Digital twinning of the human ventricular activation sequence to Clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials

Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using human-based modelling and simulation. These technologies can provide mechanistic explanations for clinically observed pathological behaviour. Designing virtual cohorts for in silico trials requires exploiting clinical data to capture the physiological variability in the human population. The clinical characterisation of ventricular activation and the Purkinje network is challenging, especially non-invasively. Our study aims to present a novel digital twinning pipeline that can efficiently generate and integrate Purkinje networks into human multiscale biventricular models based on subject-specific clinical 12-lead electrocardiogram and magnetic resonance recordings. Essential novel features of the pipeline are the human-based Purkinje network generation method, personalisation considering ECG R wave progression as well as QRS morphology, and translation from reduced-order Eikonal models to equivalent biophysically-detailed monodomain ones. We demonstrate ECG simulations in line with clinical data with clinical image-based multiscale models with Purkinje in four control subjects and two hypertrophic cardiomyopathy patients (simulated and clinical QRS complexes with Pearson's correlation coefficients > 0.7). Our methods also considered possible differences in the density of Purkinje myocardial junctions in the Eikonal-based inference as regional conduction velocities. These differences translated into regional coupling effects between Purkinje and myocardial models in the monodomain formulation. In summary, we demonstrate a digital twin pipeline enabling simulations yielding clinically consistent ECGs with clinical CMR image-based biventricular multiscale models, including personalised Purkinje in healthy and cardiac disease conditions.

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 repolarisation, and (iii) ischaemia, impaired repolarisation, and diffuse fibrosis.HCM cardiomyocytes exhibited enhanced action potential and abnormal effective refractory period shortening to ischaemic insults. Analysis of c.a. 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.

CONCLUSIONS

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.

Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment

This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (P < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771-0.777) vs. 0.683 (0.681-0.685) cross-validated AUC, P < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment.

Effects of ranolazine on the arrhythmic substrate in hypertrophic cardiomyopathy

Introduction: Hypertrophic cardiomyopathy (HCM) is a leading cause of lethal arrhythmias in the young. Although the arrhythmic substrate has been hypothesised to be amenable to late Na+ block with ranolazine, the specific mechanisms are not fully understood. Therefore, this study aimed to investigate the substrate mechanisms of safety and antiarrhythmic efficacy of ranolazine in HCM. Methods: Computational models of human tissue and ventricles were used to simulate the electrophysiological behaviour of diseased HCM myocardium for variable degrees of repolarisation impairment, validated against in vitro and clinical recordings. S1-S2 pacing protocols were used to quantify arrhythmic risk in scenarios of (i) untreated HCM-remodelled myocardium and (ii) myocardium treated with 3µM, 6µM and 10µM ranolazine, for variable repolarisation heterogeneity sizes and pacing rates. ECGs were derived from biventricular simulations to identify ECG biomarkers linked to antiarrhythmic effects. Results: 10µM ranolazine given to models manifesting ventricular tachycardia (VT) at baseline led to a 40% reduction in number of VT episodes on pooled analysis of >40,000 re-entry inducibility simulations. Antiarrhythmic efficacy and safety were dependent on the degree of repolarisation impairment, with optimal benefit in models with maximum JTc interval <370 ms. Ranolazine increased risk of VT only in models with severe-extreme repolarisation impairment. Conclusion: Ranolazine efficacy and safety may be critically dependent upon the degree of repolarisation impairment in HCM. For moderate repolarisation impairment, reductions in refractoriness heterogeneity by ranolazine may prevent conduction blocks and re-entry. With severe-extreme disease substrates, reductions of the refractory period can increase re-entry sustainability.

Electrophysiological mechanisms underlying T wave pseudonormalisation on stress ECGs in hypertrophic cardiomyopathy

BACKGROUND

Pseudonormal T waves may be detected on stress electrocardiograms (ECGs) in hypertrophic cardiomyopathy (HCM). Either myocardial ischaemia or purely exercise-induced changes have been hypothesised to contribute to this phenomenon, but the precise electrophysiological mechanisms remain unknown.

METHODS

Computational models of human HCM ventricles (n = 20) with apical and asymmetric septal hypertrophy phenotypes with variable severities of repolarisation impairment were used to investigate the effects of acute myocardial ischaemia on ECGs with T wave inversions at baseline. Virtual 12-lead ECGs were derived from a total of 520 biventricular simulations, for cases with regionally ischaemic K+ accumulation in hypertrophied segments, global exercise-induced serum K+ increases, and/or increased pacing frequency, to analyse effects on ECG biomarkers including ST segments, T wave amplitudes, and QT intervals.

RESULTS

Regional ischaemic K+ accumulation had a greater impact on T wave pseudonormalisation than exercise-induced serum K+ increases, due to larger reductions in repolarisation gradients. Increases in serum K+ and pacing rate partially corrected T waves in some anatomical and electrophysiological phenotypes. T wave morphology was more sensitive than ST segment elevation to regional K+ increases, suggesting that T wave pseudonormalisation may sometimes be an early, or the only, ECG feature of myocardial ischaemia in HCM.

CONCLUSIONS

Ischaemia-induced T wave pseudonormalisation can occur on stress ECG testing in HCM before significant ST segment changes. Some anatomical and electrophysiological phenotypes may enable T wave pseudonormalisation due to exercise-induced increased serum K+ and pacing rate. Consideration of dynamic T wave abnormalities could improve the detection of myocardial ischaemia in HCM.

Mechanisms and prognostic impact of myocardial ischaemia in hypertrophic cardiomyopathy

Despite the progress made in risk stratification, sudden cardiac death and heart failure remain dreaded complications for hypertrophic cardiomyopathy (HCM) patients. Myocardial ischaemia is widely acknowledged as a contributor to cardiovascular events, but the assessment of ischaemia is not yet included in HCM clinical guidelines. This review aims to evaluate the HCM-specific pro-ischaemic mechanisms and the potential prognostic value of imaging for myocardial ischaemia in HCM. A literature review was performed using PubMed to identify studies with non-invasive imaging of ischaemia (cardiovascular magnetic resonance, echocardiography, and nuclear imaging) in HCM, prioritising studies published after the last major review in 2009. Other studies, including invasive ischaemia assessment and post-mortem histology, were also considered for mechanistic or prognostic relevance. Pro-ischaemic mechanisms in HCM reviewed included the effects of sarcomeric mutations, microvascular remodelling, hypertrophy, extravascular compressive forces and left ventricular outflow tract obstruction. The relationship between ischaemia and fibrosis was re-appraised by considering segment-wise analyses in multimodal imaging studies. The prognostic significance of myocardial ischaemia in HCM was evaluated using longitudinal studies with composite endpoints, and reports of ischaemia-arrhythmia associations were further considered. The high prevalence of ischaemia in HCM is explained by several micro- and macrostructural pathological features, alongside mutation-associated energetic impairment. Ischaemia on imaging identifies a subgroup of HCM patients at higher risk of adverse cardiovascular outcomes. Ischaemic HCM phenotypes are a high-risk subgroup associated with more advanced left ventricular remodelling, but further studies are required to evaluate the independent prognostic value of non-invasive imaging for ischaemia.

Lysosomal calcium loading promotes spontaneous calcium release by potentiating ryanodine receptors

Spontaneous calcium release by ryanodine receptors (RyRs) due to intracellular calcium overload results in delayed afterdepolarizations, closely associated with life-threatening arrhythmias. In this regard, inhibiting lysosomal calcium release by two-pore channel 2 (TPC2) knockout has been shown to reduce the incidence of ventricular arrhythmias under β-adrenergic stimulation. However, mechanistic investigations into the role of lysosomal function on RyR spontaneous release remain missing. We investigate the calcium handling mechanisms by which lysosome function modulates RyR spontaneous release, and determine how lysosomes are able to mediate arrhythmias by its influence on calcium loading. Mechanistic studies were conducted using a population of biophysically detailed mouse ventricular models including for the first time modeling of lysosomal function, and calibrated by experimental calcium transients modulated by TPC2. We demonstrate that lysosomal calcium uptake and release can synergistically provide a pathway for fast calcium transport, by which lysosomal calcium release primarily modulates sarcoplasmic reticulum calcium reuptake and RyR release. Enhancement of this lysosomal transport pathway promoted RyR spontaneous release by elevating RyR open probability. In contrast, blocking either lysosomal calcium uptake or release revealed an antiarrhythmic impact. Under conditions of calcium overload, our results indicate that these responses are strongly modulated by intercellular variability in L-type calcium current, RyR release, and sarcoplasmic reticulum calcium-ATPase reuptake. Altogether, our investigations identify that lysosomal calcium handling directly influences RyR spontaneous release by regulating RyR open probability, suggesting antiarrhythmic strategies and identifying key modulators of lysosomal proarrhythmic action.

Slower Calcium Handling Balances Faster Cross-Bridge Cycling in Human MYBPC3 HCM

BACKGROUND

The pathogenesis of MYBPC3-associated hypertrophic cardiomyopathy (HCM) is still unresolved. In our HCM patient cohort, a large and well-characterized population carrying the MYBPC3:c772G>A variant (p.Glu258Lys, E258K) provides the unique opportunity to study the basic mechanisms of MYBPC3-HCM with a comprehensive translational approach.

METHODS

We collected clinical and genetic data from 93 HCM patients carrying the MYBPC3:c772G>A variant. Functional perturbations were investigated using different biophysical techniques in left ventricular samples from 4 patients who underwent myectomy for refractory outflow obstruction, compared with samples from non-failing non-hypertrophic surgical patients and healthy donors. Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes and engineered heart tissues (EHTs) were also investigated.

RESULTS

Haplotype analysis revealed MYBPC3:c772G>A as a founder mutation in Tuscany. In ventricular myocardium, the mutation leads to reduced cMyBP-C (cardiac myosin binding protein-C) expression, supporting haploinsufficiency as the main primary disease mechanism. Mechanical studies in single myofibrils and permeabilized muscle strips highlighted faster cross-bridge cycling, and higher energy cost of tension generation. A novel approach based on tissue clearing and advanced optical microscopy supported the idea that the sarcomere energetics dysfunction is intrinsically related with the reduction in cMyBP-C. Studies in single cardiomyocytes (native and hiPSC-derived), intact trabeculae and hiPSC-EHTs revealed prolonged action potentials, slower Ca2+ transients and preserved twitch duration, suggesting that the slower excitation-contraction coupling counterbalanced the faster sarcomere kinetics. This conclusion was strengthened by in silico simulations.

CONCLUSIONS

HCM-related MYBPC3:c772G>A mutation invariably impairs sarcomere energetics and cross-bridge cycling. Compensatory electrophysiological changes (eg, reduced potassium channel expression) appear to preserve twitch contraction parameters, but may expose patients to greater arrhythmic propensity and disease progression. Therapeutic approaches correcting the primary sarcomeric defects may prevent secondary cardiomyocyte remodeling.

Homogenisation for the monodomain model in the presence of microscopic fibrotic structures

Computational models in cardiac electrophysiology are notorious for long runtimes, restricting the numbers of nodes and mesh elements in the numerical discretisations used for their solution. This makes it particularly challenging to incorporate structural heterogeneities on small spatial scales, preventing a full understanding of the critical arrhythmogenic effects of conditions such as cardiac fibrosis. In this work, we explore the technique of homogenisation by volume averaging for the inclusion of non-conductive micro-structures into larger-scale cardiac meshes with minor computational overhead. Importantly, our approach is not restricted to periodic patterns, enabling homogenised models to represent, for example, the intricate patterns of collagen deposition present in different types of fibrosis. We first highlight the importance of appropriate boundary condition choice for the closure problems that define the parameters of homogenised models. Then, we demonstrate the technique's ability to correctly upscale the effects of fibrotic patterns with a spatial resolution of 10 µm into much larger numerical mesh sizes of 100- 250 µm . The homogenised models using these coarser meshes correctly predict critical pro-arrhythmic effects of fibrosis, including slowed conduction, source/sink mismatch, and stabilisation of re-entrant activation patterns. As such, this approach to homogenisation represents a significant step towards whole organ simulations that unravel the effects of microscopic cardiac tissue heterogeneities.

Interpretable cardiac anatomy modeling using variational mesh autoencoders

Cardiac anatomy and function vary considerably across the human population with important implications for clinical diagnosis and treatment planning. Consequently, many computer-based approaches have been developed to capture this variability for a wide range of applications, including explainable cardiac disease detection and prediction, dimensionality reduction, cardiac shape analysis, and the generation of virtual heart populations. In this work, we propose a variational mesh autoencoder (mesh VAE) as a novel geometric deep learning approach to model such population-wide variations in cardiac shapes. It embeds multi-scale graph convolutions and mesh pooling layers in a hierarchical VAE framework to enable direct processing of surface mesh representations of the cardiac anatomy in an efficient manner. The proposed mesh VAE achieves low reconstruction errors on a dataset of 3D cardiac meshes from over 1,000 patients with acute myocardial infarction, with mean surface distances between input and reconstructed meshes below the underlying image resolution. We also find that it outperforms a voxelgrid-based deep learning benchmark in terms of both mean surface distance and Hausdorff distance while requiring considerably less memory. Furthermore, we explore the quality and interpretability of the mesh VAE's latent space and showcase its ability to improve the prediction of major adverse cardiac events over a clinical benchmark. Finally, we investigate the method's ability to generate realistic virtual populations of cardiac anatomies and find good alignment between the synthesized and gold standard mesh populations in terms of multiple clinical metrics.

Remodelling of potassium currents underlies arrhythmic action potential prolongation under beta-adrenergic stimulation in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) patients often present an enhanced arrhythmogenicity that can lead to lethal arrhythmias, especially during exercise. Recent studies have indicated an abnormal response of HCM cardiomyocytes to β-adrenergic receptor stimulation (β-ARS), with prolongation of their action potential rather than shortening. The mechanisms underlying this aberrant response to sympathetic stimulation and its possible proarrhythmic role remain unknown. The aims of this study are to investigate the key ionic mechanisms underlying the HCM abnormal response to β-ARS and the resultant repolarisation abnormalities using human-based experimental and computational methodologies. We integrated and calibrated the latest models of human ventricular electrophysiology and β-ARS using experimental measurements of human adult cardiomyocytes from control and HCM patients. Our major findings include: (1) the developed in silico models of β-ARS capture the behaviour observed in the experimental data, including the aberrant response of HCM cardiomyocytes to β-ARS; (2) the reduced increase of potassium currents under β-ARS was identified as the main mechanism of action potential prolongation in HCM, rather than a more sustained inward calcium current; (3) action potential duration differences between healthy and HCM cardiomyocytes were increased upon β-ARS, while endocardial to epicardial differences in HCM cardiomyocytes were reduced; (4) models presenting repolarisation abnormalities were characterised by downregulation of the rapid delayed rectifier potassium current and the sodium‑potassium pump, while inward currents were upregulated. In conclusion, our results identify causal relationships between the HCM phenotype and its arrhythmogenic response to β-ARS through the downregulation of potassium currents.

Electrocardiogram metrics identify ionic current dysregulation relevant to atrial fibrillation

Background

Personalisation of pharmacological treatment for atrial fibrillation (AF) is challenging. Pharmacological ionic current blockers such as digoxin or flecainide are commonly used, with caution given possible cardiotoxicity and proarrhythmia. Moreover, patients are stratified based on their associated heart disease rather than individual electrophysiological substrate, in part due to the inability for its non-invasive characterisation. Here we hypothesise that the ECG may contain information on key ionic currents regulating AF initiation and sustenance, and which would enable personalisation of pharmacological treatments to increase safety and efficacy.

Purpose

To identify clinical ECG markers that reflect dysregulation of key ionic currents for AF using modelling and simulation in populations of whole-atria models without structural heart disease.

Methods

Experimental data obtained from human AF and control patients was used to develop a virtual population of 200 whole-atria models (Figure, organ-level) with individual ionic profiles (Figure 1, bottom-left), including electrophysiological regional inhomogeneities (Figure 1, bottom-right). Modified-limb 12 lead ECGs were computed during sinus rhythm (Figure 1, body-surface-level) and biomarkers were quantified for the P and Ta-waves, such as duration, time-to-peak, decay, dispersion, amplitude and P-wave terminal force.

Results

Simulated modified-limb ECG consistently reproduced the clinical ECG observed in human subjects, with an apparent Ta-wave inversion in lead II (Figure 1, body-surface-level). The inward rectified K+ current (IK1), known to be critical for AF, was the only ionic current associated with Ta-wave duration, showing an inversely proportional relationship (236±48 vs. 466±53 ms, IK1 up-regulation vs. down-regulation in lead V5; median ± interquartile range; P&lt;0.001). Elevated IK1 additionally yield Ta-wave inversion in lead V5 and a higher Ta-wave magnitude in lead II (0.15±0.03 vs. 0.07±0.04 mV, IK1 up-regulation vs. down-regulation; P&lt;0.001). However, Ta-wave magnitude showed a predominant relationship with the Na+/K+ pump (INaK), especially in the precordial leads (0.17±0.13 vs. 0.07±0.04 mV, INaK up-regulation vs. down-regulation in V5; P&lt;0.001). Thus, the up-regulation of both currents led to very short, high-amplitude Ta-waves. While elevated IK1 additionally increased the P-wave terminal force (1.58±0.37 vs. 1.31±0.33 mV ms, IK1 up-regulation vs. down-regulation; P&lt;0.001), a higher increase was observed for decreased fast Na+ current (INa) (1.35±0.17 vs. 1.86±0.30 mV ms, INa up-regulation vs. down-regulation; P&lt;0.001).

Conclusion

Ta-wave duration and amplitude are revealing of IK1 and INaK dysregulation, respectively, holding potential for improving cardiac safety and efficacy through a better stratification of AF patients for pharmacological treatment.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 860974

In-silico drug trials for precision medicine in atrial fibrillation: From ionic mechanisms to electrocardiogram-based predictions in structurally-healthy human atria

Atrial fibrillation (AF) inducibility, sustainability and response to pharmacological treatment of individual patients are expected to be determined by their ionic current properties, especially in structurally-healthy atria. Mechanisms underlying AF and optimal cardioversion are however still unclear. In this study, in-silico drug trials were conducted using a population of human structurally-healthy atria models to 1) identify key ionic current properties determining AF inducibility, maintenance and pharmacological cardioversion, and 2) compare the prognostic value for predicting individual AF cardioversion of ionic current properties and electrocardiogram (ECG) metrics. In the population of structurally-healthy atria, 477 AF episodes were induced in ionic current profiles with both steep action potential duration (APD) restitution (eliciting APD alternans), and high excitability (enabling propagation at fast rates that transformed alternans into discordant). High excitability also favored 211 sustained AF episodes, so its decrease, through prolonged refractoriness, explained pharmacological cardioversion. In-silico trials over 200 AF episodes, 100 ionic profiles and 10 antiarrhythmic compounds were consistent with previous clinical trials, and identified optimal treatments for individual electrophysiological properties of the atria. Algorithms trained on 211 simulated AF episodes exhibited >70% accuracy in predictions of cardioversion for individual treatments using either ionic current profiles or ECG metrics. In structurally-healthy atria, AF inducibility and sustainability are enabled by discordant alternans, under high excitability and steep restitution conditions. Successful pharmacological cardioversion is predicted with 70% accuracy from either ionic or ECG properties, and it is optimal for treatments maximizing refractoriness (thus reducing excitability) for the given ionic current profile of the atria.

Understanding and Improving Risk Assessment After Myocardial Infarction Using Automated Left Ventricular Shape Analysis

BACKGROUND

Left ventricular ejection fraction (LVEF) and end-systolic volume (ESV) remain the main imaging biomarkers for post-acute myocardial infarction (AMI) risk stratification. However, they are limited to global systolic function and fail to capture functional and anatomical regional abnormalities, hindering their performance in risk stratification.

OBJECTIVES

This study aimed to identify novel 3-dimensional (3D) imaging end-systolic (ES) shape and contraction descriptors toward risk-related features and superior prognosis in AMI.

METHODS

A multicenter cohort of AMI survivors (n = 1,021; median age 63 years; 74.5% male) who underwent cardiac magnetic resonance (CMR) at a median of 3 days after infarction were considered for this study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE; n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. A fully automated pipeline was developed to segment CMR images, build 3D statistical models of shape and contraction in AMI, and find the 3D patterns related to MACE occurrence.

RESULTS

The novel ES shape markers proved to be superior to ESV (median cross-validated area under the receiver-operating characteristic curve 0.681 [IQR: 0.679-0.684] vs 0.600 [IQR: 0.598-0.602]; P < 0.001); and 3D contraction to LVEF (0.716 [IQR: 0.714-0.718] vs 0.681 [IQR: 0.679-0.684]; P < 0.001) in MACE occurrence prediction. They also contributed to a significant improvement in a multivariable setting including CMR markers, cardiovascular risk factors, and basic patient characteristics (0.747 [IQR: 0.745-0.749]; P < 0.001). Based on these novel 3D descriptors, 3 impairments caused by AMI were identified: global, anterior, and basal, the latter being the most complementary signature to already known predictors.

CONCLUSIONS

The quantification of 3D differences in ES shape and contraction, enabled by a fully automated pipeline, improves post-AMI risk prediction and identifies shape and contraction patterns related to MACE occurrence.

Graph-based homogenisation for modelling cardiac fibrosis

Fibrosis, the excess of extracellular matrix, can affect, and even block, propagation of action potential in cardiac tissue. This can result in deleterious effects on heart function, but the nature and severity of these effects depend strongly on the localisation of fibrosis and its by-products in cardiac tissue, such as collagen scar formation. Computer simulation is an important means of understanding the complex effects of fibrosis on activation patterns in the heart, but concerns of computational cost place restrictions on the spatial resolution of these simulations. In this work, we present a novel numerical homogenisation technique that uses both Eikonal and graph approaches to allow fine-scale heterogeneities in conductivity to be incorporated into a coarser mesh. Homogenisation achieves this by deriving effective conductivity tensors so that a coarser mesh can then be used for numerical simulation. By taking a graph-based approach, our homogenisation technique functions naturally on irregular grids and does not rely upon any assumptions of periodicity, even implicitly. We present results of action potential propagation through fibrotic tissue in two dimensions that show the graph-based homogenisation technique is an accurate and effective way to capture fine-scale domain information on coarser meshes in the context of sharp-fronted travelling waves of activation. As test problems, we consider excitation propagation in tissue with diffuse fibrosis and through a tunnel-like structure designed to test homogenisation, interaction of an excitation wave with a scar region, and functional re-entry.

Paradoxical prolongation of QT interval during exercise in patients with hypertrophic cardiomyopathy: cellular mechanisms and implications for diastolic function

Aims

Ventricular cardiomyocytes from hypertrophic cardiomyopathy (HCM) patient hearts show prolonged action potential duration (APD), impaired intracellular Ca²⁺ homeostasis and abnormal electrical response to beta -adrenergic stimulation. We sought to determine whether this behaviour is associated with abnormal changes of repolarization during exercise and worsening of diastolic function, ultimately explaining the intolerance to exercise experienced by some patients without obstruction.

Methods and results

Non-obstructive HCM patients (178) and control subjects (81) underwent standard exercise testing, including exercise echocardiography. Ventricular myocytes were isolated from myocardial samples of 23 HCM and eight non-failing non-hypertrophic surgical patients. The APD shortening in response to high frequencies was maintained in HCM myocytes, while β-adrenergic stimulation unexpectedly prolonged APDs, ultimately leading to a lesser shortening of APDs in response to exercise. In HCM vs. control subjects, we observed a lesser shortening of QT interval at peak exercise (QTc: +27 ± 52 ms in HCM, −4 ± 50 ms in controls, P < 0.0001). In patients showing a marked QTc prolongation (>30 ms), the excessive shortening of the electrical diastolic period was linked with a limited increase of heart-rate and deterioration of diastolic function at peak effort.

Conclusions

Abnormal balance of Ca²⁺- and K⁺-currents in HCM cardiomyocytes determines insufficient APD and Ca²⁺-transient shortening with exercise. In HCM patients, exercise-induced QTc prolongation was associated with impaired diastolic reserve, contributing to the reduced exercise tolerance. Our results support the idea that severe electrical cardiomyocyte abnormalities underlie exercise intolerance in a subgroup of HCM patients without obstruction.

CalTrack: High-Throughput Automated Calcium Transient Analysis in Cardiomyocytes

[Figure: see text].

Human-based computational and experimental investigation of disease mechanisms in mutation-specific hypertrophic cardiomyopathy

Funding Acknowledgements

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 764738. British Heart Foundation Intermediate Basic Science Fellowship (FS/17/22/32644).

Background

The pathogenic TNNI3R21C/+ variant causes malignant hypertrophic cardiomyopathy (HCM) with high incidence of sudden cardiac death, even in individuals absent of hypertrophy. There is evidence to support a known biophysical defect in the protein, yet the cellular mechanisms that precipitate adverse clinical outcomes remain unclear.

Purpose

We aim to computationally model and map the TNNI3R21C/+ cellular phenotype observed in induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) to human disease, thereby explaining the key mechanisms driving HCM in TNNI3R21C/+ variant carriers. 

Methods

Wild-type (WT) and TNNI3R21C/+ iPSC-CMs were characterised by calcium transient analysis and direct sarcomere tracking to assess cellular contraction and relaxation. In-vitro data was used to inform the in-silico modelling of human cardiomyocytes. We constructed an in-silico population of WT adult cardiomyocytes and used it to transform the in-vitro data into corresponding adult phenotypes by means of a novel iPSC-to-adult data mapping. We tested the hypothesis that the abnormal TNNI3R21C/+ phenotype observed in iPSC-CMs would be explained by alterations in calcium affinity of troponin and increased myofilament calcium sensitivity. 

Results

Analysis of in-vitro iPSC-CM data showed that TNNI3R21C/+ cells exhibit increased contractility with slowed relaxation when compared to WT. They also exhibited a faster rise in the calcium transient with a slowed calcium decay in comparison to WT. The in-silico adult TNNI3R21C/+ phenotype from the iPSC-to-adult mapping replicated the abnormalities observed in iPSC-CMs. The WT in-silico population accurately covered the ranges of electromechanical biomarkers providing a representative cohort of physiological variability. The TNNI3R21C/+ calcium phenotype could be recovered by our in-silico mutant models. Simulation results suggest that calcium abnormalities in TNNI3R21C/+ are a direct consequence of abnormal calcium buffering by thin filaments, mediated by increases in calcium affinity of troponin and myofilament calcium sensitivity. The TNNI3R21C/+ phenotype could not be recovered if these two factors were considered in isolation. Corresponding contractility analyses of in-silico models showed that the calcium level changes caused by the TNNI3R21C/+ phenotype are associated with hypercontractility and diastolic dysfunction, well-known hallmarks of HCM, which were also observed in the iPSC-CM model of disease.

Conclusions

This study showcases human-based computational and experimental methodologies that unearth direct mechanistic explanations of phenotypes driven by the TNNI3R21C/+ HCM variant. We show that the TNNI3R21C/+ HCM-causing mutation exhibits multifactorial remodelling of troponin calcium affinity and myofilament calcium sensitivity. Unearthing mechanistic pathways in mutation-specific HCM will be key to develop effective pharmacological interventions for a wide variety of understudied variants.

Characterization and modelling of the abnormal electrophysiological response under beta-adrenergic stimulation in hypertrophic cardiomyopathy

Funding Acknowledgements

Type of funding sources: Foundation. Main funding source(s): British Heart Foundation

Introduction

Hypertrophic Cardiomyopathy (HCM) is the most common inheritable heart pathology and the main cause of sudden cardiac death in young adults. HCM patients often present an enhanced arrhythmogenicity that can lead to lethal arrhythmias, especially during exercise. Recent studies have shown an abnormal response of HCM myocytes to β-adrenergic stimulation (β-ARS), with prolongation of their action potential duration (APD). The mechanisms underlying this aberrant response to sympathetic stimulation remain unknown.

Purpose

To investigate the key ionic mechanisms underlying the HCM abnormal response to β-ARS using human-based experimental and computational methodologies.

Methods

Experimental ionic currents, action potential and calcium transient were recorded in human adult cardiomyocytes from control and HCM patients. Isoproterenol (10-7 mol/L) was used to elicit β-ARS. Whole-cell ruptured patch voltage clamp experiments were conducted to characterise L-type calcium and potassium currents, with recordings performed before and after 3 min of drug exposure. The latest models of human ventricular electrophysiology and beta-adrenergic receptor signalling were integrated and calibrated using the human measured data. Simulations under isoproterenol were performed to quantify the effects of β-ARS on the action potential and calcium transient. The role of the main ion currents affected by β-ARS and by HCM remodelling was evaluated.

Results

In vitro, isoproterenol shortened APD (-16 ± 3%) in control, while prolonging APD in HCM myocytes (+23 ± 8%). Analysis of the measured data indicated two possible mechanisms contributing to APD prolongation in HCM myocytes. Firstly, a protracted L-type calcium current, presenting slower inactivation kinetics in HCM compared to control. The relative increase of potassium currents under β-ARS was also lower in HCM myocytes. The developed in silico models of β-ARS replicated the behaviour observed in the experimental data, based on slower L-type calcium current inactivation kinetics and a smaller increase of potassium currents in HCM. In absence of β-ARS, simulated HCM cardiomyocytes exhibited prolonged APD compared to control (525 ± 88 vs 281 ± 56 ms, p &lt; 0.001). Under β-ARS, APD in control was reduced (-16.46%), whereas APD was prolonged in HCM (+11.63%). Further analysis showed that the reduction of the potassium currents increment under β-ARS was the main cause of the APD prolongation in HCM myocytes, with L-type calcium inactivation minimally contributing to APD prolongation.

Conclusions

In this study we assessed the effects of β-ARS on ion currents and APD in control and HCM myocytes. Our modelling results suggest that the increase of potassium repolarising currents under β-ARS is greatly reduced in HCM cardiomyocytes, being the main mechanism underlying their APD prolongation. This APD prolongation may have severe consequences in HCM patients, increasing the risk of exercise-induced arrhythmias. Abstract Figure.

Toward a broader view of mechanisms of drug cardiotoxicity

Cardiotoxicity, defined as toxicity that affects the heart, is one of the most common adverse drug effects. Numerous drugs have been shown to have the potential to induce lethal arrhythmias by affecting cardiac electrophysiology, which is the focus of current preclinical testing. However, a substantial number of drugs can also affect cardiac function beyond electrophysiology. Within this broader sense of cardiotoxicity, this review discusses the key drug-protein interactions known to be involved in cardiotoxic drug response. We cover adverse effects of anticancer, central nervous system, genitourinary system, gastrointestinal, antihistaminic, anti-inflammatory, and anti-infective agents, illustrating that many share mechanisms of cardiotoxicity, including contractility, mitochondrial function, and cellular signaling.

The 'Digital Twin' to enable the vision of precision cardiology

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Electrophysiological and anatomical factors determine arrhythmic risk in acute myocardial ischaemia and its modulation by sodium current availability

Acute myocardial ischaemia caused by coronary artery disease is one of the main causes of sudden cardiac death. Even though sodium current blockers are used as anti-arrhythmic drugs, decreased sodium current availability, also caused by mutations, has been shown to increase arrhythmic risk in ischaemic patients. The mechanisms are still unclear. Our goal is to exploit perfect control and data transparency of over 300 high-performance computing simulations to investigate arrhythmia mechanisms in acute myocardial ischaemia with variable sodium current availability. The human anatomically based torso-biventricular electrophysiological model used includes representation of realistic ventricular anatomy and fibre architecture, as well as ionic to electrocardiographic properties. Simulations show that reduced sodium current availability increased arrhythmic risk in acute regional ischaemia due to both electrophysiological (increased dispersion of refractoriness across the ischaemic border zone) and anatomical factors (conduction block from the thin right ventricle to thick left ventricle). The asymmetric ventricular anatomy caused high arrhythmic risk specifically for ectopic stimuli originating from the right ventricle and ventricular base. Increased sodium current availability was ineffective in reducing arrhythmic risk for septo-basal ectopic excitation. Human-based multiscale modelling and simulations reveal key electrophysiological and anatomical factors determining arrhythmic risk in acute ischaemia with variable sodium current availability.

Dual Transcriptomic and Molecular Machine Learning Predicts all Major Clinical Forms of Drug Cardiotoxicity

Computational methods can increase productivity of drug discovery pipelines, through overcoming challenges such as cardiotoxicity identification. We demonstrate prediction and preservation of cardiotoxic relationships for six drug-induced cardiotoxicity types using a machine learning approach on a large collected and curated dataset of transcriptional and molecular profiles (1,131 drugs, 35% with known cardiotoxicities, and 9,933 samples). The algorithm generality is demonstrated through validation in an independent drug dataset, in addition to cross-validation. The best prediction attains an average accuracy of 79% in area under the curve (AUC) for safe versus risky drugs, across all six cardiotoxicity types on validation and 66% on the unseen set of drugs. Individual cardiotoxicities for specific drug types are also predicted with high accuracy, including cardiac disorder signs and symptoms for a previously unseen set of anti-inflammatory agents (AUC = 80%) and heart failures for an unseen set of anti-neoplastic agents (AUC = 76%). Besides, independent testing on transcriptional data from the Drug Toxicity Signature Generation Center (DToxS) produces similar results in terms of accuracy and shows an average AUC of 72% for previously seen drugs and 60% for unseen respectively. Given the ubiquitous manifestation of multiple drug adverse effects in every human organ, the methodology is expected to be applicable to additional tissue-specific side effects beyond cardiotoxicity.

Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers

The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation software. In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation-contraction and active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200% - 1000% variations in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction ( k ort 2 ); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered ( P ej ) and the compliance of the Windkessel fluid model ( C ); and the longitudinal fractional shortening is dominated by the fibre angle ( ϕ ) and k ort 2 . The wall thickening does not seem to be clearly dominated by any of the considered input parameters. In summary, this study presents in detail the description and implementation of a human-based coupled electromechanical modelling and simulation framework, and a high performance computing study on the sensitivity of mechanical biomarkers to key model parameters. The tools and knowledge generated enable future investigations into disease and drug action on human ventricles.

Chaste: Cancer, Heart and Soft Tissue Environment

Chaste (Cancer, Heart And Soft Tissue Environment) is an open source simulation package for the numerical solution of mathematical models arising in physiology and biology. To date, Chaste development has been driven primarily by applications that include continuum modelling of cardiac electrophysiology ('Cardiac Chaste'), discrete cell-based modelling of soft tissues ('Cell-based Chaste'), and modelling of ventilation in lungs ('Lung Chaste'). Cardiac Chaste addresses the need for a high-performance, generic, and verified simulation framework for cardiac electrophysiology that is freely available to the scientific community. Cardiac chaste provides a software package capable of realistic heart simulations that is efficient, rigorously tested, and runs on HPC platforms. Cell-based Chaste addresses the need for efficient and verified implementations of cell-based modelling frameworks, providing a set of extensible tools for simulating biological tissues. Computational modelling, along with live imaging techniques, plays an important role in understanding the processes of tissue growth and repair. A wide range of cell-based modelling frameworks have been developed that have each been successfully applied in a range of biological applications. Cell-based Chaste includes implementations of the cellular automaton model, the cellular Potts model, cell-centre models with cell representations as overlapping spheres or Voronoi tessellations, and the vertex model. Lung Chaste addresses the need for a novel, generic and efficient lung modelling software package that is both tested and verified. It aims to couple biophysically-detailed models of airway mechanics with organ-scale ventilation models in a package that is freely available to the scientific community. Chaste is designed to be modular and extensible, providing libraries for common scientific computing infrastructure such as linear algebra operations, finite element meshes, and ordinary and partial differential equation solvers. This infrastructure is used by libraries for specific applications, such as continuum mechanics, cardiac models, and cell-based models. The software engineering techniques used to develop Chaste are intended to ensure code quality, re-usability and reliability. Primary applications of the software include cardiac and respiratory physiology, cancer and developmental biology.

Blinded In Silico Drug Trial Reveals the Minimum Set of Ion Channels for Torsades de Pointes Risk Assessment

Torsades de Pointes (TdP) is a type of ventricular arrhythmia which could be observed as an unwanted drug-induced cardiac side effect, and it is associated with repolarization abnormalities in single cells. The pharmacological evaluations of TdP risk in previous years mainly focused on the hERG channel due to its vital role in the repolarization of cardiomyocytes. However, only considering drug effects on hERG led to false positive predictions since the drug action on other ion channels can also have crucial regulatory effects on repolarization. To address the limitation of only evaluating hERG, the Comprehensive in Vitro Proarrhythmia Assay initiative has proposed to systematically integrate drug effects on multiple ion channels into in silico drug trial to improve TdP risk assessment. It is not clear how many ion channels are sufficient for reliable TdP risk predictions, and whether differences in IC₅₀ and Hill coefficient values from independent sources can lead to divergent in silico prediction outcomes. The rationale of this work is to investigate the above two questions using a computationally efficient population of human ventricular cells optimized to favor repolarization abnormality. Our blinded results based on two independent data sources confirm that simulations with the optimized population of human ventricular cell models enable efficient in silico drug screening, and also provide direct observation and mechanistic analysis of repolarization abnormality. Our results show that 1) the minimum set of ion channels required for reliable TdP risk predictions are Nav1.5 (peak), Cav1.2, and hERG; 2) for drugs with multiple ion channel blockage effects, moderate IC₅₀ variations combined with variable Hill coefficients can affect the accuracy of in silico predictions.

Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block

Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model.

Electrophysiological and Contractile Effects of Disopyramide in Patients With Obstructive Hypertrophic Cardiomyopathy: A Translational Study

•

In patients with HCM and symptomatic LVOT-obstruction, first treatment with disopyramide leads to a marked reduction of LVOT gradients, with a slight decrease of resting ejection fraction and a modest increase of corrected QT interval, highlighting high efficacy and safety.

•

In single cardiomyocytes and intact trabeculae from surgical samples of patients with obstructive HCM, in vitro treatment with 5 μmol/l disopyramide lowered force and Ca2⁺ transients while reducing action potential duration and the rate of arrhythmic afterdepolarizations.

•

These effects are mediated by the combined inhibition of peak and late Na⁺ currents, L-type Ca²⁺ current, delayed-rectifier K⁺ current, and ryanodine receptors.

•

In addition to the negative inotropic effect of disopyramide, in vitro results suggest additional antiarrhythmic actions.

Disopyramide is effective and safe in patients with obstructive hypertrophic cardiomyopathy. However, its cellular and molecular mechanisms of action are unknown. We tested disopyramide in cardiomyocytes from the septum of surgical myectomy patients: disopyramide inhibits multiple ion channels, leading to lower Ca transients and force, and shortens action potentials, thus reducing cellular arrhythmias. The electrophysiological profile of disopyramide explains the efficient reduction of outflow gradients but also the limited prolongation of the QT interval and the absence of arrhythmic side effects observed in 39 disopyramide-treated patients. In conclusion, our results support the idea that disopyramide is safe for outpatient use in obstructive patients.

Improving the clinical understanding of hypertrophic cardiomyopathy by combining patient data, machine learning and computer simulations: A case study

•

In this paper, we present how, by combining electrocardiogram and imaging data, machine learning and high performance computing simulations, we identified four phenotypes in hypertrophic cardiomyopathy (HCM), with differences in arrhythmic risk, and provided two distinct possible mechanisms that may explain the heterogeneity of HCM manifestation.

•

This led to a better HCM patient stratification and understanding of the underlying disease mechanisms, providing a step further towards tailored HCM patient management and treatment.

Most patients with hypertrophic cardiomyopathy (HCM), the most common genetic cardiac disease, remain asymptomatic, but others may suffer from sudden cardiac death. A better identification of those patients at risk, together with a better understanding of the mechanisms leading to arrhythmia, are crucial to target high-risk patients and provide them with appropriate treatment. However, this currently remains a challenge. In this paper, we present a successful example of implementing computational techniques for clinically-relevant applications. By combining electrocardiogram and imaging data, machine learning and high performance computing simulations, we identified four phenotypes in HCM, with differences in arrhythmic risk, and provided two distinct possible mechanisms that may explain the heterogeneity of HCM manifestation. This led to a better HCM patient stratification and understanding of the underlying disease mechanisms, providing a step further towards tailored HCM patient management and treatment.

Drug-induced shortening of the electromechanical window is an effective biomarker for in silico prediction of clinical risk of arrhythmias

BACKGROUND AND PURPOSE

Early identification of drug-induced cardiac adverse events is key in drug development. Human-based computer models are emerging as an effective approach, complementary to in vitro and animal models. Drug-induced shortening of the electromechanical window has been associated with increased risk of arrhythmias. This study investigates the potential of a cellular surrogate for the electromechanical window (EMw) for prediction of pro-arrhythmic cardiotoxicity, and its underlying ionic mechanisms, using human-based computer models.

EXPERIMENTAL APPROACH

In silico drug trials for 40 reference compounds were performed, testing up to 100-fold the therapeutic concentrations (EFTPC_max ) and using a control population of human ventricular action potential (AP) models, optimised to capture pro-arrhythmic ionic profiles. EMw was calculated for each model in the population as the difference between AP and Ca²⁺ transient durations at 90%. Drug-induced changes in the EMw and occurrence of repolarisation abnormalities (RA) were quantified.

KEY RESULTS

Drugs with clinical risk of Torsade de Pointes arrhythmias induced a concentration-dependent EMw shortening, while safe drugs lead to increase or small change in EMw. Risk predictions based on EMw shortening achieved 90% accuracy at 10× EFTPC_max , whereas RA-based predictions required 100× EFTPC_max to reach the same accuracy. As it is dependent on Ca²⁺ transient, the EMw was also more sensitive than AP prolongation in distinguishing between pure hERG blockers and multichannel compounds also blocking the calcium current.

CONCLUSION AND IMPLICATIONS

The EMw is an effective biomarker for in silico predictions of drug-induced clinical pro-arrhythmic risk, particularly for compounds with multichannel blocking action.

Investigating the Complex Arrhythmic Phenotype Caused by the Gain-of-Function Mutation KCNQ1-G229D

The congenital long QT syndrome (LQTS) is a cardiac electrophysiological disorder that can cause sudden cardiac death. LQT1 is a subtype of LQTS caused by mutations in KCNQ1, affecting the slow delayed-rectifier potassium current (I Ks), which is essential for cardiac repolarization. Paradoxically, gain-of-function mutations in KCNQ1 have been reported to cause borderline QT prolongation, atrial fibrillation (AF), sinus bradycardia, and sudden death, however, the mechanisms are not well understood. The goal of the study is to investigate the ionic, cellular and tissue mechanisms underlying the complex phenotype of a gain-of-function mutation in KCNQ1, c.686G > A (p.G229D) using computer modeling and simulations informed by in vitro measurements. Previous studies have shown this mutation to cause AF and borderline QT prolongation. We report a clinical description of a family that carry this mutation and that a member of the family died suddenly during sleep at 21 years old. Using patch-clamp experiments, we confirm that KCNQ1-G229D causes a significant gain in channel function. We introduce the effect of the mutation in populations of atrial, ventricular and sinus node (SN) cell models to investigate mechanisms underlying phenotypic variability. In a population of human atrial and ventricular cell models and tissue, the presence of KCNQ1-G229D predominantly shortens atrial action potential duration (APD). However, in a subset of models, KCNQ1-G229D can act to prolong ventricular APD by up to 7% (19 ms) and underlie depolarization abnormalities, which could promote QT prolongation and conduction delays. Interestingly, APD prolongations were predominantly seen at slow pacing cycle lengths (CL > 1,000 ms), which suggests a greater arrhythmic risk during bradycardia, and is consistent with the observed sudden death during sleep. In a population of human SN cell models, the KCNQ1-G229D mutation results in slow/abnormal sinus rhythm, and we identify that a stronger L-type calcium current enables the SN to be more robust to the mutation. In conclusion, our computational modeling experiments provide novel mechanistic explanations for the observed borderline QT prolongation, and predict that KCNQ1-G229D could underlie SN dysfunction and conduction delays. The mechanisms revealed in the study can potentially inform management and treatment of KCNQ1 gain-of-function mutation carriers.

Electrocardiogram phenotypes in hypertrophic cardiomyopathy caused by distinct mechanisms: apico-basal repolarization gradients vs. Purkinje-myocardial coupling abnormalities

AIMS

To identify key structural and electrophysiological features explaining distinct electrocardiogram (ECG) phenotypes in hypertrophic cardiomyopathy (HCM).

METHODS AND RESULTS

Human heart-torso anatomical models were constructed from cardiac magnetic resonance (CMR) images of HCM patients, representative of ECG phenotypes identified previously. High performance computing simulations using bidomain models were conducted to dissect key features explaining the ECG phenotypes with increased HCM Risk-SCD scores, namely Group 1A, characterized by normal QRS but inverted T waves laterally and coexistence of apical and septal hypertrophy; and Group 3 with marked QRS abnormalities (deep and wide S waves laterally) and septal hypertrophy. Hypertrophic cardiomyopathy abnormalities characterized from CMR, such as hypertrophy, tissue microstructure alterations, abnormal conduction system, and ionic remodelling, were selectively included to assess their influence on ECG morphology. Electrocardiogram abnormalities could not be explained by increased wall thickness nor by local conduction abnormalities associated with fibre disarray or fibrosis. Inverted T wave with normal QRS (Group 1A) was obtained with increased apico-basal repolarization gradient caused by ionic remodelling in septum and apex. Lateral QRS abnormalities (Group 3) were only recovered with abnormal Purkinje-myocardium coupling.

CONCLUSION

Two ECG-based HCM phenotypes are explained by distinct mechanisms: ionic remodelling and action potential prolongation in hypertrophied apical and septal areas lead to T wave inversion with normal QRS complexes, whereas abnormal Purkinje-myocardial coupling causes abnormal QRS morphology in V4-V6. These findings have potential implications for patients' management as they point towards different arrhythmia mechanisms in different phenotypes.

Slow Recovery of Excitability Increases Ventricular Fibrillation Risk as Identified by Emulation

Purpose: Rotor stability and meandering are key mechanisms determining and sustaining cardiac fibrillation, with important implications for anti-arrhythmic drug development. However, little is yet known on how rotor dynamics are modulated by variability in cellular electrophysiology, particularly on kinetic properties of ion channel recovery.

Methods: We propose a novel emulation approach, based on Gaussian process regression augmented with machine learning, for data enrichment, automatic detection, classification, and analysis of re-entrant biomarkers in cardiac tissue. More than 5,000 monodomain simulations of long-lasting arrhythmic episodes with Fenton-Karma ionic dynamics, further enriched by emulation to 80 million electrophysiological scenarios, were conducted to investigate the role of variability in ion channel densities and kinetics in modulating rotor-driven arrhythmic behavior.

Results: Our methods predicted the class of excitation behavior with classification accuracy up to 96%, and emulation effectively predicted frequency, stability, and spatial biomarkers of functional re-entry. We demonstrate that the excitation wavelength interpretation of re-entrant behavior hides critical information about rotor persistence and devolution into fibrillation. In particular, whereas action potential duration directly modulates rotor frequency and meandering, critical windows of excitability are identified as the main determinants of breakup. Further novel electrophysiological insights of particular relevance for ventricular arrhythmias arise from our multivariate analysis, including the role of incomplete activation of slow inward currents in mediating tissue rate-dependence and dispersion of repolarization, and the emergence of slow recovery of excitability as a significant promoter of this mechanism of dispersion and increased arrhythmic risk.

Conclusions: Our results mechanistically explain pro-arrhythmic effects of class Ic anti-arrhythmics in the ventricles despite their established role in the pharmacological management of atrial fibrillation. This is mediated by their slow recovery of excitability mode of action, promoting incomplete activation of slow inward currents and therefore increased dispersion of repolarization, given the larger influence of these currents in modulating the action potential in the ventricles compared to the atria. These results exemplify the potential of emulation techniques in elucidating novel mechanisms of arrhythmia and further application to cardiac electrophysiology.

Strategies of data layout and cache writing for input-output optimization in high performance scientific computing: Applications to the forward electrocardiographic problem

Input-output (I/O) optimization at the low-level design of data layout on disk drastically impacts the efficiency of high performance computing (HPC) applications. However, such a low-level optimization is in general challenging, especially when using popular scientific file formats designed with an emphasis on portability and flexibility. To reconcile these two aspects, we present a novel low-level data layout for HPC applications, fully independent of the number of dimensions in the dataset. The new data layout improves reading and writing efficiency in large HPC applications using many processors, and in particular during parallel post-processing. Furthermore, its combination with a cached write mode, in order to aggregate multiple writes into larger ones, substantially decreased the writing times of the proposed strategy. When applied to our simulation framework for the forward calculation of the human electrocardiogram, the combined strategy resulted in drastic improvements in I/O performance, of up to 40% in writing and 93–98% in reading for post-processing tasks. Given the generality of the proposed strategies and scientific file formats used, our results may represent significant improvements in I/O performance of HPC applications across multiple disciplines, reducing execution and post-processing times and leading to a more efficient use of HPC resource envelopes.

Slow Adaptation of Ventricular Repolarization as a Cause of Arrhythmia?

Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems”.

Background: Adaptation of the QT-interval to changes in heart rate reflects on the body-surface electrocardiogram the adaptation of action potential duration (APD) at the cellular level. The initial fast phase of APD adaptation has been shown to modulate the arrhythmia substrate. Whether the slow phase is potentially proarrhythmic remains unclear.

Objectives: To analyze in-vivo human data and use computer simulations to examine effects of the slow APD adaptation phase on dispersion of repolarization and reentry in the human ventricle.

Methods: Electrograms were acquired from 10 left and 10 right ventricle (LV/RV) endocardial sites in 15 patients with normal ventricles during RV pacing. Activation-recovery intervals, as a surrogate for APD, were measured during a sustained increase in heart rate. Observed dynamics were studied using computer simulations of human tissue electrophysiology.

Results: Spatial heterogeneity of rate adaptation was observed in all patients. Inhomogeneity in slow APD adaptation time constants (ΔTs) was greater in LV than RV (ΔTs LV = 31.8 ± 13.2, ΔTs RV = 19.0 ± 12.8 s, P < 0.01). Simulations showed that altering local slow time constants of adaptation was sufficient to convert partial wavefront block to block with successful reentry.

Conclusions: Using electrophysiological data acquired in-vivo in human and computer simulations, we identify heterogeneity in the slow phase of APD adaptation as an important component of arrhythmogenesis.

From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study

Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions, computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and subcellular ionic densities on Ca²⁺ transient dynamics. Results showed that 1) variability in APs and ionic densities is large, even within an apparently homogenous patient cohort, and translates into ±100% variation in ionic conductances; 2) experimentally calibrated populations of models with wide variations in ionic densities yield APs overlapping with those obtained experimentally, even if AP characteristics of the original generic model differed significantly from experimental APs; 3) model calibration with AP recordings restricts the variability in ionic densities affecting upstroke and resting potential, but redundancy in repolarization currents admits substantial variability in ionic densities; and 4) model populations constrained with experimental APs and ionic densities exhibit three Ca²⁺ transient phenotypes, differing in intracellular Ca²⁺ handling and Na⁺/Ca²⁺ membrane extrusion. These findings advance our understanding of the impact of variability in human atrial electrophysiology. NEW & NOTEWORTHY Variability in human atrial electrophysiology is investigated by integrating for the first time cellular-level and ion channel recordings in computational electrophysiological models. Ion channel calibration restricts current densities but not cellular phenotypic variability. Reduced Na⁺/Ca²⁺ exchanger is identified as a primary mechanism underlying diastolic Ca²⁺ fluctuations in human atrial myocytes.

Corrigendum: The Electrogenic Na+/K+ Pump Is a Key Determinant of Repolarization Abnormality Susceptibility in Human Ventricular Cardiomyocytes: A Population-Based Simulation Study

[This corrects the article on p. 278 in vol. 8, PMID: 28529489.].

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC₅₀/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca²⁺-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca²⁺/late Na⁺ currents and Na⁺/Ca²⁺-exchanger, reduced Na⁺/K⁺-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na⁺ and Ca²⁺ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca²⁺-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

Human ventricular activation sequence and the simulation of the electrocardiographic QRS complex and its variability in healthy and intraventricular block conditions

Aims

To investigate how variability in activation sequence and passive conduction properties translates into clinical variability in QRS biomarkers, and gain novel physiological knowledge on the information contained in the human QRS complex.

Methods and results

Multiscale bidomain simulations using a detailed heart-torso human anatomical model are performed to investigate the impact of activation sequence characteristics on clinical QRS biomarkers. Activation sequences are built and validated against experimentally-derived ex vivo and in vivo human activation data. R-peak amplitude exhibits the largest variability in terms of QRS morphology, due to its simultaneous modulation by activation sequence speed, myocardial intracellular and extracellular conductivities, and propagation through the human torso. QRS width, however, is regulated by endocardial activation speed and intracellular myocardial conductivities, whereas QR intervals are only affected by the endocardial activation profile. Variability in the apico-basal location of activation sites on the anterior and posterior left ventricular wall is associated with S-wave progression in limb and precordial leads, respectively, and occasional notched QRS complexes in precordial derivations. Variability in the number of early activation sites successfully reproduces pathological abnormalities of the human conduction system in the QRS complex.

Conclusion

Variability in activation sequence and passive conduction properties captures and explains a large part of the clinical variability observed in the human QRS complex. Our physiological insights allow for a deeper interpretation of human QRS biomarkers in terms of QRS morphology and location of early endocardial activation sites. This might be used to attain a better patient-specific knowledge of activation sequence from routine body-surface electrocardiograms.