Personalized Multiphysics Simulations for Honing Cardiac Resynchronization Therapy (PUSHCART)

Heart failure is a major cause of death in industrialized countries. It is often associated with disturbances to the cardiac electrical conduction system, leading to abnormal cardiac activation and impaired pumping performance. Cardiac Resynchronization therapy (CRT) is a proven treatment to retard or even reverse the progress of the disease by pacing the heart in a way to reduce dyssynchrony. This necessitates implantation of a pacing device with multiple leads, but optimal lead position and optimal timing of delivery of electrical stimuli remains an open question. While it is recognized that the total activation time of the ventricles should be reduced, minimizing it alone does not improve mechanical response better than placing leads elsewhere. A significant fraction (30-50%) of patients does not respond at all to this expensive therapy, with large inter-patient variability leading to the poor results. The heart is an electrically activated mechanical fluid pump. Confounding its understanding is the feedback between physical components: Electrical events trigger mechanical contraction. Contraction causes blood flow, which is mediated by the vascular resistance. Conversely, changes in vascular resistance change blood flow and pressure in the ventricular cavities, thus altering the stresses in the ventricular walls and mechanical deformation. Deformation, in turn, affects electrical function through mechano-sensitive regulatory loops, mediated through stretch activated ionic channels and pre-stretch effects of active force generation. This project will bring together electrical, mechanical and hemodynamic function in the most detailed multiphysics, multiscale representation of the heart to date. Tightly coupled electromechanical behavior will interface to a circulatory model providing the appropriate boundary conditions to the mechanical model and form a closed circuit. Personalized models will be constructed based on imaging, noninvasive electrical measurements and hemodynamic performance. We hypothesize specific differences in wall activation that should be minimized. A complete multi-system model is needed to understand lead placement in CRT due to non-electrical factors, which have too long been ignored. Validating on detailed animal studies, retrospective and prospective studies will help us develop a predictive tool to determine optimal CRT lead placement.

Heart failure (HF) is a progressive disease with a mortality of around 50% within 3 years after first diagnosis. In many patients HF is linked to a damaged conduction system of the heart that leads to an improper activation which results in a weakened heart beat. They can be treated by cardiac synchronization therapy (CRT) which aims to restore a more normal electrical activation sequence of the heart by stimulating the heart at various locations and timings with a CRT pacemaker. However, while highly beneficial in many patients, one third of patients does not respond to the therapy. One reason for this failure is due to improper placement of the electrodes and/or the timing of delivered stimuli. We sought to use computer modelling to determine optimal electrode locations and timings. We developed sophisticated computer models of the heart which included electrical activation and mechanical contraction, both of which affected the other, and incorporated a model of circulation. We developed a coordinate system to specify position in the heart, and allowed us to develop a tool to efficiently compute electrical signals (electrograms sensed by the CRT device and ECGs registered at the body surface) based on the heart's electrical activation pattern. Experiments and computer simulations showed the effects of various CRT settings on improvement of heart function, as well as showing how disease state can affect how well the device works. Future work will include human studies to predict acute CRT response from computer modelling based clinical data, thus providing a means of tailoring optimal therapies to patients to achieve the goals of precision medicine.