Systolic Time Intervals Measured by Electrical Impedance Tomography (EIT)

Electrical Impedance Tomography (EIT) is a non-invasive and low-cost functional imaging technique that measures thoracic impedance. Until now, it was primarily used to reveal respirationrelated changes in the lungs. However, recent work has shown the feasibility of using this technology to monitor hemodynamic parameters. In particular, mean arterial blood pressure can be estimated via EIT, given that the timing of the aortic valve opening is available. This Master’s thesis aims at overcoming this limitation by investigating the possibility of measuring the aortic valve opening directly via EIT. Cardiac EIT data were recorded on pigs and humans in apnea. In order to estimate the aortic valve opening, three different approaches were tested. Various questions that arose from the results obtained led to an extension of the scope of this thesis, in which the origin of cardiac EIT signals was investigated thoroughly. For this purpose, MRI and EIT data were recorded and analyzed in a comparative study. Solely one of the three approaches suggested shows partly promising results for an estimate of the heart valve opening. The latter is based on the assumption that the ventricular impedance is proportional to blood volume so that its derivative gives an estimate for blood flow. For two subjects a good correlation (r = 0.923, p < 0.001) with the invasive reference measurements was obtained whereas the approach failed for the remaining four subjects. These mixed results can be explained by the weak contribution of perfusion to the whole cardiac signal in EIT. These findings are based on simulations and detailed analysis, which revealed that for both pigs and humans, cardiac EIT signals are dominated by heart-induced movement, which seems to be in contradiction to the literature. The results presented suggest the possibility to estimate the heart valve opening via EIT. The main challenge encountered in this thesis resides in the controversial origin of cardiac-related signals, which seem to be mostly motion-induced. Understanding the genesis of these signals would require further experiments and simulations such as 1) dedicated EIT measurements with controlled protocol conditions and 2) more advanced 3D thoracic conductivity simulations. This will hopefully reveal an insight into the origin of cardiac EIT signals and clarify the potential of this technology for the monitoring of hemodynamic parameters.