bioRxivBioengineeringPreprint
A biatrial digital twin integrating electrophysiology, mechanics, and circulation: from physiology to atrial fibrillation
Sergi Pico-CabiroiD, Alberto ZingaroiD, Violeta Puche-GarcíaiD, Dimitrios I. LialiosiD, Mariano VázqueziD, Blas EchebarriaiD, Maite IzquierdoiD, Francesc CarrerasiD, Javier SáiziD, Eva CasoniiD
Abstract
Atrial electromechanics plays a key role in cardiac function by regulating ventricular filling and global hemodynamics, yet remains challenging to model consistently across scales. In this work, a multiscale atrial digital twin for simulations of normal and pathological atrial function is presented, formulated as an electromechanical framework for biatrial simulations that couples three-dimensional atrial electrophysiology and mechanics with a closed-loop zero-dimensional circulatory model. The framework is calibrated on a patient-specific biatrial anatomy to reproduce physiological regional activation times, atrial volumes, ejection fractions, and pressure-volume loop characteristics. The simulations capture all atrial functional phases throughout the cardiac cycle, including realistic figure-eight pressure-volume loops, an aspect hard to achieve in computational studies. A systematic sensitivity analysis quantifies the influence of active contraction, passive stiffness, boundary conditions, and circulatory parameters on atrial function. Finally, application to a pathological scenario through induced persistent atrial fibrillation demonstrates how electrophysiological remodelling propagates across scales, leading to loss of effective atrial contraction, altered atrioventricular flow patterns, and a clinically relevant reduction in cardiac output. Overall, this multiphysics and multiscale framework provides a robust platform to investigate how atrial electrical alterations drive mechanical and hemodynamic alterations in both healthy and pathological conditions.
- organism: human
- assay: electrophysiology
- assay: metabolomics
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- approach: simulation
- Citations
- 0
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