bioRxiv ScienceSearch

Biology subjects

Peirlinck, M.

Publications and source records attributed to Peirlinck, M..

2 recordsLinked to original sources

How drugs modulate the performance of the human heart

Many drugs interact with ion channels in the cells of the heart and trigger heart rhythm disorders with potentially fatal consequences. Computational modeling can provide mechanistic insight into the onset and propagation of drug-induced arrhythmias, but the effect of drugs on the mechanical behavior of the heart remains poorly understood. Here we establish a multiphysics framework that integrates the biochemical, electrical, and mechanical effects of drugs from single cardiac cells to the overall response of the whole heart. For the example of the drug dofetilide, we show that drug concentrations of 3.0x and 4.8x increase the heart rate to 122 and 114 beats per minute, increase the myofiber stretches up to 10%, and decrease tissue relaxation by 6%. Strikingly, the drug-induced interventricular and atrial-ventricular dyssynchrony results in a 2.5% decreased and 7% increased cardiac output, respectively. Our results demonstrate the potential for multiphysics, multiscale modeling towards understanding the mechanical implications of drug-induced arrhythmias. Knowing how differing drug concentrations affect the performance of the heart has important clinical implications in drug safety evaluation and personalized medicine.

biophysics

A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Hearts

MRI-driven computational modeling is increasingly used to simulate in vivo cardiac mechanical behavior and estimate subject-specific myocardial stiffness. However, in vivo validation of these estimates is exceedingly difficult due to the lack of a known ground-truth in vivo myocardial stiffness. We have developed 3D-printed heart phantoms of known myocardium-mimicking stiffness and MRI relaxation properties and incorporated the heart phantoms within a highly controlled MRI-compatible setup to simulate in vivo diastolic filling. The setup enables the acquisition of experimental data needed to evaluate myocardial stiffness using computational constitutive modeling: phantom geometry, loading pressures, boundary conditions, and filling strains. The pressure-volume relationship obtained from the phantom setup was used to calibrate an in silico model of the heart phantom undergoing simulated diastolic filling. The model estimated stiffness was compared with ground-truth stiffness obtained from uniaxial tensile testing. Ultimately, the setup is designed to enable extensive validation of MRI and FEM-based myocardial stiffness estimation frameworks.

bioengineering