In this project, dynamic network models of cardiovascular systems shall be subjected to modal analysis. Theoretical eigenmodes are obtained from numerical eigenvalue analysis of different networks whose topology and parameters can be taken from literature. Based on these models, it is predicted how the eigenmodes are influenced by various typical aneurysms and stenoses. Experimental modal analyses are carried out with ultrasonic measurements of blood flow velocity, which are synchronized by simultaneous measurements of a second quantity such as electrocardiogram. Blood flow signals are processed by modal analysis software for mechanical systems, which has been used successfully for determining the pressure mode shapes of oil hydraulic pipelines. Primary subject of the investigation is the arterial tree. Natural frequencies, damping ratios, and mode shapes are compared between theory and experiments. Blood flow eigenmodes of several healthy persons are determined to assess possible scatter of results. Experiments are carried out before and after surgical interventions to study the resulting change in eigenmodes. Experimental results are used to improve dynamic network models. From a medical point of view, it is assessed how modal analysis can help to improve the diagnosis of arterial defects. Possible applications include complementary information for imaging techniques, better insight at inaccessible positions, and replacement of invasive diagnosis. The objectives of associated identification problems shall be defined to specify further research for future projects.
Univ.-Prof. DI Dr. Gudrun Mikota