POTSE, Mark; KRAUSE, Dorian; KROON, Wilco; MURZILLI, Romina; MUZZARELLI, Stefano; REGOLI, François; CAIANI, Enrico G.; PRINZEN, Frits W.; KRAUSE, Rolf; AURICCHIO, Angelo

doi:10.1093/europace/euu257

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POTSE, Mark
Modélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
Center for Computational Medicine in Cardiology [CCMC]

KRAUSE, Dorian
Institute of Computational Science

KROON, Wilco
Institute of Computational Science

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EP-Europace. 2014-11-30, vol. 16, p. iv56-iv61

Oxford University Press (OUP)

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Aims Left-ventricular (LV) conduction disturbances are common in heart-failure patients and a left bundle-branch block (LBBB) ECG type is often seen. The precise cause of this pattern is uncertain and is probably variable between patients, ranging from proximal interruption of the left bundle branch to diffuse distal conduction disease in the working myocardium. Using realistic numerical simulation methods and patient-tailored model anatomies we investigated different hypotheses to explain the observed activation order on the LV endocardium, electrogram morphologies, and ECG features in two patients with heart failure and LBBB ECG.Methods Ventricular electrical activity was simulated using reaction-diffusion models with patient-specific anatomies. From the simulated action potentials, ECGs and cardiac electrograms were computed by solving the bidomain equation. Model parameters such as earliest activation sites, tissue conductivity, and densities of ionic currents were tuned to reproduce the measured signals.Results ECG morphology and activation order could be matched simultaneously. Local electrograms matched well at some sites, but overall the measured waveforms had deeper S waves than the simulated waveforms.Conclusion Tuning a reaction-diffusion model of the human heart to reproduce measured ECGs and electrograms is feasible and may provide insights in individual disease characteristics that cannot be obtained by other means.< Réduire

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Patient-specific modelling of cardiac electrophysiology in heart-failure patients

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