Sectorial bio impedance spectroscopy for monitoring and differential diagnostic of lung pathologies

• Applicants: Professor Dr. Michael Czaplik; Professor Dr.-Ing. Steffen Leonhardt
• Subject Area: Medical Physics, Biomedical Technology ; Anaesthesiology
• Term: from 2014 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 247522162

In the intensive care unit (ICU), respiratory complications occur with high incidence and great variability. Early detection and differentiation of lung pathologies (pneumonia, lung edema, etc.) is necessary for a successful treatment. However, existing technologies such as computed tomography, chest x-ray or blood culture are potentially harming to the patient, resource-consuming, unspecific and not suitable for continuous monitoring. The goal of this research project is to prove the scientific foundation, which was dealt with in preliminary work, in an experimental animal study for future differential diagnostics of the lung and long term monitoring of ICU patients at the bedside. To achieve this, the technologies bio impedance spectroscopy (BIS) and electrical impedance tomography (EIT) were combined in a preliminary project. While BIS allows the spectroscopic analysis of the thorax in a frequency region of, for example 10 kHz to 1 MHz, EIT is capable of providing spatially resolved images with high temporal resolution. The usage of a multi-channel BIS measurement setup allows the analysis of arbitrary, three dimensional electrode placements; by using a novel, partially invasive electrode setup using eletrodes inside the trachea, "sectoral BIS" measurements seem to be possible. In a simulation study, specific electrode positions, which focus on certain lung regions, were identified. Additionally, dispersion behavior of different lung pathologies was examined ex-vivo in lung cadavers. Here, based on all collected BIS-data, lung edema differs clearly from haematothorax. The next step is to validate these specific scientific results in an experimental animal trial. For this, different lung pathologies will be induced in a large animal model, while EIT and sectorial BIS measurements are performed in parallel. The goal of a subsequent data analysis is the identification of features that allow robust classification lung pathologies in specific regions. In addition to an early detection of respiratory complications, the potential of predicting the progression of disease will be evaluated.

• DFG Programme: Research Grants