Chest trauma has a significant relevance on outcome after severe trauma. Clinically, impaired lung function typically occurs within 72 hours after trauma. However, the underlying pathophysiological mechanisms are still not fully elucidated. Therefore, we aimed to establish an experimental long-term model to investigate physiological, morphologic and inflammatory changes, after severe trauma. Male pigs (sus scrofa) sustained severe trauma (including unilateral chest trauma, femur fracture, liver laceration and hemorrhagic shock). Additionally, non-injured animals served as sham controls. Chest trauma resulted in severe lung damage on both CT and histological analyses. Furthermore, severe inflammation with a systemic increase of IL-6 (p = 0.0305) and a local increase of IL-8 in BAL (p = 0.0009) was observed. The pO2/FiO2 ratio in trauma animals decreased over the observation period (p < 0.0001) but not in the sham group (p = 0.2967). Electrical Impedance Tomography (EIT) revealed differences between the traumatized and healthy lung (p < 0.0001). In conclusion, a clinically relevant, long-term model of blunt chest trauma with concomitant injuries has been developed. This reproducible model allows to examine local and systemic consequences of trauma and is valid for investigation of potential diagnostic or therapeutic options. In this context, EIT might represent a radiation-free method for bedside diagnostics.

Ubiquitous knowledge of bladder volume is of great interest to patients whose perception of bladder volume is impaired. A promising approach to provide frequent bladder volume estimates to the patient are automatic and noninvasive measurements by electrical impedance tomography (EIT). Previous studies have shown a linear correlation of abdominal electrical impedance and bladder volume. In this article, we present two methods to extract a volume estimate from EIT measurements. One method is based on the global impedance from a reconstructed image, the second method is based on a singular value decomposition of the raw voltage measurement vector. A performance evaluation in presence of noise is performed.

Electrical impedance tomography (EIT) is a radiation-free technique generating cross-sectional images of the lung. EIT visualizes global and regional ventilation by illustrating the distribution of electrical bioimpedance. With an electrode belt around the patient's thorax, rotating injection-couples of a harmless alternating current allow voltage measurement of the remaining electrodes. This enables the reconstruction of a tomogram with highly dynamic changes within ventilation. We report on a female six-year-old patient with cystic fibrosis and complete destruction of the upper and middle lobe of the right lung. Lobectomy, a rare therapeutic option in patients with cystic fibrosis that needs to be considered in cases of severe localized destruction, was performed. We show a pre- and postoperative documentation of static (radiology) and dynamic investigation tools (spirometry) in correlation with EIT as a new non-invasive and radiation-free diagnostic tool for this patient group.

A new prototype of a multi-frequency electrical impedance tomography system is presented. The system uses a field-programmable gate array as a main controller and is configured to measure at different frequencies simultaneously through a composite waveform. Both real and imaginary components of the data are computed for each frequency and sent to the personal computer over an ethernet connection, where both time-difference imaging and frequency-difference imaging are reconstructed and visualized. The system has been tested for both time-difference and frequency-difference imaging for diverse sets of frequency pairs in a resistive/capacitive test unit and in self-experiments. To our knowledge, this is the first work that shows preliminary frequency-difference images of in-vivo experiments. Results of time-difference imaging were compared with simulation results and shown that the new prototype performs well at all frequencies in the tested range of 60 kHz–960 kHz. For frequency-difference images, further development of algorithms and an improved normalization process is required to correctly reconstruct and interpreted the resulting images.