Abstract:

More than 30 million adults in the United States suffer from chronic kidney disease (CKD). In the end-stages of CKD, patients are often treated by haemodialysis to regulate for example their extracellular concentrations of potassium. Deaths caused by cardiovascular events are 10% to 30% higher in CKD patients than in patients with normal kidney functions. Rapid changes in ionic concentrations are one possible explanation, which is why a continuous, non-invasive monitoring tool could provide new insights and save lifes in the end. It has been shown that the electrocardiogram (ECG) is suitable for determining ionic concentration changes. In this work, methods for processing data of hemodialysis patients are evaluated to improve estimation results. During a session, patients underwent a twelve lead ECG recording and had five to eight extracorporeal blood tests taken. In total, there were 84 sessions of 36 patients available. One half of the data set is used to find the best processing variant for six chosen reconstruction features. Using a patient specific approach, the best estimation of potassium concentrations was achieved with the TS/SQA feature leading to an absolute error and a standard deviation of 0.34 ± 0.27mmol/l. Applying the same data processing options to the second half of the data set, an absolute error and a standard deviation of 0.59 ± 0.54mmol/l was determined. A possible cause for these varying results might be the different quality of the data. Nevertheless, it is concluded that a personalized approach for ionic concentration reconstruction is advantageous, because patients specific characteristics such as the orientation of the heart can be compensated. The impact of the heart orientation in the torso was investigated in the second part of this thesis. A model of human ventricles was rotated inside the torso around three axes. After changing the orientation, the local activation times were calculated with a fast marching method. Using single cell simulations with the Himeno et al. cell model and boundary element method the ECG was extracted and already used features were determined. The feature values deviated from each other, for example the amplitude of the T wave varied by 0.9mV in the worst case for the same potassium concentration but different orientations of the heart. The conclusion is that a definite reconstruction is not possible without knowing the exact orientation. This also supports the findings from the first part of this work. The use of a patient specific approach delivers better results, because anatomical attributes might get compensated. With regard to a global approach, methods for the compensation of patient specific characteristics need to be found.