Multi-frequency time-difference complex conductivity imaging of canine and human lungs using the KHU Mark1 EIT system

Jihyeon Kuen, Eung Je Woo, Jin Keun Seo

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21 Citations (Scopus)

Abstract

We evaluated the performance of the lately developed electrical impedance tomography (EIT) system KHU Mark1 through time-difference imaging experiments of canine and human lungs. We derived a multi-frequency time-difference EIT (mftdEIT) image reconstruction algorithm based on the concept of the equivalent homogeneous complex conductivity. Imaging experiments were carried out at three different frequencies of 10, 50 and 100 kHz with three different postures of right lateral, sitting (or prone) and left lateral positions. For three normal canine subjects, we controlled the ventilation using a ventilator at three tidal volumes of 100, 150 and 200 ml. Three human subjects were asked to breath spontaneously at a normal tidal volume. Real- and imaginary-part images of the canine and human lungs were reconstructed at three frequencies and three postures. Images showed different stages of breathing cycles and we could interpret them based on the understanding of the proposed mftdEIT image reconstruction algorithm. Time series of images were further analyzed by using the functional EIT (fEIT) method. Images of human subjects showed the gravity effect on air distribution in two lungs. In the canine subjects, the morphological change seems to dominate the gravity effect. We could also observe that two different types of ventilation should have affected the results. The KHU Mark1 EIT system is expected to provide reliable mftdEIT images of the human lungs. In terms of the image reconstruction algorithm, it would be worthwhile including the effects of three-dimensional current flows inside the human thorax. We suggest clinical trials of the KHU Mark1 for pulmonary applications.

Original languageEnglish
Pages (from-to)S149-S164
JournalPhysiological measurement
Volume30
Issue number6
DOIs
Publication statusPublished - 2009

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Physiology
  • Biomedical Engineering
  • Physiology (medical)

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