Laminar Arrangement of Ventricular Myocytes Influences Electrical Behavior of the Heart

Chaos control in cardiac dynamics: terminating chaotic states with local minima pacing

Current treatments of cardiac arrhythmias like ventricular fibrillation involve the application of a high-energy electric shock, that induces significant electrical currents in the myocardium and therefore involves severe side effects like possible tissue damage and post-traumatic stress. Using numerical simulations on four different models of 2D excitable media, this study demonstrates that low energy pulses applied shortly after local minima in the mean value of the transmembrane potential provide high success rates. We evaluate the performance of this approach for ten initial conditions of each model, ten spatially different stimuli, and different shock amplitudes. The investigated models of 2D excitable media cover a broad range of dominant frequencies and number of phase singularities, which demonstrates, that our findings are not limited to a specific kind of model or parameterization of it. Thus, we propose a method that incorporates the dynamics of the underlying system, even during pacing, and solely relies on a scalar observable, which is easily measurable in numerical simulations.

Determinants of electrical propagation and propagation block in Arrhythmogenic Cardiomyopathy

Gap junction and ion channel remodeling occur early in Arrhythmogenic Cardiomyopathy (ACM), but their pathogenic consequences have not been elucidated. Here, we identified the arrhythmogenic substrate, consisting of propagation slowing and conduction block, in ACM models expressing two different desmosomal gene variants. Neonatal rat ventricular myocytes were transduced to express variants in genes encoding desmosomal proteins plakoglobin or plakophilin-2. Studies were performed in engineered cells and anisotropic tissues to quantify changes in conduction velocity, formation of unidirectional propagation, cell-cell electrical coupling, and ion currents. Conduction velocity decreased by 71% and 63% in the two ACM models. SB216763, an inhibitor of glycogen synthase kinase-3 beta, restored conduction velocity to near normal levels. Compared to control, both ACM models showed greater propensity for unidirectional conduction block, which increased further at greater stimulation frequencies. Cell-cell electrical conductance measured in cell pairs was reduced by 86% and 87% in the two ACM models. Computer modeling showed close correspondence between simulated and experimentally determined changes in conduction velocity. The simulation identified that reduced cell-cell electrical coupling was the dominant factor leading to slow conduction, while the combination of reduced cell-cell electrical coupling, reduced sodium current and inward rectifier potassium current explained the development of unidirectional block. Expression of two different ACM variants markedly reduced cell-cell electrical coupling and conduction velocity, and greatly increased the likelihood of developing unidirectional block - both key features of arrhythmogenesis. This study provides the first quantitative analysis of cellular electrophysiological changes leading to the substrate of reentrant arrhythmias in early stage ACM.

Theoretical prediction of early afterdepolarization-evoked triggered activity formation initiating ventricular reentrant arrhythmias

BACKGROUND AND OBJECTIVE

Excessive prolongation of QT interval on ECGs in patients with congenital/acquired long QT syndrome and heart failure is a sign suggesting the development of early afterdepolarization (EAD), an abnormal repolarization in the action potential of ventricular cardiomyocytes. The development of EAD has been believed to be a trigger for fatal tachyarrhythmia, which can be a risk for sudden cardiac death. The role of EAD in triggering ventricular tachycardia (VT) remains unclear. The aim of this study was to elucidate the mechanism of EAD-induced triggered activity formation that leads to the VT such as Torsades de Pointes.

METHODS

We investigated the relationship between EAD and tachyarrhythmia initiation by constructing homogeneous myocardial sheet models consisting of the mid-myocardial cell version of a human ventricular myocyte model and performing simulations of excitation propagation.

RESULTS

A solitary island-like (clustering) occurrence of EADs in the homogeneous myocardial sheet could induce a focal excitation wave. However, reentrant excitation, an entity of tachyarrhythmia, was not able to be triggered regardless of the EAD cluster size when the focal excitation wave formed a repolarization potential difference boundary consisting of only a convex surface. The discontinuous distribution of multiple EAD clusters in the ventricular tissue formed a specific repolarization heterogeneity due to the repolarization potential difference, the shape of which depended on EAD cluster size and placed intervals. We found that the triggered activity was formed in such a manner that the repolarization potential difference boundary included a concave surface.

CONCLUSIONS

The formation of triggered activity that led to tachyarrhythmia required not only the occurrence of EAD onset-mediated focal excitation wave but also a repolarization heterogeneity-based specific repolarization potential difference boundary shape formed within the tissue.

Transmural fibre orientations based on Laplace-Dirichlet-Rule-Based-Methods and their influence on human heart simulations

It is well known that the orthotropic tissue structure decisively influences the mechanical and electrical properties of the heart. Numerous approaches to compute the orthotropic tissue structure in computational heart models have been developed in the past decades. In this study, we investigate to what extent different Laplace-Dirichlet-Rule-Based-Methods (LDRBMs) influence the local orthotropic tissue structure and thus the electromechanical behaviour of the subsequent cardiac simulation. In detail, we are utilising three Laplace-Dirichlet-Rule-Based-Methods and compare: (i) the local myofibre orientation; (ii) important global characteristics (ejection fraction, peak pressure, apex shortening, myocardial volume reduction, fractional wall thickening); (iii) local characteristics (active fibre stress, fibre strain). We observe that the orthotropic tissue structures for the three LDRBMs show significant differences in the local myofibre orientation. The global characteristics myocardial volume reduction and peak pressure are rather insensitive to a change in local myofibre orientation, while the ejection fraction is moderately influenced by the different LDRBMs. Moreover, the apical shortening and fractional wall thickening exhibit a sensitive behaviour to a change in the local myofibre orientation. The highest sensitivity can be observed for the local characteristics.

Image-Based Tools and Analysis for Human RVOT/RV Structures

The right-ventricular (RV) outflow tract (RVOT) and the transition to the RV free wall are recognized sources of arrhythmia in human hearts. However, we do not fully understand myocardial tissue structures in this region. Human heart tissue was processed for optical clarity, labelled with wheat-germ agglutin (WGA) and anti-Cx43, and imaged on a custom-built line scanning confocal microscope. The 3D images were analyzed for myocyte gross structures and cell morphology. There were regions of high organization as well as rapid changes to more heterogeneous regions. Preliminary cell segmentations were used to estimate cell morphology. Observed RVOT/RV structure is consistent with known arrhythmic substrates.Clinical Relevance- New views of human tissue structure enable clearer clinical understanding of arrhythmogenic activation pathways and targets for invasive treatment such as RF ablation.

Backscatter tensor imaging and 3D speckle tracking for simultaneous ex vivo structure and deformation measurement of myocardium

OBJECTIVE

Biaxial mechanical testing is a common method for elucidation of mechanical properties of excised ventricular myocardium, especially in the context of structural remodeling that accompanies heart disease. Current imaging strategies in biaxial testing are based on optical camera imaging of the tissue surface, thus providing no information about the tissue microstructure and limiting strain measurements to two dimensions. Here, these limitations are overcome by replacing the camera with ultrasound imaging in order to measure both transmural fiber orientation and 3D tissue deformation during biaxial testing.

METHODS

Quasi-static biaxial mechanical testing is applied to four samples of excised porcine ventricular myocardium (two left- and two right-ventricular tissues). During testing, a rotational scan of an ultrasound linear array provides data for both backscatter tensor imaging and 3D speckle tracking, from which transmural fiber orientation and tissue deformation are computed, respectively. Ultrasound-derived fiber orientation and tissue strain are validated against histology and camera surface imaging, respectively.

DISCUSSION

Ultrasound-derived fiber angle and tissue strain exhibit good accuracy, with root-mean-square errors of 9.9° and 1.2% strain, respectively. Further investigation into the optimization of backscatter tensor imaging is warranted. Replacing the rotational scan of a linear array with volume imaging with a matrix array will improve the technique.

CONCLUSION

Ultrasound imaging can replace the optical camera measurement during biaxial mechanical testing of ventricular myocardium in order to accurately provide measurements of transmural fiber orientation and tissue strain. In situ knowledge of transmural fiber structure and tissue deformation can enhance the inverse problem used to determine tissue mechanical properties from biaxial testing.

Oscillation of the orientation of cardiomyocyte aggregates in human left ventricle free wall

Orientation of local cardiomyocyte aggregates in the human left ventricle free wall experiences an oscillation in the laminar structure regions, besides its gradual change trend. We described this oscillation using five transmural samples imaged at the European Synchrotron Radiation Facility with an isotropic voxel size of 3.5 × 3.5 × 3.5 μm³ . In the reconstructed volume of each sample, we manually selected a region containing a regular laminar structure as the region of interest and measured the distribution of the orientation of local cardiomyocyte aggregates inside using a Fourier-based method. Then, we extracted the gradual change part of the orientation of cardiomyocyte aggregates with a three-dimensional centered Gaussian filter and measured the angle between the original orientation vector of local cardiomyocyte aggregates and its gradual change part. Further, we assessed the measured angles in different local coordinates. The results indicate that the oscillation amplitude of the orientation of cardiomyocyte aggregates is regional in the left ventricle wall, which may promote our understanding of the rearrangement mechanism of the cardiomyocyte aggregates and provide a new biomarker to study the heart physiological status.

The basic heart anatomy and physiology from the cardiologist's perspective: Toward a better understanding of left ventricular mechanics, systolic, and diastolic function

A comprehensive understanding of the cardiac structure-function relationship is essential for proper clinical cardiac imaging. This review summarizes the basic heart anatomy and physiology from the perspective of a heart imager focused on myocardial mechanics. The main issues analyzed are the left ventricular (LV) architecture, the LV myocardial deformation through the cardiac cycle, the LV diastolic function basic parameters and the basic parameters of the LV deformation used in clinical practice for the LV function assessment.

Advancing Engineered Heart Muscle Tissue Complexity with Hydrogel Composites

A heart attack results in the permanent loss of heart muscle and can lead to heart disease, which kills more than 7 million people worldwide each year. To date, outside of heart transplantation, current clinical treatments cannot regenerate lost heart muscle or restore full function to the damaged heart. There is a critical need to create engineered heart tissues with structural complexity and functional capacity needed to replace damaged heart muscle. The inextricable link between structure and function suggests that hydrogel composites hold tremendous promise as a biomaterial-guided strategy to advance heart muscle tissue engineering. Such composites provide biophysical cues and functionality as a provisional extracellular matrix that hydrogels cannot on their own. This review describes the latest advances in the characterization of these biomaterial systems and using them for heart muscle tissue engineering. The review integrates results across the field to provide new insights on critical features within hydrogel composites and perspectives on the next steps to harnessing these promising biomaterials to faithfully reproduce the complex structure and function of native heart muscle.

An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias

Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.

A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI: An application to the ventricular junctions

Background

Knowledge of the normal myocardial–myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented.

Methods

Three explanted sheep (ovine) hearts (size ~12×8×6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy …) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template.

Results

The template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 μm and 600 μm respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition.

Conclusions

A new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.

Confocal microscopy-based estimation of intracellular conductivities in myocardium for modeling of the normal and infarcted heart

Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytes (V_myo), gap junctions-containing voxels (V_gj), and fibrosis (V_fibrosis). We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson's equation for stationary electrical currents, we calculated normal (σ_myo,n), longitudinal (σ_myo,l), and transverse (σ_myo,t) intracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features. V_gj and V_myo were reduced in MI vs. control, but V_fibrosis was increased. Both σ_myo,l and σ_myo,n were lower in MI than in control. Differences of σ_myo,t between control and MI were not significant. We found strong positive relationships of σ_myo,l with V_myo and V_gj, and a strong negative relationship with V_fibrosis. The relationships of σ_myo,n with these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.

On the Electrophysiology and Mapping of Intramural Arrhythmic Focus

BACKGROUND

Conventional mapping of focal ventricular arrhythmias relies on unipolar electrogram characteristics and early local activation times. Deep intramural foci are common and associated with high recurrence rates following catheter-based radiofrequency ablation. We assessed the accuracy of unipolar morphological patterns and mapping surface indices to predict the site and depth of ventricular arrhythmogenic focal sources.

METHODS

An experimental beating-heart model used Langendorff-perfused, healthy swine hearts. A custom 56-pole electrode array catheter was positioned on the left ventricle. A plunge needle was placed perpendicular in the center of the grid to simulate arrhythmic foci at variable depths. Unipolar electrograms and local activation times were generated. Simulation models from 2 human hearts were also included with grids positioned simultaneously on the endocardium-epicardium from multiple left ventricular, septal, and outflow tract sites.

RESULTS

A unipolar Q or QS complex lacks specificity for superficial arrhythmic foci, as this morphology pattern occupies a large surface area and is the predominant pattern as intramural depth increases without developing a R component. There is progressive displacement from the arrhythmic focus to the surface exit as intramural focus depth increases. A shorter total activation time over the overlying electrode array, larger surface area within initial 20 ms activation, and a dual surface breakout pattern all indicate a deep focus.

CONCLUSIONS

Displacement from the focal intramural origin to the exit site on the mapping surface could lead to erroneous lesion delivery strategies. Traditional unipolar electrogram features lack specificity to predict the intramural arrhythmic source; however, novel endocardial-epicardial mapping surface indices can be used to determine the depth of arrhythmic foci.

Combined In-silico and Machine Learning Approaches Toward Predicting Arrhythmic Risk in Post-infarction Patients

Background: Remodeling due to myocardial infarction (MI) significantly increases patient arrhythmic risk. Simulations using patient-specific models have shown promise in predicting personalized risk for arrhythmia. However, these are computationally- and time- intensive, hindering translation to clinical practice. Classical machine learning (ML) algorithms (such as K-nearest neighbors, Gaussian support vector machines, and decision trees) as well as neural network techniques, shown to increase prediction accuracy, can be used to predict occurrence of arrhythmia as predicted by simulations based solely on infarct and ventricular geometry. We present an initial combined image-based patient-specific in silico and machine learning methodology to assess risk for dangerous arrhythmia in post-infarct patients. Furthermore, we aim to demonstrate that simulation-supported data augmentation improves prediction models, combining patient data, computational simulation, and advanced statistical modeling, improving overall accuracy for arrhythmia risk assessment.

Methods: MRI-based computational models were constructed from 30 patients 5 days post-MI (the “baseline” population). In order to assess the utility biophysical model-supported data augmentation for improving arrhythmia prediction, we augmented the virtual baseline patient population. Each patient ventricular and ischemic geometry in the baseline population was used to create a subfamily of geometric models, resulting in an expanded set of patient models (the “augmented” population). Arrhythmia induction was attempted via programmed stimulation at 17 sites for each virtual patient corresponding to AHA LV segments and simulation outcome, “arrhythmia,” or “no-arrhythmia,” were used as ground truth for subsequent statistical prediction (machine learning, ML) models. For each patient geometric model, we measured and used choice data features: the myocardial volume and ischemic volume, as well as the segment-specific myocardial volume and ischemia percentage, as input to ML algorithms. For classical ML techniques (ML), we trained k-nearest neighbors, support vector machine, logistic regression, xgboost, and decision tree models to predict the simulation outcome from these geometric features alone. To explore neural network ML techniques, we trained both a three - and a four-hidden layer multilayer perceptron feed forward neural networks (NN), again predicting simulation outcomes from these geometric features alone. ML and NN models were trained on 70% of randomly selected segments and the remaining 30% was used for validation for both baseline and augmented populations.

Results: Stimulation in the baseline population (30 patient models) resulted in reentry in 21.8% of sites tested; in the augmented population (129 total patient models) reentry occurred in 13.0% of sites tested. ML and NN models ranged in mean accuracy from 0.83 to 0.86 for the baseline population, improving to 0.88 to 0.89 in all cases.

Conclusion: Machine learning techniques, combined with patient-specific, image-based computational simulations, can provide key clinical insights with high accuracy rapidly and efficiently. In the case of sparse or missing patient data, simulation-supported data augmentation can be employed to further improve predictive results for patient benefit. This work paves the way for using data-driven simulations for prediction of dangerous arrhythmia in MI patients.

Novel Optics-Based Approaches for Cardiac Electrophysiology: A Review

Optical techniques for recording and manipulating cellular electrophysiology have advanced rapidly in just a few decades. These developments allow for the analysis of cardiac cellular dynamics at multiple scales while largely overcoming the drawbacks associated with the use of electrodes. The recent advent of optogenetics opens up new possibilities for regional and tissue-level electrophysiological control and hold promise for future novel clinical applications. This article, which emerged from the international NOTICE workshop in 2018, reviews the state-of-the-art optical techniques used for cardiac electrophysiological research and the underlying biophysics. The design and performance of optical reporters and optogenetic actuators are reviewed along with limitations of current probes. The physics of light interaction with cardiac tissue is detailed and associated challenges with the use of optical sensors and actuators are presented. Case studies include the use of fluorescence recovery after photobleaching and super-resolution microscopy to explore the micro-structure of cardiac cells and a review of two photon and light sheet technologies applied to cardiac tissue. The emergence of cardiac optogenetics is reviewed and the current work exploring the potential clinical use of optogenetics is also described. Approaches which combine optogenetic manipulation and optical voltage measurement are discussed, in terms of platforms that allow real-time manipulation of whole heart electrophysiology in open and closed-loop systems to study optimal ways to terminate spiral arrhythmias. The design and operation of optics-based approaches that allow high-throughput cardiac electrophysiological assays is presented. Finally, emerging techniques of photo-acoustic imaging and stress sensors are described along with strategies for future development and establishment of these techniques in mainstream electrophysiological research.

Cardiac Conduction Velocity, Remodeling and Arrhythmogenesis

Cardiac electrophysiological disorders, in particular arrhythmias, are a key cause of morbidity and mortality throughout the world. There are two basic requirements for arrhythmogenesis: an underlying substrate and a trigger. Altered conduction velocity (CV) provides a key substrate for arrhythmogenesis, with slowed CV increasing the probability of re-entrant arrhythmias by reducing the length scale over which re-entry can occur. In this review, we examine methods to measure cardiac CV in vivo and ex vivo, discuss underlying determinants of CV, and address how pathological variations alter CV, potentially increasing arrhythmogenic risk. Finally, we will highlight future directions both for methodologies to measure CV and for possible treatments to restore normal CV.

Atrial slow conduction develops and dynamically expands during premature stimulation in an animal model of persistent atrial fibrillation

Slow conduction areas and conduction block in the atria are considered pro-arrhythmic conditions. Studies examining the size and distribution of slow conduction regions in the context of persistent atrial fibrillation (AF) may help to develop improved therapeutic strategies for patients with AF. In this work, we studied the differences of size and number in slow conduction areas between control and persistent AF goats and the influence of propagation direction on the development of these pathological conduction areas. Epicardial atrial electrical activations from the left atrial roof were optically mapped with physiological pacing cycle lengths and for the shortest captured cycle lengths. The recordings were converted to local activation times and conduction velocity measures. Regions with slow conduction velocity (less than [Formula: see text]) were identified. The size of the connected regions and the number of non-connected regions were counted for propagation from different orthogonal directions. We found that regions of slow conduction significantly increases in our 15 persistent AF goat recordings in response to premature stimulation (24.4±4.3% increase to 36.6±4.4%, p < 0.001). This increase is driven by an increase of size from (3.70±0.89[mm2] to 6.36±0.91[mm2], p = 0.014) for already existing regions and not by generation of new slow conduction regions (11.6±1.8 vs. 13±1.9, p = 0.242). In 12 control goat recordings, no increase from baseline pacing to premature pacing was found. Similarly, size of the slow conduction areas and the count did not change significantly in control animals.

Which bidomain conductivity is the most important for modelling heart and torso surface potentials during ischaemia?

Mathematical simulations using the bidomain model, which represents cardiac tissue as consisting of an intracellular and an extracellular space, are a key approach that can be used to improve understanding of heart conditions such as ischaemia. However, key inputs to these models, such as the bidomain conductivity values, are not known with any certainty. Since efforts are underway to measure these values, it would be useful to be able to quantify the effect on model outputs of uncertainty in these inputs, and also to determine, if possible, which are the most important values to focus on in experimental studies. Our previous work has systematically studied the sensitivity of heart surface potentials to the bidomain conductivity values, and this was performed using a half-ellipsoidal model of the left ventricle. This study uses a bi-ventricular heart in a torso model and this time looks at the sensitivity of the torso surface potentials, as well as the heart surface potentials, to various conductivity values (blood, torso and the six bidomain conductivities). We found that both epicardial and torso potentials are the most sensitive to the intracellular longitudinal (along the cardiac fibres) conductivity (g_il) with more minor sensitivity to the torso conductivity, and that changes in g_il have a significant effect on the surface potential distributions on both the torso and the heart.

Conditioning of hiPSC-derived cardiomyocytes using surface topography obtained with high throughput technology

Surface functionalization of polymers aims to introduce novel properties that favor bioactive responses. We have investigated the possibility of surface functionalization of polyethylene terephthalate (PET) sheets by the combination of laser ablation with hot embossing and the application of such techniques in the field of stem cell research. We investigated the response of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to topography in the low micrometer range. HiPSC-CMs are expected to offer new therapeutic tools for myocardial replacement or regeneration after an infarct or other causes of cardiac tissue loss. However, hiPSC-CMs are phenotypically immature compared to myocytes in the adult myocardium, hampering their clinical application. We aimed to develop and test a high-throughput technique for surface structuring that would improve hiPSC-CMs structural maturation. We used laser ablation with a ps-laser source in combination with nanoimprint lithography to fabricate large areas of homogeneous micron- to submicron line-like pattern with a spatial period of 3 µm on the PET surface. We evaluated cell morphology, alignment, sarcomeric myofibrils assembly, and calcium transients to evaluate phenotypic changes associated with culturing hiPSC-CMs on functionalized PET. Surface functionalization through hot embossing was able to generate, at low cost, low micrometer features on the PET surface that influenced the hiPSC-CMs phenotype, suggesting improved structural and functional maturation. This technique may be relevant for high-throughput technologies that require conditioning of hiPSC-CMs and may be useful for the production of these cells for drug screening and disease modeling applications with lower costs.

Impulse Data Model For Solving The Inverse Problem of Electrocardiography

OBJECTIVE

To develop, train and test neural networks for predicting heart surface potentials (HSPs) from body surface potentials (BSPs). The method re-frames traditional inverse problems of electrocardiograpy into regression problems, constraining the solution space by decomposing signals with multidimensional Gaussian impulse basis functions.

METHODS

Impulse HSPs were generated with single Gaussian basis functions at discrete heart surface locations and projected to corresponding BSPs using a volume conductor torso model. Both BSP (inputs) and HSP (outputs) were mapped to regular 2D surface meshes and used to train a neural network. Predictive capabilities of the network were tested with unseen synthetic and experimental data.

RESULTS

A dense full connected single hidden layer neural network was trained to map body surface impulses to heart surface Gaussian basis functions for reconstructing HSP. Synthetic pulses moving across the heart surface were predicted from the neural network with root mean squared error of 9.1 +/ 1.4%. Predicted signals were robust to noise up to 20 dB and errors due to displacement and rotation of the heart within the torso were bounded and predictable. A shift of the heart 40 mm toward the spine resulted in a 4% increase in signal feature localization error. The set of training impulse function data could be reduced and prediction error remained bounded. Recorded HSPs from in-vitro pig hearts were reliably decomposed using space-time Gaussian basis functions. Activation times calculated from predicted HSPs for left-ventricular pacing had a mean absolute error of 10.4 +/ 11.4 ms. Other pacing scenarios were analyzed with similar success.

CONCLUSION

Impulses from Gaussian basis functions are potentially an effective and robust way to train simple neural network data models for reconstructing HSPs from decomposed BSPs.

SIGNIFICANCE

The HSPs predicted by the neural network can be used to generate activation maps that non-invasively identify features of cardiac electrical dysfunction and can guide subsequent treatment options.

Epicardial origin of cardiac arrhythmias: clinical evidences and pathophysiology

Recent developments in imaging, mapping, and ablation techniques have shown that the epicardial region of the heart is a key player in the occurrence of ventricular arrhythmic events in several cardiac diseases, such as Brugada syndrome, arrhythmogenic cardiomyopathy, or dilated cardiomyopathy. At the atrial level as well, the epicardial region has emerged as an important determinant of the substrate of atrial fibrillation, pointing to common underlying pathophysiological mechanisms. Alteration in the gradient of repolarization between myocardial layers favouring the occurrence of re-entry circuits has largely been described. The fibro-fatty infiltration of the subepicardium is another shared substrate between ventricular and atrial arrhythmias. Recent data have emphasized the role of the epicardial reactivation in the formation of this arrhythmogenic substrate. There are new evidences supporting this structural remodelling process to be regulated by the recruitment of epicardial progenitor cells that can differentiate into adipocytes or fibroblasts under various stimuli. In addition, immune-inflammatory processes can also contribute to fibrosis of the subepicardial layer. A better understanding of such ‘electrical fragility’ of the epicardial area will open perspectives for novel biomarkers and therapeutic strategies. In this review article, a pathophysiological scheme of epicardial-driven arrhythmias will be proposed.

It's clearly the heart! Optical transparency, cardiac tissue imaging, and computer modelling

Recent developments in clearing and microscopy enable 3D imaging with cellular resolution up to the whole organ level. These methods have been used extensively in neurobiology, but their uptake in other fields has been much more limited. Application of this approach to the human heart and effective use of the data acquired present challenges of scale and complexity. Four interlinked issues need to be addressed: 1) efficient clearing and labelling of heart tissue, 2) fast microscopic imaging of human-scale samples, 3) handling and processing of multi-terabyte 3D images, and 4) extraction of structural information in computationally tractable structure-based models of cardiac function. Preliminary studies show that each of these requirements can be achieved with the appropriate application and development of existing technologies.

3D MRI of explanted sheep hearts with submillimeter isotropic spatial resolution: comparison between diffusion tensor and structure tensor imaging

Objective

The aim of the study is to compare structure tensor imaging (STI) with diffusion tensor imaging (DTI) of the sheep heart (approximately the same size as the human heart).

Materials and methods

MRI acquisition on three sheep ex vivo hearts was performed at 9.4 T/30 cm with a seven-element RF coil. 3D FLASH with an isotropic resolution of 150 µm and 3D spin-echo DTI at 600 µm were performed. Tensor analysis, angles extraction and segments divisions were performed on both volumes.

Results

A 3D FLASH allows for visualization of the detailed structure of the left and right ventricles. The helix angle determined using DTI and STI exhibited a smooth transmural change from the endocardium to the epicardium. Both the helix and transverse angles were similar between techniques. Sheetlet organization exhibited the same pattern in both acquisitions, but local angle differences were seen and identified in 17 segments representation.

Discussion

This study demonstrated the feasibility of high-resolution MRI for studying the myocyte and myolaminar architecture of sheep hearts. We presented the results of STI on three whole sheep ex vivo hearts and demonstrated a good correspondence between DTI and STI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00913-4.

Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling

BACKGROUND

Identification of targets for ablation of post-infarction ventricular tachycardias (VTs) remains challenging, often requiring arrhythmia induction to delineate the reentrant circuit. This carries a risk for the patient and may not be feasible. Substrate mapping has emerged as a safer strategy to uncover arrhythmogenic regions. However, VT recurrence remains common.

GOAL

To use computer simulations to assess the ability of different substrate mapping approaches to identify VT exit sites.

METHODS

A 3D computational model of the porcine post-infarction heart was constructed to simulate VT and paced rhythm. Electroanatomical maps were constructed based on endocardial electrogram features and the reentry vulnerability index (RVI - a metric combining activation (AT) and repolarization timings to identify tissue susceptibility to reentry). Since scar transmurality in our model was not homogeneous, parameters derived from all signals (including dense scar regions) were used in the analysis. Potential ablation targets obtained from each electroanatomical map during pacing were compared to the exit site detected during VT mapping.

RESULTS

Simulation data showed that voltage cut-offs applied to bipolar electrograms could delineate the scar, but not the VT circuit. Electrogram fractionation had the highest correlation with scar transmurality. The RVI identified regions closest to VT exit site but was outperformed by AT gradients combined with voltage cut-offs. The performance of all metrics was affected by pacing location.

CONCLUSIONS

Substrate mapping could provide information about the infarct, but the directional dependency on activation should be considered. Activation-repolarization metrics have utility in safely identifying VT targets, even with non-transmural scars.

Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis

Cardiac resynchronization therapy (CRT) can substantially improve dyssynchronous heart failure and reduce mortality. However, about one-third of patients who are implanted, derive no measurable benefit from CRT. Non-response may partly be due to suboptimal activation of the left ventricle (LV) caused by electrophysiological heterogeneities. The goal of this study is to investigate the performance of a newly developed method used to analyze electrical wavefront propagation in a heart model including myocardial scar and compare this to clinical benchmark studies. We used computational models to measure the maximum activation front (MAF) in the LV during different pacing scenarios. Different heart geometries and scars were created based on cardiac MR images of three patients. The right ventricle (RV) was paced from the apex and the LV was paced from 12 different sites, single site, dual-site and triple site. Our results showed that for single LV site pacing, the pacing site with the largest MAF corresponded with the latest activated regions of the LV demonstrated during RV pacing, which also agrees with previous markers used for predicting optimal single-site pacing location. We then demonstrated the utility of MAF in predicting optimal electrode placements in more complex scenarios including scar and multi-site LV pacing. This study demonstrates the potential value of computational simulations in understanding and planning CRT.

Anisotropic Cardiac Conduction

Anisotropy is the property of directional dependence. In cardiac tissue, conduction velocity is anisotropic and its orientation is determined by myocyte direction. Cell shape and size, excitability, myocardial fibrosis, gap junction distribution and function are all considered to contribute to anisotropic conduction. In disease states, anisotropic conduction may be enhanced, and is implicated, in the genesis of pathological arrhythmias. The principal mechanism responsible for enhanced anisotropy in disease remains uncertain. Possible contributors include changes in cellular excitability, changes in gap junction distribution or function and cellular uncoupling through interstitial fibrosis. It has recently been demonstrated that myocyte orientation may be identified using diffusion tensor magnetic resonance imaging in explanted hearts, and multisite pacing protocols have been proposed to estimate myocyte orientation and anisotropic conduction in vivo. These tools have the potential to contribute to the understanding of the role of myocyte disarray and anisotropic conduction in arrhythmic states.

Assessing Myocardial Architecture: The Challenges and Controversies

In recent decades, investigators have strived to describe and quantify the orientation of the cardiac myocytes in an attempt to classify their arrangement in healthy and diseased hearts. There are, however, striking differences between the investigations from both a technical and methodological standpoint, thus limiting their comparability and impeding the drawing of appropriate physiological conclusions from the structural assessments. This review aims to elucidate these differences, and to propose guidance to establish methodological consensus in the field. The review outlines the theory behind myocyte orientation analysis, and importantly has identified pronounced differences in the definitions of otherwise widely accepted concepts of myocytic orientation. Based on the findings, recommendations are made for the future design of studies in the field of myocardial morphology. It is emphasised that projection of myocyte orientations, before quantification of their angulation, introduces considerable bias, and that angles should be assessed relative to the epicardial curvature. The transmural orientation of the cardiomyocytes should also not be neglected, as it is an important determinant of cardiac function. Finally, there is considerable disagreement in the literature as to how the orientation of myocardial aggregates should be assessed, but to do so in a mathematically meaningful way, the normal vector of the aggregate plane should be utilised.

Approaches for determining cardiac bidomain conductivity values: progress and challenges

Modelling the electrical activity of the heart is an important tool for understanding electrical function in various diseases and conduction disorders. Clearly, for model results to be useful, it is necessary to have accurate inputs for the models, in particular the commonly used bidomain model. However, there are only three sets of four experimentally determined conductivity values for cardiac ventricular tissue and these are inconsistent, were measured around 40 years ago, often produce different results in simulations and do not fully represent the three-dimensional anisotropic nature of cardiac tissue. Despite efforts in the intervening years, difficulties associated with making the measurements and also determining the conductivities from the experimental data have not yet been overcome. In this review, we summarise what is known about the conductivity values, as well as progress to date in meeting the challenges associated with both the mathematical modelling and the experimental techniques. Graphical abstract Epicardial potential distributions, arising from a subendocardial ischaemic region, modelled using conductivity data from the indicated studies.

An Inverse Eikonal Method for Identifying Ventricular Activation Sequences from Epicardial Activation Maps

A key mechanism controlling cardiac function is the electrical activation sequence of the heart's main pumping chambers termed the ventricles. As such, personalization of the ventricular activation sequences is of pivotal importance for the clinical utility of computational models of cardiac electrophysiology. However, a direct observation of the activation sequence throughout the ventricular volume is virtually impossible. In this study, we report on a novel method for identification of activation sequences from activation maps measured at the outer surface of the heart termed the epicardium. Conceptually, the method attempts to identify the key factors governing the ventricular activation sequence - the timing of earliest activation sites (EAS) and the velocity tensor field within the ventricular walls - from sparse and noisy activation maps sampled from the epicardial surface and fits an Eikonal model to the observations. Regularization methods are first investigated to overcome the severe ill-posedness of the inverse problem in a simplified 2D example. These methods are then employed in an anatomically accurate biventricular model with two realistic activation models of varying complexity - a simplified trifascicular model (3F) and a topologically realistic model of the His-Purkinje system (HPS). Using epicardial activation maps at full resolution, we first demonstrate that reconstructing the volumetric activation sequence is, in principle, feasible under the assumption of known location of EAS and later evaluate robustness of the method against noise and reduced spatial resolution of observations. Our results suggest that the FIMIN algorithm is able to robustly recover the full 3D activation sequence using epicardial activation maps at a spatial resolution achievable with current mapping systems and in the presence of noise. Comparing the accuracy achieved in the reconstructed activation maps with clinical data uncertainties suggests that the FIMIN method may be suitable for the patient- specific parameterization of activation models.

Multi-scale approaches for the simulation of cardiac electrophysiology: II - Tissue-level structure and function

Computational models of the heart, from cell-level models, through one-, two- and three-dimensional tissue-level simplifications, to biophysically-detailed three-dimensional models of the ventricles, atria or whole heart, allow the simulation of excitation and propagation of this excitation, and have provided remarkable insight into the normal and pathological functioning of the heart. In this article we present equations for modelling cellular excitation (i.e. the cell action potential) from both a phenomenological and a biophysical perspective. Hodgkin-Huxley formalism is discussed, along with the current generation of biophysically-detailed cardiac cell models. Alternative Markovian formulations for modelling ionic currents are also presented. Equations describing propagation of this cellular excitation, through one-, two- and three-dimensional idealised or realistic tissues, are then presented. For all types of model, from cell to tissue, methods for discretisation and integration of the underlying equations are discussed. The article finishes with a discussion of two tissue-level experimental imaging techniques - diffusion tensor magnetic resonance imaging and optical imaging - that can be used to provide data for parameterisation and validation of cell- and tissue-level cardiac models.

Factors Promoting Conduction Slowing as Substrates for Block and Reentry in Infarcted Hearts

The development of effective and safe therapies for scar-related ventricular tachycardias requires a detailed understanding of the mechanisms underlying the conduction block that initiates electrical re-entries associated with these arrhythmias. Conduction block has been often associated with electrophysiological changes that prolong action potential duration (APD) within the border zone (BZ) of chronically infarcted hearts. However, experimental evidence suggests that remodeling processes promoting conduction slowing as opposed to APD prolongation mark the chronic phase. In this context, the substrate for the initial block at the mouth of an isthmus/diastolic channel leading to ventricular tachycardia is unclear. The goal of this study was to determine whether electrophysiological parameters associated with conduction slowing can cause block and re-entry in the BZ. In silico experiments were conducted on two-dimensional idealized infarct tissue as well as on a cohort of postinfarction porcine left ventricular models constructed from ex vivo magnetic resonance imaging scans. Functional conduction slowing in the BZ was modeled by reducing sodium current density, whereas structural conduction slowing was represented by decreasing tissue conductivity and including fibrosis. The arrhythmogenic potential of APD prolongation was also tested as a basis for comparison. Within all models, the combination of reduced sodium current with structural remodeling more often degenerated into re-entry and, if so, was more likely to be sustained for more cycles. Although re-entries were also detected in experiments with prolonged APD, they were often not sustained because of the subsequent block caused by long-lasting repolarization. Functional and structural conditions associated with slow conduction rather than APD prolongation form a potent substrate for arrhythmogenesis at the isthmus/BZ of chronically infarcted hearts. Reduced excitability led to block while slow conduction shortened the wavelength of propagation, facilitating the sustenance of re-entries. These findings provide important insights for models of patient-specific risk stratification and therapy planning.

Quantitative descriptions of extended volume cardiac tissue architecture from multiple large hearts

The arrangement of cardiac cells into strand and sheet-like structures within the heart wall, confers important electrical properties onto heart tissue. Unraveling cardiomyocyte architecture in both healthy and diseased hearts is fundamental to understanding the mechanisms generating normal rhythm and arrhythmia. We analyzed five extended volume serial image stacks of normal pig left ventricular tissue. Analysis included: (1) reconstruction of original tissue volume and shape with non-linear correction maps; (2) segmentation and higher-order descriptions, areas and orientations of laminar structures through the heart wall; (3)computation of fiber directions; (4) computation of tissue connectivity using a shell filter. These measures contributed to a deeper and more objective understanding of cardiac tissue structures and their spatial variation than previously possible.

A Multiphysics Biventricular Cardiac Model: Simulations With a Left-Ventricular Assist Device

Computational models have become essential in predicting medical device efficacy prior to clinical studies. To investigate the performance of a left-ventricular assist device (LVAD), a fully-coupled cardiac fluid-electromechanics finite element model was developed, incorporating electrical activation, passive and active myocardial mechanics, as well as blood hemodynamics solved simultaneously in an idealized biventricular geometry. Electrical activation was initiated using a simplified Purkinje network with one-way coupling to the surrounding myocardium. Phenomenological action potential and excitation-contraction equations were adapted to trigger myocardial contraction. Action potential propagation was formulated within a material frame to emulate gap junction-controlled propagation, such that the activation sequence was independent of myocardial deformation. Passive cardiac mechanics were governed by a transverse isotropic hyperelastic constitutive formulation. Blood velocity and pressure were determined by the incompressible Navier-Stokes formulations with a closed-loop Windkessel circuit governing the circulatory load. To investigate heart-LVAD interaction, we reduced the left ventricular (LV) contraction stress to mimic a failing heart, and inserted a LVAD cannula at the LV apex with continuous flow governing the outflow rate. A proportional controller was implemented to determine the pump motor voltage whilst maintaining pump motor speed. Following LVAD insertion, the model revealed a change in the LV pressure-volume loop shape from rectangular to triangular. At higher pump speeds, aortic ejection ceased and the LV decompressed to smaller end diastolic volumes. After multiple cycles, the LV cavity gradually collapsed along with a drop in pump motor current. The model was therefore able to predict ventricular collapse, indicating its utility for future development of control algorithms and pre-clinical testing of LVADs to avoid LV collapse in recipients.

Conduction in the Heart Wall: Helicoidal Fibers Minimize Diffusion Bias

The mammalian heart must function as an efficient pump while simultaneously conducting electrical signals to drive the contraction process. In the ventricles, electrical activation begins at the insertion points of the Purkinje network in the endocardium. How does the diffusion component of the subsequent excitation wave propagate from the endocardium in a healthy heart wall without creating directional biases? We show that this is a consequence of the particular geometric organization of myocytes in the heart wall. Using a generalized helicoid to model fiber orientation, we treat the myocardium as a curved space via Riemannian geometry, and then use stochastic calculus to model local signal diffusion. Our analysis shows that the helicoidal arrangement of myocytes minimizes the directional biases that could lead to aberrant propagation, thereby explaining how electrophysiological principles are consistent with local measurements of cardiac fiber geometry. We discuss our results in the context of the need to balance electrical and mechanical requirements for heart function.

Three-dimensional Cardiomyocytes Structure Revealed By Diffusion Tensor Imaging and Its Validation Using a Tissue-Clearing Technique

We characterized the microstructural response of the myocardium to cardiovascular disease using diffusion tensor imaging (DTI) and performed histological validation by intact, un-sectioned, three-dimensional (3D) histology using a tissue-clearing technique. The approach was validated in normal (n = 7) and ischemic (n = 8) heart failure model mice. Whole heart fiber tracking using DTI in fixed ex-vivo mouse hearts was performed, and the hearts were processed with the tissue-clearing technique. Cardiomyocytes orientation was quantified on both DTI and 3D histology. Helix angle (HA) and global HA transmurality (HAT) were calculated, and the DTI findings were confirmed with 3D histology. Global HAT was significantly reduced in the ischemic group (DTI: 0.79 ± 0.13°/% transmural depth [TD] and 3D histology: 0.84 ± 0.26°/%TD) compared with controls (DTI: 1.31 ± 0.20°/%TD and 3D histology: 1.36 ± 0.27°/%TD, all p < 0.001). On direct comparison of DTI with 3D histology for the quantitative assessment of cardiomyocytes orientation, significant correlations were observed in both per-sample (R2 = 0.803) and per-segment analyses (R2 = 0.872). We demonstrated the capability and accuracy of DTI for mapping cardiomyocytes orientation by comparison with the intact 3D histology acquired by tissue-clearing technique. DTI is a promising tool for the noninvasive characterization of cardiomyocytes architecture.

Confocal Microscopy-Based Estimation of Parameters for Computational Modeling of Electrical Conduction in the Normal and Infarcted Heart

Computational modeling is an important tool to advance our knowledge on cardiac diseases and their underlying mechanisms. Computational models of conduction in cardiac tissues require identification of parameters. Our knowledge on these parameters is limited, especially for diseased tissues. Here, we assessed and quantified parameters for computational modeling of conduction in cardiac tissues. We used a rabbit model of myocardial infarction (MI) and an imaging-based approach to derive the parameters. Left ventricular tissue samples were obtained from fixed control hearts (animals: 5) and infarcted hearts (animals: 6) within 200 μm (region 1), 250-750 μm (region 2) and 1,000-1,250 μm (region 3) of the MI border. We assessed extracellular space, fibroblasts, smooth muscle cells, nuclei and gap junctions by a multi-label staining protocol. With confocal microscopy we acquired three-dimensional (3D) image stacks with a voxel size of 200 × 200 × 200 nm. Image segmentation yielded 3D reconstructions of tissue microstructure, which were used to numerically derive extracellular conductivity tensors. Volume fractions of myocyte, extracellular, interlaminar cleft, vessel and fibroblast domains in control were (in %) 65.03 ± 3.60, 24.68 ± 3.05, 3.95 ± 4.84, 7.71 ± 2.15, and 2.48 ± 1.11, respectively. Volume fractions in regions 1 and 2 were different for myocyte, myofibroblast, vessel, and extracellular domains. Fibrosis, defined as increase in fibrotic tissue constituents, was (in %) 21.21 ± 1.73, 16.90 ± 9.86, and 3.58 ± 8.64 in MI regions 1, 2, and 3, respectively. For control tissues, image-based computation of longitudinal, transverse and normal extracellular conductivity yielded (in S/m) 0.36 ± 0.11, 0.17 ± 0.07, and 0.1 ± 0.06, respectively. Conductivities were markedly increased in regions 1 (+75, +171, and +100%), 2 (+53, +165, and +80%), and 3 (+42, +141, and +60%). Volume fractions of the extracellular space including interlaminar clefts strongly correlated with conductivities in control and MI hearts. Our study provides novel quantitative data for computational modeling of conduction in normal and MI hearts. Notably, our study introduces comprehensive statistical information on tissue composition and extracellular conductivities on a microscopic scale in the MI border zone. We suggest that the presented data fill a significant gap in modeling parameters and extend our foundation for computational modeling of cardiac conduction.

Determining the most significant input parameters in models of subendocardial ischaemia and their effect on ST segment epicardial potential distributions

There is considerable interest in simulating ischaemia in the ventricle and its effect on the electrocardiogram, because a better understanding of the connection between the two may lead to improvements in diagnosis of myocardial ischaemia. In this work we studied subendocardial ischaemia, in a simplified half-ellipsoidal bidomain model of a ventricle, and its effect on ST segment epicardial potential distributions (EPDs). We found that the EPD changed as the ischaemic depth increased, from a single minimum (min1) over the ischaemic region to a maximum (max) there, with min1 over the border of the region. Lastly, a second minimum (min2) developed on the opposite side of the ischaemic region, in addition to min1 and max. We replicated these results in a realistic ventricular model and showed that the min1 only case could be found for ischaemic depths of up to around 35% of the ventricular wall. In addition, we systematically examined the sensitivity of EPD parameters, such as the potentials and positions of min1, max and min2, to various inputs to the half-ellipsoidal model, such as fibre rotation angle, ischaemic depth and conductivities. We found that the EPD parameters were not sensitive to the blood or transverse bidomain conductivities and were most sensitive to either ischaemic depth and/or fibre rotation angle. This allowed us to conclude that the asynchronous development of the two minima might provide a way of distinguishing between low and high thickness subendocardial ischaemia, and that this method may well be valid despite variability in the population.

Influence of atrial contraction dynamics on cardiac function

In recent years, there has been a move from monoventricular or biventricular models of the heart, to more complex models that incorporate the electromechanical function in all 4 chambers. However, the biophysical foundation is still underdeveloped, with most work in atrial cellular models having focused on electrophysiological properties. Here, we present a biophysical model of human atrial contraction at body temperature and use it to study the effects of atrial contraction on whole organ function and a study of the effects of remodelling due to atrial fibrillation on atrial and ventricular function.

Toward improved myocardial maturity in an organ-on-chip platform with immature cardiac myocytes

In vitro studies of cardiac physiology and drug response have traditionally been performed on individual isolated cardiomyocytes or isotropic monolayers of cells that may not mimic desired physiological traits of the laminar adult myocardium. Recent studies have reported a number of advances to Heart-on-a-Chip platforms for the fabrication of more sophisticated engineered myocardium, but cardiomyocyte immaturity remains a challenge. In the anisotropic musculature of the heart, interactions between cardiac myocytes, the extracellular matrix (ECM), and neighboring cells give rise to changes in cell shape and tissue architecture that have been implicated in both development and disease. We hypothesized that engineered myocardium fabricated from cardiac myocytes cultured in vitro could mimic the physiological characteristics and gene expression profile of adult heart muscle. To test this hypothesis, we fabricated engineered myocardium comprised of neonatal rat ventricular myocytes with laminar architectures reminiscent of that observed in the mature heart and compared their sarcomere organization, contractile performance characteristics, and cardiac gene expression profile to that of isolated adult rat ventricular muscle strips. We found that anisotropic engineered myocardium demonstrated a similar degree of global sarcomere alignment, contractile stress output, and inotropic concentration-response to the β-adrenergic agonist isoproterenol. Moreover, the anisotropic engineered myocardium exhibited comparable myofibril related gene expression to muscle strips isolated from adult rat ventricular tissue. These results suggest that tissue architecture serves an important developmental cue for building in vitro model systems of the myocardium that could potentially recapitulate the physiological characteristics of the adult heart. Impact statement With the recent focus on developing in vitro Organ-on-Chip platforms that recapitulate tissue and organ-level physiology using immature cells derived from stem cell sources, there is a strong need to assess the ability of these engineered tissues to adopt a mature phenotype. In the present study, we compared and contrasted engineered tissues fabricated from neonatal rat ventricular myocytes in a Heart-on-a-Chip platform to ventricular muscle strips isolated from adult rats. The results of this study support the notion that engineered tissues fabricated from immature cells have the potential to mimic mature tissues in an Organ-on-Chip platform.

Ventricular myocardium development and the role of connexins in the human fetal heart

The developmental timeline of the human heart remains elusive. The heart takes on its characteristic four chambered appearance by ~56 days gestational age (DGA). However, owing to the complexities (both technical and logistical) of exploring development in utero, we understand little of how the ventricular walls develop. To address this, we employed diffusion tensor magnetic resonance imaging to explore the architecture and tissue organization of the developing heart aged 95-143 DGA. We show that fractional anisotropy increases (from ~0.1 to ~0.5), diffusion coefficients decrease (from ~1 × 10-3mm2/sec to ~0.4 × 10-3mm2/sec), and fiber paths, extracted by tractography, increase linearly with gestation, indicative of the increasing organization of the ventricular myocytes. By 143 DGA, the developing heart has the classical helical organization observed in mature mammalian tissue. This was accompanied by an increase in connexin 43 and connexin 40 expression levels, suggesting their role in the development of the ventricular conduction system and that electrical propagation across the heart is facilitated in later gestation. Our findings highlight a key developmental window for the structural organization of the fetal heart.

Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia

Reduced blood flow in the coronary arteries can lead to damaged heart tissue (myocardial ischaemia). Although one method for detecting myocardial ischaemia involves changes in the ST segment of the electrocardiogram, the relationship between these changes and subendocardial ischaemia is not fully understood. In this study, we modelled ST-segment epicardial potentials in a slab model of cardiac ventricular tissue, with a central ischaemic region, using the bidomain model, which considers conduction longitudinal, transverse and normal to the cardiac fibres. We systematically quantified the effect of uncertainty on the input parameters, fibre rotation angle, ischaemic depth, blood conductivity and six bidomain conductivities, on outputs that characterise the epicardial potential distribution. We found that three typical types of epicardial potential distributions (one minimum over the central ischaemic region, a tripole of minima, and two minima flanking a central maximum) could all occur for a wide range of ischaemic depths. In addition, the positions of the minima were affected by both the fibre rotation angle and the ischaemic depth, but not by changes in the conductivity values. We also showed that the magnitude of ST depression is affected only by changes in the longitudinal and normal conductivities, but not by the transverse conductivities.

Incorporating inductances in tissue-scale models of cardiac electrophysiology

In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and we examine the effect of intracellular and extracellular inductances on the virtual electrode phenomenon.

Imaging the dynamics of cardiac fiber orientation in vivo using 3D Ultrasound Backscatter Tensor Imaging

The assessment of myocardial fiber disarray is of major interest for the study of the progression of myocardial disease. However, time-resolved imaging of the myocardial structure remains unavailable in clinical practice. In this study, we introduce 3D Backscatter Tensor Imaging (3D-BTI), an entirely novel ultrasound-based imaging technique that can map the myocardial fibers orientation and its dynamics with a temporal resolution of 10 ms during a single cardiac cycle, non-invasively and in vivo in entire volumes. 3D-BTI is based on ultrafast volumetric ultrasound acquisitions, which are used to quantify the spatial coherence of backscattered echoes at each point of the volume. The capability of 3D-BTI to map the fibers orientation was evaluated in vitro in 5 myocardial samples. The helicoidal transmural variation of fiber angles was in good agreement with the one obtained by histological analysis. 3D-BTI was then performed to map the fiber orientation dynamics in vivo in the beating heart of an open-chest sheep at a volume rate of 90 volumes/s. Finally, the clinical feasibility of 3D-BTI was shown on a healthy volunteer. These initial results indicate that 3D-BTI could become a fully non-invasive technique to assess myocardial disarray at the bedside of patients.

Transmural gradients of myocardial structure and mechanics: Implications for fiber stress and strain in pressure overload

Although a truly complete understanding of whole heart activation, contraction, and deformation is well beyond our current reach, a significant amount of effort has been devoted to discovering and understanding the mechanisms by which myocardial structure determines cardiac function to better treat patients with cardiac disease. Several experimental studies have shown that transmural fiber strain is relatively uniform in both diastole and systole, in contrast to predictions from traditional mechanical theory. Similarly, mathematical models have largely predicted uniform fiber stress across the wall. The development of this uniform pattern of fiber stress and strain during filling and ejection is due to heterogeneous transmural distributions of several myocardial structures. This review summarizes these transmural gradients, their contributions to fiber mechanics, and the potential functional effects of their remodeling during pressure overload hypertrophy.

Nonlinear physics of electrical wave propagation in the heart: a review

The beating of the heart is a synchronized contraction of muscle cells (myocytes) that is triggered by a periodic sequence of electrical waves (action potentials) originating in the sino-atrial node and propagating over the atria and the ventricles. Cardiac arrhythmias like atrial and ventricular fibrillation (AF,VF) or ventricular tachycardia (VT) are caused by disruptions and instabilities of these electrical excitations, that lead to the emergence of rotating waves (VT) and turbulent wave patterns (AF,VF). Numerous simulation and experimental studies during the last 20 years have addressed these topics. In this review we focus on the nonlinear dynamics of wave propagation in the heart with an emphasis on the theory of pulses, spirals and scroll waves and their instabilities in excitable media with applications to cardiac modeling. After an introduction into electrophysiological models for action potential propagation, the modeling and analysis of spatiotemporal alternans, spiral and scroll meandering, spiral breakup and scroll wave instabilities like negative line tension and sproing are reviewed in depth and discussed with emphasis on their impact for cardiac arrhythmias.

Evaluation of the Differences of Myocardial Fibers between Acute and Chronic Myocardial Infarction: Application of Diffusion Tensor Magnetic Resonance Imaging in a Rhesus Monkey Model

Objective

To understand microstructural changes after myocardial infarction (MI), we evaluated myocardial fibers of rhesus monkeys during acute or chronic MI, and identified the differences of myocardial fibers between acute and chronic MI.

Materials and Methods

Six fixed hearts of rhesus monkeys with left anterior descending coronary artery ligation for 1 hour or 84 days were scanned by diffusion tensor magnetic resonance imaging (MRI) to measure apparent diffusion coefficient (ADC), fractional anisotropy (FA) and helix angle (HA).

Results

Comparing with acute MI monkeys (FA: 0.59 ± 0.02; ADC: 5.0 ± 0.6 × 10^-4 mm²/s; HA: 94.5 ± 4.4°), chronic MI monkeys showed remarkably decreased FA value (0.26 ± 0.03), increased ADC value (7.8 ± 0.8 × 10^-4mm²/s), decreased HA transmural range (49.5 ± 4.6°) and serious defects on endocardium in infarcted regions. The HA in infarcted regions shifted to more components of negative left-handed helix in chronic MI monkeys (-38.3 ± 5.0°–11.2 ± 4.3°) than in acute MI monkeys (-41.4 ± 5.1°–53.1 ± 3.7°), but the HA in remote regions shifted to more components of positive right-handed helix in chronic MI monkeys (-43.8 ± 2.7°–66.5 ± 4.9°) than in acute MI monkeys (-59.5 ± 3.4°–64.9 ± 4.3°).

Conclusion

Diffusion tensor MRI method helps to quantify differences of mechanical microstructure and water diffusion of myocardial fibers between acute and chronic MI monkey's models.

Electrophysiology of Heart Failure Using a Rabbit Model: From the Failing Myocyte to Ventricular Fibrillation

Heart failure is a leading cause of death, yet its underlying electrophysiological (EP) mechanisms are not well understood. In this study, we use a multiscale approach to analyze a model of heart failure and connect its results to features of the electrocardiogram (ECG). The heart failure model is derived by modifying a previously validated electrophysiology model for a healthy rabbit heart. Specifically, in accordance with the heart failure literature, we modified the cell EP by changing both membrane currents and calcium handling. At the tissue level, we modeled the increased gap junction lateralization and lower conduction velocity due to downregulation of Connexin 43. At the biventricular level, we reduced the apex-to-base and transmural gradients of action potential duration (APD). The failing cell model was first validated by reproducing the longer action potential, slower and lower calcium transient, and earlier alternans characteristic of heart failure EP. Subsequently, we compared the electrical wave propagation in one dimensional cables of healthy and failing cells. The validated cell model was then used to simulate the EP of heart failure in an anatomically accurate biventricular rabbit model. As pacing cycle length decreases, both the normal and failing heart develop T-wave alternans, but only the failing heart shows QRS alternans (although moderate) at rapid pacing. Moreover, T-wave alternans is significantly more pronounced in the failing heart. At rapid pacing, APD maps show areas of conduction block in the failing heart. Finally, accelerated pacing initiated wave reentry and breakup in the failing heart. Further, the onset of VF was not observed with an upregulation of SERCA, a potential drug therapy, using the same protocol. The changes introduced at the cell and tissue level have increased the failing heart’s susceptibility to dynamic instabilities and arrhythmias under rapid pacing. However, the observed increase in arrhythmogenic potential is not due to a steepening of the restitution curve (not present in our model), but rather to a novel blocking mechanism.

Ventricular fibrillation (VF) is one of the leading causes of sudden death. During VF, the electrical wave of activation in the heart breaks up chaotically. Consequently, the heart is unable to contract synchronously and pump blood to the rest of the body. In our work we formulate and validate a model of heart failure (HF) that allows us to evaluate the arrhythmogenic potential of individual and combined electrophysiological changes. In diagnostic cardiology, the electrocardiogram (ECG) is one of the most commonly used tools for detecting abnormalities in the heart electrophysiology. One of our goals is to use our numerical model to link changes at the cellular and tissue level in a failing heart to a numerically computed ECG. This allows us to characterize the precursor to and the risk of VF. In order to understand the mechanisms underlying VF in HF, we design a test that simulates a HF patient performing physical exercise. We show that under fast heart rates with changes in pacing, HF patients are more prone to VF due to a new conduction blocking mechanism. In the long term, our mathematical model is suitable for investigating the effect of drug therapies in HF.