An Optimized Method for 3D Magnetic Navigation of Nanoparticles inside Human Arteries
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An Optimized Method for 3D Magnetic Navigation of Nanoparticles inside Human Arteries

Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

Abstract:

In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: CFD, CMA evolution strategy, DEM, magnetic navigation, spherical particles.

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References:


[1] Q. Pankhurst, J. Connolly, S. Jones, J. Dobson, Applications of magnetic nanoparticles in biomedicine, J. Phys. D: Appl. Phys., vol. 36, no. 13, pp. 167–181, 2003.
[2] M. Ramezanpour, S.S.W. Leung, K.H. Delgado-Magnero, B.Y.M. Bashe, J. Thewalt, D.P. Tieleman, Computational and experimental approaches for investigating nanoparticle-based drug delivery systems, Biochim. Biophys. Acta, vol. 1858, pp. 1688–1709, 2016.
[3] V.P. Podduturi, I.B. Magana, D.P. O’Neal, P.A. Derosa, Simulation of transport and extravasation of nanoparticles in tumors which exhibit enhanced permeability and retention effect, Com put. Methods Programs Biomed., vol. 112, pp. 58–68, 2013.
[4] J. Llandro, J.J. Palfreyman, A. Ionescu, C.H.W. Barnes, Magnetic biosensor technologies for medical applications: a review, Med. Biol. Eng. Comput., vol. 48, pp. 977–998, 2010.
[5] P. Babinec, A. Krafcik, M. Babincova, J. Rosenecker, Dynamics of magnetic particles in cylindrical halbach array: implications for magnetic cell separation and drug targeting, Med. Biol. Eng. Comput., vol. 48, pp. 745–753, 2010.
[6] D.H. Nquyen, J.S. Lee, J.H. Choi, K.M. Park, Y. Lee, K.D. Park, Hierarchical self-assembly of magnetic nanoclusters for theranostics: tunable size, enhanced magnetic resonance imagability, and controlled and targeted drug delivery, Acta Biometerialia, vol. 35, pp. 109–117, 2016.
[7] K. Widder, P. Marino, R. Morris, A. Senyei, Targeted Drugs, Wiley, New York, 1983.
[8] H.G. Weller, G. Tabor, H. Jasak, C. Fureby, A tensorial approach to computational continuum mechanics using object-oriented techniques, Comput. Phys., vol. 12, no. 6, pp. 620–631, 2010.
[9] P. Kennedy and R. Zheng, Flow Analysis of Injection Molds: Hanser, 2013.
[10] E.G. Karvelas, N.K. Lampropoulos, I.E. Sarris, A numerical model for aggregations formation and magnetic driving of spherical particles based on OpenFOAM, Comp. Methods Progr. Biomed., vol. 142, pp. 21–30, 2017.
[11] E.G. Karvelas, T.E. Karakasidis, I.E.Sarris, Computational analysis of paramagnetic spherical Fe3O4 nanoparticles under permanent magnetic fields, Comput. Mat. Sci., vol. 154, pp. 464-471, 2018.
[12] E.G. Karvelas, N.K. Lampropoulos, L. Benos, T.E. Karakasidis, I.E. Sarris, On the magnetic aggregation of Fe3O4 nanoparticles, Comp. Methods Progr. Biomed., DOI: 10.1016/j.cmpb.2020.105778
[13] B.K. Bharadvaj, R.F. Mabon, D.P. Giddens, Steady flow in a model of a human carotid bifurcation. part 1-Flow visualization. J. Biomech. vol. 15, pp. 349–362, 1982.
[14] N. Hansen, The CMA evolution strategy; a comparing review, Adv. Estim. Distrib. Algorithms, vol. 192, pp. 1769–1776, 2006.
[15] N.K. Lampropoulos, E.G. Karvelas, D.I. Papadimitriou, I.E. Sarris, Computational study of the optimum gradient magnetic field for the navigation of spherical particles into targeted areas, Journal of Physics: Conference Series vol. 637, no. 1, pp. 012038, 2015.
[16] N.K. Lampropoulos, E.G. Karvelas, T.E. Karakasidis, I.E. Sarris, Computational Study of the Optimum Gradient Magnetic Field for the Navigation of the Spherical Particles in the Process of Cleaning the Water from Heavy Metals, Procedia Engineering, vol. 162, pp. 77-82, 2016.
[17] N.K. Lampropoulos, E.G. Karvelas, D.I. Papadimitriou, T.E. Karakasidis, I.E. Sarris, Computational study of the effect of gradient magnetic field in navigation of spherical particles, Journal of Physics: Conference Series, vol. 931, no. 1, pp. 012014, 2017.