Computational Modeling and Visualization of Ischemic Effects on an Advanced Purkinje Network

The cardiac Purkinje network plays a vital role in the heart’s electrical conduction system, ensuring efficient and synchronized ventricular contraction. When impaired—particularly by ischemia—it can trigger life-threatening arrhythmias. In this study, we present an advanced computational model of the Purkinje network that integrates cell-level heterogeneity, spatial organization, and localized ischemic zones with customizable severity gradients. Developed in Python using open-source libraries (NumPy, matplotlib, pandas, seaborn), the model generates rich visualizations of network structure, conduction velocities, ischemia severity, and electrophysiological parameters. Simulations demonstrate how ischemia alters conduction and refractoriness in a spatially dependent manner, providing insights into arrhythmogenic risk. This modeling framework can advance understanding of cardiac conduction under pathological conditions and support therapeutic development.