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Casoni, E.

Publications and source records attributed to Casoni, E..

2 recordsLinked to original sources

A biatrial digital twin integrating electrophysiology, mechanics, and circulation: from physiology to atrial fibrillation

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.

bioengineering↗

Can In Silico Models Predict Drug-Induced Cardiac Risk in Vulnerable Populations?

This study evaluates virtual cardiac populations for preclinical assessment of drug-induced QT interval prolongation and arrhythmic risk. Traditional predictions often rely on small, healthy cohorts, excluding vulnerable populations. Using computational models of realistic heart anatomies and electrophysiology, we generated a virtual cohort of 512 subjects across healthy and diseased hearts (heart failure, dilated and hypertrophic cardiomyopathy, ischaemia, and myocardial infarction). We assessed QT prolongation and arrhythmic events following administration of moxifloxacin (benchmark antibiotic) and contraindicated drugs including quinidine, bepridil, and flecainide. Patients with heart failure, hypertrophic and dilated cardiomyopathy showed greater QT prolongation to moxifloxacin, unlike ischaemia and myocardial infarction, which resembled healthy subjects. Females exhibited consistently higher QT prolongation than males. Contraindicated drugs markedly increased arrhythmia risk in populations with heart failure, dilated and hypertrophic cardiomyopathy, and ischaemia, frequently leading to lethal arrhythmias such as Torsades des Pointes or ventricular fibrillation, particularly in females. These findings demonstrate that computational models capture variability in drug response across pathologies and sexes, offering a predictive framework for preclinical safety evaluations and supporting safer, more personalized drug development strategies.

bioengineering↗