Multiscale computational analysis of the bioelectric consequences of myocardial ischaemia and infarction

Efficient electrocardiogram generation based on cardiac electric vector simulation model

This study introduces a novel Cardiac Electric Vector Simulation Model (CEVSM) to address the computational inefficiencies and low fidelity of traditional electrophysiological models in generating electrocardiograms (ECGs). Our approach leverages CEVSM to efficiently produce reliable ECG samples, facilitating data augmentation essential for the computer-aided diagnosis of myocardial infarction (MI). Significantly, experimental results show that our model dramatically reduces computation time compared to conventional models, with the self-adapting regression transformation matrix method (SRTM) providing clear advantages. SRTM not only achieves high fidelity in ECG simulations but also ensures exceptional consistency with the gold standard method, greatly enhancing MI localization accuracy by data augmentation. These advancements highlight the potential of our model to generate dependable ECG training samples, making it highly suitable for data augmentation and significantly advancing the development and validation of intelligent MI diagnostic systems. Furthermore, this study demonstrates the feasibility of applying life system simulations in the training of medical big models.

An ECG generative model of myocardial infarction

Background and Objective Computer-aided diagnosis (CAD) of Myocardial Infarction (MI) using machine learning depends on a large amount of clinical Electrocardiogram (ECG) data. Existing infarct ECG databases face the problem of class imbalance. Data augmentation using generative simulation models is a new approach to effectively address this problem. Methods A multiscale ECG generative model was established for ECG data augmentation. In the cellular layer, an ischemic Action Potential (AP) model was established to generate APs in cardiomyocytes with different transmural regions of infraction or different ischemic durations. In the tissue layer, a probability-driven cellular automata excitation propagation model was established to simulate the propagation speed and direction of excitation. An infarct tissue model and a coronary artery model were established to describe the spatiotemporal diversity of MI. A ventricle model, a human torso model, and a computational model of surface ECG based on field source theory were established in the heart-torso layer. Results The model generated pathological 12-lead ECGs of MI with different topography and different extent. When simulating different ventricular wall infarction, the lesions appear in the same leads as the clinical 12-lead ECG. The ST-segment decreases and the T-wave amplitude decreases, similar to the clinical ECG features when simulating subendocardial ischemia. The average fidelity of the 12-lead ECG the model generated is 95.6%, according to the designed DTW-GRA distance algorithm. Conclusions The generative model considers the electrophysiological properties of the natural heart, the pathology of myocardial infarction, and the diversity of clinical ECGs. The model can provide many reliable samples for machine learning of MI.

The study of border zone formation in ischemic heart using electro-chemical coupled computational model

Myocardial infarction (MI) is the most common cause of a heart failure, which occurs due to myocardial ischemia leading to left ventricular (LV) remodeling. LV remodeling particularly occurs at the ischemic area and the region surrounds it, known as the border zone. The role of the border zone in initiating LV remodeling process urges the investigation on the correlation between early border zone changes and remodeling outcome. Thus, this study aims to simulate a preliminary conceptual work of the border zone formation and evolution during onset of MI and its effect towards early LV remodeling processes by incorporating the oxygen concentration effect on the electrophysiology of an idealized three-dimensional LV through electro-chemical coupled mathematical model. The simulation result shows that the region of border zone, represented by the distribution of electrical conductivities, keeps expanding over time. Based on this result, the border zone is also proposed to consist of three sub-regions, namely mildly, moderately, and seriously impaired conductivity regions, which each region categorized depending on its electrical conductivities. This division could be used as a biomarker for classification of reversible and irreversible myocardial injury and will help to identify the different risks for the survival of patient. Larger ischemic size and complete occlusion of the coronary artery can be associated with an increased risk of developing irreversible injury, in particular if the reperfusion treatment is delayed. Increased irreversible injury area can be related with cardiovascular events and will further deteriorate the LV function over time.

The study of myocardial ischemia-reperfusion treatment through computational modelling

Reperfusion of the blood flow to ischemic myocardium is the standard treatment for patients suffering myocardial infarction. However, the reperfusion itself can also induce myocardial injury, in which the actual mechanism and its risk factors remain unclear. This work aims to study the mechanism of ischemia-reperfusion treatment using a three-dimensional (3D) oxygen diffusion model. An electrical model is then coupled to an oxygen model to identify the possible region of myocardial damage. Our findings show that the value of oxygen exceeds its optimum (>1.0) at the ischemic area during early reperfusion period. This complication was exacerbated in a longer ischemic period. While a longer reperfusion time causes a continuous excessive oxygen supply to the ischemic area throughout the reperfusion time. This work also suggests the use of less than 0.8 of initial oxygen concentration in the reperfusion treatment to prevent undesired upsurge at the early reperfusion period and further myocardial injury. We also found the region at risk for myocardial injury is confined in the ischemic vicinity revealed by its electrical conductivity impairment. Although there is a risk that reperfusion leads to myocardial injury for excessive oxygen accumulation, the reperfusion treatment is helpful in reducing the infarct size.

Non-ischemic endocardial scar geometric remodeling toward topological machine learning

Scar tissues have been important factors in determining the progression of myocardial diseases and the development of adverse cardiac failure outcomes. Accurate segmentation of the scar tissues can be helpful to the clinicians for risk prediction and better evaluation of cardiovascular diseases. Our goal is to apply topology data analysis toward machine learning algorithms to confirm the geometry of scar tissue, in addition to gaining better visualization and quantification of the scar tissue present. We have introduced architecture for integrating geometry in the form of topology toward machine learning. Morphological image processing was carried out to define the regions of the endocardial wall. We implemented convolutional neural networks on delayed enhancement cardiac computed tomography images for the recognition of scar tissue. Segmented two-dimensional images were stacked up to build the geometry of the scar area for visualization purposes. Mathematical calculations were executed for the validation of the scar tissue in addition to performing morphological image processing and marking the scar tissue present on the endocardial wall of the left ventricular. We applied convolutional neural network over convolution and pooling the layers with small sizes; we achieved 89.23% accuracy, 91.11% sensitivity, and 87.75% specificity, and found the dissimilarity distance between the normal endocardial tissue distances to be 9.37. This new concept in this study contributes toward a better understanding of scar structure and transmural variation of the endocardial wall of the left ventricular.

Computational models in cardiology

The treatment of individual patients in cardiology practice increasingly relies on advanced imaging, genetic screening and devices. As the amount of imaging and other diagnostic data increases, paralleled by the greater capacity to personalize treatment, the difficulty of using the full array of measurements of a patient to determine an optimal treatment seems also to be paradoxically increasing. Computational models are progressively addressing this issue by providing a common framework for integrating multiple data sets from individual patients. These models, which are based on physiology and physics rather than on population statistics, enable computational simulations to reveal diagnostic information that would have otherwise remained concealed and to predict treatment outcomes for individual patients. The inherent need for patient-specific models in cardiology is clear and is driving the rapid development of tools and techniques for creating personalized methods to guide pharmaceutical therapy, deployment of devices and surgical interventions.

Influence of the distribution of fibrosis within an area of myocardial infarction on wave propagation in ventricular tissue

The presence of fibrosis in heart tissue is strongly correlated with an incidence of arrhythmia, which is a leading cause of sudden cardiac death (SCD). However, it remains incompletely understood how different distributions, sizes and positions of fibrotic tissues contribute to arrhythmogenesis. In this study, we designed 4 different ventricular models mimicking wave propagation in cardiac tissues under normal, myocardial infarction (MI), MI with random fibrosis and MI with gradient fibrosis conditions. Simulation results of ideal square tissues indicate that vulnerable windows (VWs) of random and gradient fibrosis distributions are similar with low levels of fibrosis. However, with a high level of fibrosis, the VWs significantly increase in random fibrosis tissue but not in gradient fibrosis tissue. In addition, we systematically analyzed the effects of the size and position of fibrosis tissues on VWs. Simulation results show that it is more likely for a reentry wave to appear when the length of the infarcted area is greater than 25% of the perimeter of the ventricle, when the width is approximately half that of the ventricular wall, or when the infarcted area is attached to the inside or outside of the ventricular wall.

Modeling the Electrophysiological Properties of the Infarct Border Zone

Ventricular arrhythmias (VA) in patients with myocardial infarction (MI) are thought to be associated with structural and electrophysiological remodeling within the infarct border zone (BZ). Personalized computational models have been used to investigate the potential role of the infarct BZ in arrhythmogenesis, which still remains incompletely understood. Most recent models have relied on experimental data to assign BZ properties. However, experimental measurements vary significantly resulting in different computational representations of this region. Here, we review experimental data available in the literature to determine the most prominent properties of the infarct BZ. Computational models are then used to investigate the effect of different representations of the BZ on activation and repolarization properties, which may be associated with VA. Experimental data obtained from several animal species and patients with infarct show that BZ properties vary significantly depending on disease's stage, with the early disease stage dominated by ionic remodeling and the chronic stage by structural remodeling. In addition, our simulations show that ionic remodeling in the BZ leads to large repolarization gradients in the vicinity of the scar, which may have a significant impact on arrhythmia simulations, while structural remodeling plays a secondary role. We conclude that it is imperative to faithfully represent the properties of regions of infarction within computational models specific to the disease stage under investigation in order to conduct in silico mechanistic investigations.

Mechanism underlying impaired cardiac pacemaking rhythm during ischemia: A simulation study

Ischemia in the heart impairs function of the cardiac pacemaker, the sinoatrial node (SAN). However, the ionic mechanisms underlying the ischemia-induced dysfunction of the SAN remain elusive. In order to investigate the ionic mechanisms by which ischemia causes SAN dysfunction, action potential models of rabbit SAN and atrial cells were modified to incorporate extant experimental data of ischemia-induced changes to membrane ion channels and intracellular ion homeostasis. The cell models were incorporated into an anatomically detailed 2D model of the intact SAN-atrium. Using the multi-scale models, the functional impact of ischemia-induced electrical alterations on cardiac pacemaking action potentials (APs) and their conduction was investigated. The effects of vagal tone activity on the regulation of cardiac pacemaker activity in control and ischemic conditions were also investigated. The simulation results showed that at the cellular level ischemia slowed the SAN pacemaking rate, which was mainly attributable to the altered Na+-Ca2+ exchange current and the ATP-sensitive potassium current. In the 2D SAN-atrium tissue model, ischemia slowed down both the pacemaking rate and the conduction velocity of APs into the surrounding atrial tissue. Simulated vagal nerve activity, including the actions of acetylcholine in the model, amplified the effects of ischemia, leading to possible SAN arrest and/or conduction exit block, which are major features of the sick sinus syndrome. In conclusion, this study provides novel insights into understanding the mechanisms by which ischemia alters SAN function, identifying specific conductances as contributors to bradycardia and conduction block.

Effects of electrophysiological heterogeneity on vulnerability to re-entry in human ventricular tissue: A simulation study

In this study, we constructed a two-dimensional ventricular tissue sheet with cellular electrophysiology modified from the Ten Tusscher 2006 Model. Heterogeneity was created by dividing the tissue into endocardium, midmyocardium and epicardium, further enhanced by a central ischemic zone. Subsequently, we investigated how electrophysiological heterogeneity affects re-entry initiation and maintenance in this tissue. Furthermore, we analyzed the vulnerable window (VW) under several conditions and concluded that heterogeneity across various myocardia expands the VW further than the monolayer myocardium model does.

Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics

This is the second of the two White Papers from the fourth UC Davis Cardiovascular Symposium Systems Approach to Understanding Cardiac Excitation-Contraction Coupling and Arrhythmias (3-4 March 2016), a biennial event that brings together leading experts in different fields of cardiovascular research. The theme of the 2016 symposium was 'K⁺ channels and regulation', and the objectives of the conference were severalfold: (1) to identify current knowledge gaps; (2) to understand what may go wrong in the diseased heart and why; (3) to identify possible novel therapeutic targets; and (4) to further the development of systems biology approaches to decipher the molecular mechanisms and treatment of cardiac arrhythmias. The sessions of the Symposium focusing on the functional roles of the cardiac K⁺ channel in health and disease, as well as K⁺ channels as therapeutic targets, were contributed by Ye Chen-Izu, Gideon Koren, James Weiss, David Paterson, David Christini, Dobromir Dobrev, Jordi Heijman, Thomas O'Hara, Crystal Ripplinger, Zhilin Qu, Jamie Vandenberg, Colleen Clancy, Isabelle Deschenes, Leighton Izu, Tamas Banyasz, Andras Varro, Heike Wulff, Eleonora Grandi, Michael Sanguinetti, Donald Bers, Jeanne Nerbonne and Nipavan Chiamvimonvat as speakers and panel discussants. This article summarizes state-of-the-art knowledge and controversies on the functional roles of cardiac K⁺ channels in normal and diseased heart. We endeavour to integrate current knowledge at multiple scales, from the single cell to the whole organ levels, and from both experimental and computational studies.

Association between Myocardial Infarction and Periodontitis: A Meta-Analysis of Case-Control Studies

Background and Objective: Many clinical researches have been carried out to investigate the relationship between myocardial infarction (MI) and periodontitis. Despite most of them indicated that the periodontitis may be associated with an increased risk of MI, the findings and study types of these studies have been inconsistent. The goal of this meta-analysis was to critically assess the strength of the association between MI and periodontitis in case-control studies.

Methods: PubMed and the Cochrane Library were searched for eligible case-control studies reporting relevant parameters that compared periodontal status between MI and control subjects. The odds ratios (ORs) and 95% confidence intervals (CIs) from each study were pooled to estimate the strength of the association between MI and periodontitis. The mean differences and 95% CIs for periodontal-related parameters were calculated to determine their overall effects.

Results: Seventeen studies including a total of 3456 MI patients and 3875 non-MI control subjects were included. The pooled OR for the association between MI and periodontitis was 2.531 (95% CI: 1.927–3.324). The mean differences (95% CIs) for clinical attachment loss, probing depth, bleeding on probing, plaque index, and the number of missing teeth were 1.000 (0.726–1.247), 1.209 (0.538–1.880), 0.342 (0.129–0.555), 0.383 (0.205–0.560), and 4.122 (2.012–6.232), respectively.

Conclusion: With the current evidence, the results support the presence of a significant association between MI and periodontitis. Moreover, MI patients had worse periodontal and oral hygiene status and fewer teeth than did control subjects. More high-quality and well-designed studies focusing on the casual relationship between MI and periodontitis should be conducted in the future.

Comparison of Electric- and Magnetic-Cardiograms Produced by Myocardial Ischemia in Models of the Human Ventricle and Torso

Myocardial ventricular ischemia arises from a lack of blood supply to the heart, which may cause abnormal repolarization and excitation wave conduction patterns in the tissue, leading to cardiac arrhythmias and even sudden death. Current diagnosis of cardiac ischemia by the 12-lead electrocardiogram (ECG) has limitations as they are insensitive in many cases and may show unnoticeable differences to normal patterns. As the magnetic field provides extra information on cardiac excitation and is more sensitive to tangential currents to the surface of the chest, whereas the electric field is more sensitive to flux currents, it has been hypothesized that the magnetocardiogram (MCG) may provide a complementary method to the ECG in ischemic diagnosis. However, it is unclear yet about the differences in sensitivity regions of body surface ECG and MCG signals to ischemic conditions. The aim of this study was to investigate such differences by using 12-, 36- ECG and 36-MCG computed from multi-scale biophysically detailed computational models of the human ventricles and torso in both control and ischemic conditions. It was shown that ischemia produced changes in the ECG and MCG signals in the QRS complex, T-wave and ST-segment, with greater relative differences seen in the 36-lead ECG and MCG as compared to the 12-leads ECG (34% and 37% vs 26%, respectively). The 36-lead ECG showed more averaged sensitivity than the MCG in the change of T-wave due to ischemia (37% vs 32%, respectively), whereas the MCG showed greater sensitivity than the ECG in the change of the ST-segment (50% vs 40%, respectively). In addition, both MCG and ECG showed regional-dependent changes to ischemia, but with MCG showing a stronger correlation between ischemic region in the heart. In conclusion, MCG shows more sensitivity than ECG in response to ischemia, which may provide an alternative method for the diagnosis of ischemia.

Post-repolarization refractoriness increases vulnerability to block and initiation of reentrant impulses in heterogeneous infarcted myocardium

Myocardial infarction causes remodeling of the tissue structure and the density and kinetics of several ion channels in the cell membrane. Heterogeneities in refractory period (ERP) have been shown to occur in the infarct border zone and have been proposed to lead to initiation of arrhythmias. The purpose of this study is to quantify the window of vulnerability (WV) to block and initiation of reentrant impulses in myocardium with ERP heterogeneities using computer simulations. We found that ERP transitions at the border between normal ventricular cells (NZ) with different ERPs are smooth, whereas ERP transitions between NZ and infarct border zone cells (IZ) are abrupt. The profile of the ERP transitions is a combination of electrotonic interaction between NZ and IZ cells and the characteristic post-repolarization refractoriness (PRR) of IZ cells. ERP heterogeneities between NZ and IZ cells are more vulnerable to block and initiation of reentrant impulses than ERP heterogeneities between NZ cells. The relationship between coupling intervals of premature impulses (V1V2) and coupling intervals between premature and first reentrant impulses (V2T1) at NZ/NZ and NZ/IZ borders is inverse (i.e. the longer the coupling intervals of premature impulses the shorter the coupling interval between the premature and first reentrant impulses); this is in contrast with the reported V1V2/V2T1 relationship measured during initiation of reentrant impulses in canine infarcted hearts which is direct.

IN CONCLUSION

(1) ERP transitions at the NZ-IZ border are abrupt as a consequence of PRR; (2) PRR increases the vulnerability to block and initiation of reentrant impulses in heterogeneous myocardium; (3) V1V2/V2T1 relationships measured at ERP heterogeneities in the computer model and in experimental canine infarcts are not consistent. Therefore, it is likely that other mechanisms like micro and/or macro structural heterogeneities also contribute to initiation of reentrant impulses in infarcted hearts.

Three-dimensional cardiac computational modelling: methods, features and applications

The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty years, describing their information sources, features, development methods and online availability. This paper also reviews the necessary components to build a 3D computational model of the heart aimed at biophysical simulation, paying especial attention to cardiac electrophysiology (EP), and the existing approaches to incorporate those components. We assess the challenges associated to the different steps of the building process, from the processing of raw clinical or biological data to the final application, including image segmentation, inclusion of substructures and meshing among others. We briefly outline the personalisation approaches that are currently available in 3D cardiac computational modelling. Finally, we present examples of several specific applications, mainly related to cardiac EP simulation and model-based image analysis, showing the potential usefulness of 3D cardiac computational modelling into clinical environments as a tool to aid in the prevention, diagnosis and treatment of cardiac diseases.

Cardioprotective effects of fucoidan against hypoxia-induced apoptosis in H9c2 cardiomyoblast cells

CONTEXT

Cardiomyocyte apoptosis plays a critical role in the progress of heart diseases. Fucoidan, a complex-sulfated polysaccharide, has been reported to possess potential cardioprotective efficacy in vivo.

OBJECTIVE

The present study determines whether fucoidan could provide cardioprotection on hypoxia-induced cardiomyocyte apoptosis.

MATERIALS AND METHODS

H9c2 cardiomyoblast cells were incubated with various concentrations (15, 30, and 60 μg/ml) of fucoidan in a humidified incubator at 37 °C with 95% O2 and 5% CO2. After 6 h, hypoxia was processed and the cardioprotective effects of fucoidan were evaluated by applying MTT, ELISA, Hoechst 33258 nucleus staining, and western blot.

RESULTS

Following a 6 h exposure of H9c2 to hypoxic condition, significant reduction was found in cell survival (0.57-fold) and superoxide dismutase (SOD) activity (0.56-fold), which were associated with the increase of malondialdehyde (MDA) level (2.58-fold), creatine phosphokinase (CK, 3.57-fold), and lactate dehydrogenase (LDH) activities (2.39-fold). Moreover, hypoxia-induced apoptosis was confirmed by Hoechst 33258 nuclear staining, and these changes were accompanied by the increase of Bcl-2 (1.27-fold) and Bax expression (2.6-fold). However, preincubation of the cells with fucoidan prior to hypoxia exposure elevated the cell viability (30 μg/ml, 1.18-fold; 60 μg/ml, 1.32-fold) and SOD activity (30 μg/ml, 1.12-fold; 60 μg/ml, 1.25-fold), but decreased the MDA level (30 μg/ml, 0.70-fold; 60 μg/ml, 0.80-fold), CK (30 μg/ml, 0.69-fold; 60 μg/ml, 0.76-fold), and LDH (30 μg/ml, 0.67-fold; 60 μg/ml, 0.86-fold) leakages. Hoechst 33258 nuclear staining observations demonstrated the same protective effect of fucoidan on hypoxia-induced myocardial injury. Also, cardioprotective effects of fucoidan were reflected by increasing Bcl-2 (60 μg/ml, 1.84-fold), as well as decreasing Bax (60 μg/ml, 0.6-fold).

CONCLUSION

Fucoidan had protective effect against hypoxia-induced cardiomyocytes apoptosis, and the mechanism might involve protections of the cell from oxidative injury.

ESC working group cellular biology of the heart: position paper: improving the preclinical assessment of novel cardioprotective therapies

Ischaemic heart disease (IHD) remains the leading cause of death and disability worldwide. As a result, novel therapies are still needed to protect the heart from the detrimental effects of acute ischaemia–reperfusion injury, in order to improve clinical outcomes in IHD patients. In this regard, although a large number of novel cardioprotective therapies discovered in the research laboratory have been investigated in the clinical setting, only a few of these have been demonstrated to improve clinical outcomes. One potential reason for this lack of success may have been the failure to thoroughly assess the cardioprotective efficacy of these novel therapies in suitably designed preclinical experimental animal models. Therefore, the aim of this Position Paper by the European Society of Cardiology Working Group Cellular Biology of the Heart is to provide recommendations for improving the preclinical assessment of novel cardioprotective therapies discovered in the research laboratory, with the aim of increasing the likelihood of success in translating these new treatments into improved clinical outcomes.