J. Osypka. EIT sensitivity analysis of local pulmonary blood flow in front of realistic background tissue distributions in a porcine model. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Bachelorarbeit. 2019
Electrical Impedance Tomography (EIT) is a radiation-free and non-invasive imaging method suitable for monitoring lung function at the bedside. The interest for EIT in the medical community is grounded in the potential ability to monitor not only pulmonary ventilation, but also pulmonary perfusion. EIT is already a well-established method for monitoring pulmonary ventilation and is currently in a research state for monitoring pulmonary perfusion. The successful simultaneous monitoring of both of these physiological processes would assist in the diagnosis of pulmonary diseases as well as aid in the optimization of mechanical ventilator settings during recruitment maneuvers. This is especially important for patients who’s lungs demonstrate an imbalance of pulmonary perfusion and ventilation, such as those diagnosed with Acute Respiratory Distress Syndrome (ARDS). A significant problem with monitoring pulmonary perfusion with EIT is the influence that the amount of electrical contrast between blood and the background tissue has on the sensitivity of EIT measurements. Therefore, the goal of this thesis was to analyse and quantify the effect that various realistic background tissues have on sensitivity, in response to a local blood volume change. To achieve this goal, EIT forward simulations were performed on three porcine FEM models representing various lung health states: healthy lungs, single-side ventilated lungs, and collapsed lungs. Additionally, each model was separately simulated using pulmonary meshes with a homogenous uniform conductivity or with a realistic heterogenous conductivity distribution. The FEM models were generated from the porcine CT data. Highly conductive spheres (110% of background tissue’s conductivity) were integrated into the pulmonary meshes of each state to simulate a local change in blood volume and therefore a local relative increase in conductivity. The results of the forward simulation were used to calculate the sensitivity to the blood volume changes for each model. Three expectations were formulated and investigated for the sensitivity results. The first stated that pulmonary regions in the proximity of the electrode belt should be more sensitive than regions close to the base or apex of the lung. The results of the simulations were in agreement with this expectation. The second expectation stated that, in comparing the realistic and homogenous pulmonary meshes within individual states, a general difference in spatial sensitivity distributions between the two types of pulmonary tissue mesh should be evident. Additionally the realistic models should be cumulatively less sensitive than the homogenous models. This expectation was also supported by the results. The final expectation was that regions of high conductivity (collapsed lung areas) should be less sensitive than regions of high conductivity. However, the results’ accordance with the third expectation varied from state to state. To model a clinical scenario, an additional comparison between varying background tissues was made to highlight the effect that background tissue might have on sensitivity, and therefore influence the reconstructed images viewed by a physician, evaluating lung function before and after recruitment maneuvers. It was found that by simply changing the background tissue from a well ventilated lung to a collapsed lung in a dorsal region at the electrode belt level, that there was a difference in sensitivity of about 0.0135 mV /S. In a different dorsal lung region at the electrode belt level, a change from collapsed pulmonary tissue to well ventilated pulmonary tissue caused a difference in sensitivity of about 0.0200 mV /S.