A model for mechano-electrical feedback effects on atrial flutter interval variability

The frequency of atrial fibrillatory waves is modulated by the spatiotemporal pattern of acetylcholine release: a 3D computational study

In atrial fibrillation (AF), the ECG P-wave, which represents atrial depolarization, is replaced with chaotic and irregular fibrillation waves (f waves). The f-wave frequency, F f, shows significant variations over time. Cardiorespiratory interactions regulated by the autonomic nervous system have been suggested to play a role in such variations. We conducted a simulation study to test whether the spatiotemporal release pattern of the parasympathetic neurotransmitter acetylcholine (ACh) modulates the frequency of atrial reentrant circuits. Understanding parasympathetic involvement in AF may guide more effective treatment approaches and could help to design autonomic markers alternative to heart rate variability (HRV), which is not available in AF patients. 2D tissue and 3D whole-atria models of human atrial electrophysiology in persistent AF were built. Different ACh release percentages (8% and 30%) and spatial ACh release patterns, including spatially random release and release from ganglionated plexi (GPs) and associated nerves, were considered. The temporal pattern of ACh release, ACh(t), was simulated following a sinusoidal waveform of frequency 0.125 Hz to represent the respiratory frequency. Different mean concentrations ( A C h ¯ ) and peak-to-peak ranges of ACh (ΔACh) were tested. We found that temporal variations in F f, F f(t), followed the simulated temporal ACh(t) pattern in all cases. The temporal mean of F f(t), F ¯ f , depended on the fibrillatory pattern (number and location of rotors), the percentage of ACh release nodes and A C h ¯ . The magnitude of F f(t) modulation, ΔF f, depended on the percentage of ACh release nodes and ΔACh. The spatial pattern of ACh release did not have an impact on F ¯ f and only a mild impact on ΔF f. The f-wave frequency, being indicative of vagal activity, has the potential to drive autonomic-based therapeutic actions and could replace HRV markers not quantifiable from AF patients.

MicroRNAs: New contributors to mechano-electric coupling and atrial fibrillation

Atrial fibrillation (AF) is a multifactorial disease, which often occurs in the presence of underlying cardiac abnormalities and is supported by electrophysiological and structural alterations, generally referred to as atrial remodeling. Abnormal substrates are commonly encountered in various conditions that predispose to AF, such as hypertension, heart failure, obesity, and sleep apnea, in which atrial stretch plays a key mechanistic role. Emerging evidence suggests a role for microRNAs (small non-coding RNAs) in the pathogenesis of AF, where they can act as post-transcriptional regulators of the genes involved in atrial remodeling. This review summarizes the experimental and clinical evidence that supports the role of microRNAs in the modulation of atrial electrical and structural remodeling with a focus on overload-induced atrial alterations, and discusses the potential contribution of microRNAs to mechano-electrical coupling and AF.

Cardiac Mechano-Electric Coupling: Acute Effects of Mechanical Stimulation on Heart Rate and Rhythm

The heart is vital for biological function in almost all chordates, including humans. It beats continually throughout our life, supplying the body with oxygen and nutrients while removing waste products. If it stops, so does life. The heartbeat involves precise coordination of the activity of billions of individual cells, as well as their swift and well-coordinated adaption to changes in physiological demand. Much of the vital control of cardiac function occurs at the level of individual cardiac muscle cells, including acute beat-by-beat feedback from the local mechanical environment to electrical activity (as opposed to longer term changes in gene expression and functional or structural remodeling). This process is known as mechano-electric coupling (MEC). In the current review, we present evidence for, and implications of, MEC in health and disease in human; summarize our understanding of MEC effects gained from whole animal, organ, tissue, and cell studies; identify potential molecular mediators of MEC responses; and demonstrate the power of computational modeling in developing a more comprehensive understanding of ‟what makes the heart tick.ˮ.

An orthotropic electro-viscoelastic model for the heart with stress-assisted diffusion

We propose and analyse the properties of a new class of models for the electromechanics of cardiac tissue. The set of governing equations consists of nonlinear elasticity using a viscoelastic and orthotropic exponential constitutive law, for both active stress and active strain formulations of active mechanics, coupled with a four-variable phenomenological model for human cardiac cell electrophysiology, which produces an accurate description of the action potential. The conductivities in the model of electric propagation are modified according to stress, inducing an additional degree of nonlinearity and anisotropy in the coupling mechanisms, and the activation model assumes a simplified stretch-calcium interaction generating active tension or active strain. The influence of the new terms in the electromechanical model is evaluated through a sensitivity analysis, and we provide numerical validation through a set of computational tests using a novel mixed-primal finite element scheme.

Modeling Framework for the Generation of Synthetic RR Series during Atrial Arrhythmias

We introduced a modeling framework for the generation of realistic ventricular interval (RR) series to be used in the validation of atrial arrhythmia detection algorithms. The framework included three previously proposed models, which reproduced the specific variability properties of RR series in normal sinus rhythm, atrial flutter (AFL) and atrial fibrillation (AF). Transitions between the three rhythms were governed by a three-state continuous-time Markov chain model, which could be tuned to obtain arrhythmic episodes of the requested length. As a representative application, the modeling framework was used to generate a database of RR series for the validation of a previously proposed AF detection algorithm, which was based on RR pattern similarity. The validation showed the deterioration of detector performance in presence of simulated AFL episodes. Thanks to the detailed reproduction of the specific features of the two most common atrial arrhythmias, our modeling framework may constitute a novel tool for the assessment and comparison of detection algorithm performance.

A note on stress-driven anisotropic diffusion and its role in active deformable media

We introduce a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to employ diffusion tensors directly influenced by the coupling with mechanical stress. The proposed generalised reaction-diffusion-mechanics model reveals that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the mathematical model and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-driven diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electric feedback in actively deforming bio-materials such as the cardiac tissue.

Dynamics of AV coupling during human atrial fibrillation: role of atrial rate

The causal relationship between atrial and ventricular activities during human atrial fibrillation (AF) is poorly understood. This study analyzed the effects of an increase in atrial rate on the link between atrial and ventricular activities during AF. Atrial and ventricular time series were determined in 14 patients during the spontaneous acceleration of the atrial rhythm at AF onset. The dynamic relationship between atrial and ventricular activities was quantified in terms of atrioventricular (AV) coupling by AV synchrogram analysis. The technique identified n: m coupling patterns ( n atrial beats in m ventricular cycles), quantifying their percentage, maximal length, and conduction ratio (= m/ n). Simulations with a difference-equation AV model were performed to correlate the observed dynamics to specific atrial/nodal properties. The atrial rate increase significantly affected AV coupling and ventricular response during AF. The shortening of atrial intervals from 185 ± 32 to 165 ± 24 ms ( P < 0.001) determined transitions toward AV patterns with progressively decreasing m/ n ratios (from conduction ratio = 0.34 ± 0.09 to 0.29 ± 0.08, P < 0.01), lower occurrence (from percentage of coupled beats = 27.1 ± 8.0 to 21.8 ± 6.9%, P < 0.05), and higher instability (from maximal length = 3.9 ± 1.5 to 2.8 ± 0.7 s, P < 0.01). Advanced levels of AV block and coupling instability at higher atrial rates were associated with increased ventricular interval variability (from 123 ± 52 to 133 ± 55 ms, P < 0.05). AV pattern transitions and coupling instability in patients were predicted, assuming the filtering of high-rate irregular atrial beats by the slow recovery of nodal excitability. These results support the role of atrial rate in determining AV coupling and ventricular response and may have implications for rate control in AF.

Nodal recovery, dual pathway physiology, and concealed conduction determine complex AV dynamics in human atrial tachyarrhythmias

The genesis of complex ventricular rhythms during atrial tachyarrhythmias in humans is not fully understood. To clarify the dynamics of atrioventricular (AV) conduction in response to a regular high-rate atrial activation, 29 episodes of spontaneous or pacing-induced atrial flutter (AFL), covering a wide range of atrial rates (cycle lengths from 145 to 270 ms), were analyzed in 10 patients. AV patterns were identified by applying firing sequence and surrogate data analysis to atrial and ventricular activation series, whereas modular simulation with a difference-equation AV node model was used to correlate the patterns with specific nodal properties. AV node response at high atrial rate was characterized by 1) AV patterns of decreasing conduction ratios at the shortening of atrial cycle length (from 236.3 ± 32.4 to 172.6 ± 17.8 ms) according to a Farey sequence ordering (conduction ratio from 0.34 ± 0.12 to 0.23 ± 0.06; P < 0.01); 2) the appearance of high-order alternating Wenckebach rhythms, such as 6:2, 10:2, and 12:2, associated with ventricular interval oscillations of large amplitude (407.7 ± 150.4 ms); and 3) the deterioration of pattern stability at advanced levels of block, with the percentage of stable patterns decreasing from 64.3 ± 35.2% to 28.3 ± 34.5% ( P < 0.01). Simulations suggested these patterns to originate from the combined effect of nodal recovery, dual pathway physiology, and concealed conduction. These results indicate that intrinsic nodal properties may account for the wide spectrum of AV block patterns occurring during regular atrial tachyarrhythmias. The characterization of AV nodal function during different AFL forms constitutes an intermediate step toward the understanding of complex ventricular rhythms during atrial fibrillation.

Voltage-gated channel mechanosensitivity: fact or friction?

The heart is a continually active pulsatile fluid pump. It generates appropriate forces by precisely timed and spaced engagement of its contractile machinery. Largely, it makes its own control signals, the most crucial of which are precisely timed and spaced fluxes of ions across the sarcolemma, achieved by the timely opening and closing of diverse voltage-gated channels (VGC). VGCs have four voltage sensors around a central ion-selective pore that opens and closes under the influence of membrane voltage. Operation of any VGC is secondarily tuned by the mechanical state (i.e., structure) of the bilayer in which it is embedded. Rates of opening and closing, in other words, vary with bilayer structure. Thus, in the intensely mechanical environment of the myocardium and its vasculature, VGCs kinetics might be routinely modulated by reversible and irreversible nano-scale changes in bilayer structure. If subtle bilayer deformations are routine in the pumping heart, VGCs could be subtly transducing bilayer mechanical signals, thereby tuning cardiac rhythmicity, collectively contributing to mechano-electric feedback. Reversible bilayer deformations would be expected with changing shear flows and tissue distension, while irreversible bilayer restructuring occurs with ischemia, inflammation, membrane remodeling, etc. I suggest that tools now available could be deployed to help probe whether/how the inherent mechanosensitivity of VGCs - an attribute substantially reflecting the dependence of voltage sensor stability on bilayer structure - contributes to cardiac rhythmicity. Chief among these tools are voltage sensor toxins (whose inhibitory efficacy varies with the mechanical state of bilayer) and arrhythmia-inducing VGC mutants with distinctive mechano-phenotypes.

Cardiorespiratory interactions in patients with atrial flutter

Respiratory sinus arrhythmia (RSA) is generally known as the autonomically mediated modulation of the sinus node pacemaker frequency in synchrony with respiration. Cardiorespiratory interactions have been largely investigated during sinus rhythm, whereas little is known about interactions during reentrant arrhythmias. In this study, cardiorespiratory interactions at the atrial and ventricular level were investigated during atrial flutter (AFL), a supraventricular arrhythmia based on a reentry, by using cross-spectral analysis and computer modeling. The coherence and phase between respiration and atrial (γ[Formula: see text], φAA) and ventricular (γ[Formula: see text], φRR) interval series were estimated in 20 patients with typical AFL (68.0 ± 8.8 yr) and some degree of atrioventricular (AV) conduction block. In all patients, atrial intervals displayed oscillations strongly coupled and in phase with respiration (γ[Formula: see text]= 0.97 ± 0.05, φAA = 0.71 ± 0.31 rad), corresponding to a paradoxical lengthening of intervals during inspiration. The modulation pattern was frequency independent, with in-phase oscillations and short time delays (0.40 ± 0.15 s) for respiratory frequencies in the range 0.1–0.4 Hz. Ventricular patterns were affected by AV conduction type. In patients with fixed AV conduction, ventricular intervals displayed oscillations strongly coupled (γ[Formula: see text]= 0.97 ± 0.03) and in phase with respiration (φRR = 1.08 ± 0.80 rad). Differently, in patients with variable AV conduction, respiratory oscillations were secondary to Wencheback rhythmicity, resulting in a decreased level of coupling (γ[Formula: see text]= 0.50 ± 0.21). Simulations with a simplified model of AV conduction showed ventricular patterns to originate from the combination of a respiratory modulated atrial input with the functional properties of the AV node. The paradoxical frequency-independent modulation pattern of atrial interval, the short time delays, and the complexity of ventricular rhythm characterize respiratory arrhythmia during AFL and distinguish it from normal RSA. These peculiar features can be explained by assuming a direct mechanical action of respiration on AFL reentrant circuit.