Cardiovascular System Dynamics: Models and Measurements
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Furthermore, the occurrence of alternans can be significantly modulated by steep conduction velocity restitution slopes . These aspects will require a careful computational evaluation. Such computational studies will permit to understand the possibilities and limitations of our framework in greater detail, and they are expected to provide additional insights into dynamical phenomena emerging at multicellular scales, such as spatially discordant alternans  , .
In conclusion, stochastic pacing combined with ARMA model identification represents a novel frequency domain approach to study cardiac dynamics. This approach should be applicable experimentally for the accurate evaluation of the propensity to alternans and the prediction of its onset. Because its mathematical foundation does not make any a priori assumptions about the ionic mechanisms of alternans, it pertains to any type of myocardial cell or tissue, irrespective of species, disease status or pharmacological interventions.
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Performed the experiments: JPK. Abstract Alternans of cardiac action potential duration APD is a well-known arrhythmogenic mechanism which results from dynamical instabilities. Author Summary Cardiac arrhythmias are frequent complications of heart disease and an important cause of morbidity and mortality. Introduction In cardiac physiology, alternans designates the alternation of action potential AP parameters e. Methods Cell model and computer simulations We used the model of Sato et al. Eigenmode analysis using internal model variables , derivation of transfer functions, and link with classical restitution slopes, alternans and memory In all ionic cardiac cell models, including the Sato et al.
Derivation of transfer functions. Link with classical restitution slopes.
Autoregressive-moving-average ARMA modeling analysis based on the memory of previous pacing cycles , derivation of transfer functions, and link with classical restitution slopes and alternans Derivation of transfer functions using the memory model of previous pacing cycles. Test protocols with the cell model, ARMA model identification and data analysis For each BCL tested in decremental steps of 5 ms from ms to ms, and then in steps of 1 ms , the 3 versions of the Sato et al.
For every BCL at which the S1S2 protocol was conducted, steady state conditions were first obtained as described above. Stochastic pacing protocol and ARMA model identification: After having reached steady state, the cell model was paced at cycle lengths CLs varying randomly around BCL with a Gaussian distribution having a predefined standard deviation SD.
S S1S2 and S dyn were estimated according to Eqs. Results Occurrence of alternans, main eigenvalues and rate adaptation in the three model versions Figure 1 A depicts steady-state APD vs. Download: PPT. Figure 1. Bifurcation to alternans and eigenvalues in the three model versions. Restitution curves in the three model versions Figure 2 illustrates dynamic and S1S2 restitution curves obtained using conventional pacing protocols. Figure 2. Dynamic and S1S2 restitution curves in the three model versions.
Figure 3. Figure 4.
Behavior of alternans markers in the three model versions. Aspect of the transfer functions at pacing regimes closer and closer to the bifurcation to alternans Representations of frequency response spectra are intuitively easier to interpret than corresponding sets of poles and zeros. Figure 5. Aspect of the transfer functions at regimes closer and closer to the bifurcation to alternans. Prediction of the onset of alternans during a ramp decrease of BCL The analyses presented above were conducted in stationary regimes, for which mean BCL and cellular properties did not evolve with time.
Figure 6. Figure 7. Predicting alternans in the V m -driven model during a progressive decrease of I Ks conductance. Superiority of ARMA model identification compared to a time domain analysis To investigate whether ARMA model identification during stochastic pacing offers a significant advantage over a simpler time domain analysis consisting of quantifying the decay of APD oscillations following a perturbation, we examined the response of the Sato et al.
Figure 8. Superiority of ARMA model identification during stochastic pacing vs. Discussion Alternans is a clinically relevant phenomenon leading to dispersion of refractoriness, which precipitates conduction block and reentrant arrhythmias  — . A new unified framework for restitution, alternans and memory In the present study, we revisit restitution by examining it in a generalized framework based on eigenmode analysis, a sound mathematical approach for the characterization of dynamical systems. Perspectives, limitations and challenges Stochastic pacing and ARMA model identification would be straightforward to implement in any electrophysiological apparatus.
Conclusion In conclusion, stochastic pacing combined with ARMA model identification represents a novel frequency domain approach to study cardiac dynamics. References 1. Lewis T Notes upon alternation of the heart. Quart J Med 4: — View Article Google Scholar 2. Circ Res — View Article Google Scholar 3.
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Cardiovascular System Dynamics: Models and Measurements
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Am J Physiol H— J Cardiovasc Electrophysiol — Chaos Wu R, Patwardhan A Mechanism of repolarization alternans has restitution of action potential duration dependent and independent components. J Cardiovasc Electrophysiol 87— Wu R, Patwardhan A Restitution of action potential duration during sequential changes in diastolic intervals shows multimodal behavior.
Ann Biomed Eng — Heart Rhythm 2: — Jordan PN, Christini DJ Action potential morphology influences intracellular calcium handling stability and the occurrence of alternans. Jordan PN, Christini DJ Characterizing the contribution of voltage- and calcium-dependent coupling to action potential stability: implications for repolarization alternans. J Physiol Lond — Hayes MH Statistical digital signal processing and modeling. Wu R, Patwardhan A Effects of rapid and slow potassium repolarization currents and calcium dynamics on hysteresis in restitution of action potential duration.
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Cardiovascular System Dynamics: Models and Measurements by T. A. Kenner - metgastziltore.tk
Hinghofer-Szalkay, T. Leopold, M. Alberto P. Avolio, Jos A. Spaan, John D. Cardiac Output: Is it Signaled to the Brain? Pessenhofer, P.