Journal of Clinical Monitoring and Computing

, Volume 32, Issue 4, pp 753–761 | Cite as

Ventilation inhomogeneity in obstructive lung diseases measured by electrical impedance tomography: a simulation study

  • B. SchullckeEmail author
  • S. Krueger-Ziolek
  • B. Gong
  • R. A. Jörres
  • U. Mueller-Lisse
  • K. Moeller
Original Research


Electrical impedance tomography (EIT) has mostly been used in the Intensive Care Unit (ICU) to monitor ventilation distribution but is also promising for the diagnosis in spontaneously breathing patients with obstructive lung diseases. Beside tomographic images, several numerical measures have been proposed to quantitatively assess the lung state. In this study two common measures, the ‘Global Inhomogeneity Index’ and the ‘Coefficient of Variation’ were compared regarding their capability to reflect the severity of lung obstruction. A three-dimensional simulation model was used to simulate obstructed lungs, whereby images were reconstructed on a two-dimensional domain. Simulations revealed that minor obstructions are not adequately recognized in the reconstructed images and that obstruction above and below the electrode plane may result in misleading values of inhomogeneity measures. EIT measurements on several electrode planes are necessary to apply these measures in patients with obstructive lung diseases in a promising manner.


Electrical impedance tomography Ventilation inhomogeneity Obstructive lung diseases Simulation study 



This work has been partially supported by the Federal Ministry of Education and Research (BMBF) under Grant No. 03FH038I3 (MOSES).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

This article does not contain any studies with human participant performed by any of the authors.


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Institute of Technical MedicineFurtwangen UniversityVS-SchwenningenGermany
  2. 2.Department of RadiologyLudwig-Maximilians-UniversitätMunichGermany
  3. 3.Institute and Outpatient Clinic for Occupational, Social and Environmental MedicineLudwig-Maximilians-UniversitätMunichGermany

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