Alterations of atrial electrophysiology related to hemodialysis session: insights from a multiscale computer model

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Immediate and Delayed Response of Simulated Human Atrial Myocytes to Clinically-Relevant Hypokalemia

Although plasma electrolyte levels are quickly and precisely regulated in the mammalian cardiovascular system, even small transient changes in K⁺, Na⁺, Ca²⁺, and/or Mg²⁺ can significantly alter physiological responses in the heart, blood vessels, and intrinsic (intracardiac) autonomic nervous system. We have used mathematical models of the human atrial action potential (AP) to explore the electrophysiological mechanisms that underlie changes in resting potential (V_r) and the AP following decreases in plasma K⁺, [K⁺]_o, that were selected to mimic clinical hypokalemia. Such changes may be associated with arrhythmias and are commonly encountered in patients (i) in therapy for hypertension and heart failure; (ii) undergoing renal dialysis; (iii) with any disease with acid-base imbalance; or (iv) post-operatively. Our study emphasizes clinically-relevant hypokalemic conditions, corresponding to [K⁺]_o reductions of approximately 1.5 mM from the normal value of 4 to 4.5 mM. We show how the resulting electrophysiological responses in human atrial myocytes progress within two distinct time frames: (i) Immediately after [K⁺]_o is reduced, the K⁺-sensing mechanism of the background inward rectifier current (I_K1) responds. Specifically, its highly non-linear current-voltage relationship changes significantly as judged by the voltage dependence of its region of outward current. This rapidly alters, and sometimes even depolarizes, V_r and can also markedly prolong the final repolarization phase of the AP, thus modulating excitability and refractoriness. (ii) A second much slower electrophysiological response (developing 5-10 minutes after [K⁺]_o is reduced) results from alterations in the intracellular electrolyte balance. A progressive shift in intracellular [Na⁺]_i causes a change in the outward electrogenic current generated by the Na⁺/K⁺ pump, thereby modifying V_r and AP repolarization and changing the human atrial electrophysiological substrate. In this study, these two effects were investigated quantitatively, using seven published models of the human atrial AP. This highlighted the important role of I_K1 rectification when analyzing both the mechanisms by which [K⁺]_o regulates V_r and how the AP waveform may contribute to "trigger" mechanisms within the proarrhythmic substrate. Our simulations complement and extend previous studies aimed at understanding key factors by which decreases in [K⁺]_o can produce effects that are known to promote atrial arrhythmias in human hearts.

ECG-based Estimation of Potassium and Calcium Concentrations: Proof of Concept with Simulated Data

In Europe, the prevalence of chronic kidney disease lay at approximately 18.38% in 2016. A common treatment for patients in the end stage of this disease is haemodialysis. However, patients undergoing this therapy suffer from an increased risk of cardiac death. A hypothesis is that the cause is an inbalanced electrolyte concentration. To study the underlying mechanisms of this phenomenon and fight the consequences, a continous non-invasive monitoring technique is desired. In this work, we investigated the possibility to reconstruct the extracellular concentrations of potassium and calcium from ECG signals. Therefore, we extracted 71 ECGs using the simulation results of a modified Himeno et al. ventricular cell model comprising variations of the extracellular ionic concentrations of potassium and calcium. The changes dependent on the different extracellular ionic concentrations were captured with five ECG features. These were used to train an artificial neural network for regression. The study was performed both for noise-free and noisy data. The estimation error for the reconstruction of the potassium concentrations was -0.01±0.14mmol/l (mean±standard deviation) in the noise-free case, -0.03±0.46mmol/l in the noisy case (30dB SNR). For calcium, the result was 0.01±0.11mmol/l in the noise-free case, 0.02±0.17mmol/l in the noisy case. For both ion types, the result was improved by augmenting the dataset. We therefore conclude that with the calculated features, we are able to reconstruct the extracellular ionic concentrations for both potassium and calcium with an acceptable precision. When analysing noisy signals, the accuracy of the estimation method is still sufficient but can be further improved by an augmentation of the dataset.

Acute effect of a peritoneal dialysis exchange on electrolyte concentration and QT interval in uraemic patients

BACKGROUND

Hemodialysis (HD) sessions induce changes in plasma electrolytes that lead to modifications of QT interval, virtually associated with dangerous arrhythmias. It is not known whether such a phenomenon occurs even during peritoneal dialysis (PD). The aim of the study is to analyze the relationship between dialysate and plasma electrolyte modifications and QT interval during a PD exchange.

METHODS

In 15 patients, two manual PD 4-h exchanges were performed, using two isotonic solutions with different calcium concentration (Ca⁺⁺1.25 and Ca1.75⁺⁺ mmol/L). Dialysate and plasma electrolyte concentration and QT interval (ECG Holter recording) were monitored hourly. A computational model simulating the ventricular action potential during the exchange was also performed.

RESULTS

Dialysis exchange induced a significant plasma alkalizing effect (p < 0.001). Plasma K⁺ significantly decreased at the third hour (p < 0.05). Plasma Na⁺ significantly decreased (p < 0.001), while plasma Ca⁺⁺ slightly increased only when using the Ca 1.75⁺⁺ mmol/L solution (p < 0.01). The PD exchange did not induce modifications of clinical relevance in the QT interval, while a significant decrease in heart rate (p < 0.001) was observed. The changes in plasma K⁺ values were significantly inversely correlated to QT interval modifications (p < 0.001), indicating that even small decreases of K⁺ were consistently paralleled by small QT prolongations. These results were perfectly confirmed by the computational model.

CONCLUSIONS

The PD exchange guarantees a greater cardiac electrical stability compared to the HD session and should be preferred in patients with a higher arrhythmic risk. Moreover, our study shows that ventricular repolarization is extremely sensitive to plasma K⁺ changes, also in normal range.

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.

How disruption of endo-epicardial electrical connections enhances endo-epicardial conduction during atrial fibrillation

Aims

Loss of side-to-side electrical connections between atrial muscle bundles is thought to underlie conduction disturbances predisposing to atrial fibrillation (AF). Putatively, disruption of electrical connections occurs not only within the epicardial layer but also between the epicardial layer and the endocardial bundle network, thus impeding transmural conductions (‘breakthroughs’). However, both clinical and experimental studies have shown an enhancement of breakthroughs during later stages of AF. We tested the hypothesis that endo-epicardial uncoupling enhances endo-epicardial electrical dyssynchrony, breakthrough rate (BTR), and AF stability.

Methods and Results

In a novel dual-layer computer model of the human atria, 100% connectivity between the two layers served as healthy control. Atrial structural remodelling was simulated by reducing the number of connections between the layers from 96 to 6 randomly chosen locations. With progressive elimination of connections, AF stability increased. Reduction in the number of connections from 96 to 24 resulted in an increase in endo-epicardial dyssynchrony from 6.6 ± 1.9 to 24.6 ± 1.3%, with a concomitant increase in BTR. A further reduction to 12 and 6 resulted in more pronounced endo-epicardial dyssynchrony of 34.4 ± 1.15 and 40.2 ± 0.52% but with BTR reduction. This biphasic relationship between endo-epicardial coupling and BTR was found independently from whether AF was maintained by re-entry or by ectopic focal discharges.

Conclusion

Loss of endo-epicardial coupling increases AF stability. There is a biphasic relation between endo-epicardial coupling and BTR. While at high degrees of endo-epicardial connectivity, the BTR is limited by the endo-epicardial synchronicity, at low degrees of connectivity, it is limited by the number of endo-epicardial connections.

Atrial Fibrillation Characteristics in Patients on Haemodialysis vs. Peritoneal Dialysis

Atrial fibrillation (AF) is highly prevalent in dialysis patients, however whether its impact differs between patients on haemodialysis (HD) vs. peritoneal dialysis (PD) is unknown. We aimed to compare the association of AF and clinical outcomes in different dialysis modalities. We performed a population based retrospective cohort study, including adult patients who initiated dialysis between the years 2002 and 2015. Clinical, echocardiographic and laboratory data were reviewed and correlated with outcomes in HD vs. PD. During the study period, 1,130 patients began dialysis. Of the 997 patients without AF before dialysis initiation, 17% developed new-onset AF after the initiation of dialysis (17.3% of HD vs. 13.7% of PD patients, p = 0.27). Using multivariate analysis, only enlarged left atrium at dialysis initiation (hazard ratio (HR) 2.82, CI95% 2.00–3.99) and age (HR 1.04, CI95% 1.03–1.06) were significantly associated with AF. Dialysis modality was not a significant predictor of AF in either univariate or multivariate analysis. In conclusion, our study demonstrated that AF is common in dialysis patients irrespective of modality. In our cohort, the risk factors associated with AF were older age and enlarged left atrium. AF was associated with increased rates of heart failure and mortality, but not stroke.

Atrial fibrillation in dialysis patients: time to abandon warfarin?

Atrial fibrillation (AF) is a frequent clinical complication in dialysis patients, and warfarin therapy represents the most common approach for reducing the risk of stroke in this population. However, current evidence based on observational studies, offer conflicting results, whereas no randomized controlled trials have been carried out so far. Additionally, many clinicians are wary of the possible role of warfarin as vascular calcification inducer and its potential to increase the high risk of bleeding among patients on dialysis. Ideally the most promising therapy would be based on direct inhibitors of factor IIa or Xa; however, at the moment, none of these drugs can be safely prescribed in dialysis patients, because of their potentially dangerous accumulation, and the lack of sufficient experience with apixaban or rivaroxaban, two drugs showing a favorable pharmacokinetic profile in end-stage renal disease. Hence, the use of vitamin K inhibitors is currently the only pharmacological option for stroke prevention in dialysis patients with atrial fibrillation, leaving the clinicians in a management conundrum.This review discusses the trade-offs implicated in warfarin use for this population, the promises of newly developed drugs, the role of dialysis as atrial fibrillation trigger, as well as potential non-pharmacological management options suitable in selected clinical situations.

Electrolyte disturbances differentially regulate sinoatrial node and pulmonary vein electrical activity: A contribution to hypokalemia- or hyponatremia-induced atrial fibrillation

BACKGROUND

Hypokalemia and hyponatremia increase the occurrence of atrial fibrillation. Sinoatrial nodes (SANs) and pulmonary veins (PVs) play a critical role in the pathophysiology of atrial fibrillation.

OBJECTIVE

The purpose of this study was to evaluate whether electrolyte disturbances with low concentrations of potassium ([K(+)]) or sodium ([Na(+)]) modulate SAN and PV electrical activity and arrhythmogenesis, and to investigate potential underlying mechanisms.

METHODS

Conventional microelectrodes were used to record electrical activity in rabbit SAN and PV tissue preparations before and after perfusion with different low [K(+)] or [Na(+)], interacting with the Na(+)-Ca(2+) exchanger inhibitor KB-R7943 (10 μΜ).

RESULTS

Low [K(+)] (3.5, 3, 2.5, and 2 mM) decreased beating rates in PV cardiomyocytes with genesis of delayed afterdepolarizations (DADs), burst firing, and increased diastolic tension. Low [K(+)] (3.5, 3, 2.5, and 2 mM) also decreased SAN beating rates, with genesis of DADs. Low [Na(+)] increased PV diastolic tension, DADs, and burst firing, which was attenuated in the co-superfusion with low [K(+)] (2 mM). In contrast, low [Na(+)] had little effect on SAN electrical activities. KB-R7943 (10 μΜ) reduced the occurrences of low [K(+)] (2 mM)- or low [Na(+)] (110 mM)-induced DAD and burst firing in both PVs and SANs.

CONCLUSION

Low [K(+)] and low [Na(+)] differentially modulate SAN and PV electrical properties. Low [K(+)]- or low [Na(+)]-induced slowing of SAN beating rate and genesis of PV burst firing may contribute to the high occurrence of atrial fibrillation during hypokalemia or hyponatremia.

Human atrial cell models to analyse haemodialysis-related effects on cardiac electrophysiology: work in progress

During haemodialysis (HD) sessions, patients undergo alterations in the extracellular environment, mostly concerning plasma electrolyte concentrations, pH, and volume, together with a modification of sympathovagal balance. All these changes affect cardiac electrophysiology, possibly leading to an increased arrhythmic risk. Computational modeling may help to investigate the impact of HD-related changes on atrial electrophysiology. However, many different human atrial action potential (AP) models are currently available, all validated only with the standard electrolyte concentrations used in experiments. Therefore, they may respond in different ways to the same environmental changes. After an overview on how the computational approach has been used in the past to investigate the effect of HD therapy on cardiac electrophysiology, the aim of this work has been to assess the current state of the art in human atrial AP models, with respect to the HD context. All the published human atrial AP models have been considered and tested for electrolytes, volume changes, and different acetylcholine concentrations. Most of them proved to be reliable for single modifications, but all of them showed some drawbacks. Therefore, there is room for a new human atrial AP model, hopefully able to physiologically reproduce all the HD-related effects. At the moment, work is still in progress in this specific field.

The effects of a single dialysis session on atrial electromechanical conduction times and functions

BACKGROUND/AIMS

Abnormalities in atrial electromechanical delay (EMD) times and mechanical functions are considered as independent predictors of atrial fibrillation. However, to date, effects of a single hemodialysis (HD) session and acute volume-preload changes on atrial-EMD functions have not been investigated by Tissue Doppler Echocardiography (TDE). The aim of the present study was to evaluate atrial-EMD times and mechanical functions in HD patients.

METHODS

Thirty-five non-diabetic, normotensive HD patients and 35 healthy control subjects were enrolled in the study. Standard and TDE performed before mid-week dialysis session for hemodialysis group and on admission for control group.

RESULTS

Interatrial and left-right intraatrial-EMD intervals and left atrial mechanical volumes were significantly longer in hemodialysis group compared to controls (all p<0.01) and were reduced after HD session. Furthermore, removed ultrafiltration volume was associated with reduction in atrial-EMD intervals and functional volumes. LA-passive emptying volume, ultrafiltration volume, LV-E/E' ratio, and Vp were independent predictors of interatrial-EMD.

CONCLUSIONS

The present study confirms negative effects in HD patients of structural remodeling and reveals negative effects of electrical remodeling. Prolonged inter and intraatrial-EMD intervals should be the underlying pathophysiological factors of increased rate of atrial fibrillation in the HD population.

In-silico modeling of atrial repolarization in normal and atrial fibrillation remodeled state

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and the total number of AF patients is constantly increasing. The mechanisms leading to and sustaining AF are not completely understood yet. Heterogeneities in atrial electrophysiology seem to play an important role in this context. Although some heterogeneities have been used in in-silico human atrial modeling studies, they have not been thoroughly investigated. In this study, the original electrophysiological (EP) models of Courtemanche et al., Nygren et al. and Maleckar et al. were adjusted to reproduce action potentials in 13 atrial regions. The parameter sets were validated against experimental action potential duration data and ECG data from patients with AV block. The use of the heterogeneous EP model led to a more synchronized repolarization sequence in a variety of 3D atrial anatomical models. Combination of the heterogeneous EP model with a model of persistent AF-remodeled electrophysiology led to a drastic change in cell electrophysiology. Simulated Ta-waves were significantly shorter under the remodeling. The heterogeneities in cell electrophysiology explain the previously observed Ta-wave effects. The results mark an important step toward the reliable simulation of the atrial repolarization sequence, give a deeper understanding of the mechanism of atrial repolarization and enable further clinical investigations.

Computational cardiology: how computer simulations could be used to develop new therapies and advance existing ones

This article reviews the latest developments in computational cardiology. It focuses on the contribution of cardiac modelling to the development of new therapies as well as the advancement of existing ones for cardiac arrhythmias and pump dysfunction. Reviewed are cardiac modelling efforts aimed at advancing and optimizing existent therapies for cardiac disease (defibrillation, ablation of ventricular tachycardia, and cardiac resynchronization therapy) and at suggesting novel treatments, including novel molecular targets, as well as efforts to use cardiac models in stratification of patients likely to benefit from a given therapy, and the use of models in diagnostic procedures.

Personalization of atrial anatomy and electrophysiology as a basis for clinical modeling of radio-frequency ablation of atrial fibrillation

Multiscale cardiac modeling has made great advances over the last decade. Highly detailed atrial models were created and used for the investigation of initiation and perpetuation of atrial fibrillation. The next challenge is the use of personalized atrial models in clinical practice. In this study, a framework of simple and robust tools is presented, which enables the generation and validation of patient-specific anatomical and electrophysiological atrial models. Introduction of rule-based atrial fiber orientation produced a realistic excitation sequence and a better correlation to the measured electrocardiograms. Personalization of the global conduction velocity lead to a precise match of the measured P-wave duration. The use of a virtual cohort of nine patient and volunteer models averaged out possible model-specific errors. Intra-atrial excitation conduction was personalized manually from left atrial local activation time maps. Inclusion of LE-MRI data into the simulations revealed possible gaps in ablation lesions. A fast marching level set approach to compute atrial depolarization was extended to incorporate anisotropy and conduction velocity heterogeneities and reproduced the monodomain solution. The presented chain of tools is an important step towards the use of atrial models for the patient-specific AF diagnosis and ablation therapy planing.

Computational cardiology: the heart of the matter

This paper reviews the newest developments in computational cardiology. It focuses on the contribution of cardiac modeling to the development of new therapies as well as the advancement of existing ones for cardiac arrhythmias and pump dysfunction. Reviewed are cardiac modeling efforts aimed at advancing and optimizing existent therapies for cardiac disease (defibrillation, ablation of ventricular tachycardia, and cardiac resynchronization therapy) and at suggesting novel treatments, including novel molecular targets, as well as efforts to use cardiac models in stratification of patients likely to benefit from a given therapy, and the use of models in diagnostic procedures.

Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology

Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.

Computational modeling of the human atrial anatomy and electrophysiology

This review article gives a comprehensive survey of the progress made in computational modeling of the human atria during the last 10 years. Modeling the anatomy has emerged from simple "peanut"-like structures to very detailed models including atrial wall and fiber direction. Electrophysiological models started with just two cellular models in 1998. Today, five models exist considering e.g. details of intracellular compartments and atrial heterogeneity. On the pathological side, modeling atrial remodeling and fibrotic tissue are the other important aspects. The bridge to data that are measured in the catheter laboratory and on the body surface (ECG) is under construction. Every measurement can be used either for model personalization or for validation. Potential clinical applications are briefly outlined and future research perspectives are suggested.

euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.