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Biocybernetics and Biomedical Engineering

Tytuł artykułu

Magnetic navigation and tracking of multiple ferromagnetic microrobots inside an arterial phantom setup for MRI guided drug therapy

Autorzy Kumar, N.  Verma, V.  Behera, L. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
EN Magnetic steering of ferromagnetic microrobots facilitates active drug targeting and minimally invasive treatment of deep seated tumour cells. Several techniques for magnetic steering of nanostructured single microrobot in human vasculature exist but literatures on multirobot navigation are scarce. In the current work, preliminary experimental validation of a novel magnetic navigation model for multiple ferromagnetic microrobots is performed inside a bifurcated arterial phantom apparatus. The proposed model includes the formation of a single linear assembly of ferromagnetic microrobots inside the arterial setup placed under a magnetic field. This field is intended to mimic the magnetic field generated by a Magnetic Resonance Imaging (MRI) device which finds application in targeted drug therapy. The linear assembly process was studied with the help of Newtonian dynamics simulation including dipole–dipole and near field forces. As, the assembly was found to be structurally intact in a pulsatile flow, its simulated trajectory was controlled by manipulating a single microrobot present in the middle of the assembly. The trajectory convergence algorithm used for this purpose includes a fuzzy logic based nonlinear ‘‘Proportional-Integral-Derivative’’ (PID) control scheme with magnetic field gradient as its control input. Since most of the modern MRI devices are based on PID controller for manipulation of magnetic gradients, the proposed fuzzy PID based control scheme can easily be interfaced with these devices for the intended application.
Słowa kluczowe
PL mikrorobot wielokrotny   dynamika newtonowska   nawigacja magnetyczna  
EN multiple microrobot   Newtonian dynamics   magnetic navigation  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 347--356
Opis fizyczny Bibliogr. 36 poz., rys., tab., wykr.
autor Kumar, N.
  • Department of Materials Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India
autor Verma, V.
  • Department of Materials Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India; Centre for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India
autor Behera, L.
  • Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016, India,
[1] Ricotti L, Menciassi A. Nanotechnology in biorobotics: opportunities and challenges. J Nanopart Res 2015;17:84.
[2] Nelson B, Kaliakatsos IK, Abbott JJ. Microrobots for minimally invasive medicine. Annu Rev Biomed Eng 2010;12:55–85.
[3] Freitas Jr RA. Nanomedicine: basic capabilities, vol. 1. Georgetown, TX: Landes Bioscience; 1999.
[4] Chitra K, Annadurai G. Rapid capture and exemplary detection of clinical pathogen using surface modified fluorescent silica coated iron oxide nanoparticles. Biocybern Biomed Eng 2014;34:230–7.
[5] Ummat A, Dubey A, Sharma G, Mavroidis C. Bionanorobotics: state of the art and future challenges. Boca Raton, FL: CRC; 2006.
[6] Sitti M. Miniature devices: voyage of the microbots. Nature 2009;458:1121–2.
[7] Rowhanimanesh A, Akbarzadeh MRT. Control of low-density liproprotein concentration in the arterial wall by proportional drug encapsulated nanoparticles. IEEE Trans Nanobiosci 2012;11:394–401.
[8] Masuda K. Development of a drug delivery system using microcapsules with ultrasound. Biocybern Biomed Eng 2011;31:23–32.
[9] Lenaghan SC, Wang Y, Xi N, Fukuda T, Tarn T, Hamel WR, et al. Grand challenges in bioengineered nanorobotics for cancer therapy. IEEE Trans Biomed Eng 2013;60:667–73.
[10] Xing R, Ashwinkumar AB, Wang S, Sun X, Liu G, Hou YL, et al. Hollow iron oxide nanoparticles as multidrug resistant drug delivery and imaging vehicles. Nano Res 2013;6:1–9.
[11] Kim PSS, Becker A, Ou Y, Julius AA, Kim MJ. Imparting magnetic dipole heterogeneity to internalized iron oxide nanoparticles for microorganism swarm control. J Nanopart Res 2015;17:144.
[12] Yan X, Zhou Q, Yu TXJ, Deng Y, Tang T, Feng Q, et al. Magnetite nanostructured porous hollow helical microswimmers for targeted delivery. Adv Funct Mater 2015;25:5333.
[13] Ricotti L, Cafarelli A, Lacovacci V, Vannozzi L, Meniassi A. Advanced micro-nano-bio systems for future targeted therapies. Curr Nanosci 2015;11:144–60.
[14] Vartholomeos P, Fruchard M, Ferreira A, Mavroidis C. MRI-guided nanorobotic systems for therapeutic and diagnostic applications. Annu Rev Biomed Eng 2011;13:157–84.
[15] Matheieu JB, Beaudoin G, Martel S. Method of propulsion of a ferromagnetic core in the cardiovascular system through magnetic gradients generated by an MRI system. IEEE Trans Biomed Eng 2006;53:292–9.
[16] Arcese L, Fruchard M, Ferreira A. Endovascular magnetically guided robots: navigation, modelling and optimization. IEEE Trans Biomed Eng 2012;59:977–87.
[17] Ghanbari A, Chang PH, Nelson BJ, Choi H. Magnetic actuation of a cylindrical microrobot using time-delay-estimation closed-loop control: modeling and experiments. Smart Mater Struct 2014;23:35013–25.
[18] Tamaz S, Gourdeau R, Chanu A, Mathieu JB, Martel S. Real-time MRI based control of a ferromagnetic core for endovascular navigation. IEEE Trans Biomed Eng 2008;55:1854–63.
[19] Arcese L, Cherry A, Fruchard M, Ferreira A. Dynamic behavior investigation for trajectory control of a microbot in blood vessels. Proceeding of the IEEE International Conference on Intelligent Robots and Systems; 2010. pp. 5774–9.
[20] Mitra A, Behera L. Development of fuzzy sliding mode controller with adaptive tuning technique for a MRI guided robot in the human vasculature. Proceedings of the IEEE International Conference on Industrial Informatics; 2015.
[21] Mellal L, Belharet K, Folio D, Ferreira A. Optimal structure of particles-based superparamagnetic microrobots: application to MRI guided targeted drug therapy. J Nanopart Res 2015;17:64.
[22] Cheang UK, Meshkati F, Kim H, Lee K, Fu HC, Kim MJ. Versatile microrobotics using simple modular subunits. Sci Rep 2016;6:30472.
[23] Cheang UK, Meshkati F, Kim D, Kim MJ, Fu HC. Minimal geometric requirements for micropropulsion via magnetic rotation. Phys Rev E 2014;90:033007.
[24] Tam CW. The drag on a cloud of spherical particles in low Reynolds number flow. J Fluid Mech 1969;38:537–46.
[25] Srivastava VP. Particle-fluid suspension model of blood flow through stenotic vessels with applications. Int J Bio-Med Comp 1995;38:141–54.
[26] Odenbach S. Colloidal magnetic fluids: basics, development and application of ferrofluids. Lect Notes Phys, vol. 763. Springer; 2009.
[27] Chunha FR. Hydrodynamic dispersion in suspensions [PhD thesis]. Cambridge, UK: Dept. of Applied Mathematics and Theoretical Physics, Cambridge University; 2001.
[28] Gontijo RG. Micromechanics and microhydrodynamics of magnetic suspensions [PhD thesis]. Brazil: University of Brasilia; 2013.
[29] Bordas R, Seshadhri S, Janiga G, Skalej M, Thevenin D. Experimental validation of numerical simulations on a cerebral aneurysm phantom model. Interv Med Appl Sci 2012;4:193–205.
[30] Amundsen BH, Wisloff U, Helgerud J, Hoff J, Slordahl SA. Ultrasound recorded axillary artery blood flow during elbow- flexion exercise. Med Sci Sports Exerc 2002;34:1288–93.
[31] Vartholomeos P, Mavroidis C. Simulation platform for self- assembly structures in MRI-guided nanorobotic drug delivery systems. Proceedings of the IEEE International Conference on Robotics and Automation; 2010. p. 5594–600.
[32] Vartholomeos P, Mavroidis C. In silico studies of magnetic microparticle aggregations in fluid environments for MRI-guided drug delivery. IEEE Trans Biomed Eng 2012;59:3028–38.
[33] Reich FA, Stahn O, Muller WH. The magnetic field of a permanent hollow cylindrical magnet. Continuum Mech Thermodyn 2016;28:1435–44.
[34] Ibrahim AAS. Nonlinear PID controller design using fuzzy logic. IEEE Melecon 2002;595–9.
[35] Takagi T, Sugeno M. Fuzzy identification of systems and its applications to modelling and control. IEEE Trans Sys Man Cybern 1985;15:116–32.
[36] Figurredo RJPD, Chen G. Nonlinear feedback control systems: an operator theory approach. New York: Academic; 1993.
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-c96d552e-e594-4500-8e1d-fe82e1cf184c
DOI 10.1016/j.bbe.2017.04.002