Skip to main content

Impact of Heart Rate on Ventilation and Pulmonary Perfusion Associated Impedance Changes

  • Conference paper
  • First Online:
XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016

Part of the book series: IFMBE Proceedings ((IFMBE,volume 57))

  • 73 Accesses

Abstract

The potential of electrical impedance tomography (EIT) to assess perfusion changes in the lung has already been demonstrated in several studies. Methods like frequency domain filtering, principal component analysis or breath holding have been introduced. Since EIT is noninvasive and radiation-free, it depicts a promising supplement to current methods such as single photon emission computed tomography. In our study we investigated ventilation and pulmonary perfusion associated impedance changes as a function of heart rate in four healthy spontaneously breathing subjects. EIT measurements were conducted during physical exercises on a bicycle ergometer to get various heart rates. EIT data were acquired at three to four different heart rates in the 3rd and 5th intercostal space (ICS), respectively. Spirometry was performed simultaneously to determine tidal ventilation. A Fast Fourier Transform and frequency domain filtering were applied to separate ventilation from pulmonary perfusion signals. Ratios of ventilation and pulmonary perfusion related impedance changes ∆IV/∆IQ were calculated in a predefined region of interest within the different thorax planes. All subjects showed a higher gain in ∆IV/∆IQ dependent on heart rate in the 3rd ICS than in the 5th ICS. It was observed that in all subjects pulmonary perfusion associated impedance amplitudes increased stronger in the 5th ICS compared to the 3rd ICS. Minute volumes determined by spirometry (MVspiro) featured similar trends like minute variations calculated with ventilation related impedance amplitudes (MVEIT). EIT measurements could reliable conducted on spontaneously breathing subjects during physical exercises. Separation of ventilation and pulmonary perfusion associated impedance changes was successfully achieved by frequency domain filtering within the different thorax planes for all subjects.

The original version of this chapter was inadvertently published with an incorrect chapter pagination 1264–1269 and DOI 10.1007/978-3-319-32703-7_242. The page range and the DOI has been re-assigned. The correct page range is 1270–1275 and the DOI is 10.1007/978-3-319-32703-7_243. The erratum to this chapter is available at DOI: 10.1007/978-3-319-32703-7_260

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-32703-7_260

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. T. Muders, H. Luepschen, J. Zinserling et al. (2012) Tidal recruitment assessed by electrical impedance tomography and computed tomography in a porcine model of lung injury*. Crit Care Med 40:903-11

    Google Scholar 

  2. G. K. Wolf, C. Gomez-Laberge, J. S. Rettig et al. (2013) Mechanical ventilation guided by electrical impedance tomography in experimental acute lung injury. Crit Care Med 41:1296-304

    Google Scholar 

  3. J. Karsten, C. Grusnick, H. Paarmann et al. (2015) Positive end-expiratory pressure titration at bedside using electrical impedance tomography in post-operative cardiac surgery patients. Acta Anaesthesiol Scand 59:723-32

    Google Scholar 

  4. P. Blankman, D. Hasan, G. Erik et al. (2014) Detection of ‘best’ positive end-expiratory pressure derived from electrical impedance tomography parameters during a decremental positive end-expiratory pressure trial. Crit Care 18:R95

    Google Scholar 

  5. S. H. Alves, M. B. Amato, R. M. Terra et al. (2014) Lung reaeration and reventilation after aspiration of pleural effusions. A study using electrical impedance tomography. Ann Am Thorac Soc 11:186-91

    Google Scholar 

  6. I. Frerichs, S. Pulletz, G. Elke et al. (2009) Assessment of changes in distribution of lung perfusion by electrical impedance tomography. Respiration 77:282-91

    Google Scholar 

  7. C. A. Grant, T. Pham, J. Hough et al. (2011) Measurement of ventilation and cardiac related impedance changes with electrical impedance tomography. Crit Care 15:R37

    Google Scholar 

  8. J. M. Deibele, H. Luepschen, and S. Leonhardt (2008) Dynamic separation of pulmonary and cardiac changes in electrical impedance tomography. Physiol Meas 29:S1-14

    Google Scholar 

  9. B. M. Eyuboglu, B. H. Brown, and D. C. Barber (1989) In vivo imaging of cardiac related impedance changes. IEEE Eng Med Biol Mag 8:39-45

    Google Scholar 

  10. A. Vonk Noordegraaf, P. W. Kunst, A. Janse et al. (1998) Pulmonary perfusion measured by means of electrical impedance tomography. Physiol Meas 19:263-73

    Google Scholar 

  11. H. J. Smit, M. L. Handoko, A. Vonk Noordegraaf et al. (2003) Electrical impedance tomography to measure pulmonary perfusion: is the reproducibility high enough for clinical practice? Physiol Meas 24:491-9

    Google Scholar 

  12. I. Frerichs, J. Hinz, P. Herrmann et al. (2002) Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam CT imaging. IEEE Trans Med Imaging 21:646-52

    Google Scholar 

  13. J. B. Borges, F. Suarez-Sipmann, S. H. Bohm et al. (2012) Regional lung perfusion estimated by electrical impedance tomography in a piglet model of lung collapse. J Appl Physiol (1985) 112:225-36

    Google Scholar 

  14. D. T. Nguyen, A. Bhaskaran, W. Chik et al. (2015) Perfusion redistribution after a pulmonary-embolism-like event with contrast enhanced EIT. Physiol Meas 36:1297-309

    Google Scholar 

  15. H. Reinius, J. B. Borges, F. Freden et al. (2015) Real-time ventilation and perfusion distributions by electrical impedance tomography during one-lung ventilation with capnothorax. Acta Anaesthesiol Scand 59:354-68

    Google Scholar 

  16. S. Krueger-Ziolek, B. Schullcke, J. Kretschmer et al. (2015) Positioning of electrode plane systematically influences EIT imaging. Physiol Meas 36:1109-18

    Google Scholar 

  17. S. Pulletz, H. R. van Genderingen, G. Schmitz et al. (2006) Comparison of different methods to define regions of interest for evaluation of regional lung ventilation by EIT. Physiol Meas 27:S115-27

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sabine Krueger-Ziolek .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Krueger-Ziolek, S., Zhao, Z., Schullcke, B., Gong, B., Moeller, K. (2016). Impact of Heart Rate on Ventilation and Pulmonary Perfusion Associated Impedance Changes. In: Kyriacou, E., Christofides, S., Pattichis, C. (eds) XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016. IFMBE Proceedings, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-32703-7_243

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-32703-7_243

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32701-3

  • Online ISBN: 978-3-319-32703-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics