Improved Phenotyping of Cardiomyopathy Patients by Means of Imaging-Driven Computational Modeling of Cardiac Biomechanics
In this project, we will combine clinical cardiovascular magnetic resonance imaging (CMR) with computational modeling of cardiac biomechanics in order to improve diagnosis of cardiomyopathy. Different kinds of cardiomyopathy cannot be sufficiently differentiated with currently available diagnostic tools, which hinders optimal treatment tailoring. The dynamics of the contraction of the heart are driven by the interplay of the active tension developed by the heart muscle cells and the passive mechanical properties of the cardiac tissue. Despite considerable advances in CMR techniques, the spatiotemporal distribution of active tension and most of the tissue properties cannot be imaged in vivo today. However, these measures could be of great value to address the challenge of phenotyping different kinds of cardiomyopathy to optimally tailor therapy for individual patients. Therefore, we will develop a method to estimate active and passive mechanical properties of the individual patient by combining cutting edge imaging data with a computational model of cardiac elastomechanics. In detail, we will solve the ‘inverse problem of cardiac mechanics’ and demonstrate for the first time the feasibility using actual imaging data.
The expertise of the Cardiac Imaging Group at University Hospital Heidelberg and the Institute of Biomedical Engineering at Karlsruhe Institute of Technology (KIT), both partners with a track-record of scientific excellence and high innovation potential, will be combined within the HeiKa Research Bridge “Medical Technology for Health”. By synergistically joining forces, we will deliver a proof of concept for a highly innovative diagnostic tool, allowing to optimally phenotype cardiomyopathy patients based on non-invasive CMR measurements. The demonstrated feasibility will form the basis of a follow-up grant proposal for third-party funding ensuring sustainable use of the initial HeiKa funding and the research results as well as continuance of the project.