Cardiac anisotropy in boundary-element models for the electrocardiogram

Reduced Graphene-Oxide-Doped Elastic Biodegradable Polyurethane Fibers for Cardiomyocyte Maturation

Conductive biomaterials offer promising solutions to enhance the maturity of cultured cardiomyocytes. While the conventional culture of cardiomyocytes on nonconductive materials leads to more immature characteristics, conductive microenvironments have the potential to support sarcomere development, gap junction formation, and beating of cardiomyocytes in vitro. In this study, we systematically investigated the behaviors of cardiomyocytes on aligned electrospun fibrous membranes composed of elastic and biodegradable polyurethane (PU) doped with varying concentrations of reduced graphene oxide (rGO). Compared to PU and PU-4%rGO membranes, the PU-10%rGO membrane exhibited the highest conductivity, approaching levels close to those of native heart tissue. The PU-rGO membranes retained anisotropic viscoelastic behavior similar to that of the porcine left ventricle and a superior tensile strength. Neonatal rat cardiomyocytes (NRCMs) and human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) on the PU-rGO membranes displayed enhanced maturation with cell alignment and enhanced sarcomere structure and gap junction formation with PU-10%rGO having the most improved sarcomere structure and CX-43 presence. hiPSC-CMs on the PU-rGO membranes exhibited a uniform and synchronous beating pattern compared with that on PU membranes. Overall, PU-10%rGO exhibited the best performance for cardiomyocyte maturation. The conductive PU-rGO membranes provide a promising matrix for in vitro cardiomyocyte culture with promoted cell maturation/functionality and the potential for cardiac disease treatment.

Injectable hydrogel electrodes as conduction highways to restore native pacing

There is an urgent clinical need for a treatment regimen that addresses the underlying pathophysiology of ventricular arrhythmias, the leading cause of sudden cardiac death. The current report describes the design of an injectable hydrogel electrode and successful deployment in a pig model with access far more refined than any current pacing modalities allow. In addition to successful cardiac capture and pacing, analysis of surface ECG tracings and three-dimensional electroanatomic mapping revealed a QRS morphology comparable to native sinus rhythm, strongly suggesting the hydrogel electrode captures the deep septal bundle branches and Purkinje fibers. In an ablation model, electroanatomic mapping data demonstrated that the activation wavefront from the hydrogel reaches the mid-myocardium and endocardium much earlier than current single-point pacing modalities. Such uniform activation of broad swaths of tissue enables an opportunity to minimize the delayed myocardial conduction of heterogeneous tissue that underpins re-entry. Collectively, these studies demonstrate the feasibility of a new pacing modality that most closely resembles native conduction with the potential to eliminate lethal re-entrant arrhythmias and provide painless defibrillation.

Effects of graphene oxide and reduced graphene oxide nanomaterials on porcine endothelial progenitor cells

Graphene oxide (GO) and reduced graphene oxide (rGO) have been widely used in the field of tissue regeneration and various biomedical applications. In order to use these nanomaterials in organisms, it is imperative to possess an understanding of their impact on different cell types. Due to the potential of these nanomaterials to enter the bloodstream, interact with the endothelium and accumulate within diverse tissues, it is highly relevant to probe them when in contact with the cellular components of the vascular system. Endothelial progenitor cells (EPCs), involved in blood vessel formation, have great potential for tissue engineering and offer great advantages to study the possible angiogenic effects of biomaterials. Vascular endothelial growth factor (VEGF) induces angiogenesis and regulates vascular permeability, mainly activating VEGFR2 on endothelial cells. The effects of GO and two types of reduced GO, obtained after vacuum-assisted thermal treatment for 15 min (rGO15) and 30 min (rGO30), on porcine endothelial progenitor cells (EPCs) functionality were assessed by analyzing the nanomaterial intracellular uptake, reactive oxygen species (ROS) production and VEGFR2 expression by EPCs. The results evidence that short annealing (15 and 30 minutes) at 200 °C of GO resulted in the mitigation of both the increased ROS production and decline in VEGFR2 expression of EPCs upon GO exposure. Interestingly, after 72 hours of exposure to rGO30, VEGFR2 was higher than in the control culture, suggesting an early angiogenic potential of rGO30. The present work reveals that discrete variations in the reduction of GO may significantly affect the response of porcine endothelial progenitor cells.

Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation

Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF).

Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh.

Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients.

Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm.

An Electroconductive, Thermosensitive, and Injectable Chitosan/Pluronic/Gold-Decorated Cellulose Nanofiber Hydrogel as an Efficient Carrier for Regeneration of Cardiac Tissue

Myocardial infarction is a major cause of death worldwide and remains a social and healthcare burden. Injectable hydrogels with the ability to locally deliver drugs or cells to the damaged area can revolutionize the treatment of heart diseases. Herein, we formulate a thermo-responsive and injectable hydrogel based on conjugated chitosan/poloxamers for cardiac repair. To tailor the mechanical properties and electrical signal transmission, gold nanoparticles (AuNPs) with an average diameter of 50 nm were physically bonded to oxidized bacterial nanocellulose fibers (OBC) and added to the thermosensitive hydrogel at the ratio of 1% w/v. The prepared hydrogels have a porous structure with open pore channels in the range of 50−200 µm. Shear rate sweep measurements demonstrate a reversible phase transition from sol to gel with increasing temperature and a gelation time of 5 min. The hydrogels show a shear-thinning behavior with a shear modulus ranging from 1 to 12 kPa dependent on gold concentration. Electrical conductivity studies reveal that the conductance of the polymer matrix is 6 × 10−2 S/m at 75 mM Au. In vitro cytocompatibility assays by H9C2 cells show high biocompatibility (cell viability of >90% after 72 h incubation) with good cell adhesion. In conclusion, the developed nanocomposite hydrogel has great potential for use as an injectable biomaterial for cardiac tissue regeneration.

Reducing Line-of-block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods

OBJECTIVE

To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs.

METHODS

Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals.

RESULTS

AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had a negligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays.

CONCLUSION

LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs.

SIGNIFICANCE

Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts and methods to reduce them.

Conductive Polymeric-Based Electroactive Scaffolds for Tissue Engineering Applications: Current Progress and Challenges from Biomaterials and Manufacturing Perspectives

The practice of combining external stimulation therapy alongside stimuli-responsive bio-scaffolds has shown massive potential for tissue engineering applications. One promising example is the combination of electrical stimulation (ES) and electroactive scaffolds because ES could enhance cell adhesion and proliferation as well as modulating cellular specialization. Even though electroactive scaffolds have the potential to revolutionize the field of tissue engineering due to their ability to distribute ES directly to the target tissues, the development of effective electroactive scaffolds with specific properties remains a major issue in their practical uses. Conductive polymers (CPs) offer ease of modification that allows for tailoring the scaffold's various properties, making them an attractive option for conductive component in electroactive scaffolds. This review provides an up-to-date narrative of the progress of CPs-based electroactive scaffolds and the challenge of their use in various tissue engineering applications from biomaterials perspectives. The general issues with CP-based scaffolds relevant to its application as electroactive scaffolds were discussed, followed by a more specific discussion in their applications for specific tissues, including bone, nerve, skin, skeletal muscle and cardiac muscle scaffolds. Furthermore, this review also highlighted the importance of the manufacturing process relative to the scaffold's performance, with particular emphasis on additive manufacturing, and various strategies to overcome the CPs' limitations in the development of electroactive scaffolds.

Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes

Short QT (SQT) syndrome is a genetic cardiac disorder characterized by an abbreviated QT interval of the patient's electrocardiogram. The syndrome is associated with increased risk of arrhythmia and sudden cardiac death and can arise from a number of ion channel mutations. Cardiomyocytes derived from induced pluripotent stem cells generated from SQT patients (SQT hiPSC-CMs) provide promising platforms for testing pharmacological treatments directly in human cardiac cells exhibiting mutations specific for the syndrome. However, a difficulty is posed by the relative immaturity of hiPSC-CMs, with the possibility that drug effects observed in SQT hiPSC-CMs could be very different from the corresponding drug effect in vivo. In this paper, we apply a multistep computational procedure for translating measured drug effects from these cells to human QT response. This process first detects drug effects on individual ion channels based on measurements of SQT hiPSC-CMs and then uses these results to estimate the drug effects on ventricular action potentials and QT intervals of adult SQT patients. We find that the procedure is able to identify IC50 values in line with measured values for the four drugs quinidine, ivabradine, ajmaline and mexiletine. In addition, the predicted effect of quinidine on the adult QT interval is in good agreement with measured effects of quinidine for adult patients. Consequently, the computational procedure appears to be a useful tool for helping predicting adult drug responses from pure in vitro measurements of patient derived cell lines.

Three-Dimensional Heart Model-Based Screening of Proarrhythmic Potential by in silico Simulation of Action Potential and Electrocardiograms

The proarrhythmic risk is a major concern in drug development. The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative has proposed the JTpeak interval on electrocardiograms (ECGs) and qNet, an in silico metric, as new biomarkers that may overcome the limitations of the hERG assay and QT interval. In this study, we simulated body-surface ECGs from patch-clamp data using realistic models of the ventricles and torso to explore their suitability as new in silico biomarkers for cardiac safety. We tested seven drugs in this study: dofetilide (high proarrhythmic risk), ranolazine, verapamil (QT increasing, but safe), bepridil, cisapride, mexiletine, and diltiazem. Human ventricular geometry was reconstructed from computed tomography (CT) images, and a Purkinje fiber network was mapped onto the endocardial surface. The electrical wave propagation in the ventricles was obtained by solving a reaction-diffusion equation using finite-element methods. The body-surface ECG data were calculated using a torso model that included the ventricles. The effects of the drugs were incorporated in the model by partly blocking the appropriate ion channels. The effects of the drugs on single-cell action potential (AP) were examined first, and three-dimensional (3D) body-surface ECG simulations were performed at free Cmax values of 1×, 5×, and 10×. In the single-cell and ECG simulations at 5× Cmax, dofetilide, but not verapamil or ranolazine, caused arrhythmia. However, the non-increasing JTpeak caused by verapamil and ranolazine that has been observed in humans was not reproduced in our simulation. Our results demonstrate the potential of 3D body-surface ECG simulation as a biomarker for evaluation of the proarrhythmic risk of candidate drugs.

Considering New Regularization Parameter-Choice Techniques for the Tikhonov Method to Improve the Accuracy of Electrocardiographic Imaging

The electrocardiographic imaging (ECGI) inverse problem highly relies on adding constraints, a process called regularization, as the problem is ill-posed. When there are no prior information provided about the unknown epicardial potentials, the Tikhonov regularization method seems to be the most commonly used technique. In the Tikhonov approach the weight of the constraints is determined by the regularization parameter. However, the regularization parameter is problem and data dependent, meaning that different numerical models or different clinical data may require different regularization parameters. Then, we need to have as many regularization parameter-choice methods as techniques to validate them. In this work, we addressed this issue by showing that the Discrete Picard Condition (DPC) can guide a good regularization parameter choice for the two-norm Tikhonov method. We also studied the feasibility of two techniques: The U-curve method (not yet used in the cardiac field) and a novel automatic method, called ADPC due its basis on the DPC. Both techniques were tested with simulated and experimental data when using the method of fundamental solutions as a numerical model. Their efficacy was compared with the efficacy of two widely used techniques in the literature, the L-curve and the CRESO methods. These solutions showed the feasibility of the new techniques in the cardiac setting, an improvement of the morphology of the reconstructed epicardial potentials, and in most of the cases of their amplitude.

Biomimetic Carbon Fiber Systems Engineering: A Modular Design Strategy To Generate Biofunctional Composites from Graphene and Carbon Nanofibers

Carbon-based fibrous scaffolds are highly attractive for all biomaterial applications that require electrical conductivity. It is additionally advantageous if such materials resembled the structural and biochemical features of the natural extracellular environment. Here, we show a novel modular design strategy to engineer biomimetic carbon fiber-based scaffolds. Highly porous ceramic zinc oxide (ZnO) microstructures serve as three-dimensional (3D) sacrificial templates and are infiltrated with carbon nanotubes (CNTs) or graphene dispersions. Once the CNTs and graphene coat the ZnO template, the ZnO is either removed by hydrolysis or converted into carbon by chemical vapor deposition. The resulting 3D carbon scaffolds are both hierarchically ordered and free-standing. The properties of the microfibrous scaffolds were tailored with a high porosity (up to 93%), a high Young's modulus (ca. 0.027-22 MPa), and an electrical conductivity of ca. 0.1-330 S/m, as well as different surface compositions. Cell viability, fibroblast proliferation rate and protein adsorption rate assays have shown that the generated scaffolds are biocompatible and have a high protein adsorption capacity (up to 77.32 ± 6.95 mg/cm3) so that they are able to resemble the extracellular matrix not only structurally but also biochemically. The scaffolds also allow for the successful growth and adhesion of fibroblast cells, showing that we provide a novel, highly scalable modular design strategy to generate biocompatible carbon fiber systems that mimic the extracellular matrix with the additional feature of conductivity.

Noninvasive Imaging of Epicardial and Endocardial Potentials With Low Rank and Sparsity Constraints

In this study, we explore the use of low rank and sparse constraints for the noninvasive estimation of epicardial and endocardial extracellular potentials from body-surface electrocardiographic data to locate the focus of premature ventricular contractions (PVCs). The proposed strategy formulates the dynamic spatiotemporal distribution of cardiac potentials by means of low rank and sparse decomposition, where the low rank term represents the smooth background and the anomalous potentials are extracted in the sparse matrix. Compared to the most previous potential-based approaches, the proposed low rank and sparse constraints are batch spatiotemporal constraints that capture the underlying relationship of dynamic potentials. The resulting optimization problem is solved using alternating direction method of multipliers. Three sets of simulation experiments with eight different ventricular pacing sites demonstrate that the proposed model outperforms the existing Tikhonov regularization (zero-order, second-order) and L1-norm based method at accurately reconstructing the potentials and locating the ventricular pacing sites. Experiments on a total of 39 cases of real PVC data also validate the ability of the proposed method to correctly locate ectopic pacing sites.

In silico evaluation of the acute occlusion effect of coronary artery on cardiac electrophysiology and the body surface potential map

Body surface potential map, an electric potential distribution on the body torso surface, enables us to infer the electrical activities of the heart. Therefore, observing electric potential projected to the torso surface can be highly useful for diagnosing heart diseases such as coronary occlusion. The BSPM for the heart of a patient show a higher level of sensitivity than 12-lead ECG. Relevant research has been mostly based on clinical statistics obtained from patients, and, therefore, a simulation for a variety of pathological phenomena of the heart is required. In this study, by using computer simulation, a body surface potential map was implemented according to various occlusion locations (distal, mid, proximal occlusion) in the left anterior descending coronary artery. Electrophysiological characteristics of the body surface during the ST segment period were observed and analyzed based on an ST isointegral map. We developed an integrated system that takes into account the cellular to organ levels, and performed simulation regarding the electrophysiological phenomena of the heart that occur during the first 5 minutes (stage 1) and 10 minutes (stage 2) after commencement of coronary occlusion. Subsequently, we calculated the bipolar angle and amplitude of the ST isointegral map, and observed the correlation between the relevant characteristics and the location of coronary occlusion. In the result, in the ventricle model during the stage 1, a wider area of ischemia led to counterclockwise rotation of the bipolar angle; and, during the stage 2, the amplitude increased when the ischemia area exceeded a certain size.

High Modulus Conductive Hydrogels Enhance In Vitro Maturation and Contractile Function of Primary Cardiomyocytes for Uses in Drug Screening

Effective and quick screening and cardiotoxicity assessment are very crucial for drug development. Here, a novel composite hydrogel composed of carbon fibers (CFs) with high conductivity and modulus with polyvinyl alcohol (PVA) is reported. The conductivity of the composite hydrogel PVA/CFs is similar to that of natural heart tissue, and the elastic modulus is close to that of natural heart tissue during systole, due to the incorporation of CFs. PVA/CFs remarkably enhance the maturation of neonatal rat cardiomyocytes (NRCM) in vitro by upregulating the expression of α-actinin, troponin T, and connexin-43, activating the signaling pathway of α5 and β1 integrin-dependent ILK/p-AKT, and increasing the level of RhoA and hypoxia-inducible factor-1α. As a result, the engineered cell sheet-like constructs NRCM@PVA/CFs display much more synchronous, stable, and robust beating behavior than NRCM@PVA. When exposed to doxorubicin or isoprenaline, NRCM@PVA/CFs can retain effective beating for much longer time or change the contractile rate much faster than NRCM@PVA, respectively, therefore representing a promising heart-like platform for in vitro drug screening and cardiotoxicity assessment.

Simulated P wave morphology in the presence of endo-epicardial activation delay

Aims

Evidences of asynchrony between epicardial and endocardial activation in the atrial wall have been reported. We used a computer model of the atria and torso to investigate the consequences of such activation delay on P wave morphology, while controlling for P wave duration.

Methods and results

We created 390 models of the atria based on the same geometry. These models differed by atrial wall thickness (from 2 to 3 mm), transmural coupling, and tissue conductivity in the endocardial and epicardial layers. Among them, 18 were in baseline, 186 had slower conduction in the epicardium layer and 186 in the endocardial layer. Conduction properties were adjusted in such a way that total activation time was the same in all models. P waves on a 16-lead system were simulated during sinus rhythm. Activation maps were similar in all cases. Endo-epicardial delay varied between -5.5 and 5.5 ms vs. 0 ± 0.5 ms in baseline. All P waves had the same duration but variability in their morphology was observed. With slower epicardial conduction, P wave amplitude was reduced by an average of 20% on leads V3-V5 and P wave area decreased by 50% on leads V1-V2 and by 40% on lead V3. Reversed, lower magnitude effects were observed with slower endocardial conduction.

Conclusion

An endo-epicardial delay of a few milliseconds is sufficient to significantly alter P wave morphology, even if the activation map remains the same.

Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

The roles of mid-myocardial and epicardial cells in T-wave alternans development: a simulation study

Background

The occurrence of T-wave alternans in electrocardiographic signals was recently linked to susceptibility to ventricular arrhythmias and sudden cardiac death. Thus, by detecting and comprehending the origins of T-wave alternans, it might be possible to prevent such events.

Results

Here, we simulated T-wave alternans in a computer-generated human heart model by modulating the action potential duration and amplitude during the first part of the repolarization phase. We hypothesized that changes in the intracardiac alternans patterns of action potential properties would differentially influence T-wave alternans measurements at the body surface. Specifically, changes were simulated globally in the whole left and right ventricles to simulate concordant T-wave alternans, and locally in selected regions to simulate discordant and regional discordant, hereinafter referred to as “regional”, T-wave alternans. Body surface potential maps and 12-lead electrocardiographic signals were then computed. In depth discrimination, the influence of epicardial layers on T-wave alternans development was significantly higher than that of mid-myocardial cells. Meanwhile, spatial discrimination revealed that discordant and regional action potential property changes had a higher influence on T-wave alternans amplitude than concordant changes. Notably, varying T-wave alternans sources yielded distinct body surface potential map patterns for T-wave alternans amplitude, which can be used for location of regions within hearts exhibiting impaired repolarization. The highest ability for T-wave alternans detection was achieved in lead V1. Ultimately, we proposed new parameters Vector Magnitude Alternans and Vector Angle Alternans, with higher ability for T-wave alternans detection when using multi-lead electrocardiographic signals processing than for single leads. Finally, QT alternans was found to be associated with the process of T-wave alternans generation.

Conclusions

The distributions of the body surface T-wave alternans amplitude have been shown to have unique patterns depending on the type of alternans (concordant, discordant or regional) and the location of the disturbance in the heart. The influence of epicardial cells on T-wave alternans development is significantly higher than that of mid-myocardial cells, among which the sub-endocardial layer exerted the highest influence. QT interval alternans is identified as a phenomenon that correlate with T-wave alternans.

Biodegradable and electroconductive poly(3,4-ethylenedioxythiophene)/carboxymethyl chitosan hydrogels for neural tissue engineering

Electroconductive hydrogels with excellent electromechanical properties have become crucial for biomedical applications. In this study, we developed a conductive composite hydrogel via in-situ chemical polymerization based on carboxymethyl chitosan (CMCS), as a biodegradable base macromolecular network, and poly(3,4-ethylenedioxythiophene) (PEDOT), as a conductive polymer layer. The physicochemical and electrochemical properties of conductive hydrogels (PEDOT/CMCS) with different contents of PEDOT polymer were analyzed. Cell viability and proliferation of neuron-like rat phaeochromocytoma (PC12) cells on these three-dimensional conductive hydrogels were evaluated in vitro. As results, the prepared semi-interpenetrating network hydrogels were shown to consist of up to 1825±135wt% of water with a compressive modulus of 9.59±0.49kPa, a porosity of 93.95±1.03% and an electrical conductivity of (4.68±0.28)×10^-3S·cm^-1. Cell experiments confirmed that PEDOT/CMCS hydrogels not only had no cytotoxicity, but also supported cell adhesion, viability and proliferation. These results demonstrated that the incorporation of conductive PEDOT component into CMCS hydrogels endowed the hydrogels with enhanced mechanical strength, conductivity and kept the biocompatibility. Thus, the attractive performances of these composite hydrogels would make them suitable for further neural tissue engineering application, such as nerve regeneration scaffold materials.

Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Sensitivity analysis of ventricular activation and electrocardiogram in tailored models of heart-failure patients

Cardiac resynchronization therapy is not effective in a variable proportion of heart failure patients. An accurate knowledge of each patient's electroanatomical features could be helpful to determine the most appropriate treatment. The goal of this study was to analyze and quantify the sensitivity of left ventricular (LV) activation and the electrocardiogram (ECG) to changes in 39 parameters used to tune realistic anatomical-electrophysiological models of the heart. Electrical activity in the ventricles was simulated using a reaction-diffusion equation. To simulate cellular electrophysiology, the Ten Tusscher-Panfilov 2006 model was used. Intracardiac electrograms and 12-lead ECGs were computed by solving the bidomain equation. Parameters showing the highest sensitivity values were similar in the six patients studied. QRS complex and LV activation times were modulated by the sodium current, the cell surface-to-volume ratio in the LV, and tissue conductivities. The T-wave was modulated by the calcium and rectifier-potassium currents, and the cell surface-to-volume ratio in both ventricles. We conclude that homogeneous changes in ionic currents entail similar effects in all ECG leads, whereas the effects of changes in tissue properties show larger inter-lead variability. The effects of parameter variations are highly consistent between patients and most of the model tuning could be performed with only ~10 parameters.

Evaluation of a Rapid Anisotropic Model for ECG Simulation

State-of-the-art cardiac electrophysiology models that are able to deliver physiologically motivated activation maps and electrocardiograms (ECGs) can only be solved on high-performance computing architectures. This makes it nearly impossible to adopt such models in clinical practice. ECG imaging tools typically rely on simplified models, but these neglect the anisotropic electric conductivity of the tissue in the forward problem. Moreover, their results are often confined to the heart-torso interface. We propose a forward model that fully accounts for the anisotropic tissue conductivity and produces the standard 12-lead ECG in a few seconds. The activation sequence is approximated with an eikonal model in the 3d myocardium, while the ECG is computed with the lead-field approach. Both solvers were implemented on graphics processing units and massively parallelized. We studied the numerical convergence and scalability of the approach. We also compared the method to the bidomain model in terms of ECGs and activation maps, using a simplified but physiologically motivated geometry and 6 patient-specific anatomies. The proposed methods provided a good approximation of activation maps and ECGs computed with a bidomain model, in only a few seconds. Both solvers scaled very well to high-end hardware. These methods are suitable for use in ECG imaging methods, and may soon become fast enough for use in interactive simulation tools.

Equivalent dipole sources to estimate the influence of extracellular myocardial anisotropy in thin-walled cardiac forward models

The extracellular domain of the heart is anisotropic, which affects volume conduction and therefore body surface potentials. This paper tests the hypothesis that when wall thickness is sufficiently small (such as in the atria), the effect of extracellular anisotropy can be estimated by modifying local dipole current sources. A formula based on the Gabor-Nelson equivalent dipole and on the reciprocity theorem is derived to compute a linear transformation of the dipole sources that approximates in an isotropic volume conductor the far-field of the actual sources in an anisotropic volume conductor. It involves solving three Poisson equation (once for all). The results obtained in an atrial model embedded in a boundary-element torso model suggest that when wall thickness is < 3  mm, simulated P waves are weakly altered by extracellular anisotropy during sinus rhythm: an anisotropy ratio of 4:1 typically reduced the longitudinal component of the dipole sources by < 3%, increased the transverse component by < 5%, and increased the transmural component by ≈ 25% (which may be relevant in case of epicardial-endocardial dissociation). Due to uncertainty on experimental conductivity values, it is proposed that atrial extracellular anisotropy may be neglected when computing P waves.

Influence of Modeling Errors on the Initial Estimate for Nonlinear Myocardial Activation Times Imaging Calculated With Fastest Route Algorithm

Noninvasive reconstruction of cardiac electrical activity has a great potential to support clinical decision making, planning, and treatment. Recently, significant progress has been made in the estimation of the cardiac activation from body surface potential maps (BSPMs) using boundary element method (BEM) with the equivalent double layer (EDL) as a source model. In this formulation, noninvasive assessment of activation times results in a nonlinear optimization problem with an initial estimate calculated with the fastest route algorithm (FRA). Each FRA-simulated activation sequence is converted into the ECG. The best initialization is determined by the sequence providing the highest correlation between predicted and measured potentials. We quantitatively assess the effects of the forward modeling errors on the FRA-based initialization. We present three simulation setups to investigate the effects of volume conductor model simplifications, neglecting the cardiac anisotropy and geometrical errors on the localization of ectopic beats starting on the ventricular surface. For the analysis, 12-lead ECG and 99 electrodes BSPM system were used. The areas in the heart exposing the largest localization errors were volume conductor model and electrode configuration specific with an average error <10 mm. The results show the robustness of the FRA-based initialization with respect to the considered modeling errors.

Numerical simulation of electrocardiograms for full cardiac cycles in healthy and pathological conditions

This work is dedicated to the simulation of full cycles of the electrical activity of the heart and the corresponding body surface potential. The model is based on a realistic torso and heart anatomy, including ventricles and atria. One of the specificities of our approach is to model the atria as a surface, which is the kind of data typically provided by medical imaging for thin volumes. The bidomain equations are considered in their usual formulation in the ventricles, and in a surface formulation on the atria. Two ionic models are used: the Courtemanche-Ramirez-Nattel model on the atria and the 'minimal model for human ventricular action potentials' by Bueno-Orovio, Cherry, and Fenton in the ventricles. The heart is weakly coupled to the torso by a Robin boundary condition based on a resistor-capacitor transmission condition. Various electrocardiograms (ECGs) are simulated in healthy and pathological conditions (left and right bundle branch blocks, Bachmann's bundle block, and Wolff-Parkinson-White syndrome). To assess the numerical ECGs, we use several qualitative and quantitative criteria found in the medical literature. Our simulator can also be used to generate the signals measured by a vest of electrodes. This capability is illustrated at the end of the article. Copyright © 2015 John Wiley & Sons, Ltd.

Patient-specific modelling of cardiac electrophysiology in heart-failure patients

Aims

Left-ventricular (LV) conduction disturbances are common in heart-failure patients and a left bundle-branch block (LBBB) electrocardiogram (ECG) type is often seen. The precise cause of this pattern is uncertain and is probably variable between patients, ranging from proximal interruption of the left bundle branch to diffuse distal conduction disease in the working myocardium. Using realistic numerical simulation methods and patient-tailored model anatomies, we investigated different hypotheses to explain the observed activation order on the LV endocardium, electrogram morphologies, and ECG features in two patients with heart failure and LBBB ECG.

Methods and results

Ventricular electrical activity was simulated using reaction–diffusion models with patient-specific anatomies. From the simulated action potentials, ECGs and cardiac electrograms were computed by solving the bidomain equation. Model parameters such as earliest activation sites, tissue conductivity, and densities of ionic currents were tuned to reproduce the measured signals. Electrocardiogram morphology and activation order could be matched simultaneously. Local electrograms matched well at some sites, but overall the measured waveforms had deeper S-waves than the simulated waveforms.

Conclusion

Tuning a reaction–diffusion model of the human heart to reproduce measured ECGs and electrograms is feasible and may provide insights in individual disease characteristics that cannot be obtained by other means.

Modeling left and right atrial contributions to the ECG: A dipole-current source approach

This paper presents the mathematical formulation, the numerical validation and several illustrations of a forward-modeling approach based on dipole-current sources to compute the contribution of a part of the heart to the electrocardiogram (ECG). Clinically relevant applications include identifying in the ECG the contributions from the right and the left atrium. In a Courtemanche-based monodomain computer model of the atria and torso, 1000 dipoles distributed throughout the atrial mid-myocardium are found to be sufficient to reproduce body surface potential maps with a relative error <1% during both sinus rhythm and atrial fibrillation. When the boundary element method is applied to solve the forward problem, this approach enables fast offline computation of the ECG contribution of any anatomical part of the atria by applying the principle of superposition to the dipole sources. In the presence of a right-left activation delay (sinus rhythm), pulmonary vein isolation (sinus rhythm) or left-right differences in refractory period (atrial fibrillation), the decomposition of the ECG is shown to help interpret ECG morphology in relation to the atrial substrate. These tools provide a theoretical basis for a deeper understanding of the genesis of the P wave or fibrillatory waves in normal and pathological cases.

Noninvasive identification of two lesions with local repolarization changes using two dipoles in inverse solution simulation study

BACKGROUND

The method for inverse localization and identification of two distinct simultaneous lesions with changed repolarization in the ventricular myocardium (two-vessel disease) is proposed and its robustness to errors in input data is tested in this simulation study.

METHOD

The inverse solution was obtained from the difference between STT integral body surface potential map computed with repolarization changes and the STT integral map from normal activation. In a numerical model of ventricles 48 cases of two simultaneous lesions and 48 cases of a single lesion were modeled. The effect of the lesions was taken to be represented by two dipoles. The input data were disturbed by three types of added noise. Twenty three characteristics of every obtained inverse solution were defined and four of them were used as the features in discriminant analysis task distinguishing the correct inverse solutions identifying two lesions.

RESULTS

The mean localization error for identified two lesions was 1.1±0.7cm. The sensitivity and specificity of quadratic discriminant analysis with cross-validation and feature selection was higher than 90%.

CONCLUSIONS

The combination of the inverse solution with two dipoles and discriminant analysis allows the identification of two simultaneous lesions without a priori information about the number of lesions.

Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals

Diagnosis and treatment of dilated cardiomyopathy (DCM) is challenging due to a large variety of causes and disease stages. Computational models of cardiac electrophysiology (EP) can be used to improve the assessment and prognosis of DCM, plan therapies and predict their outcome, but require personalization. In this work, we present a data-driven approach to estimate the electrical diffusivity parameter of an EP model from standard 12-lead electrocardiograms (ECG). An efficient forward model based on a mono-domain, phenomenological Lattice-Boltzmann model of cardiac EP, and a boundary element-based mapping of potentials to the body surface is employed. The electrical diffusivity of myocardium, left ventricle and right ventricle endocardium is then estimated using polynomial regression which takes as input the QRS duration and electrical axis. After validating the forward model, we computed 9500 EP simulations on 19 different DCM patients in just under three seconds each to learn the regression model. Using this database, we quantify the intrinsic uncertainty of electrical diffusion for given ECG features and show in a leave-one-patient-out cross-validation that the regression method is able to predict myocardium diffusion within the uncertainty range. Finally, our approach is tested on the 19 cases using their clinical ECG. 84% of them could be personalized using our method, yielding mean prediction errors of 18.7ms for the QRS duration and 6.5° for the electrical axis, both values being within clinical acceptability. By providing an estimate of diffusion parameters from readily available clinical data, our data-driven approach could therefore constitute a first calibration step toward a more complete personalization of cardiac EP.

Electrically conductive chitosan/carbon scaffolds for cardiac tissue engineering

In this work, carbon nanofibers were used as doping material to develop a highly conductive chitosan-based composite. Scaffolds based on chitosan only and chitosan/carbon composites were prepared by precipitation. Carbon nanofibers were homogeneously dispersed throughout the chitosan matrix, and the composite scaffold was highly porous with fully interconnected pores. Chitosan/carbon scaffolds had an elastic modulus of 28.1 ± 3.3 KPa, similar to that measured for rat myocardium, and excellent electrical properties, with a conductivity of 0.25 ± 0.09 S/m. The scaffolds were seeded with neonatal rat heart cells and cultured for up to 14 days, without electrical stimulation. After 14 days of culture, the scaffold pores throughout the construct volume were filled with cells. The metabolic activity of cells in chitosan/carbon constructs was significantly higher as compared to cells in chitosan scaffolds. The incorporation of carbon nanofibers also led to increased expression of cardiac-specific genes involved in muscle contraction and electrical coupling. This study demonstrates that the incorporation of carbon nanofibers into porous chitosan scaffolds improved the properties of cardiac tissue constructs, presumably through enhanced transmission of electrical signals between the cells.

Computational assessment of drug-induced effects on the electrocardiogram: from ion channel to body surface potentials

Background and Purpose

Understanding drug effects on the heart is key to safety pharmacology assessment and anti-arrhythmic therapy development. Here our goal is to demonstrate the ability of computational models to simulate the effect of drug action on the electrical activity of the heart, at the level of the ion-channel, cell, heart and ECG body surface potential.

Experimental Approach

We use the state-of-the-art mathematical models governing the electrical activity of the heart. A drug model is introduced using an ion channel conductance block for the hERG and fast sodium channels, depending on the IC₅₀ value and the drug dose. We simulate the ECG measurements at the body surface and compare biomarkers under different drug actions.

Key Results

Introducing a 50% hERG-channel current block results in 8% prolongation of the APD₉₀ and 6% QT interval prolongation, hERG block does not affect the QRS interval. Introducing 50% fast sodium current block prolongs the QRS and the QT intervals by 12% and 5% respectively, and delays activation times, whereas APD₉₀ is not affected.

Conclusions and Implications

Both potassium and sodium blocks prolong the QT interval, but the underlying mechanism is different: for potassium it is due to APD prolongation; while for sodium it is due to a reduction of electrical wave velocity. This study shows the applicability of in silico models for the investigation of drug effects on the heart, from the ion channel to the ECG-based biomarkers.

Towards real-time simulation of cardiac electrophysiology in a human heart at high resolution

We have developed the capability to rapidly simulate cardiac electrophysiological phenomena in a human heart discretised at a resolution comparable with the length of a cardiac myocyte. Previous scientific investigation has generally invoked simplified geometries or coarse-resolution hearts, with simulation duration limited to 10s of heartbeats. Using state-of-the-art high-performance computing techniques coupled with one of the most powerful computers available (the 20 PFlop/s IBM BlueGene/Q at Lawrence Livermore National Laboratory), high-resolution simulation of the human heart can now be carried out over 1200 times faster compared with published results in the field. We demonstrate the utility of this capability by simulating, for the first time, the formation of transmural re-entrant waves in a 3D human heart. Such wave patterns are thought to underlie Torsades de Pointes, an arrhythmia that indicates a high risk of sudden cardiac death. Our new simulation capability has the potential to impact a multitude of applications in medicine, pharmaceuticals and implantable devices.

Computer simulation of ECG manifestations of left ventricular electrical remodeling

An increased QRS voltage is considered to be specific for the electrocardiogram (ECG) diagnosis of left ventricular hypertrophy (LVH). However, the QRS-complex patterns in patients with LVH cover a broader spectrum: increased QRS voltage, prolonged QRS duration, left axis deviation, and left anterior fascicular block- and left bundle branch block-like patterns, as well as pseudo-normal QRS patterns. The classical interpretation of the QRS patterns in LVH relates these changes to increased left ventricular mass (LVM) per se, while tending to neglect the modified active and passive electrical properties of the myocardium. However, it has been well documented that both active and passive electrical properties in LVH are altered. Using computer simulations, we have shown that an increased LVM is not the only determinant of QRS complex changes in LVH, as these changes could also be produced without changing the left ventricular mass, implying that these QRS patterns can be present in patients before their LVM exceeds the arbitrary upper normal limits. Our results link the experimental evidence on electrical remodeling with clinical interpretation of ECG changes in patients with LVH and stress the necessity of a complex interpretation of the QRS patterns considering both spatial and nonspatial determinants in terms of the spatial angle theory. We assume that hypertrophic electrical remodeling in combination with changes in left ventricular size and shape explains the variety of ECG patterns as well as the discrepancies between ECG and left ventricular mass.

Patient-specific identification of optimal ubiquitous electrocardiogram (U-ECG) placement using a three-dimensional model of cardiac electrophysiology

A bipolar mini-ECG for ubiquitous healthcare (U-ECG) has been introduced, and various studies using the U-ECG device are in progress. Because it uses two electrodes within a small torso surface area, the design of the U-ECG must be suitable for detecting ECG signals. Using a 3-D model of cardiac electrophysiology, we have developed a simulation method for identifying the optimal placement of U-ECG electrodes on the torso surface. We simulated the heart-torso model to obtain a body surface potential map and ECG waveforms, which were compared with the empirical data. Using this model, we determined the optimal placement of the two U-ECG electrodes, spaced 5 cm apart, for detecting the P, R, and T waves. The ECG data, obtained using the optimal U-ECG placement for a specific wave, showed a clear shape for the target wave, but equivocal shapes for the other waves. The present study provides an efficient simulation method to identify the optimal attachment position and direction of the U-ECG electrodes on the surface of the torso.

Predicting the optimal position and direction of a ubiquitous ECG using a multi-scale model of cardiac electrophysiology

In this study, we determined the optimal position and direction of a one-channel bipolar electrocardiogram (ECG), used ubiquitously in healthcare. To do this, we developed a three-dimensional (3D) electrophysiological model of the heart coupled with a torso model that can generate a virtual body surface potential map (BSPM). Finite element models of the atria and ventricles incorporated the electrophysiological dynamics of atrial and ventricular myocytes, respectively. The torso model, in which the electric wave pattern on the cardiac tissue is reflected onto the body surface, was implemented using a boundary element method. Using the model, we derived the optimal positions of two electrodes, 5 cm apart, of the bipolar ubiquitous ECG (U-ECG) for detecting the P, R, and T waves. This model can be used as a simulation tool to design U-ECG device for use for various arrhythmia and normal patients.

Mathematical modeling and simulation of ventricular activation sequences: implications for cardiac resynchronization therapy

Next to clinical and experimental research, mathematical modeling plays a crucial role in medicine. Biomedical research takes place on many different levels, from molecules to the whole organism. Due to the complexity of biological systems, the interactions between components are often difficult or impossible to understand without the help of mathematical models. Mathematical models of cardiac electrophysiology have made a tremendous progress since the first numerical ECG simulations in the 1960s. This paper briefly reviews the development of this field and discusses some example cases where models have helped us forward, emphasizing applications that are relevant for the study of heart failure and cardiac resynchronization therapy.

Closed-form analytical expressions for the potential fields generated by triangular monolayers with linearly distributed source strength

The solution of the mixed boundary value problem of potential theory involves the computation of the potential field generated by monolayer and double layer source distributions on surfaces at which boundary conditions are known. Closed-form analytical expressions have been described in the literature for the potential field generated by double layers having a linearly distributed strength over triangular source elements. This contribution presents the corresponding expression for the linearly distributed monolayer strength. The solution is shown to be valid for all observation points in space, including those on the interior, edges and vertices of the source triangle.

Nanoengineering the heart: conductive scaffolds enhance connexin 43 expression

Scaffolds that couple electrical and elastic properties may be valuable for cardiac cell function. However, existing conductive materials do not mimic physiological properties. We prepared and characterized a tunable, hybrid hydrogel scaffold based on Au nanoparticles homogeneously synthesized throughout a polymer templated gel. Conductive gels had Young's moduli more similar to myocardium relative to polyaniline and polypyrrole, by 1-4 orders of magnitude. Neonatal rat cardiomyocytes exhibited increased expression of connexin 43 on hybrid scaffolds relative to HEMA with or without electrical stimulation.