Killing Many Birds With Two Stones: Hypoxia and Fibrosis Can Generate Ectopic Beats in a Human Ventricular Model

Mechanisms of ischaemia-induced arrhythmias in hypertrophic cardiomyopathy: a large-scale computational study

AIMS

Lethal arrhythmias in hypertrophic cardiomyopathy (HCM) are widely attributed to myocardial ischaemia and fibrosis. How these factors modulate arrhythmic risk remains largely unknown, especially as invasive mapping protocols are not routinely used in these patients. By leveraging multiscale digital twin technologies, we aim to investigate ischaemic mechanisms of increased arrhythmic risk in HCM.

METHODS AND RESULTS

Computational models of human HCM cardiomyocytes, tissue, and ventricles were used to simulate outcomes of Phase 1A acute myocardial ischaemia. Cellular response predictions were validated with patch-clamp studies of human HCM cardiomyocytes (n = 12 cells, N = 5 patients). Ventricular simulations were informed by typical distributions of subendocardial/transmural ischaemia as analysed in perfusion scans (N = 28 patients). S1-S2 pacing protocols were used to quantify arrhythmic risk for scenarios in which regions of septal obstructive hypertrophy were affected by (i) ischaemia, (ii) ischaemia and impaired repolarization, and (iii) ischaemia, impaired repolarization, and diffuse fibrosis. HCM cardiomyocytes exhibited enhanced action potential and abnormal effective refractory period shortening to ischaemic insults. Analysis of ∼75 000 re-entry induction cases revealed that the abnormal HCM cellular response enabled establishment of arrhythmia at milder ischaemia than otherwise possible in healthy myocardium, due to larger refractoriness gradients that promoted conduction block. Arrhythmias were more easily sustained in transmural than subendocardial ischaemia. Mechanisms of ischaemia-fibrosis interaction were strongly electrophysiology dependent. Fibrosis enabled asymmetric re-entry patterns and break-up into sustained ventricular tachycardia.

CONCLUSION

HCM ventricles exhibited an increased risk to non-sustained and sustained re-entry, largely dominated by an impaired cellular response and deleterious interactions with the diffuse fibrotic substrate.

Mitochondrial Dysfunction in Cyanotic Congenital Heart Disease: A Promising Therapeutic Approach for the Future

Congenital heart disease (CHD) is one of the most specific and yet challenging fields of heart surgery. Apart from the known clinical approaches, including surgery, a significant scale of regenerative therapeutic options is available, which increase the number of cardiomyocytes and restore cardiac function. Although it has been revealed in recent years that mitochondrial transplantation can be used as a promising treatment option in this disease group, there is no clinical evidence for the significance of mitochondrial function in myocardial tissue of patients with CHD regarding cardiac surgery. In this study, mitochondrial morphology and function, myocardial fibrosis, and myocyte atypia were evaluated in myocardial biopsy tissue of pediatric patients with cyanotic and acyanotic CHD, five from each group. After histopathological evaluation of myocardial tissue specimens, mitochondrial morphology and network were analyzed by immunofluorescence staining using an anti-Tom20 antibody, electron transport chain complexes of myocardium were examined by cytochrome c oxidase/succinate dehydrogenase staining, and the amount of ATP was measured by bioluminescence assay. In addition, cardiac markers have been tested to be reviewed as a potential indicator for postoperative follow-up. Myocyte atypia and fibrosis were classified on a scale of 1 to 4. In this study, unlike patients with acyanotic CHD, alterations in mitochondrial network and reduction in ATP production were detected in all pediatric patients with cyanotic CHD. A statistically significant correlation was also determined between mitochondrial dysfunction and cardiac markers. These findings may be assumed as a promising pathway for evaluating the relationship between mitochondrial dysfunction and cyanotic CHD.

Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clustered in areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find that strong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.

Machine Learning Identification of Pro-arrhythmic Structures in Cardiac Fibrosis

Cardiac fibrosis and other scarring of the heart, arising from conditions ranging from myocardial infarction to ageing, promotes dangerous arrhythmias by blocking the healthy propagation of cardiac excitation. Owing to the complexity of the dynamics of electrical signalling in the heart, however, the connection between different arrangements of blockage and various arrhythmic consequences remains poorly understood. Where a mechanism defies traditional understanding, machine learning can be invaluable for enabling accurate prediction of quantities of interest (measures of arrhythmic risk) in terms of predictor variables (such as the arrangement or pattern of obstructive scarring). In this study, we simulate the propagation of the action potential (AP) in tissue affected by fibrotic changes and hence detect sites that initiate re-entrant activation patterns. By separately considering multiple different stimulus regimes, we directly observe and quantify the sensitivity of re-entry formation to activation sequence in the fibrotic region. Then, by extracting the fibrotic structures around locations that both do and do not initiate re-entries, we use neural networks to determine to what extent re-entry initiation is predictable, and over what spatial scale conduction heterogeneities appear to act to produce this effect. We find that structural information within about 0.5 mm of a given point is sufficient to predict structures that initiate re-entry with more than 90% accuracy.

Evaluation of the Cardioprotective Effect of Granulocyte Colony Stimulating Factor in Patients with Carbon Monoxide Poisoning

BACKGROUND

Carbon monoxide (CO), which is well known as silent killer, has many toxic effects on organs with high rate of metabolism such as heart and brain. CO-induced cardiotoxicity resulted in a wide range of disabilities including electrocardiogram (ECG) abnormalities, elevation in level of cardiac enzymes, arrhythmias, impairment of left ventricular and myocardial infarction (MI). Cardio-protective effects of Granulocyte colony-stimulating factor (G-CSF) on infarcted heart was proved previously in various reports.

OBJECTIVE

In this study, possible effect of G-CSF on cardiac function of patients with moderate to severe acute CO poisoning was investigated.

METHODS

Cardioprotective effects of G-CSF in CO-poisoned patients was evaluated through ECG, Holter monitoring, echocardiography, and biochemical studies. Continuous intravenous infusion of G-CSF (90 μg/kg) and normal saline were administered respectively to treatment and placebo groups.

RESULTS

The results demonstrated that in moderate to severe CO poisoning, myocardial injury is common. ECG changes (e.g., ST-segment and T-wave changes, QTC), cardiac arrhythmias (e.g., heart blocks and ventricular arrhythmias), serum level of Troponin I, left ventricular ejection fraction were determined after G-CSF administration. Frequencies of ST depression, inversion or flatting of T wave and QTC in ECG were significantly reduced after G-CSF treatment. In addition, incidence of cardiac arrhythmias due to CO poisoning were reduced after G-CSF treatment. However, G-CSF did not exert protective effects on TPI level and function of left ventricular in CO-poisoned patients.

CONCLUSION

GCSF could probably reduce CO-induced cardiac ischemia in patients with acute CO poisoning.

CLINICAL TRIAL REGISTRATION

The trial protocol was registered in the Iranian Registry of Clinical Trials (http://www.irct.ir) registry (Irct ID: IRCT201607232083N7).

Burden of premature ventricular contractions beyond nonsustained ventricular tachycardia is related to the myocardial extracellular space expansion in patients with hypertrophic-cardiomyopathy

Background

Although nonsustained ventricular tachycardia (NSVT) is a risk factor for sudden cardiac death in hypertrophic‐cardiomyopathy (HCM), the impact of premature ventricular contraction (PVC) burden, in the absence of NSVT, is not well‐known.

Hypothesis

PVC burden may be associated with myocardial fibrosis and genetic mutations in patients with HCM.

Methods

Of the 212 patients prospectively enrolled to the HCM registry of genetics, 84 were evaluated with both cardiac magnetic resonance, 24‐hour Holter monitoring and genetic analysis. Among them, 71 patients have not been diagnosed with NSVT.

Results

Patients with NSVT (n = 13) had a higher late gadolinium enhancement (LGE) amount, extracellular volume fraction (ECV), and prevalence of sarcomere mutations compared with patients without NSVT. Among patients without NSVT, those with LGE (n = 46) had a higher total PVC (109 ± 332 vs 7 ± 13, P = .003) and PVC burden (0.114 ± 0.225 vs 0.008 ± 0.014%, P = .003) during 24‐hour Holter monitoring compared with others. The %LGE and global ECV were correlated with PVC burden (r = 0.377, P = .001; r = 0.401, P = .001). The optimal cutoff value for PVC number for LGE was 45 (37.0% and 100% sensitivity and specificity, respectively) with 0.733 of the area under the receiver operating characteristic‐curve (P < .001). Thick filament gene mutation was more prevalent in the higher PVC burden group (41.2% vs 16.7%, P = .048).

Conclusion

Total PVC burden is significantly related to increase in myocardial fibrosis in HCM patients without NSVT.

Cardiac computational modelling

Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's response. Within this framework, the Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective of the VHeart-SN network is the development of an integrated, modular and multiscale multiphysical computational model of the heart. This general objective is addressed through the following specific objectives: a) to integrate the different numerical methods and models taking into account the specificity of patients; b) to assist in advancing knowledge of the mechanisms associated with cardiac and vascular diseases; and c) to support the application of different personalized therapies. This article presents the current state of cardiac computational modelling and different scientific works conducted by the members of the network to gain greater understanding of the characteristics and usefulness of these models.

COVID-19: Electrophysiological mechanisms underlying sudden cardiac death during exercise with facemasks

The mandatory use of facemasks is a public health measure implemented by various countries in response to the novel coronavirus disease 19 (COVID-19) pandemic. However, there have been case reports of sudden cardiac death (SCD) with the wearing of facemasks during exercise. In this paper, we hypothesize that exercise with facemasks may increase the risk of ventricular tachycardia/ventricular fibrillation (VT/VF) leading to SCD via the development of acute and/or intermittent hypoxia and hypercapnia. We discuss the potential underlying mechanisms including increases in adrenergic stimulation and oxidative stress leading to electrophysiological abnormalities that promote arrhythmias via non-reentrant and reentrant mechanisms. Given the interplay of multiple variables contributing to the increased arrhythmic risk, we advise avoidance of a facemask during high intensity exercise, or if wearing of a mask is mandatory, exercise intensity should remain low to avoid precipitation of lethal arrhythmias. However, we cannot exclude the possibility of an arrhythmic substrate even with low intensity exercise especially in those with established chronic cardiovascular disease in whom baseline electrophysiological abnormalities may be found.

Acute effects of alcohol on cardiac electrophysiology and arrhythmogenesis: Insights from multiscale in silico analyses

Acute excessive ethyl alcohol (ethanol) consumption alters cardiac electrophysiology and can evoke cardiac arrhythmias, e.g., in 'holiday heart syndrome'. Ethanol acutely modulates numerous targets in cardiomyocytes, including ion channels, Ca²⁺-handling proteins and gap junctions. However, the mechanisms underlying ethanol-induced arrhythmogenesis remain incompletely understood and difficult to study experimentally due to the multiple electrophysiological targets involved and their potential interactions with preexisting electrophysiological or structural substrates. Here, we employed cellular- and tissue-level in-silico analyses to characterize the acute effects of ethanol on cardiac electrophysiology and arrhythmogenesis. Acute electrophysiological effects of ethanol were incorporated into human atrial and ventricular cardiomyocyte computer models: reduced I_Na, I_Ca,L, I_to, I_Kr and I_Kur, dual effects on I_K1 and I_K,ACh (inhibition at low and augmentation at high concentrations), and increased I_NCX and SR Ca²⁺ leak. Multiscale simulations in the absence or presence of preexistent atrial fibrillation or heart-failure-related remodeling demonstrated that low ethanol concentrations prolonged atrial action-potential duration (APD) without effects on ventricular APD. Conversely, high ethanol concentrations abbreviated atrial APD and prolonged ventricular APD. High ethanol concentrations promoted reentry in tissue simulations, but the extent of reentry promotion was dependent on the presence of altered intercellular coupling, and the degree, type, and pattern of fibrosis. Taken together, these data provide novel mechanistic insight into the potential proarrhythmic interactions between a preexisting substrate and acute changes in cardiac electrophysiology. In particular, acute ethanol exposure has concentration-dependent electrophysiological effects that differ between atria and ventricles, and between healthy and diseased hearts. Low concentrations of ethanol can have anti-fibrillatory effects in atria, whereas high concentrations promote the inducibility and maintenance of reentrant atrial and ventricular arrhythmias, supporting a role for limiting alcohol intake as part of cardiac arrhythmia management.

Stabilized hybrid discontinuous Galerkin finite element method for the cardiac monodomain equation

Numerical methods for solving the cardiac electrophysiology model, which describes the electrical activity in the heart, are proposed. The model problem consists of a nonlinear reaction-diffusion partial differential equation coupled to systems of ordinary differential equations that describes electrochemical reactions in cardiac cells. The proposed methods combine an operator splitting technique for the reaction-diffusion equation with primal hybrid methods for spatial discretization considering continuous or discontinuous approximations for the Lagrange multiplier. A static condensation is adopted to form a reduced global system in terms of the multiplier only. Convergence studies exhibit optimal rates of convergence and numerical experiments show that the proposed schemes can be more efficient than standard numerical techniques commonly used in this context when preconditioned iterative methods are used for the solution of linear systems.

Variability in electrophysiological properties and conducting obstacles controls re-entry risk in heterogeneous ischaemic tissue

Ischaemia, in which inadequate blood supply compromises and eventually kills regions of cardiac tissue, can cause many types of arrhythmia, some life-threatening. A significant component of this is the effects of the resulting hypoxia, and concomitant hyperklaemia and acidosis, on the electrophysiological properties of myocytes. Clinical and experimental data have also shown that regions of structural heterogeneity (fibrosis, necrosis, fibro-fatty infiltration) can act as triggers for arrhythmias under acute ischaemic conditions. Mechanistic models have successfully captured these effects in silico. However, the relative significance of these separate facets of the condition, and how sensitive arrhythmic risk is to the extents of each, is far less explored. In this work, we use partitioned Gaussian process emulation and new metrics for source-sink mismatch that rely on simulations of bifurcating cardiac fibres to interrogate a model of heterogeneous ischaemic tissue. Re-entries were most sensitive to the level of hypoxia and the fraction of non-excitable tissue. In addition, our results reveal both protective and pro-arrhythmic effects of hyperklaemia, and present the levels of hyperklaemia, hypoxia and percentage of non-excitable tissue that pose the highest arrhythmic risks. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.