Electrical Impedance Tomography and its Perspectives in Intensive Care Medicine

MEFS - MIND electrical impedance tomography forward solver

Electrical impedance tomography (EIT) offers a possibility of realizing of a low cost and safe modality for clinically monitoring patients being treated with mechanical ventilation. However, image reconstruction algorithm employed at different clinical or research settings varies from one to another, which in turn makes interpretation of regional ventilation across institutions difficult. Seeing the lack of a standardized algorithm, GREIT (Graz consensus Reconstruction algorithm for EIT) was proposed lately in an attempt to develop a unified EIT image reconstruction algorithm. To assess GREIT, an anatomically-detailed electrical model of the thorax is indispensable. In view of this need, we describe a high resolution, image-based electrical thoracic modeling software environment, named MEFS (MIND EIT Forward Solver). The software environment utilizes anatomically realistic geometry of the thorax, allows placing electrode of any shape interactively, and yields the detailed field information in the simulated volume. The goals of the development of MEFS are: 1) to generate electrical measurements needed for EIT image reconstruction, 2) to provide a platform to compare various EIT reconstruction algorithms.