Self-organization of conducting pathways explains complex wave trajectories in procedurally interpolated fibrotic cardiac tissue: A virtual replica study

In precision cardiology, virtual replicas (VRs) hold promise for predicting arrhythmias by leveraging patient-specific data and biophysics knowledge. A crucial first step is creating VRs of cardiac tissue based on retrospective patient data. However, VRs aim to replicate biopotential conduction directly, whereas only non-invasive methods are feasible for clinical use on real organs and tissues. This discrepancy challenges our understanding of VR applicability limits. This study aims to enhance the mathematical template of VR by developing an in vitro validation complement. We performed a frame-by-frame comparison of in vitro optical mapping of biopotential conduction with VR predictions. Patient-specific self-organized tissue samples from human induced pluripotent stem cell-derived cardiomyocytes (CMs) with diffuse fibrosis were utilized as VR prototypes. High-resolution optical mapping recordings (Δx = 117 ± 4 μm, Δt = 7.69 ms) and immunostaining were used to reproduce fibrotic samples of linear size 7.5 mm. We applied data-driven Bayesian optimization of the Cellular Potts model (CPM) to study wave propagation at the subcellular level. The modified CPM accurately reflected the "perinatal window" until the 20th day of differentiation, affecting CMs' self-organization. The percolation threshold of virtual conductive pathways reached 0.26 (0.27 ± 0.03 of CMs in vitro), yielding a spatial correlation of amplitude maps with Pearson's coefficients of 0.83 ± 0.02. As a proof-of-concept, we demonstrated that CPM-enhanced VR could predict wavefront trajectories in optical mapping recordings, showing that approximating fibrosis distribution is crucial for improving VR prediction accuracy.