Flow, Turbulence and Combustion

, Volume 96, Issue 3, pp 837–860 | Cite as

On Recent Progress in Modelling and Simulations of Multi-scale Transfer of Mass, Momentum and Particles in Bio-medical Applications

Open Access
Article

Abstract

We present a short overview of some of our most recent work that combines the mathematical modeling, advanced computer simulations and state-of-the-art experimental techniques of physical transport phenomena in various bio-medical applications. In the first example, we tackle predictions of complex blood flow patterns in the patient-specific vascular system (carotid artery bifurcation) and transfer of the so-called “bad” cholesterol (low-density lipoprotein, LDL) within the multi-layered artery wall. This two-way coupling between the blood flow and corresponding mass transfer of LDL within the artery wall is essential for predictions of regions where atherosclerosis can develop. It is demonstrated that a recently developed mathematical model, which takes into account the complex multi-layer arterial-wall structure, produced LDL profiles within the artery wall in good agreement with in-vivo experiments in rabbits, and it can be used for predictions of locations where the initial stage of development of atherosclerosis may take place. The second example includes a combination of pulsating blood flow and medical drug delivery and deposition controlled by external magnetic field gradients in the patient specific carotid artery bifurcation. The results of numerical simulations are compared with own PIV (Particle Image Velocimetry) and MRI (Magnetic Resonance Imaging) in the PDMS (silicon-based organic polymer) phantom. A very good agreement between simulations and experiments is obtained for different stages of the pulsating cycle. Application of the magnetic drug targeting resulted in an increase of up to ten fold in the efficiency of local deposition of the medical drug at desired locations. Finally, the LES (Large Eddy Simulation) of the aerosol distribution within the human respiratory system that includes up to eight bronchial generations is performed. A very good agreement between simulations and MRV (Magnetic Resonance Velocimetry) measurements is obtained. Magnetic steering of aerosols towards the left or right part of lungs proved to be possible, which can open new strategies for medical treatment of respiratory diseases.

Keywords

Blood flow LDL transfer Aerosol distribution Magnetization force 

References

  1. 1.
    Truskey, G.A., Yuan, F., Katz, D.F.: Transport phenomena in biological systems, 2nd Edition, pearson prentice hall bioengineering (2009)Google Scholar
  2. 2.
    Tarbell, J.M.: Mass transport in arteries and the localization of atherosclerosis. Annu. Rev. Biomed. Eng. 5, 79–118 (2003)CrossRefGoogle Scholar
  3. 3.
    Yang, N., Vafai, K.: Modelling of low-density lipoprotein (LDL) transport in the artery-effects of hypertension. Int. J. Heat and Mass Transfer 49, 850–867 (2006)CrossRefMATHGoogle Scholar
  4. 4.
    Ai, L., Vafai, K.: A coupling model for macromolecule transport in a stenosed arterial wall. Int. J. Heat and Mass Transfer 49, 1568–1591 (2006)CrossRefMATHGoogle Scholar
  5. 5.
    Olgac, U., Poulikakos, D., Saur, S.C., Alkadhi, H., Kurtcuoglu, V.: Patient-specific three-dimensional simulation of LDL accumulation in a human left coronary artery in its healthy and atherosclerotic states. Am. J. Physiol. Heart Circ. Physiol. 296, H1969—H1982 (2009)CrossRefGoogle Scholar
  6. 6.
    Kenjereš, S, de Loor, A.: Modelling and simulation of low-density lipoprotein transport through multilayered wall of an anatomically realistic carotid artery bifurcation. J. R. Soc. Interface. 11(91), 1–13 (2014). Art. No. 20130941Google Scholar
  7. 7.
    Academic Research, A.N.S.Y.S.: Release 15.0 ANSYS Inc (2014)Google Scholar
  8. 8.
    Groen, H.C., Simons, L., van den Bouwhuijsen, Q.J.A., Bosboom, E.M.H., Gijsen, F.H.J., van der Giessen, A.G., van de Vosse, F.N., Hofman, A., van der Steen, A.F.W., Witteman, J. C. M., van der Lugt, A., Wentzel J. J.: MRI-based quantification of outflow boundary conditions for computational fluid dynamics of stenosed human carotid arteries. J. Biomech. 43(12), 2332–2338 (2010)CrossRefGoogle Scholar
  9. 9.
    Meyer, G., Merval, R., Tedgui, A.: Effects of pressure-induced stretch and convection on low-density lipoprotein and albumin uptake in the rabbit aortic wall. Circ. Res. 79(3), 532–540 (1996)CrossRefGoogle Scholar
  10. 10.
    Holdsworth, D.W., Norley, C.J.D., Frayne, R., Steinman, D.A., Rutt, B.K.: Characterization of common carotid artery blood-flow waveforms in normal human subjects. Physiol. Meas 20, 219–240 (1999)CrossRefGoogle Scholar
  11. 11.
    Ballyk, P.D., Steinman, D.A., Ethier, C.R.: Simulation of non-Newtonian blood-flow in an end-to-side anastomosis. Biorheology 31(5), 565–586 (1994)Google Scholar
  12. 12.
    Morsi, S.A., Alexander, A.J.: Investigation of particle trajectories in 2-phase flow systems. J. Fluid Mech. 55(2), 193–208 (1972)CrossRefMATHGoogle Scholar
  13. 13.
    Lübbe, A.S., Bergemann, C., Riess, H., Schriever, F., Reichardt, P., Possinger, K., Matthias, M., Dorken, B., Herrmann, F., Gurtler, R., Hohenberger, P., Haas, N., Sohr, R., Sander, B., Lemke, A.J., Ohlendorf, D., Huhnt, W., Huhn, D.: Clinical experiences with magnetic drag targeting: A phase I study with 4’-epidoxorubicin in 14 patients with advanced solid tumors. Cancer Res. 56(20), 4686–4693 (1996a)Google Scholar
  14. 14.
    Lübbe, A.S., Bergemann, C., Huhnt, W., Fricke, T., Riess, H., Brock, J.W., Huhn, D.: Cinical experiences with magnetic drug targeting: Tolerance and efficacy. Cancer Res. 56(20), 4694–4701 (1996b)Google Scholar
  15. 15.
    Alexiou, C., Schmid, R.J., Jurgons, R., Kremer, M., Wanner, G., Bergemann, C., Huenges, E., Nawroth, T., Arnold, W., Parak, F.G.: Targeting cancer cells: magnetic nanoparticles as drug carriers. Eur. Biophys. J. 35(5), 446–450 (2006)CrossRefGoogle Scholar
  16. 16.
    Torchilin, V. P.: Nanoparticulates as drug carriers. Imperial College Press, London (2006)CrossRefGoogle Scholar
  17. 17.
    Kenjereš, S.: Numerical analysis of blood flow in realistic arteries subjected to strong non-uniform magnetic fields. Int. J. Heat and Fluid Flow 29(3), 752–764 (2008)CrossRefGoogle Scholar
  18. 18.
    Haverkort, J.W., Kenjereš, S., Kleijn, C.R.: Magnetic particle motion in a Poiseuille flow. Phys. Rev. E 80(1), 1–12 (2009). Art. No. 016302CrossRefGoogle Scholar
  19. 19.
    Cohen Stuart, D.C., Kleijn, C.R., Kenjereš, S.: An efficient and robust method for Lagrangian magnetic particle tracking in fluid flow simulations on unstructured grids. Computer and Fluids 40(1), 188–194 (2011)CrossRefMATHGoogle Scholar
  20. 20.
    Rusli, N., Kueh, A.B.H., Kenjereš, S.: Magnetic field effects on 3D blood flow patterns of straight and stenotic arteries. Advanced Science Latters 19(9), 2690–2693 (2013)CrossRefGoogle Scholar
  21. 21.
    Haverkort, J.W., Kenjereš, S., Kleijn, C.R.: Computational simulations of magnetic particle capture in arterial flows. Ann. Biomed. Eng. 37(12), 2436–2448 (2009)CrossRefGoogle Scholar
  22. 22.
    Kenjereš, S., Righolt, B.W.: Simulations of magnetic capturing of drug carriers in the brain vascular system. Int. J. Heat and Fluid Flow 35(3), 68–75 (2012)CrossRefGoogle Scholar
  23. 23.
    Chauhan, A.J., Johnston, S.L.: Air pollution and infection in respiratory illness. Br. Med. Bull. 68, 95–112 (2003)CrossRefGoogle Scholar
  24. 24.
    Ayres, J., Maynard, R., Richards, R.: Air Pollution and Health, Air Pollution Reviews -vol. 3. Imperial College Press, London (2006)Google Scholar
  25. 25.
    Kleinstreuer, C., Zhang, Z., Donohue, J.F.: Targeted drug-aerosol delivery in the human respiratory system. Annu. Rev. Biomed. Eng. 10, 195–220 (2008)CrossRefGoogle Scholar
  26. 26.
    Grotberg, J. B.: Respiratory fluid mechanics. Phys. Fluids 23(021301), 1–15 (2011)Google Scholar
  27. 27.
    Dames, P., Gleich, B., Flemmer, A., Hajek, K., Seidl, N., Wiekhorst, F., Eberbeck, D., Bittmann, I., Bergemann, C., Weyh, T., Trahms, L., Rosenecker, J., Rudolph, C.: Targeted delivery of magnetic aerosol droplets to the lung. Nat. Nanotechnol. 2(8), 495–499 (2007)CrossRefGoogle Scholar
  28. 28.
    Menter, F.R., Langtry, R., Völker, S.: Transition modelling for general purpose CFD codes. Flow Turbulence and Combustion 77(1-4), 277–303 (2006)CrossRefMATHGoogle Scholar
  29. 29.
    Nicoud, F., Ducros, F.: Subgrid-scale stress modelling based on the square of the velocity gradient tensor. Flow Turbulence and Combustion 62, 183–200 (1999)CrossRefMATHGoogle Scholar
  30. 30.
    Colleti, F., et al.: private communication (2014)Google Scholar
  31. 31.
    Cheng, Y.S., Zhou, Y., Chen, B.T.: Particle deposition in a cast of human oral airways. Aerosol Sci. Technol. 31, 286–300 (1999)CrossRefGoogle Scholar

Copyright information

© The Author(s) 2015

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Transport Phenomena Section, Department of Chemical Engineering, Faculty of Applied SciencesDelft University of TechnologyDelftThe Netherlands
  2. 2.J. M. Burgers Centre for Fluid MechanicsDelftThe Netherlands

Personalised recommendations