Key result
Minimal functional cluster size distribution predicts reentry probability across fibrosis densities and excitabilities in simulations.
Why the study?
Cardiac fibrosis promotes arrhythmogenesis and sudden cardiac death, but the relation between specific fibrosis texture and the onset of reentry remains an open question of theoretical and practical importance.
A new conceptual framework using minimal functional clusters accurately characterizes reexcitation paths and predicts reentry probability in simulated cardiac fibrotic tissue.
Answers are grounded in this paper and cite their sources.
Hypothesis-generating for reentry risk in fibrotic hearts; leaves open experimental and clinical validation.
Cardiac fibrosis is a well-known arrhythmogenic condition which can lead to sudden cardiac death. Physically, fibrosis can be viewed as a large number of small obstacles in an excitable medium, which may create nonlinear wave turbulence or reentry. The relation between the specific texture of fibrosis and the onset of reentry is of great theoretical and practical importance. Here, we present a conceptual framework which combines functional aspects of propagation manifested as conduction blocks, with reentry wavelength and geometrical clusters of fibrosis. We formulate them into the single concept of minimal functional cluster and through extensive simulations show that it characterizes the path of reexcitation accurately, and importantly its size distribution quantitatively predicts the reentry probability for different fibrosis densities and tissue excitabilities.
No takes yet. Share an insight, caveat, or question.
Pashakhanloo et al. (2021) studied Cardiac fibrosis. Minimal functional clusters was evaluated on Reentry probability. The size distribution of minimal functional clusters quantitatively predicts the probability of reentry for different cardiac fibrosis densities and tissue excitabilities in simulations.
Synapse has enriched 10 related papers. Consider them for comparative context: