Skip to main content
Log in

A Chicken Tissue Phantom for Studying an Electrical Impedance Tomography (EIT) System Suitable for Clinical Imaging

  • Original Paper
  • Published:
Sensing and Imaging: An International Journal Aims and scope Submit manuscript

Abstract

The study of practical phantoms is essential for assessing the reconstruction algorithms and instrumentation used in Electrical Impedance Tomography (EIT). Responses of saline phantoms with insulator inhomogeneities differ from the real tissue phantoms in several aspects. Also, it is difficult to reconstruct the actual resistivity of the insulator inhomogeneity in a saline background because of their large resistivity difference. A practical biological phantom consisting of two different materials with low resistivity difference is more suitable for impedance imaging studies. In order to demonstrate this, a chicken tissue phantom was developed to study the resistivity imaging in EIT. A 16-electrode array was placed inside the phantom tank filled with chicken muscle tissue paste and chicken tissue. A 1 mA, 50 kHz sinusoidal current was injected at the phantom boundary and the boundary potentials are measured using opposite current injection protocol. Resistivity images were reconstructed from the boundary data using Electrical Impedance and Diffuse Optical Reconstruction Software (EIDORS) and the reconstruction was evaluated by calculating the contrast parameters of the images. Results show that the resistivity of the chicken fat is successfully reconstructed with a proper background resistivity. Impedance spectroscopic studies show that the chicken tissue phantom can be suitably used to evaluate a multifrequency EIT system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Webster, J. G. (1990). Electrical impedance tomography. Adam Hilger Series of Biomedical Engineering. Adam Hilger, New York, USA.

  2. Holder, D. S. (2005). Electrical impedance tomography: Methods, history and applications. (Series in Medical Physics and Biomedical Engineering). Institute of Physics Publishing Ltd.

  3. Cheney, M., Isaacson, D., & Newell, J. C. (1999). Electrical impedance tomography, SIAM REVIEW. Society for Industrial and Applied Mathematics, 41(1), 85–101.

    MathSciNet  MATH  Google Scholar 

  4. Bayford, R. H. (2006). Bioimpedance tomography (electrical impedance tomography). Annual Review of Biomedical Engineering, 8, 63–91.

    Article  Google Scholar 

  5. Denyer, C. W. L. (1996). Electronics for real-time and three-dimensional electrical impedance tomographs. Ph.D. thesis, Oxford Brookes University.

  6. Huang, C. N., Yu, F. M., & Chung, H. Y. (2008). The scanning data collection strategy for enhancing the quality of electrical impedance tomography. IEEE Transactions on Instrumentation and Measurement, 57(6), 1193–1198.

    Google Scholar 

  7. Metherall, P. (1998). Three dimensional electrical impedance tomography of the human thorax. Ph.D. thesis, University of Sheffield.

  8. Bushberg, J. T., Seibert, J. A., Leidholdt, E. M., Jr., & Boone, J. M. (2001). The essential physics of medical imaging (2nd ed.). Lippincott Williams & Wilkins.

  9. Reifferscheid, F., Elke, G., Pulletz, S., Gawelczyk, B., Lautenschläger, I., Steinfath, M., et al. (2011). Regional ventilation distribution determined by electrical impedance tomography: Reproducibility and effects of posture and chest plane. Respirology, 16, 523–531. doi:10.1111/j.1440-1843.2011.01929.x

    Google Scholar 

  10. Fabrizi, L., McEwan, A., Oh, T., Woo, E. J., & Woo, D. S. (2009). An electrode addressing protocol for imaging brain function with electrical impedance tomography using a 16-channel semi-parallel system. Physiological Measurement, 30, S85–S101.

    Article  Google Scholar 

  11. Bagshaw, A. P., Liston, A. D., Bayford, R. H., Tizzard, A., Gibson, A. P., Tidswell, A. T., et al. (2003). Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method. NeuroImage, 20, 752–764.

    Article  Google Scholar 

  12. Murphy, D., Burton, P., Coombs, R., Tarassenko, L., & Rolfe, P. (1987). Impedance imaging in the newborn. Clinical Physics and Physiological Measurement, 8(Suppl. A), 131–140.

    Article  Google Scholar 

  13. Hinz, J., Neumann, P., Dudykevych, T., Andersson, L. G., Wrigge, H., Burchardi, H., et al. (2003). Regional ventilation by electrical impedance tomography: A comparison with ventilation scintigraphy in pigs. Chest, 124, 314–322.

    Article  Google Scholar 

  14. Noordegraaf, A. V., Faes, T. J. C., Janse, A., Marcus, J. T., Heethaar, R. M., Postmus, P. E., et al. (1996). Improvement of cardiac imaging in electrical impedance tomography by means of a new electrode configuration. Physiological Measurement, 17, 179–188.

    Article  Google Scholar 

  15. Hope, T. A., & Iles, S. E. (2004). Technology review: The use of electrical impedance scanning in the detection of breast cancer. Breast Cancer Research, 6, 69–74.

    Article  Google Scholar 

  16. Dickin, F., & Wang, M. (1996). Electrical resistance tomography for process applications. Measurement Science and Technology, 7, 247.

    Article  Google Scholar 

  17. Stephensona, D. R., Rodgersa, T. L., Manna, R., & York, T. A. (2009). Application of three-dimensional electrical impedance tomography to investigate fluid mixing in a stirred vessel. 13th European conference on mixing, London, April 14–17, 2009.

  18. Kotre, C. J. (1996). Subsurface electrical impedance imaging: Measurement strategy, image reconstruction and in vivo results. Physiological Measurement, 17, A197–A204 (printed in the UK).

  19. Linderholm, P., Marescot, L., Loke, M. H., & Renaud, P. (2008). Cell culture imaging using microimpedance tomography. IEEE Transactions on Biomedical Engineering, 55(1).

  20. Holder, D. S., Hanquan, Y., & Rao, A. (1996). Some practical biological phantoms for calibrating multifrequency electrical impedance tomography. Physiological Measurement, 17, A167–A177.

    Article  Google Scholar 

  21. Bera, T. K., & Nagaraju, J. (2009). A stainless steel electrode phantom to study the forward problem of electrical impedance tomography (EIT). Sensors & Transducers Journal, 104(5), 33–40.

    Google Scholar 

  22. Bera, T. K., & Nagaraju, J. (2011). Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography. Measurement, 44(3), 518–526. doi:10.1016/j.measurement.2010.11.015

    Article  Google Scholar 

  23. Webster, J. G. (1995). Medical instrumentation: Principle and design. Hoboken, NJ, USA: Wiley.

    Google Scholar 

  24. Bera, T. K., & Nagaraju, J. (2009). Studying the boundary data profile of a practical phantom for medical electrical impedance tomography with different electrode geometries. In O. Dössel, W. C. Schlegel (Eds.), Proceedings of the world congress on medical physics and biomedical engineering-2009, September 7–12, 2009, Munich, Germany. WC 2009, IFMBE proceedings 25/II (pp. 925–929). doi:10.1007/978-3-642-03879-2_258.

  25. Bera, T. K., & Nagaraju J. (2009). A study of practical biological phantoms with simple instrumentation for electrical impedance tomography (EIT). In Proceedings of IEEE International Instrumentation and Measurement Technology Conference (I 2 MTC2009), Singapore, May 5–7, 2009 (pp. 511–516). doi:10.1109/IMTC.2009.5168503.

  26. Bera, T. K., Nagaraju, J. (2010). A multifrequency constant current source for medical electrical impedance tomography. In Proceedings of the IEEE International Conference on Systems in Medicine and Biology 2010 (IEEE ICSMB 2010), Kharagpur, India, December 16–18, 2010 (pp. 290–295). doi:10.1109/ICSMB.2010.5735387.

  27. Bera, T. K., & Nagaraju, J. (2009). A simple instrumentation calibration technique for electrical impedance tomography (EIT) using a 16-electrode phantom. In Proceedings of the fifth annual IEEE Conference on Automation Science and Engineering (IEEE CASE 2009), Bangalore, August 22–25, 2009 (pp 347–352). doi:10.1109/COASE.2009.5234117.

  28. Bera, T. K., & Nagaraju, J. (2009). A reconfigurable practical phantom for studying the 2-D electrical impedance tomography (EIT) using a fem based forward solver. 10th International conference on biomedical applications of Electrical Impedance Tomography (EIT 2009), School of Mathematics, The University of Manchester, UK, June 16–19, 2009.

  29. Bera, T. K., & Nagaraju, J. (2009). A FEM-based forward solver for studying the forward problem of electrical impedance tomography (EIT) with a practical biological phantom. In Proceedings of IEEE International Advance Computing Conference’ 2009 (IEEE IACC-2009), Patiala, Punjab, India, March 6–7, 2009 (pp. 1375–1381). doi:10.1109/IADCC.2009.4809217.

  30. Qiao, G., Wang, W., Wang, L., He, Y., Bramer, B., & Al-Akaidi, M. (2007). Investigation of biological phantom for 2D and 3D breast EIT images. 13th International conference on electrical bioimpedance and the 8th conference on electrical impedance tomography, IFMBE proceedings, 2007 (Vol. 17, Part 10, pp. 328–331). doi:10.1007/978-3-540-73841-1_86.

  31. Soni, N. K., Dehghani, H., Hartov, A., & Paulsen, K. D. (2003). A novel data calibration scheme for electrical impedance tomography. Physiological Measurement, 24, 421–435.

    Article  Google Scholar 

  32. Conway, J. (1987). Electrical impedance tomography for thermal monitoring of hyperthermia treatment: An assessment using in vitro and in vivo measurements. Clinical Physics and Physiological Measurement, 8(Suppl. A), 141–146.

    Article  Google Scholar 

  33. Goharian, M., Soleimani, M., Jegatheesan, A., Chin, K., & Moran, G. R. (2008). A DSP based multi-frequency 3D electrical impedance tomography system. Annals of Biomedical Engineering, 36(9), 1594–1603.

    Article  Google Scholar 

  34. Ahn, S., Jun, S. C., Seo, J. K., Lee, J., Woo, E. J., & Holder, D. (2010). Frequency-difference electrical impedance tomography: Phantom imaging experiments. Journal of Physics: Conference Series, 224, 012152.

    Article  Google Scholar 

  35. Griffiths, H. (1988). A phantom for electrical impedance tomography. Clinical Physics and Physiological Measurement, 9(Suppl. A), 15–20.

    Article  Google Scholar 

  36. Schneider, I. D., Kleffel, R., Jennings, D., & Courtenay, A. J. (2007). Design of an electrical impedance tomography phantom using active elements. Medical and Biological Engineering and Computing, 38(4), 390–394. doi:10.1007/BF02345007.

    Article  Google Scholar 

  37. Woo, E. J. (1990). Finite element method and reconstruction algorithm in electrical impedance tomography. Ph.D. thesis, University of Wisconsin Madison, Madison, Wisconsin.

  38. Jones, O. C., Lin, J. T., Ovacik, L., & Shu, H. (1993). Impedance imaging relative to gas–liquid systems. Nuclear Engineering and Design, 141, 159–176.

    Article  Google Scholar 

  39. Cho, K. H., Kim, S., & Lee, Y. J. (1999). A fast EIT image reconstruction method for the two-phase flow visualization. International Communications in Heat and Mass, 26, 637.

    Article  Google Scholar 

  40. Lionheart, W. R. B. (2004). EIT reconstruction algorithms: Pitfalls, challenges and recent developments. Physiological Measurement, 25, 125–142 (review article).

    Article  Google Scholar 

  41. Graham, B. M. (2007). Enhancements in electrical impedance tomography (EIT) image reconstruction for 3D lung imaging. Ph.D. thesis, University of Ottawa.

  42. Yorkey, T. J. (1986). Comparing reconstruction methods for electrical impedance tomography. Ph.D. thesis, University of Wisconsin at Madison, Madison, WI.

  43. Reddy, J. N. (2006) An introduction to the finite element method (3rd ed.), 2nd reprint. TATA McGraw-Hill Publication Co. Ltd.

  44. Biswas, S. K., Rajan, K., & Vasu, R. M. (2010). Interior photon absorption based adaptive regularization improves diffuse optical tomography. Proceedings of SPIE, 7546, 754611–754616. doi:10.1117/12.853421.

    Article  Google Scholar 

  45. Arridge, S. R. (1999). Optical tomography in medical imaging. Topical Review, Inverse Problems, 15, R41–R93.

    Article  MathSciNet  MATH  Google Scholar 

  46. Grootveld, C. J. (1996). Measuring and modeling of concentrated settling suspensions using electrical impedance tomography. Ph.D. thesis, Delft University of Technology, The Netherlands.

  47. Soleimani, M., Yalavarthy, P. K., & Dehghani, H. (2010). Helmholtz-type regularization method for permittivity reconstruction using experimental phantom data of electrical capacitance tomography. IEEE Transactions on Instrumentation and Measurement, 59(1), 78–83.

    Article  Google Scholar 

  48. Soleimani, M., & Lionheart, W. R. B. (2005). Nonlinear image reconstruction in electrical capacitance tomography using experimental data. Measurement Science and Technology, 16(10), 1987–1996.

    Article  Google Scholar 

  49. Chan, T. F., & Tai, X. C. (2004). Level set and total variation regularization for elliptic inverse problems with discontinuous coefficients. Journal of Computational Physics, 193(1), 40–66.

    Article  MathSciNet  MATH  Google Scholar 

  50. Wei, D. H., & Yu-Long, M. (2002). New regularization method in electrical impedance tomography. Journal of Shanghai University (English Edition), 6(3), 211–215.

    Article  Google Scholar 

  51. Rosell, J., & Riu, P. (1992). Common-mode feedback in electrical impedance tomography. Clinical Physics and Physiological Measurement, 13(4), 11–14.

    Article  Google Scholar 

  52. Barsoukov, E., & Macdonald, J. R. (2005). Impedance spectroscopy: Theory, experiment, and applications (2nd ed.). Wiley-Interscience.

  53. Data sheet, MAX038-high-frequency waveform generator. Maxim Integrated Products, Inc., CA.

  54. Data sheet, AD829—high performance video Op Amp. Analog Devices, Inc.

  55. Polydorides, N., & Lionheart, W. R. B. (2002). A Matlab toolkit for three-dimensional electrical impedance tomography: A contribution to the electrical impedance and diffuse optical reconstruction software project. Measurement Science and Technology, 13, 1871–1883.

    Article  Google Scholar 

  56. Vauhkonen, M., Lionheart, W. R. B., Heikkinen, L. M., Vauhkonen, P. J., & Kaipio, J. P. (2001). A MATLAB package for the EIDORS project to reconstruct two dimensional EIT images. Physiological Measurement, 22, 107–111.

    Article  Google Scholar 

  57. Kanmani, B., Vasu, R. M., & Institute of Physics Publishing Physics in Medicine and Biology. (2005). Diffuse optical tomography using intensity measurements and the a priori acquired regions of interest: Theory and simulations. Physics in Medicine and Biology, 50, 247–264.

    Article  Google Scholar 

  58. Reyes, M., Malandain, G., Koulibaly, P. M., González-Ballester, M. A., & Darcourt, J. (2007). Model-based respiratory motion compensation for emission tomography image reconstruction. Physics in Medicine and Biology, 52, 3579–3600.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. Nagaraju.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bera, T.K., Nagaraju, J. A Chicken Tissue Phantom for Studying an Electrical Impedance Tomography (EIT) System Suitable for Clinical Imaging. Sens Imaging 12, 95–116 (2011). https://doi.org/10.1007/s11220-011-0063-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11220-011-0063-4

Keywords

Navigation