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Standardized modeling of cardiac arrest and cardiopulmonary resuscitation (CPR) is crucial to evaluate new treatment options.
In this context, computational modeling of cardiac hemodynamics presents as a powerful non-invasive modality that can fill this information gap, and significantly impact the diagnosis as well as the treatment of cardiac disease.
However, the modeling of cardiac tissue is computationally expensive due to several physical constraints which result in fine spatiotemporal discretization over large spatiotemporal regions.
We have demonstrated that simple and complex models share a large extent of similarities in the functional modeling of cardiac electrical behavior.
Over the last four decades, computational modeling of cardiac mechanics has evolved, incorporating biophysically-based hyperelastic strain energy laws [2 5], anisotropic tissue structure [6 8], patient-specific geometries [9] and cellular activation [10] to effectively simulate the myocardial behavior assuming basic Newtonian physics [11].
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Methods: An established model of cardiac arrest in the pig was used.
We studied the haemodynamic differences of such waveforms in a porcine model of cardiac arrest.
Moreover, maintenance of high AcCoA levels inhibited maladaptive autophagy in a model of cardiac pressure overload.
A simple model of cardiac muscle was designed for multiscale simulation of heart mechanics.
We then illustrate and assess our proposed observer method with test problems pertaining to electrophysiology modeling, including with a realistic model of cardiac atria.
PRAM is not a useful method for measurement of the CI in this pediatric model of cardiac arrest.
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