر به پارگی و خونریزی مغزی گردد. روش‌های درمان متداول آن عبارت از برداشتن با جراحی، آمبولیزاسیون و پرتو درمانی است. مدل‌سازی و شبیه‌سازی جریان خون در سیستم عروقی بدن انسان به پزشکان کمک می‌کند که درک بهتری از بیماری‌های عروقی و نحوه رشد آن‌ها داشته باشند تا بتوانند قبل از جراحی تصمیمات صحیح و مهمی را اتخاذ کنند. سه نوع مدل‌سازی متداول برای جریان خون در عروق، عبارت از مدل‌سازی ریاضی، مکانیکی و الکتریکی است که در ارتباط با هر کدام از آن‌ها مطالعات مهمی صورت گرفته است. در پژوهش حاضر به بررسی انواع مدل‌سازی‌ها و مطالعات مرتبط با آن‌ها پرداخته شده است.

کلیدواژه‌ها

موضوعات


[1] Kumar, Y. Kiran, Mehta, Shashi Bhushan, and Ramachandra, Manjunath. Computer simulation of cerebral arteriovenous malformation-validation analysis of hemodynamics parameters. PeerJ, 5:e2724–e2724, Jan 2017. 28149675[pmid].
[2] Lawton, Michael T, Rutledge, W Caleb, Kim, Helen, Stapf, Christian, Whitehead, Kevin J, Li, Dean Y, Krings, Timo, Kondziolka, Douglas, Morgan, Michael K, Moon, Karam, et al. Brain arteriovenous malformations. Nature reviews disease primers, 1(1):1–20, 2015.
[3] Golovin, S. V., Khe, A. K., and Gadylshina, K. A. Hydraulic model of cerebral arteriovenous malformations. Journal of Fluid Mechanics, 797:110–129, 2016.
[4] Kumar, YK, Mehta, S, and Ramachandra, M. Review paper: Cerebral arteriovenous malformations modelling. International Journal of Scientific and Engineering Research, 4:129–139, 2013.
[5] Reymond, Philippe, Bohraus, Yvette, Perren, Fabienne, Lazeyras, Francois, and Stergiopulos, Nikos. Validation of a patient-specific one-dimensional model of the systemic arterial tree. American Journal of Physiology-Heart and Circulatory Physiology, 301(3):H1173–H1182, 2011.
[6] Tian, Fang-Bao, Zhu, Luoding, Fok, Pak-Wing, and Lu, Xi-Yun. Simulation of a pulsatile non-newtonian flow past a stenosed 2d artery with atherosclerosis. Computers in biology and medicine, 43(9):1098– 1113, 2013.
[7] Ghodsi, SR, Esfahanian, V, and Ghodsi, SM. Modeling requirements for computer simulation of cerebral aneurysm. Journal of Computational Medicine, 2014, 2014.
[8] Gromeka, IS. On the theory of fluid motion in narrow cylindrical tubes. Gromeka, IS, pp. 149–171, 1952.
[9] Womersley, John R. Method for the calculation of velocity, rate of flow and viscous drag in arteries when the pressure gradient is known. The Journal of physiology, 127(3):553–563, 1955.
[10] Waite, Lee, Fine, Jerry, et al. Applied biofluid mechanics. McGraw-Hill Education, 2017.
[11] Pedley, Timothy J and Luo, XY. Fluid mechanics of large blood vessels. Shaanxi People’s Press, 1995.
[12] Sherwin, Spencer J, Formaggia, Luca, Peiro, Joaquim, and Franke, V. Computational modelling of 1d blood flow with variable mechanical properties and its application to the simulation of wave propagation in the human arterial system. International journal for numerical methods in fluids, 43(6- 7):673–700, 2003.
[13] Formaggia, Luca, Quarteroni, Alfio, and Veneziani, Allesandro. Cardiovascular Mathematics: Modeling and simulation of the circulatory system, vol. 1. Springer Science & Business Media, 2010.
[14] Müller, Lucas O and Toro, Eleuterio F. A global multiscale mathematical model for the human circulation with emphasis on the venous system. International journal for numerical methods in biomedical engineering, 30(7):681–725, 2014.
[15] Alastruey, Jordi, Khir, Ashraf W, Matthys, Koen S, Segers, Patrick, Sherwin, Spencer J, Verdonck, Pascal R, Parker, Kim H, and Peiró, Joaquim. Pulse wave propagation in a model human arterial network: assessment of 1-d visco-elastic simulations against in vitro measurements. Journal of biomechanics, 44(12):2250–2258, 2011.
[16] Smith, FT and Jones, MA. One-to-few and one-tomany branching tube flows. Journal of Fluid Mechanics, 423:1–31, 2000.
[17] White, AH and Smith, FT. Computational modelling of the embolization process for the treatment of arteriovenous malformations (avms). Mathematical and Computer Modelling, 57(5-6):1312–1324, 2013.
[18] Orlowski, Piotr, Summers, Paul, Noble, J Alison, Byrne, James, and Ventikos, Yiannis. Computational modelling for the embolization of brain arteriovenous malformations. Medical engineering & physics, 34(7):873–881, 2012.
[19] Quick, Christopher M, Leonard, Edward F, and Young, William L. Adaptation of cerebral circulation to brain arteriovenous malformations increases feeding artery pressure and decreases regional hypotension. Neurosurgery, 50(1):167–175, 2002.
[20] Henkes, H, Gotwald, TF, Brew, S, Kaemmerer, F, Miloslavski, E, and Kuehne, D. Pressure measurements in arterial feeders of brain arteriovenous malformations before and after endovascular embolization. Neuroradiology, 46(8):673–677, 2004.
[21] Orlowski, Piotr, Al-Senani, Fahmi, Summers, Paul, Byrne, James, Noble, J Alison, and Ventikos, Yiannis. Towards treatment planning for the embolization of arteriovenous malformations of the brain: intranidal hemodynamics modeling. IEEE transactions on biomedical engineering, 58(7):1994–2001, 2011.
[22] Jeong, Woowon and Rhee, Kyehan. Hemodynamics of cerebral aneurysms: computational analyses of aneurysm progress and treatment. Computational and mathematical methods in medicine, 2012, 2012.
[23] Cebral, Juan R, Castro, Marcelo Adrián, Appanaboyina, Sunil, Putman, Christopher M, Millan, Daniel, and Frangi, Alejandro F. Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity. IEEE transactions on medical imaging, 24(4):457– 467, 2005.
[24] Cebral, Juan R, Castro, Marcelo A, Soto, Orlando, Löhner, Rainald, and Alperin, Noam. Blood-flow models of the circle of willis from magnetic resonance data. Journal of Engineering Mathematics, 47(3):369–386, 2003.
[25] Castro, MA, Putman, Christopher M, and Cebral, JR. Computational fluid dynamics modeling of intracranial aneurysms: effects of parent artery segmentation on intra-aneurysmal hemodynamics. American Journal of Neuroradiology, 27(8):1703–1709, 2006.
[26] Yim, Peter, Demarco, Kevin, Castro, Marcelo A, and Cebral, Juan. Characterization of shear stress on the wall of the carotid artery using magnetic resonance imaging and computational fluid dynamics. Studies in health technology and informatics, 113:412–442, 2005.
[27] Karmonik, Christof, Yen, Christopher, Diaz, Orlando, Klucznik, Richard, Grossman, Robert G, and Benndorf, Goetz. Temporal variations of wall shear stress parameters in intracranial aneurysms— importance of patient-specific inflow waveforms for cfd calculations. Acta neurochirurgica, 152(8):1391–1398, 2010.
[28] Karmonik, Christof, Yen, Christopher, Grossman, Robert G, Klucznik, Richard, and Benndorf, Goetz. 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 neurochirurgica, 151(5):479–485, 2009.
[29] Spiegel, Martin, Redel, Thomas, Zhang, Y Jonathan, Struffert, Tobias, Hornegger, Joachim, Grossman, Robert G, Doerfler, Arnd, and Karmonik, Christof. Tetrahedral vs. polyhedral mesh size evaluation on flow velocity and wall shear stress for cerebral hemodynamic simulation. Computer methods in biomechanics and biomedical engineering, 14(01):9–22, 2011.