Sign in
BiophysicsbioRxiv
Preprint

The simulation of functional heterogeneity in procedurally generated fibrotic atrial tissue

A. Kalinin, S. Kovalenko, A. K. Berezhnoy, M. M. Slotvitsky, S. Shcherbina, V. Syrovnev, V. A. Tsvelaya

Abstract

The occurrence of atrial fibrillation (AF), one of the most common and socially significant arrhythmias, is associated with the presence of fibrosis sites. Fibrosis is the presence of non-conductive fibroblast cells, separating cardiomyocytes and introducing heterogeneity into the conducting atrial tissue. Thus fibrosis may be a substrate of spiral-wave reentry, provoking the occurrence of AF and is often associated with its persistent form. In this work, we propose for the first time a fundamentally new approach to modeling the fibrotic heart that takes into account the cellular structure of the tissue: a realistic texture of atrial tissue remodeled by fibroblasts is generated by the Potts model, and the local membrane potential of individual cells is calculated by the Courtemanche model. We have shown the occurrence of conductive pathways in such a system with a low proportion of fibroblasts (up to 10%) and revealed the connection of the form of the action potential (AP) of cells with their location in the tissue and the direction of the propagating wave front. The combination of these effects creates dynamic heterogeneity of the conducting tissue and affects the migration and pinning of spiral waves, which makes the model a potential tool for prognostic modeling of AP and search for ablation targets. The computer prediction of ablation targets (reentry nodes) will help to increase the efficiency of treatment of patients with persistent form of AF.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKudryashova '19Moise '25Hirose '25Pikunov '23Heitmann '20Telle '25
78% semantic matchSystems Biology
Nina Kudryashova, Aygul Nizamieva, Valeriya A. Tsvelaya+2 more·PLoS Computational Biology·Mar 18, 2019· 39 citations