Methods Inf Med 2009; 48(02): 113-122
DOI: 10.3414/ME0539
Original Articles
Schattauer GmbH

Computer Simulation of Coronary Flow Waveforms during Caval Occlusion

C. De Lazzari
1   C.N.R., Institute of Clinical Physiology – Section of Rome, Rome, Italy
,
D. Neglia
2   C.N.R., Institute of Clinical Physiology, Pisa, Italy
,
G. Ferrari
1   C.N.R., Institute of Clinical Physiology – Section of Rome, Rome, Italy
,
F. Bernini
2   C.N.R., Institute of Clinical Physiology, Pisa, Italy
,
M. Micalizzi
2   C.N.R., Institute of Clinical Physiology, Pisa, Italy
,
A L’Abbate
2   C.N.R., Institute of Clinical Physiology, Pisa, Italy
3   Scuola Superiore Sant’Anna, Pisa, Italy
,
M. G. Trivella
2   C.N.R., Institute of Clinical Physiology, Pisa, Italy
› Author Affiliations
Further Information

Publication History

received: 15 February 2008

accepted: 27 February 2008

Publication Date:
17 January 2018 (online)

Summary

Objectives: Mathematical modeling of the cardiovascular system is a powerful tool to extract physiologically relevant information from multi-parametric experiments. The purpose of the present work was to reproduce by means of a computer simulator, systemic and coronary measurements obtained by in vivo experiments in the pig.

Methods: We monitored in anesthetized open-chest pig the phasic blood flow of the left descending coronary artery, aortic pressure, left ventricular pressure and volume. Data were acquired before, during, and after caval occlusion.

Inside the software simulator (CARDIOSIM©) of the cardiovascular system, coronary circulation was modeled in three parallel branching sections. Both systemic and pulmonary circulations were simulated using a lumped parameter mathematical model. Variable elastance model reproduced Starling’s law of the heart.

Results: Different left ventricular pressure-volume loops during experimental caval occlusion and simulated cardiac loops are presented. The sequence of coronary flow-aortic pressure loops obtained in vivo during caval occlusion together with the simulated loops reproduced by the software simulator are reported. Finally experimental and simulated instantaneous coronary blood flow waveforms are shown.

Conclusions: The lumped parameter model of the coronary circulation, together with the cardiovascular system model, is capable of reproducing the changes during caval occlusion, with the profound shape deformation of the flow signal observed during the in vivo experiment. In perspectives, the results of the present model could offer new tool for studying the role of the different determinants of myocardial perfusion, by using the coronary loop shape as a “sensor” of ventricular mechanics in various physiological and pathophysiological conditions.

 
  • References

  • 1 Mosher P, Ross J, McFate PA, Shaw RF. Control of coronary blood flow by an autoregolatory mechanism. Circ Res 1964; 14: 250-259.
  • 2 Mancini GB, Cleary RM, DeBoe SF, Moore NB, Gallagher KP. Instantaneous hyperemic flow-versus-pressure slope index: Microsphere validation of an alternative to measures of coronary reserve. Circulation 1991; 84: 862-870.
  • 3 Di Mario C, Kramas R, Gil R, Serruys PW. Slope of the instantaneous hyperemic diastolic coronary flow velocity-pressure relation. A new index for assessment of the physiological significance of coronary stenosis in humans. Circulation 1994; 90: 1215-1224.
  • 4 Steele BN, Jing W, Ku JP, Hughes TJR, Taylor CA. In vivo validation of a one-dimensional finite-element method predicting blood flow in cardiovascular bypass grafts. IEEE Trans Biomed Eng 2003; 50 (06) 649-656.
  • 5 Ku DN. Blood flow in arteries. Annual Review of Fluid Mechanics 1997; 29: 399-434.
  • 6 Ferrari G, De Lazzari C, Mimmo R, Tosti G, Ambrosi D. A modular numerical model of the cardiovascular system for studying and training in the field of cardiovascular physiopathology. J Biomed Eng 1992; 14: 91-107.
  • 7 De Lazzari C, Darowski M, Wolski P, Ferrari G, Tosti G, Pisanelli DM. In Vivo and Simulation Study of Artificial Ventilation Effects on Energetic Variables in Cardiosurgical Patients. Methods Inf Med 2005; 44 (01) 98-105.
  • 8 De Lazzari C, Darowski M, Ferrari G, Pisanelli DM, Tosti G. Modelling in the study of interaction of Hemopump device and artificial ventilation. Comput Biol Med 2006; 36 (11) 1235-1251.
  • 9 De Lazzari C, Ferrari G. Right ventricular assistance by countinuous flow device: a numerical simulation. Methods Inf Med 2007; 46 (05) 530-537.
  • 10 Spaan JA, Nreuls NP, Laird JD. Diastolic-systolic coronary flow differences are caused by intramyocardial pump action in the anesthetized dog. Circ Res 1981; 49: 584-593.
  • 11 Spaan JA, Nreuls NP, Laird JD. Forward coronary flow normally seen in sistole is the result of both forward and concealed back flow. Basic Res Cardiol 1981; 76: 582-586.
  • 12 Micalizzi M, Conforti F, Macerata A, Passino C, Varanini M, Emdin M. Remote biosignal monitoring, display, online analysis and retrieval. Comput Cardiol 2001; 28: 557-560.
  • 13 L’Abbate A, Camici P, Trivella MG, Pelosi G, Davies GJ, Ballestra AM, Taddei L. Time dependent response of coronary flow to prolonged adenosine infusion: doubling of peak reactive hyperaemic flow. Cardiovasc Res 1981; 15 (05) 282-286.
  • 14 Sagawa K, Maughan L, Suga H, Sunagawa K. Cardiac contraction and the Pressure-Volume relationships. Oxford University Press; New York: 1988
  • 15 Gilbert JC, Glantz SA. Determinants of left ventricular filling and of the diastolic pressure volume relation. Circ Res 1989; 64: 827-852.
  • 16 De Lazzari C, L’Abbate A, Trivella MG. et al. Modelling Cardiovascular System and Mechanical Circulatory Support. Edited by C. De Lazzari. National Research Council Press; Rome: 2007
  • 17 Matthys KS, Alastruey J, Peiro J, Khir AW, Segers P, Verdonck PR, Parkerb KH, Sherwin SJ. Pulse wave propagation in a model human arterial network: Assessment of 1-D numerical simulations against in vitro measurements. J Biomech 2007; 40: 3476-3486.
  • 18 Khir AW, Parker KH. Measurements of wave speed and reflected waves in elastic tubes and bifurcations. J Biomech 2002; 35: 775-783.
  • 19 Wang JJ, Parker KH. Wave propagation in a model of the arterial circulation. J Biomech 2004; 37: 457-470.
  • 20 Manor D, Shofti R, Sideman S, Beyar R. Quantitative sorting of normal and abnormal coronary flow wave form shapes. IEEE Trans Biomed Eng 1994; 41.