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Related Experiment Videos

Evaluation of an EIT reconstruction algorithm using finite difference human thorax models as phantoms.

Robert P Patterson1, Jie Zhang

  • 1Biomedical Engineering Institute, and Department of Physical Medicine and Rehabilitation, University of Minnesota, Minneapolis, MN 55455, USA. patte001@tc.umn.edu

Physiological Measurement
|June 19, 2003
PubMed
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Electrical Impedance Tomography (EIT) imaging of the thorax shows changes are less than the model, but linearly track resistivity changes. The Sheffield DAS-01P system best tracks lung changes, suggesting potential for physiological monitoring.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Physiological Monitoring

Background:

  • Electrical Impedance Tomography (EIT) is a non-invasive imaging technique.
  • Accurate modeling is crucial for validating EIT systems.
  • The Sheffield DAS-01P system is a specific EIT device for thoracic imaging.

Purpose of the Study:

  • To evaluate the Sheffield DAS-01P EIT system using a detailed human thorax model.
  • To quantify the system's ability to detect resistivity and structural changes in thoracic organs.
  • To assess the linearity and volume dependence of EIT imaging.

Main Methods:

  • A finite difference model of the human thorax (113,400 nodes) based on MRI images was created.
  • Simulated EIT data was generated using 16 electrode positions and sequential current injection.

Related Experiment Videos

  • The Sheffield filtered back projection algorithm reconstructed images from simulated voltage data.
  • Resistivity changes (1-40%) in lungs, ventricles, and atria were simulated and quantified.

    • Main Results:

    • EIT image changes were consistently lower than model resistivity changes but showed a near-linear relationship.
    • For a 40% resistivity change, the right lung showed 32% change, right ventricle 11%, and right atrium 5.5% in the ROI.
    • Simulated cardiac structural changes (end diastole to end systole) caused significant resistivity changes in the heart region.
    • The EIT algorithm demonstrated the closest tracking of resistivity changes in the lungs.

    Conclusions:

    • The Sheffield DAS-01P EIT system's reconstruction algorithm shows strong volume dependence.
    • The system most accurately tracks changes in the lungs compared to cardiac structures.
    • With appropriate scaling, the Sheffield DAS-01P EIT system shows promise for monitoring physiological changes in the thorax.