Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial Ischemia

Abstract

Myocardial ischemia is an early clinical indicator of several underlying cardiac pathologies. Significant progress has been made in computing body-surface potentials from cardiac sources by solving the forward problem of electrocardiography. However, the lack of in vivo studies to validate such computations from ischemic sources has limited the translational potential of such models. We have developed a large-animal experimental model that includes simultaneous recordings within the myocardium, on the epicardial surface, and on the torso surface during episodes of acute, controlled ischemia with comprehensive imaging and subject specific modeling for each animal. We then identified ischemic sources and used the finite element method to solve a static bidomain equation on a geometric model to compute torso surface potentials. Across 33 individual heartbeats, the forward computed torso potentials showed only moderate agreement in both pattern and amplitude with Pearson’s correlation coefficient, root mean squared error, and absolute error varying significantly by heartbeat (0.1642 ± 0.223, 0.10 ± 0.03mV, and 0.08±0.03mV, respectively). Qualitative analysis showed a more encouraging pattern of elevations and depressions shared by computed and measured torso potentials. Further studies will focus on characterizing these sources of error and understanding how they effect the study results.