Electrophysiological Model Research Articles

Computational modeling of electromechanical coupling in human cardiomyocyte applied to study hypertrophic cardiomyopathy and its drug response

Background and objectiveKnowledge of electromechanical coupling in cardiomyocyte and how it is influenced by various pathophysiological factors is fundamental to understanding the pathogenesis of myocardial disease and its response to medication, which is however hard to be thoroughly addressed by clinical/experimental studies due to technical limitations. At this point, computational modeling offers an alternative approach. The main objective of the study was to develop a computational model capable of simulating the process of electromechanical coupling and quantifying the roles of various factors in play in the human left ventricular cardiomyocyte. MethodsA new electrophysiological model was firstly built by combining several existing electrophysiological models and incorporating the mechanism of electrophysiological homeostasis, which was subsequently coupled to models representing the cross-bridge dynamics and active force generation during excitation-contraction coupling and the passive mechanical properties of cardiomyocyte to yield an integrative electromechanical model. Model parameters were calibrated or optimized based on a large amount of experimental data. The resulting model was applied to delineate the characteristics of electromechanical coupling and explore underlying determinant factors in hypertrophic cardiomyopathy (HCM) cardiomyocyte, as well as quantify their changes in response to different medications. ResultsModel predictions captured the major electromechanical characteristics of cardiomyocyte under both normal physiological and HCM conditions. In comparison with normal cardiomyocyte, HCM cardiomyocyte suffered from systemic changes in both electrophysiological and mechanical variables. Numerical simulations of drug response revealed that Mavacamten and Metoprolol could both reduce the active contractility and alleviate calcium overload but had marked differential influences on many other electromechanical variables, which theoretically explained why the two drugs have differential therapeutic effects. In addition, our numerical experiments demonstrated the important role of compensatory ion transport in maintaining electrophysiological homeostasis and regulating cytoplasmic volume. ConclusionsA sophisticated computational model has the advantage of providing quantitative and integrative insights for understanding the pathogenesis and drug responses of HCM or other myocardial diseases at the level of cardiomyocyte, and hence may contribute as a useful complement to clinical/experimental studies. The model may also be coupled to tissue- or organ-level models to strengthen the physiological implications of macro-scale numerical simulations.

Development and validation of an advanced ex vivo brain slice invasion assay to model glioblastoma cell invasion into the complex brain microenvironment.

Organotypic cultures of murine brain slices are well-established tools in neuroscience research, including electrophysiology studies, modeling neurodegeneration, and cancer research. Here, we present an optimized ex vivo brain slice invasion assay that models glioblastoma multiforme (GBM) cell invasion into organotypic brain slices. Using this model, human GBM spheroids can be implanted with precision onto murine brain slices and cultured ex vivo to allow tumour cell invasion into the brain tissue. Traditional top-down confocal microscopy allows for imaging of GBM cell migration along the top of the brain slice, but there is limited resolution of tumour cell invasion into the slice. Our novel imaging and quantification technique involves embedding stained brain slices into an agar block, re-sectioning the slice in the Z-direction onto slides, and then using confocal microscopy to image cellular invasion into the brain tissue. This imaging technique allows for the visualization of invasive structures beneath the spheroid that would otherwise go undetected using traditional microscopy approaches. Our ImageJ macro (BraInZ) allows for the quantification of GBM brain slice invasion in the Z-direction. Importantly, we note striking differences in the modes of motility observed when GBM cells invade into Matrigel in vitro versus into brain tissue ex vivo highlighting the importance of incorporating the brain microenvironment when studying GBM invasion. In summary, our version of the ex vivo brain slice invasion assay improves upon previously published models by more clearly differentiating between migration along the top of the brain slice versus invasion into the slice.

Robust morris screening method (RMSM) for complex physiological models

Background and objectives: Morris screening sensitivity analysis (MSM) comes forth as the method needing the minimum number of model simulations to qualify the impact of input parameter variations on outputs of complex, nonlinear and overparametrized models. However, the reliability of MSM indices (mean and standard deviation) and the reproducibility of their results are rarely explored despite the input parameter tuning/identification needs. In fact, these models, such those used in medical applications as digital twins, often lie in this category and need efficient and robust tools to assess both sensitivity and reliability of the outputs to numerous input model parameters.Methods: In this study, a new Robust Morris Screening Method (RMSM) is proposed and based on new indices: the absolute median (χ*) and the median absolute deviation (ρ). The proposed RMSM approach is evaluated on a complex multi-scales neuromuscular electrophysiological model simulating HD-sEMG (high density surface electromyography) signals at the skin surface. The reliability and stability of new RMSM indicators are evaluated at different trajectories within the parameter space and compared to classical MSM results. For this purpose, We propose a new methodology for parameter screening based on the ratio ρ/χ* as a graphic indicator of (non)linearity and (non)monotonicity of parameter effects.Results: Firstly, the results demonstrated that the computed elementary effects (EE) of inputs are not normally distributed using MSM indices contrary to the proposed RMSM indices. Secondly, the ranking stability of RMSM indices was earlier obtained from 20 trajectories (T=20), while MSM ranking remained unstable until T = 100. Thirdly, The screening separation between influential and negligible input model parameters was more distinct and interpretable with RMSM than MSM.Conclusion: The proposed RMSM approach ensures a fast, reliable and stable ranking of parameters for complex and overparametrized models compared to classical MSM. this allows a more precise exploration of the model parameter influence space for future application in parameter tuning and identification.

Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models.

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.

Quantifying the impact of shape uncertainty on predicted arrhythmias

Background.Personalised computer models are increasingly used to diagnose cardiac arrhythmias and tailor treatment. Patient-specific models of the left atrium are often derived from pre-procedural imaging of anatomy and fibrosis. These images contain noise that can affect simulation predictions. There are few computationally tractable methods for propagating uncertainties from images to clinical predictions. Method.We describe the left atrium anatomy using our Bayesian shape model that captures anatomical uncertainty in medical images and has been validated on 63 independent clinical images. This algorithm describes the left atrium anatomy using Nmodes=15 principal components, capturing 95% of the shape variance and calculated from 70 clinical cardiac magnetic resonance (CMR) images. Latent variables encode shape uncertainty: we evaluate their posterior distribution for each new anatomy. We assume a normally distributed prior. We use the unscented transform to sample from the posterior shape distribution. For each sample, we assign the local material properties of the tissue using the projection of late gadolinium enhancement CMR (LGE-CMR) onto the anatomy to estimate local fibrosis. To test which activation patterns an atrium can sustain, we perform an arrhythmia simulation for each sample. We consider 34 possible outcomes (31 macro-re-entries, functional re-entry, atrial fibrillation, and non-sustained arrhythmia). For each sample, we determine the outcome by comparing pre- and post-ablation activation patterns following a cross-field stimulus. Results.We create patient-specific atrial electrophysiology models of ten patients. We validate the mean and standard deviation maps from the unscented transform with the same statistics obtained with 12,000 Monte Carlo (ground truth) samples. We found discrepancies <3% and <2% for the mean and standard deviation for fibrosis burden and activation time, respectively. For each patient case, we then compare the predicted outcome from a model built on the clinical data (deterministic approach) with the probability distribution obtained from the simulated samples. We found that the deterministic approach did not predict the most likely outcome in 80% of the cases. Finally, we estimate the influence of each source of uncertainty independently. Fixing the anatomy to the posterior mean and maintaining uncertainty in fibrosis reduced the prediction of self-terminating arrhythmias from ≃14% to ≃7%. Keeping the fibrosis fixed to the sample mean while retaining uncertainty in shape decreased the prediction of substrate-driven arrhythmias from ≃33% to ≃18% and increased the prediction of macro-re-entries from ≃54% to ≃68%. Conclusions.We presented a novel method for propagating shape uncertainty in atrial models through to uncertainty in numerical simulations. The algorithm takes advantage of the unscented transform to compute the output distribution of the outcomes. We validated the unscented transform as a viable sampling strategy to deal with anatomy uncertainty. We then showed that the prediction computed with a deterministic model does not always coincide with the most likely outcome. Finally, we found that shape uncertainty affects the predictions of macro-re-entries, while fibrosis uncertainty affects the predictions of functional re-entries.

Chirped modulated wave excitations in an electrical model of microtubules

Inspired by standard electrophysiological models of microtubules (MTs), we consider a relatively large one-dimensional spatial array of nonlinear electrical transmission network with a negative nonlinear resistance. Employing the reductive perturbation approach in the semi-discrete approximation, we show that the evolution of ionic waves in this electrical circuit model of microtubules is described by a nonlinear Schrödinger (NLS) equation with a dissipative/amplification term in the presence of an external linear potential. The modulational instability analysis of the amplitude equation shows that the derived NLS equation suitably describes the dynamics of our lattice of biochemical units as an excitable medium. Based on exact and approximate solutions of the amplitude equation, we investigate analytically the existence of modulated chirped solitonic waves along microtubules. We suggest possible biological implications of these nonlinear modulated waves. Our system is found to amplify significantly the amplitude of the input signal, confirming thus known experimental results on MTs. Nevertheless, a proper choice of various parameters of the negative nonlinear resistance is required for further validation of our theoretical results.

Interindividual Age-Independent Differences in Human CX43 Impact Ventricular Arrhythmic Risk.

Connexin 43 (CX43) is one of the major components of gap junctions, the structures responsible for the intercellular communication and transmission of the electrical impulse in the left ventricle. There is limited information on the histological changes of CX43 with age and their effect on electrophysiology, especially in humans. Here, we analyzed left ventricular biopsies from living donors starting at midlife to characterize age-related CX43 remodeling. We assessed its quantity, degree of lateralization, and spatial heterogeneity together with fibrotic deposition. We observed no significant age-related remodeling of CX43. Only spatial heterogeneity increased slightly with age, and this increase was better explained by biological age than by chronological age. Importantly, we found that CX43 features varied considerably among individuals in our population with no relevant relationship to age or fibrosis content, in contrast to animal species. We used our experimental results to feed computational models of human ventricular electrophysiology and to assess the effects of interindividual differences in specific features of CX43 and fibrosis on conduction velocity, action potential duration, and arrhythmogenicity. We found that larger amounts of fibrosis were associated with the highest arrhythmic risk, with this risk being increased when fibrosis deposition was combined with a reduction in CX43 amount and/or with an increase in CX43 spatial heterogeneity. These mechanisms underlying high arrhythmic risk in some individuals were not associated with age in our study population. In conclusion, our data rule out CX43 remodeling as an age-related arrhythmic substrate in the population beyond midlife, but highlight its potential as a proarrhythmic factor at the individual level, especially when combined with increased fibrosis.

Cardioprotective and hypotensive mechanistic insights of hydroethanolic extract of Cucumis melo L. kernels in isoprenaline-induced cardiotoxicity based on metabolomics and in silico electrophysiological models.

Background: Cardiovascular diseases (CVD) continue to threaten health worldwide, and account for a significant portion of deaths and illnesses. In both developing and industrialized nations, they challenge their health systems. There are several traditional uses of Cucurbitaceae seeds in Pakistan, India, Iran, and China, including treating cardiovascular, neurological, and urogenital diseases. Methods: In the present work, integrated techniques of metabolomics profiling and computational cardiomyocyte stimulation were used to investigate possible mechanisms of C. melo in isoprenaline (ISO)-induced myocardial infarction. In vitro, vasoconstrictions, paired atria, and in vivo invasive blood pressure measurement models were performed to explore the mechanism of action of C. melo hydroethanolic seed extract (Cm-EtOH). Results: Results showed that Cm-EtOH demonstrates NO-based endothelium-derived relaxing factor (EDRF) vasorelaxant response, negative chronotropic and inotropic response in the atrium, and hypotensive effects in normotensive rats. Results also revealed that Cm-EtOH decreases cardiomyocyte hypertrophy and reverts the altered gene expressions, biochemical, and metabolites in ISO-induced myocardial infarction (MI) rats. The extract additionally reversed ISO-induced MI-induced oxidative stress, energy consumption, and amino acid metabolism. Moreover, C. melo seeds increased EDRF function, energy production, and antioxidant capacity to treat myocardial and vascular disorders. In computational cardiomyocyte simulation, gallic acid reduced action potential duration, upstroke velocity (dV/dtmax), and effective refractory period. Conclusion: This study highlights the therapeutic potential of C. melo seeds to treat cardiovascular diseases and provides mechanistic insight into its antihypertensive and cardioprotective activities.

Global Sensitivity Analysis and Uncertainty Quantification for Simulated Atrial Electrocardiograms

The numerical modeling of cardiac electrophysiology has reached a mature and advanced state that allows for quantitative modeling of many clinically relevant processes. As a result, complex computational tasks such as the creation of a variety of electrocardiograms (ECGs) from virtual cohorts of models representing biological variation are within reach. This requires a correct representation of the variability of a population by suitable distributions of a number of input parameters. Hence, the assessment of the dependence and variation of model outputs by sensitivity analysis and uncertainty quantification become crucial. Since the standard metrological approach of using Monte–Carlo simulations is computationally prohibitive, we use a nonintrusive polynomial chaos-based approximation of the forward model used for obtaining the atrial contribution to a realistic electrocardiogram. The surrogate increases the speed of computations for varying parameters by orders of magnitude and thereby greatly enhances the versatility of uncertainty quantification. It further allows for the quantification of parameter influences via Sobol indices for the time series of 12 lead ECGs and provides bounds for the accuracy of the obtained sensitivities derived from an estimation of the surrogate approximation error. Thus, it is capable of supporting and improving the creation of synthetic databases of ECGs from a virtual cohort mapping a representative sample of the human population based on physiologically and anatomically realistic three-dimensional models.

Global Lipschitz stability of multiple space dependent ionic parameters for the MEA/hiPSC-CM assays

In this paper, we consider an inverse problem of determining two space dependent ionic parameters of a strongly coupled parabolic-elliptic reaction–diffusion system arising in cardiac electrophysiology modeling when simulating drugs action with multi-electrode array/human induced pluripotent stem cells-cardiomyocytes assays. We use the bidomain model coupled to an ordinary differential equation and we consider the classical phenomenological model in cardiac electrophysiology of FitzHugh–Nagumo to describe the ionic exchanges at the microscopic level. Our main result is the uniqueness and a Lipschitz stability estimate for two ionic parameters of the model using sub-boundary observations over an interval of time. The key ingredients are a global Carleman-type estimates with a suitable observations acting on a part of the boundary.

Conditions for Kir-induced bistability of membrane potential in capillary endothelial cells

A simplified model for electrophysiology of endothelial cells is used to examine the conditions that can lead to bistability of membrane resting potential. The model includes the effects of inward-rectifying potassium (Kir) ion channels, whose current–voltage relationship shows an interval of negative slope and whose maximum conductance is dependent on the extracellular potassium concentration. The background current resulting from other types of channels is assumed to be linearly related to membrane potential. A method is presented for identifying the boundaries in the parameter space for the background currents of the regions of bistability. It is shown that these regions are relatively narrow and depend on extracellular potassium concentration. The results are used to define conditions leading to transitions between depolarized and hyperpolarized membrane states. These behaviors can influence the properties of conducted responses, in which changes in membrane potential are propagated along blood vessel walls. Conducted responses are important in the local regulation of blood flow in the brain and other tissues.

A unique cardiac electrocardiographic 3D model. Toward interpretable AI diagnosis.

Mathematical models of cardiac electrical activity are one of the most important tools for elucidating information about heart diagnostics. In this paper, we present an efficient mathematical formulation for this modeling simple enough to be easily parameterized and rich enough to provide realistic signals. It relies on a five dipole representation of the cardiac electric source, each one associated with the well-known waves of the electrocardiogram signal. Beyond the physical basis of the model, the parameters are physiologically interpretable as they characterize the wave shape, similar to what a physician would look for in signals, thus making them very useful in diagnosis. The model accurately reproduces the electrocardiogram signals of any diseased or healthy heart. This new discovery represents a significant advance in electrocardiography research. It is especially useful for diagnosis, patient follow-up or decision-making on new therapies; is also a promising tool for well-performing, transparent and interpretable AI approaches.

A finite element model of the embryonic zebrafish heart electrophysiology

Background and objectiveIn the last 30 years, a growing interest has involved the study of zebrafish thanks to its physiological characteristics similar to those of humans. The aim of the following work is to create an electrophysiological computational model of the zebrafish heart and lay the foundation for the development of an in-silico model of the zebrafish heart that will allow to study the correlation between pathologies and drug administration with the main electrophysiological parameters as the ECG signal. MethodsThe model considers a whole body and the two chambers of three days post fertilization (3 dpf) zebrafish. A four-variable phenomenological action potential model describes the action potential of different heart regions. Tissue conductivity was calibrated to reproduce the experimentally described activation sequence. ResultsThe model is able to correctly reproduce the activation sequence and times found in literature, with activation of the atrium and ventricle that correspond to 36 and 59 ms, respectively, and a delay of 14 ms caused by the presence of the atrioventricular band (AV band). Moreover, the obtained in-silico ECG reflects the main characteristics of the zebrafish ECG in good agreement with experimental records, a P-wave with a duration of approximately the total atrial activation, followed by a QRS complex of approximately 109 ms corresponding to ventricle activation. ConclusionsThe model allows the assessment of the main electrophysiological parameters in terms of activation sequence and timing, reproducing monopolar and bipolar ECG signals in line with experimental data. Coupling the proposed model with an electrophysiological detailed action potential model of zebrafish will represent a significant breakthrough toward the development of an in-silico zebrafish heart.

Cortical VIP neurons locally control the gain but globally control the coherence of gamma band rhythms

Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.

Abstract 14991: Local Prolongation of Repolarization Prevents Post Myocardial Infarction Ventricular Tachycardia

Introduction: Reentry is the predominant mechanism underlying ventricular arrhythmias in chronic myocardial infarction patients. Reentry can be prevented by prolonging effective refractory period, thereby blocking reexcitation of recently activated tissue. This is currently achieved with systemically administered class III antiarrhythmic drugs. These therapies are limited by their risk of provoking ventricular arrhythmias by off-target effects. Hypothesis: Local prolongation of repolarization in healthy myocardium adjacent to the exit site attenuates reentry and postinfarction arrhythmias. Method and results: We used a pig model and generated myocardial infarction by balloon occlusion of the left anterior descending coronary artery and performed epicardial mapping 6 weeks later during Langendorff-perfusion. Programmed stimulation induced reentry leading to ventricular premature beats and sustained ventricular tachycardia (VT). Local injection of Sotalol adjacent to the infarcted myocardium prolonged repolarization and prevented VT after programmed stimulation. To translate these experimental findings to the patient situation we used a virtual heart based on data from a patient suffering from postmyocardial infarction VTs. The patient underwent pre-ablation cardiac late gadolinium enhanced- magnetic resonance imaging followed by geometrical reconstruction of the left ventricle and computational electrophysiological modelling of VT induction. We used a rapid pacing protocol to induce VT and determined the site where the activation front exited the infarct zone and reactivated the adjacent normal myocardium. Next, we prolonged repolarization of the normal myocardium adjacent to the exit site with 50 ms and performed rapid pacing to induce VT. This only resulted in a single premature ventricular beat after which sinus rhythm restored. Conclusion: Our experimental and in silico findings show the potential of local prolongation of repolarization a novel potentially genetic anti-arrhythmic therapy in post-infarction patients.

A meshless fragile points method for the solution of the monodomain model for cardiac electrophysiology simulation

Meshless methods for in silico modeling and simulation of cardiac electrophysiology are gaining more and more popularity. These methods do not require a mesh and are more suitable than the Finite Element Method (FEM) to simulate the activity of complex geometrical structures like the human heart. However, challenges such as numerical integration accuracy and time efficiency remain, which limit their applicability. Recently, the Fragile Points Method (FPM) has been introduced in the meshless methods family. It uses local, simple, polynomial, discontinuous functions to construct trial and test functions in the Galerkin weak form. This allows for accurate integration and improved efficiency while enabling the imposition of essential and natural boundary conditions as in FEM. In this work, we consider the application of FPM for cardiac electrophysiology simulation. We derive the cardiac monodomain model using the FPM formulation and we solve several benchmark problems in 2D and 3D. We show that FPM leads to solutions of accuracy and efficiency similar to FEM while alleviating the need for a mesh. Additionally, FPM demonstrates comparable convergence to FEM in the considered benchmarks.

Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar.

Reliable and robust simulation of individual patients using patient-specific models (PSMs) is one of the next frontiers for modeling and simulation (M&S) in healthcare. PSMs, which form the basis of digital twins, can be employed as clinical tools to, for example, assess disease state, predict response to therapy, or optimize therapy. They may also be used to construct virtual cohorts of patients, for in silico evaluation of medical product safety and/or performance. Methods and frameworks have recently been proposed for evaluating the credibility of M&S in healthcare applications. However, such efforts have generally been motivated by models of medical devices or generic patient models; how best to evaluate the credibility of PSMs has largely been unexplored. The aim of this paper is to understand and demonstrate the credibility assessment process for PSMs using patient-specific cardiac electrophysiological (EP) modeling as an exemplar. We first review approaches used to generate cardiac PSMs and consider how verification, validation, and uncertainty quantification (VVUQ) apply to cardiac PSMs. Next, we execute two simulation studies using a publicly available virtual cohort of 24 patient-specific ventricular models, the first a multi-patient verification study, the second investigating the impact of uncertainty in personalized and non-personalized inputs in a virtual cohort. We then use the findings from our analyses to identify how important characteristics of PSMs can be considered when assessing credibility with the approach of the ASME V&V40 Standard, accounting for PSM concepts such as inter- and intra-user variability, multi-patient and “every-patient” error estimation, uncertainty quantification in personalized vs non-personalized inputs, clinical validation, and others. The results of this paper will be useful to developers of cardiac and other medical image based PSMs, when assessing PSM credibility.

Electrochemical potential enables dormant spores to integrate environmental signals.

The dormant state of bacterial spores is generally thought to be devoid of biological activity. We show that despite continued dormancy, spores can integrate environmental signals over time through a preexisting electrochemical potential. Specifically, we studied thousands of individual Bacillus subtilis spores that remain dormant when exposed to transient nutrient pulses. Guided by a mathematical model of bacterial electrophysiology, we modulated the decision to exit dormancy by genetically and chemically targeting potassium ion flux. We confirmed that short nutrient pulses result in step-like changes in the electrochemical potential of persistent spores. During dormancy, spores thus gradually release their stored electrochemical potential to integrate extracellular information over time. These findings reveal a decision-making mechanism that operates in physiologically inactive cells.

Verification of the Efficacy of Mexiletine Treatment for the A1656D Mutation on Downgrading Reentrant Tachycardia Using a 3D Cardiac Electrophysiological Model.

The SCN5A mutations have been long associated with long QT variant 3 (LQT3). Recent experimental and computation studies have reported that mexiletine effectively treats LQT3 patients associated with the A1656D mutation. However, they have primarily focused on cellular level evaluations and have only looked at the effects of mexiletine on action potential duration (APD) or QT interval reduction. We further investigated mexiletine’s effects on cardiac cells through simulations of single-cell (behavior of alternant occurrence) and 3D (with and without mexiletine). We discovered that mexiletine could shorten the cell’s APD and change the alternant’s occurrence to a shorter basic cycle length (BCL) between 350 and 420 ms. The alternant also appeared at a normal heart rate under the A1656D mutation. Furthermore, the 3D ventricle simulations revealed that mexiletine could reduce the likelihood of a greater spiral wave breakup in the A1656D mutant condition by minimizing the appearance of rotors. In conclusion, we found that mexiletine could provide extra safety features during therapy for LQT3 patients because it can change the alternant occurrence from a normal to a faster heart rate, and it reduces the chance of a spiral wave breakup. Therefore, these findings emphasize the promising efficacy of mexiletine in treating LQT3 patients under the A1656D mutation.

Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds

Models of electrical excitation and recovery in the heart have become increasingly detailed, but have yet to be used routinely in the clinical setting to guide personalized intervention in patients. One of the main challenges is calibrating models from the limited measurements that can be made in a patient during a standard clinical procedure. In this work, we propose a novel framework for the probabilistic calibration of electrophysiology parameters on the left atrium of the heart using local measurements of cardiac excitability. Parameter fields are represented as Gaussian processes on manifolds and are linked to measurements via surrogate functions that map from local parameter values to measurements. The posterior distribution of parameter fields is then obtained. We show that our method can recover parameter fields used to generate localised synthetic measurements of effective refractory period. Our methodology is applicable to other measurement types collected with clinical protocols, and more generally for calibration where model parameters vary over a manifold.