Confocal microscopy-based estimation of intracellular conductivities in myocardium for modeling of the normal and infarcted heart

Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytes (Vmyo), gap junctions-containing voxels (Vgj), and fibrosis (Vfibrosis). We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson's equation for stationary electrical currents, we calculated normal (amyo,n), longitudinal (amyo,l), and transverse (amyo,t) intracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features. Vgj and Vmyo were reduced in MI vs. control, but Vfibrosis was increased. Both amyo,l and amyo,n were lower in MI than in control. Differences of amyo,t between control and MI were not significant. We found strong positive relationships of amyo,l with Vmyo and Vgj, and a strong negative relationship with Vfibrosis. The relationships of amyo,n with these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.

Automated summary

Ventricular arrhythmias are a major cause of mortality in patients with ischemic heart diseases. Computational simulation of cardiac electrophysiology can provide insights into these arrhythmias and their treatment, but there is limited information on model parameters. This study introduces an approach to estimate intracellular electrical conductivities in normal and myocardial infarction hearts and finds strong correlations with tissue features.