Maio 2014 vol. 1 num. 1 - 10th World Congress on Computational Mechanics

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Determination of Cardiac Ejection Fraction by Electrical Impedance Tomography using a Hybrid Heuristic Approach, a Simulation Study

Ribeiro, Marcos H. F. ; Santos, Rodrigo Weber dos ; Barra, Luis Paulo S. ; Peters, Franciane C. ;

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An important parameter to analyze the efficiency of the heart as a pump is Cardiac Ejection Fraction (EF), which is clinically highly correlated to the functional status of the heart. Diverse non invasive methods can be applied to measure EF, like Computer Tomography, Magnetic Resonance, Echocardiography, and others. Nevertheless, none of these techniques can be used to continuous monitoring of such parameter. On the other hand, electrical impedance tomography (EIT) may be applied to accomplish this goal. In addition, low cost and high portability are also EIT’s features that justify the research for solutions involving such technique to monitor EF. EIT consists in reconstruct images of the conductivity distribution of the interior of a conductor domain by applying electric currents and measuring electrical potential on the boundary of the body. Mathematically, EIT can be classified as a non-linear inverse problem. This work proposes a method for the continuous estimation of cardiac ejection fraction, addressing it as an optimization problem. The models used in our approach assume that recent two-dimensional magnetic resonance images of the patient are available, and use them to reduce the search space. Another important feature is the parametrization of the geometry of internal inclusions inside the domain, which also reduces the cost of the method. This work proposes a Hybrid Iterated Local Search (ILS) heuristic for EIT inverse problem using Levenberg-Marquardt Method as local search. Experiments are performed on two-dimensional images with synthetically generated data for electric potentials. Two different protocols for current injection are tested in such experiments and preliminary results are presented.

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Palavras-chave: Cardiac Ejection Fraction, Electrical Impedance Tomography, Inverse Problem, Iterated Local Search,

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DOI: 10.5151/meceng-wccm2012-19371

Referências bibliográficas
  • [1] M. Kim, K. Kim, and S. Kim, “Phase boundary estimation in two-phase flows with electrical impedance tomography,” Int. Comm. Heat Transfer, vol. 31, no. 8, pp. 1105– 1114, 2004.
  • [2] F. Trigo, R. Lima, and M. Amato, “Electrical impedance tomography using extended kalman filter,” vol. 51, no. 1, pp. 72–81, 2004.
  • [3] N. Polydorides, W. R. B. Lionheart, and H. McCann, “Krylov subspace iterative thechniques: On the brain activity with electrical impedance tomography,” vol. 21, no. 6, pp. 596–603, 2002.
  • [4] J. Seo, O. Kwon, H. Ammari, and E. Woo, “A mathematical model for breast cancer lesion estimation: Electrical impedance technique using ts2000 commercial system,” vol. 51, no. 11, pp. 1898–1906, 200
  • [5] F. Peters, L. Barra, and R. Santos, “Determination of cardiac ejection fraction by electrical impedance tomography - numerical experiments and viability analysis,” in Computational Science - ICCS 2009, ser. Lecture Notes in Computer Science, vol. 5544/2009. Springer Berlin / Heidelberg, 2009, pp. 819–828.[Online]. Available: http://www.springerlink.com/content/ln75256l546p5973
  • [6] L. P. S. Barra, F. C. Peters, C. P. Martins, and H. J. C. Barbosa, “Computational experiments in electrical impedance tomography,” in XXVII Iberian Latin American Congress on Computational Methods in Engineering, Bel´em, Brazil, 200
  • [7] L. P. S. Barra, R. W. Santos, F. Peters, E. P. Santos, and H. Barbosa, “Parallel computational experiments in electrical impedance tomography,” in 18th Symposium on Computer Architecture and High Performance Computing, vol. 1, Sociedade Brasileira de Computac¸ ão. Ouro Preto, Brazil: High Perfomance Computing in the Life Sciences, 2006, pp. 7–13.
  • [8] L. P. S. Barra, P. Mappa, S. Cardoso, and F. C. Peters, “Comparison of the computational performance of optimization algorithms in the solution of an inverse problem (in portuguese),” in VIII Simpósio de Mecˆanica Computacional - SIMMEC. Belo Horizonte, Brazil: PUC-Minas, junho 200
  • [9] F. C. Peters, L. P. S. Barra, and R.W. Santos, “Determination of cardiac ejection fraction by electrical impedance tomography,” in Medical Imaging, O. F. Erondu, Ed. InTech, 2011, pp. 253–270.
  • [10] C. T. Hsiao, G. Chahine, and N. Gumerov, “Application of a hybrid genetic/powell algorithm and a boundary element method to electrical impedance tomography,” vol. 173, pp. 433–454, 2001.
  • [11] C. Blanc and C. Schlick, “X-splines: a spline model designed for the end-user,” in Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, ser. SIGGRAPH ’95. New York, NY, USA: ACM, 1995, pp. 377–386.[Online]. Available: http://doi.acm.org/10.1145/218380.218488
  • [12] S. Grimnes and O. G. Martinsen, Bioimpedance and Bioelectricity Basics, Second Edition. Academic Press, 2008.
  • [13] C. Gabriel, S. Gabriel, and E. Corthout, “The dielectric properties of biological tissue: I. literature survey,” Physics in Medicine and Biology, vol. 41, no. 11, pp. 2231–2249, 1996.
  • [14] H. Bruder, B. Scholz, and K. Abraham-Fuchs, “The influence of inhomogeneous volume conductor models on the ecg and the mcg,” Physics in Medicine and Biology, vol. 39, no. 11, pp. 1949–1968, 1994.
  • [15] S. Rush, J. A. Abildskov, and McFeer, “Resistivity of body tissues at low frequencies,” Circulation research, vol. 12, pp. 40–50, 1963.
  • [16] D. Barber and A. Seagar, “Applied potential tomography,” Clin. Phys. Physiol. Meas., vol. 8, pp. 47–54, 1984.
  • [17] F. Yang and R. P. Patterson, “The contribution of the lungs to thoracic impedance measurements: a simulation study based on a high resolution finite difference model,” Physiological Measurement, vol. 28, no. 7, pp. S153–S161, 2007.
  • [18] H. Schwan and C. Kay, “Specific resistance of body tissues,” Circulation Research, vol. 4, no. 6, pp. 664–670, 1956.
  • [19] R. P. Patterson and J. Zhang, “Evaluation of an eit reconstruction algorithm using finite difference human thorax models as phantoms,” Physiological Measurement, vol. 24, no. 2, p. 467475, 2003.
  • [20] U. Baysal and E. B. M. , “Tissue resistivity estimation in the presence of positional and geometrical uncertainties,” Physics in Medicine and Biology, vol. 45, no. 8, p. 23732388, 2000.
  • [21] C. Brebbia, J. C. F. Telles, and L. C. Wrobel, Boundary Elements Techniques: Theory and Applications in Engineering. Springer-Verlag, 1984.
  • [22] L. P. S. Barra, F. C. Peters, and R. W. Santos, “Numerical experiments for the viability analysis of the determination of the cardiac ejection fraction by the electrical impedance tomography (in portuguese),” in XXIX CILAMCE - Congresso Ibero Latino Americano de M´etodos Computacionais em Engenharia, Maceió, Brasil, 2008.
  • [23] F. C. Peters and L. P. S. Barra, “A strategy for parametrization refinement in the solution of a geometric inverse problem,” in 3rd Southern Conference on Computational Modeling - MCSUL, 2009, pp. 136–142.
  • [24] K. Madsen, H. B. Nielsen, and O. Tingleff, Methods for Non-Linear Least Squares Problems (2nd ed.), 2004.
  • [25] H. R. Lourenco, O. C. Martin, and T. Stutzle, “Iterated local search,” Social Science Research Network, vol. 57, no. 513, p. 49, 2001.
  • [26] W. Press, S. Teukolsky, W. Vetterling, and Flannery, Numerical Recipes in Fortran77. Cambridge University Press, 1986.
  • [27] J. H. Holland, Hidden order: how adaptation builds complexity. Redwood City, CA, USA: Addison Wesley Longman Publishing Co., Inc., 1995.
  • [28] ——, Adaptation in Natural and Artificial Systems. University of Michigan Press, 1978.
  • [29] J. Herskovits, “Feasible direction interior-point technique for nonlinear optimization,” J. Optim. Theory Appl., vol. 99, no. 1, pp. 121–146, 1998.
  • [30] J. L. Bentley, “Multidimensional binary search trees used for associative searching,” Commun. ACM, vol. 18, no. 9, pp. 509–517, 1975.
  • [31] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd ed. The MIT Press, 2001.
  • [32] F. C. Peters and L. P. S. Barra, “Some numerical results on the influence of measurement strategies and load patterns in the eit inverse problem,” Journal of Physics: Conference Series, vol. 224, no. 1, p. 012145, 2010.
Como citar:

Ribeiro, Marcos H. F.; Santos, Rodrigo Weber dos; Barra, Luis Paulo S.; Peters, Franciane C.; "Determination of Cardiac Ejection Fraction by Electrical Impedance Tomography using a Hybrid Heuristic Approach, a Simulation Study", p. 3456-3475 . In: In Proceedings of the 10th World Congress on Computational Mechanics [= Blucher Mechanical Engineering Proceedings, v. 1, n. 1]. São Paulo: Blucher, 2014.
ISSN 2358-0828, DOI 10.5151/meceng-wccm2012-19371

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