Simulation numérique du système cardiovasculaire

Jean-Frédéric Gerbeau; Dominique Chapelle

doi:10.1051/medsci/2005215530

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Volume 21 / No 5 (Mai 2005)

Med Sci (Paris), 21 5 (2005) 530-534

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Issue		Med Sci (Paris) Volume 21, Number 5, Mai 2005


Page(s)		530 - 534
Section		M/S revues
DOI		https://doi.org/10.1051/medsci/2005215530
Published online		15 May 2005

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Caro CG, Fitz-Gerald JM, Schroter RC. Atheroma and aterial wall shear : observation, correlation and proposal of a shear dependant mass transfer mechanism for atherogenesis. Proc R Soc Lond B Biol Sci 1971; 177 : 109–59. [Google Scholar]
Zarins CK, Giddens DP, Bharadvaj BK, et al. Carotid bifurcation atherosclerosis : quantitative correlation of plaque localization with flow velocity profiles and wall shear stress. Circ Res 1983; 53 : 502–14. [Google Scholar]
Yamamoto T, Tanaka H, Jones CJH, et al. Blood velocity profiles in the origin of the canine renal-artery and their relevance in the localization and development of atherosclerosis. Arterioscler Thromb 1992; 12 : 626–32. [Google Scholar]
Asakura T, Karino T. Flow patterns and spatial distribution of atherosclerotic lesions in human coronary arterie. Circ Res 1990; 66 : 1045–66. [Google Scholar]
Botnar R, Rappitsch G, Scheidegger MB, et al. Hemodynamics in the carotid artery bifurcation : a comparison between numerical simulations and in vitro MRI measurements. J Biomec 2000; 33 : 137–44. [Google Scholar]
Gerbeau JF, Vidrascu M. A quasi-Newton algorithm based on a reduced model for fluid-structure interaction problems in blood flows. Math Model Num Anal 2003; 37 : 663–80. [Google Scholar]
Gerbeau JF, Vidrascu M, Frey P. Fluid-structure interaction in blood flows on geometries coming from medical imaging. Comput Struct 2005; 83 : 155-65 (accessible sur http://www.sciencedirect.com/science/journal/00457949). [Google Scholar]
Quarteroni A, Rozza G. Optimal control and shape optimization in aorto-coronaric bypass anastomoses. Math Models Meth Appl Sci 2003; 13 : 1801–23. [Google Scholar]
Panfilov AV, Holden AV. Computational biology of the heart. Chichester : John Wiley and Sons, 1997. [Google Scholar]
Huxley AF. Muscle structure and theories of contraction. In : Progress in biophysics and biological chemistry, vol. 7, chapter 6. Oxford : Pergamon Press, 1957. [Google Scholar]
Zahalak GI. A distribution moment approximation for kinetic theories of muscular contraction. Math Biosci 1981; 55 : 89–114. [Google Scholar]
Bestel J, Clément F, Sorine M. A biomechanical model of muscle contraction. In : Niessen WJ, Viergever MA, eds. Lecture notes in computer science, vol. 2208. New York : Springer Verlag, 2001. [Google Scholar]
Jülicher F, Adjari A, Prost J. Modeling molecular motors. Rev Modern Phys 1997; 69 : 1269–81. [Google Scholar]
Hill AV. The heat of shortening and the dynamic constants in muscle. Proc Roy Soc Lond B Biol Sci 1938; 126 : 136–95. [Google Scholar]
Chapelle D, Clément F, Génot F, et al. A physiologically-based model for active cardiac muscle contraction. In : Katila T, Magnin I, Clarysse P, et al. eds. Functional imaging and modeling of the heart. New York : Springer Verlag, 2001. [Google Scholar]
Blum J, Le Dimet FX. Assimilation de données pour les fluides géophysiques. Matapli 2002; 67 : 33–55. [Google Scholar]
Sainte-Marie J, Chapelle D, Sorine M. Data assimilation for an electromechanical model of the myocardium. In : Bathe KJ, ed. Proceedings of the second MIT Conference on computational fluid and solid mechanics, 17-20 juin 2003, Cambridge, MA, USA, vol. 2. Amsterdam : Elsevier, 2003. [Google Scholar]

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[1] Segers P, Stergiopulos N, Westerhof N, et al. Systemic and pulmonary hemodynamics assessed with a lumped-parameter heart-arterial interaction model. J Engin Mathematics 2003; 14 : 185–99. [Google Scholar]

[2] Monti A, Médigue C, Sorine M. Short-term control of the cardiovascular system : modelling and signal analysis. Rapport de recherche INRIA n° 4427. Paris : INRIA, 2002. [Google Scholar]

[3] Caro CG, Fitz-Gerald JM, Schroter RC. Atheroma and aterial wall shear : observation, correlation and proposal of a shear dependant mass transfer mechanism for atherogenesis. Proc R Soc Lond B Biol Sci 1971; 177 : 109–59. [Google Scholar]

[4] Zarins CK, Giddens DP, Bharadvaj BK, et al. Carotid bifurcation atherosclerosis : quantitative correlation of plaque localization with flow velocity profiles and wall shear stress. Circ Res 1983; 53 : 502–14. [Google Scholar]

[5] Yamamoto T, Tanaka H, Jones CJH, et al. Blood velocity profiles in the origin of the canine renal-artery and their relevance in the localization and development of atherosclerosis. Arterioscler Thromb 1992; 12 : 626–32. [Google Scholar]

[6] Asakura T, Karino T. Flow patterns and spatial distribution of atherosclerotic lesions in human coronary arterie. Circ Res 1990; 66 : 1045–66. [Google Scholar]

[7] Botnar R, Rappitsch G, Scheidegger MB, et al. Hemodynamics in the carotid artery bifurcation : a comparison between numerical simulations and in vitro MRI measurements. J Biomec 2000; 33 : 137–44. [Google Scholar]

[8] Gerbeau JF, Vidrascu M. A quasi-Newton algorithm based on a reduced model for fluid-structure interaction problems in blood flows. Math Model Num Anal 2003; 37 : 663–80. [Google Scholar]

[9] Gerbeau JF, Vidrascu M, Frey P. Fluid-structure interaction in blood flows on geometries coming from medical imaging. Comput Struct 2005; 83 : 155-65 (accessible sur http://www.sciencedirect.com/science/journal/00457949). [Google Scholar]

[10] Quarteroni A, Rozza G. Optimal control and shape optimization in aorto-coronaric bypass anastomoses. Math Models Meth Appl Sci 2003; 13 : 1801–23. [Google Scholar]

[11] Panfilov AV, Holden AV. Computational biology of the heart. Chichester : John Wiley and Sons, 1997. [Google Scholar]

[12] Huxley AF. Muscle structure and theories of contraction. In : Progress in biophysics and biological chemistry, vol. 7, chapter 6. Oxford : Pergamon Press, 1957. [Google Scholar]

[13] Zahalak GI. A distribution moment approximation for kinetic theories of muscular contraction. Math Biosci 1981; 55 : 89–114. [Google Scholar]

[14] Bestel J, Clément F, Sorine M. A biomechanical model of muscle contraction. In : Niessen WJ, Viergever MA, eds. Lecture notes in computer science, vol. 2208. New York : Springer Verlag, 2001. [Google Scholar]

[15] Jülicher F, Adjari A, Prost J. Modeling molecular motors. Rev Modern Phys 1997; 69 : 1269–81. [Google Scholar]

[16] Hill AV. The heat of shortening and the dynamic constants in muscle. Proc Roy Soc Lond B Biol Sci 1938; 126 : 136–95. [Google Scholar]

[17] Chapelle D, Clément F, Génot F, et al. A physiologically-based model for active cardiac muscle contraction. In : Katila T, Magnin I, Clarysse P, et al. eds. Functional imaging and modeling of the heart. New York : Springer Verlag, 2001. [Google Scholar]

[18] Blum J, Le Dimet FX. Assimilation de données pour les fluides géophysiques. Matapli 2002; 67 : 33–55. [Google Scholar]

[19] Sainte-Marie J, Chapelle D, Sorine M. Data assimilation for an electromechanical model of the myocardium. In : Bathe KJ, ed. Proceedings of the second MIT Conference on computational fluid and solid mechanics, 17-20 juin 2003, Cambridge, MA, USA, vol. 2. Amsterdam : Elsevier, 2003. [Google Scholar]