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Many researchers have suggested evaluation methods and Torsades de Pointes (TdP) metrics to assess the proarrhythmic risk of a drug based on the in silico simulation, as part of the Comprehensive in-vitro Proarrhythmia Assay (CiPA) project. In the previous study, we validated the robustness of 12 in silico features using the ordinal logistic regression (OLR) model by comparing the classification performances of metrics according to the in-vitro experimental datasets used; however, the OLR model using 12 in silico features did not provide desirable results. This study proposed a convolutional neural network (CNN) model using the variability of promising in silico TdP metrics hypothesizing that the variability of in silico features based on beats has more information than the single value of in silico features. We performed the action potential (AP) simulation using a human ventricular myocyte model to calculate seven in silico features representing the electrophysiological cell states of drug effects over 1,000 beats: qNet, qInward, intracellular calcium duration at returning to 50% baseline (CaD50) and 90% baseline (CaD90), AP duration at 50% repolarization (APD50) and 90% repolarization (APD90), and dVm/dtMax_repol. The proposed CNN classifier was trained using 12 train drugs and tested using 16 test drugs among CiPA drugs. The torsadogenic risk of drugs was classified as high, intermediate, and low risks. We determined the CNN classifier by comparing the classification performance according to the variabilities of seven in silico biomarkers computed from the in silico drug simulation using the Chantest dataset. The proposed CNN classifier performed the best when using qInward variability to classify the TdP-risk drugs with 0.94 AUC for high risk and 0.93 AUC for low risk. In addition, the final CNN classifier was validated using the qInward variability obtained after merging three in-vitro datasets, but the model performance decreased to a moderate level of 0.75 and 0.78 AUC. These results suggest the need for the proposed CNN model to be trained and tested using various types of drugs.

Hypertension is a severe public health issue worldwide that significantly increases the risk of cardiac vascular disease, stroke, brain hemorrhage, and renal dysfunction. Early screening of blood pressure (BP) levels is essential to prevent the dangerous complication associated with hypertension as the leading cause of death. Recent studies have focused on employing photoplethysmograms (PPG) with machine learning to classify BP levels. However, several studies claimed that electrocardiograms (ECG) also strongly correlate with blood pressure. Therefore, we proposed a concatenated convolutional neural network which integrated the features extracted from PPG and ECG signals. This study used the MIMIC III dataset, which provided PPG, ECG, and arterial blood pressure (ABP) signals. A total of 14,298 signal segments were obtained from 221 patients, which were divided into 9150 signals of train data, 2288 signals of validation data, and 2860 signals of test data. In the training process, five-fold cross-validation was applied to select the best model with the highest classification performance. The proposed concatenated CNN architecture using PPG and ECG obtained the highest test accuracy of 94.56–95.15% with a 95% confidence interval in classifying BP levels into hypotension, normotension, prehypertension, hypertension stage 1, and hypertension stage 2. The result shows that the proposed method is a promising solution to categorize BP levels effectively, assisting medical personnel in making a clinical diagnosis.

Since the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiation, many studies have suggested various in silico features based on ionic charges, action potentials (AP), or intracellular calcium (Ca) to assess proarrhythmic risk. These in silico features are computed through electrophysiological simulations using in vitro experimental datasets as input, therefore changing with the quality of in vitro experimental data; however, research to validate the robustness of in silico features for proarrhythmic risk assessment of drugs depending on in vitro datasets has not been conducted. This study aims to verify the availability of in silico features commonly used in assessing the cardiac toxicity of drugs through an ordinal logistic regression model and three in vitro datasets measured under different experimental environments and with different purposes. We performed in silico drug simulations using the Tomek-Ohara Rudy (ToR-ORD) ventricular myocyte model and computed 12 in silico features comprising six AP features, four Ca features, and two ion charge features, which reflected the effect and characteristics of each in vitro data for CiPA 28 drugs. We then compared the classific performances of ordinal logistic regressions according to these 12 in silico features and used in vitro datasets to validate which in silico feature is the best for assessing the proarrhythmic risk of drugs at high, intermediate, and low levels. All 12 in silico features helped determine high-risky torsadogenic drugs, regardless of the in vitro datasets used in the in silico simulation as input. In the three types of in silico features, AP features were the most reliable for determining the three Torsade de Pointes (TdP) risk standards. Among AP features, AP duration at 50% repolarization (APD50) was the best when individually using in silico features per in vitro dataset. In contrast, the AP repolarization velocity (dVm/dtMax_repol) was the best when merging all in silico features computed through three in vitro datasets.

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

Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines’ TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when a limited number of drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models for various two-drug combinations. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as features. The drug combination maps were also utilized to illustrate the impact of DDIs on the TdP risk of combined medicines. We found that the DDIs of the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.

Since the Comprehensive

Comprehensive in vitro Proarrhythmia Assay (CiPA) projects for assessing proarrhythmic drugs suggested a logistic regression model using qNet as the Torsades de Pointes (TdP) risk assessment biomarker, obtained from in silico simulation. However, using a single in silico feature, such as qNet, cannot reflect whole characteristics related to TdP in the entire action potential (AP) shape. Thus, this study proposed a deep convolutional neural network (CNN) model using differential action potential shapes to classify three proarrhythmic risk levels: high, intermediate, and low, considering both characteristics related to TdP not only in the depolarization phase but also the repolarization phase of AP shape. We performed an in silico simulation and got AP shapes with drug effects using half-maximal inhibitory concentration and Hill coefficients of 28 drugs released by CiPA groups. Then, we trained the deep CNN model with the differential AP shapes of 12 drugs and tested it with those of 16 drugs. Our model had a better performance for classifying the proarrhythmic risk of drugs than the traditional logistic regression model using qNet. The classification accuracy was 98% for high-risk level drugs, 94% for intermediate-risk level drugs, and 89% for low-risk level drugs.

Cardiovascular disorders, including atrial fibrillation (AF) and congestive heart failure (CHF), are the significant causes of mortality worldwide. The diagnosis of cardiovascular disorders is heavily reliant on ECG signals. Therefore, extracting significant features from ECG signals is the most challenging aspect of representing each condition of ECG signal. Earlier studies have claimed that the Hjorth descriptor is assigned as a simple feature extraction algorithm capable of class separation among AF, CHF, and normal sinus rhythm (NSR) conditions. However, due to noise interference, certain features do not represent the characteristics of the ECG signals. This study addressed this critical gap by applying the discrete wavelet transform (DWT) to decompose the ECG signals into sub-bands and extracting Hjorth descriptor features and entropy-based features in the DWT domain. Therefore, the calculation of Hjorth descriptor and entropy-based features performed on each sub-band will produce more detailed information of ECG signals. The optimization of various classifier algorithms, including k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), artificial neural network (ANN), and radial basis function network (RBFN), was investigated to provide the best system performance. This study obtained an accuracy of 100% for the k-NN, SVM, RF, and ANN classifiers, respectively, and 97% for the RBFN classifier. The results demonstrated that the optimization of the classifier algorithm could improve the classification accuracy of AF, CHF, and NSR conditions, compared to earlier studies.

As part of the Comprehensive in vitro Proarrhythmia Assay initiative, methodologies for predicting the occurrence of drug-induced torsade de pointes via computer simulations have been developed and verified recently. However, their predictive performance still requires improvement. Herein, we propose an artificial neural networks (ANN) model that uses nine multiple input features, considering the action potential morphology, calcium transient morphology, and charge features to further improve the performance of drug toxicity evaluation. The voltage clamp experimental data for 28 drugs were augmented to 2,000 data entries using an uncertainty quantification technique. By applying these data to the modified O’Hara Rudy in silico model, nine features (dVm/dtmax, APresting, APD90, APD50, Caresting, CaD90, CaD50, qNet, and qInward) were calculated. These nine features were used as inputs to an ANN model to classify drug toxicity into high-risk, intermediate-risk, and low-risk groups. The model was trained with data from 12 drugs and tested using the data of the remaining 16 drugs. The proposed ANN model demonstrated an AUC of 0.92 in the high-risk group, 0.83 in the intermediate-risk group, and 0.98 in the low-risk group. This was higher than the classification performance of the method proposed in previous studies.

Heart sound auscultation is one of the most widely used approaches for detecting cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope depends on the physician’s skill and judgement. Several studies have shown promising results in the automatic detection of cardiovascular disorders based on heart sound signals. However, the accuracy performance needs to be improved as automated heart sound classification aids in the early detection and prevention of the dangerous effects of cardiovascular problems. In this study, an optimal heart sound classification method based on machine learning technologies for cardiovascular disease prediction is performed. It consists of three steps: pre-processing that sets the 5 s duration of the Physionet Challenge 2016 datasets, feature extraction using mel-frequency cepstrum coefficients (MFCC), and classification using an artificial neural network (ANN) with one hidden layer that provides low parameter consumption. Ten-fold cross-validation was used to evaluate the performance of the proposed method. The best model obtained 94% accuracy and 93% AUC score, which were assessed using 1626 test datasets. Taken together, the results show that the proposed method obtained excellent classification results and provided low parameter consumption, thereby reducing computational time to facilitate a real-time implementation.

Methodologies for predicting the occurrence of torsade de pointes by drugs via computer simulations have been developed and verified recently, as part of the Comprehensive in vitro Proarrhythmia Assay initiative. However, the predictive performance still requires improvement. Herein, we propose a deep learning algorithm based on artificial neural networks that receives nine multiple features and ​considers the action potential morphology, calcium concentration morphology, and charge characteristics to further improve drug toxicity evaluation performance. The voltage clamp experimental data for 28 drugs were augmented to 2,000 data entries using an uncertainty quantification technique. By applying these data to the modified Ohara Rudy in silico model, nine features (dVm/dtmax, APresting, APD90, APD50, Caresting, CaD90, CaD50, qNet, and qInward) were predicted. These nine features were used as inputs to an artificial neural network (ANN) model to classify drug toxicity into high-risk, intermediate, and low-risk groups. The model was trained with data of 12 drugs and tested with the data of the remaining 16 drugs. The proposed ANN model demonstrated an AUC of 0.94 in the high-risk group, 0.73 in the intermediate group, and 0.91 in the low-risk group. This is higher than the classification performance of the method proposed in previous studies.

Myocardial fibrosis is an integral component of most forms of heart failure. Clinical and computational studies have reported that spatial fibrosis pattern and fibrosis amount play a significant role in ventricular arrhythmogenicity. This study investigated the effect of the spatial distribution of fibrosis and fibrosis amount on the electrophysiology and mechanical performance of the human ventricles. Seventy-five fibrosis distributions comprising diffuse, patchy, and compact fibrosis types that contain 10–50% fibrosis amount were generated. The spatial fibrosis distribution was quantified using the fibrosis entropy (FE) metric. Electrical simulations under reentry conditions induced using the S1–S2 protocol were conducted to investigate the fibrosis arrhythmogenicity. We also performed mechanical simulations to examine the influence of the fibrosis amount and the spatial distribution of fibrosis on the pumping efficacy of the LV. We observed that the mean FE of the compact type is the largest among the three types. The electrical simulation results revealed that the ventricular arrhythmogenicity of diffuse fibrosis depends on the fibrosis amount and marginally on the spatial distribution of fibrosis. Meanwhile, the ventricular arrhythmogenicity of the compact and patchy fibrosis pattern is more reliant on the spatial distribution of fibrosis than on the fibrosis amount. The average number of phase singularities (PSs) in the compact fibrosis pattern was the highest among the three patterns of fibrosis. The diffuse type of fibrosis has the lowest average number of PSs than that in the patchy and compact fibrosis. The reduction in the stroke volume (SV) showed high influence from the electrical instabilities induced by the fibrosis amount and pattern. The compact fibrosis exhibited the lowest SV among the three patterns except in the 40% fibrosis amount. In conclusion, the fibrosis pattern is as crucial as the fibrosis amount for sustaining and aggravating ventricular arrhythmogenesis.

The KCNH2 L532P mutation is an alteration in the IKr channel that is associated with short QT syndrome and atrial fibrillation in zebrafish. In preliminary studies, the electrophysiological effects of the hERG L532P mutation were investigated using a mathematical model in a single-cell and 2D sheet medium. The objective of this study was to quantify the effects of the KCNH2 L532P mutation on the 3D ventricular electrophysiological behavior and the mechanical pumping responses. We used a realistic three-dimensional ventricular electrophysiological-mechanical model, which was adjusted into two conditions: the wild-type (WT) condition, i.e., the original case of the Tusscher et al. model, and the L532P mutation condition, with modification of the original IKr equation. The action potential duration (APD) in the mutant ventricle was reduced by 73% owing to the significant increase of the IKr current density. In the 3D simulation, the L532P mutation maintained the sustainability of reentrant waves; however, the reentry was terminated in the WT condition. The contractility of the ventricle with L532P mutation was significantly reduced compared with that in WT which results in sustain shivering heart during reentry condition. The reduction of the contractility was associated with the shortening APD which simultaneously shortened the duration of the Ca2+ channel opening. In conclusion, the ventricle with KCNH2 L532P mutation is prone to reentry generation with a sustained chaotic condition, and the mutation significantly reduced the pumping performance of the ventricles.

In ventricular tachyarrhythmia, electrical instability features including action potential duration, dominant frequency, phase singularity, and filaments are associated with mechanical contractility. However, there are insufficient studies on estimated mechanical contractility based on electrical features during ventricular tachyarrhythmia using a stochastic model. In this study, we predicted cardiac mechanical performance from features of electrical instability during ventricular tachyarrhythmia simulation using machine learning algorithms, including support vector regression (SVR) and artificial neural network (ANN) models. We performed an electromechanical tachyarrhythmia simulation and extracted 12 electrical instability features and two mechanical properties, including stroke volume and the amplitude of myocardial tension (ampTens). We compared predictive performance according to kernel types of the SVR model and the number of hidden layers of the ANN model. In the SVR model, the prediction accuracies of stroke volume and ampTens were the highest when using the polynomial kernel and linear kernel, respectively. The predictive performance of the ANN model was better than that of the SVR model. The prediction accuracies were the highest when the ANN model consisted of three hidden layers. Accordingly, we propose the ANN model with three hidden layers as an optimal model for predicting cardiac mechanical contractility in ventricular tachyarrhythmia. The results of this study are expected to be used to indirectly estimate the hemodynamic response from the electrical cardiac map measured by the optical mapping system during cardiac surgery, as well as cardiac contractility under normal sinus rhythm conditions.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Background and aims: Clinical and computational studies have reported that spatial fibrosis pattern and fibrosis amount play a significant role in ventricular arrhythmogenicity. Nonetheless, the underlying mechanisms of arrhythmogenicity of fibrosis are not known accurately. In addition, we believe that the effect of different fibrosis types and fibrosis amount on the cardiac mechanical performance requires a further investigation. Therefore, this study investigated the effect of spatial distribution of fibrosis and fibrosis amount on the electrical and mechanical performance of the left ventricle (LV). Methods: We employed a human ventricular model that simulates both the electrophysiological and the mechanical contraction characteristics of the ventricle. The electrophysiological conduction model mimics the exchange of ions through the plasma membrane of myocardial cells whereas the mechanical contraction model simulates the mechanical cardiac response. Seventy-five fibrosis distributions comprising diffuse, patchy, and compact fibrosis types that contain 10%–50% fibrosis amount were generated to cover a wide range of fibrosis cases. The spatial fibrosis distribution in the human ventricular model was quantified using fibrosis entropy (FE) metric. Then, electrophysiological simulations under reentry conditions induced using the S1-S2 protocol were conducted to investigate the correlation between different patterns of fibrosis and ventricular arrhythmogenicity. Finally, we compared the mechanical response by conducting mechanical simulations to examine the influence of the fibrosis amount and spatial distribution of fibrosis on the pumping efficacy of the LV by extracting the calcium information from the electrophysiological simulation. Results: We observed that the spatial patchy fibrosis distribution was more chaotic (higher mean FE) than those of the compact and diffuse types. The electrical simulation results revealed that the ventricular arrhythmogenicity of diffuse fibrosis depends on the fibrosis amount and marginally on the spatial distribution of fibrosis. Meanwhile, the ventricular arrhythmogenicity of the compact and patchy fibrosis types is reliant on the spatial distribution of fibrosis than on the fibrosis amount. The average number of phase singularities in the electrical simulations with compact fibrosis was higher than those with patchy and diffuse fibrosis. As a result, compact fibrosis resulted a lower stroke volume (SV) of the LV, whereas the diffuse fibrosis resulted in a higher SV of the LV. The reduction in the stroke volume (SV) of the LV was linearly correlated to the electrical instabilities induced by the fibrosis amount and spatial distribution of fibrosis. Conclusion: The increase in the amount of diffuse, patchy and compact fibrosis in the myocardium increased the electrical instability and likely decreased the pumping efficacy of LV. Moreover, the effect fibrosis pattern on ventricular arrhythmogenesis was more significant in compact and patchy fibrosis types than in diffuse fibrosis.

There are representative electrical parameters for understanding the mechanism of reentrant waves in studies on tachyarrhythmia, namely the action potential duration (APD), dominant frequency, phase singularity, and filament. However, there are no studies that have directly identified the correlation between these electrophysiological parameters and cardiac contractility. Therefore, we have identified individual and integrative correlations between these electrical phenomena and contractility during tachyarrhythmia by deriving regression equations and also investigated the electrophysiological parameters affecting cardiac contractility during tachyarrhythmia. We simulated ventricular tachyarrhythmia with 48 types of electrical patterns by applying four reentry generation methods and changing the electrical conductivity of the potassium channel, which has the greatest effect on ventricular tissue. The mechanical responses reflecting electrical complexity were obtained through deterministic simulations of excitation–contraction coupling. We used the stroke volume and amplitude of myocardial tension (ampTens) as the variables representing contractility. We derived stochastic models through single- and multivariable regression analyses to identify the electrical parameters affecting contractility during tachyarrhythmia. In single-variable regression analysis, the APD, dominant frequency, and filament, excluding phase singularity, have statistically significant correlations with the stroke volume and ampTens. Among them, the APD has the maximum influence on these two mechanical parameters (standard beta coefficient: 0.859 for stroke volume, 0.930 for ampTens). The stochastic model using all four electrical parameters fails to accurately predict contractility owing to the multicollinearity between the APD and dominant frequency. We have rederived the multi-variable stochastic model using three electrical parameters without the APD. The filament has the greatest effect on the stroke volume stochastically (standard beta coefficient: 0.853 and 0.752). The dominant frequency has the greatest effect on ampTens statistically (standard beta coefficient: −0.813). We conclude that among the electrical parameters, the APD has the highest individual influence on mechanical contraction, and the filament has the highest integrative influence in both statistical terms.

Background Atrial arrhythmia is a cardiac disorder caused by abnormal electrical signaling and transmission, which can result in atrial fibrillation and eventual death. Genetic defects in ion channels can cause myocardial repolarization disorders. Arrhythmia-associated gene mutations, including KCNH2 gene mutations, which are one of the most common genetic disorders, have been reported. This mutation causes abnormal QT intervals by a gain of function in the rapid delayed rectifier potassium channel (IKr). In this study, we demonstrated that mutations in the KCNH2 gene cause atrial arrhythmia. Methods The N588K and L532P mutations were induced in the Courtemanche-Ramirez-Nattel (CRN) cell model, which was subjected to two-dimensional and three-dimensional simulations to compare the electrical conduction patterns of the wild-type and mutant-type genes. Results In contrast to the early self-termination of the wild-type conduction waveforms, the conduction waveform of the mutant-type retained the reentrant wave (N588K) and caused a spiral break-up, resulting in irregular wave generation (L532P). Conclusion The present study confirmed that the KCNH2 gene mutation increases the vulnerability of the atrial tissue for arrhythmia., Graphical Abstract

Background Atrial arrhythmia is a cardiac disorder caused by abnormal electrical signaling and transmission, which can result in atrial fibrillation and eventual death. Genetic defects in ion channels can cause myocardial repolarization disorders. Arrhythmia-associated gene mutations, including KCNH2 gene mutations, which are one of the most common genetic disorders, have been reported. This mutation causes abnormal QT intervals by a gain of function in the rapid delayed rectifier potassium channel (IKr). In this study, we demonstrated that mutations in the KCNH2 gene cause atrial arrhythmia. Methods The N588K and L532P mutations were induced in the Courtemanche-Ramirez-Nattel (CRN) cell model, which was subjected to two-dimensional and three-dimensional simulations to compare the electrical conduction patterns of the wild-type and mutant-type genes. Results In contrast to the early self-termination of the wild-type conduction waveforms, the conduction waveform of the mutant-type retained the reentrant wave (N588K) and caused a spiral break-up, resulting in irregular wave generation (L532P). Conclusion The present study confirmed that the KCNH2 gene mutation increases the vulnerability of the atrial tissue for arrhythmia.

This study hypothesized that a left ventricular assist device (LVAD) shortens the electromechanical delay (EMD) by mechanical unloading. The goal of this study is to examine, by computational modeling, the influence of LVAD on EMD for four heart failure (HF) cases ranging from mild HF to severe HF. We constructed an integrated model of an LVAD-implanted cardiovascular system, then we altered the Ca2+ transient magnitude, with scaling factors 1, 0.9, 0.8, and 0.7 representing HF1, HF2, HF3, and HF4, respectively, in order of increasing HF severity. The four HF conditions are classified into two groups. Group one is the four HF conditions without LVAD, and group two is the conditions treated with continuous LVAD pump. The single-cell mechanical responses showed that EMD was prolonged with the higher load. The findings indicated that in group one, the HF-induced Ca2 + transient remodeling prolonged the mechanical activation time (MAT) and decreased the contractile tension, which reduced the left ventricle (LV) pressure, and increased the end-diastolic strain. In group two, LVAD shortened MAT of the ventricles. Furthermore, LVAD reduced the contractile tension, and end-diastolic strain, but increased the aortic pressure. The computational study demonstrated that LVAD shortens EMD by mechanical unloading of the ventricle. Electronic supplementary material The online version of this article (10.1007/s11517-017-1730-y) contains supplementary material, which is available to authorized users.

The KCNJ2 gene mutations induce short QT syndrome (SQT3) by directly increasing the IK1 current. There have been many studies on the electrophysiological effects of mutations such as the KCNJ2 D172N that cause the SQT3. However, the KCNJ2 E299V mutation is distinguished from other representative gene mutations that can induce the short QT syndrome (SQT3) in that it increased IK1 current by impairing the inward rectification of K+ channels. The studies of the electromechanical effects on myocardial cells and mechanisms of E299V mutations are limited. Therefore, we investigated the electrophysiological changes and the concomitant mechanical responses according to the expression levels of the KCNJ2 E299V mutation during sinus rhythm and ventricular fibrillation. We performed excitation-contraction coupling simulations using a human ventricular model with both electrophysiological and mechanical properties. In order to observe the electromechanical changes due to the expression of KCNJ2 E299V mutation, the simulations were performed under normal condition (WT), heterogeneous mutation condition (WT/E299V), and pure mutation condition (E299V). First, a single-cell simulation was performed in three types of ventricular cells (endocardial cell, midmyocardial cell, and epicardial cell) to confirm the electrophysiological changes and arrhythmogenesis caused by the KCNJ2 E299V mutation. In three-dimensional sinus rhythm simulations, we compared electrical changes and the corresponding changes in mechanical performance caused by the expression level of E299V mutation. Then, we observed the electromechanical properties of the E299V mutation during ventricular fibrillation using the three-dimensional reentry simulation. The KCNJ2 E299V mutation accelerated the opening of the IK1 channel and increased IK1 current, resulting in a decrease in action potential duration. Accordingly, the QT interval was reduced by 48% and 60% compared to the WT condition, for the WT/E299V and E299V conditions, respectively. During sustained reentry, the wavelength was reduced due to the KCNJ2 E299V mutation. Furthermore, there was almost no ventricular contraction in both WT/E299V and E299V conditions. We concluded that in both sinus rhythm and fibrillation, the KCNJ2 E299V mutation results in very low contractility regardless of the expression level of mutation and increases the risk of cardiac arrest and cardiac death.

Electrical stimulation therapy is a promising method for treating neurological diseases. This method induces the activity and differentiation of nerve cells by the direct or indirect transmission of an electrical signal through biomedical electrodes. We demonstrated the efficacy of a graphene sheet as a bioelectrode to differentiate neurites from hippocampal neuron, through electrical stimulation. In order to the artificially induce the differentiation of hippocampal neurons, we directly transmitted electrical signals of square pulse through the graphene electrode to directly stimulate neurons cultured onto graphene surface. Compared to cell culture plates, the average length of differentiated neurites increased 111.1% on pristine graphene with electrical stimulation. And the average number of differentiated neurites on a single cell increased to 281.9% on oxygenated graphene with electrical stimulation. Electrical stimulation with graphene electrodes promoted the differentiation of neurites and activated the production of intercellular networks of hippocampal neurons.

Purpose Although the quantitative analysis of electromechanical alternans is important, previous studies have focused on electrical alternans, and there is a lack quantitative analysis of mechanical alternans at the subcellular level according to various basic cycle lengths (BCLs). Therefore, we used the excitation–contraction (E–C) coupling model of human ventricular cells to quantitatively analyze the mechanical alternans of ventricular cells according to various BCLs. Methods To implement E–C coupling, we used calcium transient data, which is the output data of electrical simulation using the electrophysiological model of human ventricular myocytes, as the input data of mechanical simulation using the contractile myofilament dynamics model. Moreover, we applied various loads on ventricular cells for implementation of isotonic and isometric contraction. Results As the BCL was reduced from 1000 to 200 ms at 30 ms increments, mechanical alternans, as well as electrical alternans, were observed. At this time, the myocardial diastolic tension increased, and the contractile ATP consumption rate remained greater than zero even in the resting state. Furthermore, the time of peak tension, equivalent cell length, and contractile ATP consumption rate were all reduced. There are two tendencies that endocardial, mid-myocardial, and epicardial cells have the maximum amplitude of tension and the peak systolic tension begins to appear at a high rate under the isometric condition at a particular BCL. Conclusions We observed mechanical alternans of ventricular myocytes as well as electrical alternans, and identified unstable conditions associated with mechanical alternans. We also determined the amount of BCL given to each ventricular cell to generate stable and high tension state in the case of isometric contraction.

Background The heart wall exhibits three layers of different thicknesses: the outer epicardium, mid-myocardium, and inner endocardium. Among these layers, the mid-myocardium is typically the thickest. As indicated by preliminary studies, heart-wall layers exhibit various characteristics with regard to electrophysiology, pharmacology, and pathology. Construction of an accurate three-dimensional (3D) model of the heart is important for predicting physiological behaviors. However, the wide variability of myocardial shapes and the unclear edges between the epicardium and soft tissues are major challenges in the 3D model segmentation approach for identifying the boundaries of the epicardium, mid-myocardium, and endocardium. Therefore, this results in possible variations in the heterogeneity ratios between the epicardium, mid-myocardium, and endocardium. The objective of this study was to observe the effects of different thickness ratios of the epicardium, mid-myocardium, and endocardium on cardiac arrhythmogenesis, reentry instability, and mechanical responses during arrhythmia. Methods We used a computational method and simulated three heterogeneous ventricular models: Model 1 had the thickest M cell layer and thinnest epicardium and endocardium. Model 2 had intermediate layer thicknesses. Model 3 exhibited the thinnest mid-myocardium and thickest epicardium and endocardium. Electrical and mechanical simulations of the three heterogeneous models were performed under normal sinus rhythm and reentry conditions. Results Model 1 exhibited the highest probability of terminating reentrant waves, and Model 3 exhibited to experience greater cardiac arrhythmia. In the reentry simulation, at 8 s, Model 3 generated the largest number of rotors (eight), while Models 1 and 2 produced five and seven rotors, respectively. There was no significant difference in the cardiac output obtained during the sinus rhythm. Under the reentry condition, the highest cardiac output was generated by Model 1 (19 mL/s), followed by Model 2 (9 mL/s) and Model 3 (7 mL/s). Conclusions A thicker mid-myocardium led to improvements in the pumping efficacy and contractility and reduced the probability of cardiac arrhythmia. Conversely, thinner M cell layers generated more unstable reentrant spiral waves and hindered the ventricular pumping.

Highlights • We numerically investigated the physiological relationship between the severity of regurgitation and the effect of a left ventricular assist device (LVAD) on cardiovascular system responses. • Under conditions of mitral regurgitation, the effects of both pulsatile and continuous LVAD treatment on ventricular unloading were significant. • Under conditions of aortic regurgitation (AR), the effects of the LVADs on ventricular unloading were not significant. The effects of LVAD treatment decreased according to the severity of AR., Background A left ventricular assist device (LVAD) is normally contraindicated in significant aortic regurgitation (AR) and requires intraoperative valve repair or exclusion. Nevertheless, AR can coexist with an LVAD, so a valid question when asked might still be of clinical significance. The purpose of this study is to analyze the effects of valve regurgitation on the pumping efficacy of continuous and pulsatile LVADs with a computational method. Methods A cardiovascular model was developed based on the Windkessel model, which reflects the hemodynamic flow resistance and the blood wall elasticity. Using the Windkessel model, important cardiovascular components, such as the right atrium, right ventricle, pulmonary artery, pulmonary vein, left atrium (LA), left ventricle (LV), aorta, and branching blood vessels, were expressed. Results In the case of AR, continuous and pulsatile LVADs improved cardiac output and reduced mechanical load slightly. In the case of mitral regurgitation, the LVADs improved cardiac output (cardiac outputs were about 5 L/min regardless of the severity of regurgitation) and reduced afterload significantly. Conclusion AR reduced both continuous and pulsatile LVAD function significantly while mitral regurgitation did not affect their pumping efficacy.

Background/Objectives: This research is an experimental research to output the DICOM image of carpus through 3D printer and to confirm the identity of 3D medical image and the shape. An experimental analysis was conducted as follows: First, the size on the 3D medical image and the length of the shape output through 3D printer were measured and compared using Digital Vernier Calipers; second, the anatomical forms and shapes before and after an experimental study were evaluated based on a survey of evaluators composed of 10 medical imaging experts and the results were reflected. Methods/Statistical Analysis: The purpose of an experiment in this research is to contribute to improving learning effects by manufacturing a phantom for medical learning about carpus and to establishing a clinical diagnosis and treatment plan. Carpus was used as the object of an experiment. The reason is that since carpus has the very irregular and smallest bones in human body, it has advantages in comparing the precision of a manufactured shape and improves educational understanding in medical learning. Findings: According to the research results, the length of the longitudinal plane in carpus used for the experiment was 120 mm equally in the medical image and the shape output through 3D printer. As the results of comparing the form and shape of carpus output through 3D printer with DICOM image of carpus, radiologists represented 16% for Good and 84% for Very Good and radiological technicians represented 2% for Fair, 20% for Good and 78% for Very Good. Improvements: In conclusion, if the material equivalent to human body can be developed and its shape can be output through 3D printer, the learning effects through a phantom is expected to be greatly improved.

Nanocrystalline diamond (NCD) film surfaces were modified with fluorine or oxygen by plasma treatment in an O 2 or C 3 F 8 gas environment in order to induce wettability. The oxygenated-NCD (O-NCD) film surface was hydrophilic and the fluorinated-NCD (F-NCD) surface was hydrophobic. The efficiency of early cell adhesion, which is dependent on the wettability of the cell culture plate and necessary for the growth and proliferation of cells, was 89.62 ± 3.92% on the O-NCD film and 7.78 ± 0.77% on the F-NCD film surface after 3 h of cell culture. The wettability of the NCD film surface was artificially modified using a metal mask and plasma treatment to fabricate a micro-pattern. Four types of micro-patterns were fabricated (line, circle, mesh, and word) on the NCD film surface. We precisely arrayed the neuroblastoma cells on the micro-patterned NCD film surfaces by controlling the surface wettability and cell seeding density. The neuroblastoma cells adhered and proliferated along the O-NCD film surface.

To fabricate micro-patterns for bioengineering applications, we used graphene sheet, metal mask, and plasma treatment rather than the commonly used photolithography process. Two types of micro-patterns were fabricated (line, and circle) on SiO 2 /Si (100, p-typed) substrate. In the line and circle micro-patterns, graphene etched areas were 100 and 150 μm, respectively, with fluorinated graphene spacing. The efficiencies of early cell adhesion, which is necessary for the growth and proliferation of cells, were 62, 17, and 65% on the pristine, fluorinated, and etched graphene surface, respectively, for 6 h of cell culture. After seeding the neuron cells on the patterned substrate, neuron cells proliferated and differentiated along the graphene etched regions. The graphene sheet was used as a passivation layer for micro-array of the neuron cell on SiO 2 /Si.

Death due to ventricular fibrillation (VF) can occur over a relatively short time period. During the first stage, an irregular heartbeat or arrhythmia of the heart may occur. Therefore, studying arrhythmia could reveal important insights relevant to the prevention of VF. One of the factors known to cause arrhythmia is the generation of mutations in the ion channels of myocytes. The current experimental methods to monitor and observe subjects with arrhythmia are invasive, and could possibly harm the subject with no guarantee of obtaining good results. These limitations could be overcome by using an extensively validated computational simulation study. This study aims to enhance our understanding of the effect of the V241F mutation on electromechanical behavior in the heart. We simulated three conditions; wild-type (WT), heterozygous/intermediate V241F, and pure V241F conditions in an electrophysiological single cell model and three-dimensional electro-mechanics ventricular model. The electro-mechanics model is a one-way coupling of the electrical compartment to the mechanical compartment by Ca2+ transient concentration. Consistent with a previous study, the V241F mutation significantly shortened the action potential duration at 90% repolarization (APD90) under pure V241F mutation conditions, due to the gain of function of the slow delayed rectifier potassium (IKs) channel. This APD90 shortening is associated with a short electrical wavelength, which shortens the Ca2+ activation time as well. The hemodynamic responses showed that the V241F mutation lowered ventricular contraction under normal sinus rhythm conditions by decreasing the stroke volume, stroke work, and ejection fraction. During reentry, the V241F mutation significantly reduced the ventricular contractility compared with the WT condition. In conclusions, the effect of the two variants of V241F (intermediate and pure) mutation not only disturbed the electrophysiological events but also affected the mechanical behavior significantly. The result of this study can be used as a reference for the cardiovascular expert to decide the appropriate pharmacology of IKs conductance block for the patient.

The understanding of cardiac arrhythmia under genetic mutations has grown in interest among researchers. Previous studies focused on the effect of the D172N mutation on electrophysiological behavior. In this study, we analyzed not only the electrophysiological activity but also the mechanical responses during normal sinus rhythm and reentry conditions by using computational modeling. We simulated four different ventricular conditions including normal case of ten Tusscher model 2006 (TTM), wild-type (WT), heterozygous (WT/D172N), and homozygous D172N mutation. The 2D simulation result (in wire-shaped mesh) showed the WT/D172N and D172N mutation shortened the action potential duration by 14%, and by 23%, respectively. The 3D electrophysiological simulation results showed that the electrical wavelength between TTM and WT conditions were identical. Under sinus rhythm condition, the WT/D172N and D172N reduced the pumping efficacy with a lower left ventricle (LV) and aortic pressures, stroke volume, ejection fraction, and cardiac output. Under the reentry conditions, the WT condition has a small probability of reentry. However, in the event of reentry, WT has shown the most severe condition. Furthermore, we found that the position of the rotor or the scroll wave substantially influenced the ventricular pumping efficacy during arrhythmia. If the rotor stays in the LV, it will cause very poor pumping performance. Graphical Abstract A model of a ventricular electromechanical system. This whole model was established to observe the effect of D172N KCNJ2 mutation on ventricular pumping behavior during sinus rhythm and reentry conditions. The model consists of two components; electrical component and mechanical component. The electrophysiological model based on ten Tusscher et al. with the IK1 D172N KCNJ2 mutation, and the myofilament dynamic (cross-bridge) model based on Rice et al. study. The 3D electrical component is a ventricular geometry based on MRI which composed of nodes representing single-cell with electrophysiological activation. The 3D ventricular mechanic is a finite element mesh composed of single-cells myofilament dynamic model. Both components were coupled with Ca2+ concentration. We used Gaussian points for the calcium interpolation from the electrical mesh to the mechanical mesh.

The KCNQ1 S140G mutation, which is involved in IKs current, affects atrial fibrillation. However, little is known about its effect on the mechanical behavior of the heart. Therefore, we assessed the influence of the KCNQ1 S140G mutation on ventricular electrophysiological stability and mechanical pumping performance using a multi-scale model of cardiac electromechanics. An image-based electromechanical model was used to assess the effect on electrical propagation and arrhythmogenesis of the KCNQ1 S140G mutation. In addition, it was used to compare the mechanical response under the wild-type (WT) and S140G mutation conditions. The intracellular calcium transient obtained from the electrophysiological model was applied as an input parameter to a mechanical model to implement excitation–contraction coupling. The IKs current equation was modified to account for expression of the KCNQ1 S140G mutation, and it included a scaling factor (ϕ) for mutant expressivity. The WT and S140G mutation conditions were compared at the single-cell and three-dimensional (3D) tissue levels. The action potential duration (APD) was reduced by 60% by the augmented IKs current under the S140G mutation condition, which resulted in shorter QT interval. This reduced the 3D sinus rhythm wavelength by 60% and the sustained re-entry by 56%. However, pumping efficiency of mutant ventricles was superior in sinus rhythm condition. In addition, the shortened wavelength in cardiac tissue allowed a re-entrant circuit to form and increased the probability of sustaining ventricular tachycardia and ventricular fibrillation. In contrast, under the WT condition, a normal wavelength (20.8 cm) was unlikely to initiate and sustain re-entry in the cardiac tissue. Subsequently, the S140G mutant ventricles developed a higher dominant frequency distribution range (2.0–5.3 Hz) than the WT condition (2.8–3.7 Hz). In addition, stroke volume of mutant ventricles was reduced by 65% in sustained re-entry compared to the WT condition. In conclusion, signs of the S140G mutation might be difficult to identify in sinus rhythm even though the mutant ventricles show shortened QT interval. This suggests that the KCNQ1 S140G mutation increases the risk of death by sudden cardiac arrest. In addition, the KCNQ1 S140G mutation can induce ventricular arrhythmia and lessen ventricular contractility under re-entrant conditions.

Background Counter-pulsation control (CPC) by ventricular assist devices (VADs) is believed to reduce cardiac load and increase coronary perfusion. However, patients with VADs have a higher risk of arrhythmia, which may cause the CPC to fail. Consequently, CPC has not been applied by VADs in clinical practice. The phase-locked loop (PLL) algorithm for CPC is readily implemented in VADs; however, it requires a normal, consistent heartbeat for adequate performance. When an arrhythmia occurs, the algorithm maintains a constant pumping rate despite the unstable heartbeat. Therefore, to apply the PLL algorithm to CPC, the hemodynamic effects of abnormal heartbeats must be analyzed. Objectives This study sought to predict the hemodynamic effects in patients undergoing CPC using VADs, based on electrocardiogram (ECG) data, including a wide range of heart rate (HR) changes caused by premature ventricular contraction (PVC) or other reasons. Methods A four-element Windkessel hemodynamic model was used to reproduce the patient’s aortic blood pressure in this study. ECG data from 15 patients with severe congestive heart failure were used to assess the effect of the CPC on the patients’ hemodynamic state. The input and output flow characteristics of the pulsatile VAD (LibraHeart I, Cervika, Korea) were measured using an ultrasound blood flow meter (TS410, Transonic, USA), with the aortic pressure maintained at 80–120 mmHg. All other patient conditions were also reproduced. Results In patients with PVCs or normal heartbeats, CPC controlled by a VAD reduced the cardiac load by 20 and 40%, respectively. When the HR was greater for other reasons, such as sinus tachycardia, simultaneous ejection from the heart and VAD was observed; however, the cardiac load was not increased by rapid cardiac contractions resulting from decreased left ventricle volume. These data suggest that the PLL algorithm reduces the cardiac load and maintains consistent hemodynamic changes.

The purpose of the study is to examine the effects of pacemaker location on cardiac pumping efficacy the-oretically. We used a three-dimensional finite element cardiac electromechanical model of canine ventricles with mod-els of the circulatory system. Electrical activation time for normal sinus rhythm and artificial pacing in apex, leftventricular free wall, and right ventricular free wall were obtained from electrophysiological model. We applied theelectrical activation time maps to the mechanical contraction model and obtained cardiac mechanical responses suchas myocardial contractile ATP consumption, stroke work, stroke volume, ejection fraction, and etc. Among three arti-ficial pacing methods, left ventricle pacing showed best performance in ventricular pumping efficacy.Key words: Cardiac electromechanical model, Electrical activation time, ATP consumption rate, Stroke work, Strokevolume I. 서 론 정상동성리듬(Normal sinus rhythm)에 의한 심실의 수축은 퍼킨제섬유의 빠른 전도에 의해 심내막에 균일하고 동시자극을 주게 되고 이 자극이 심내막에서 심외막으로 전달됨으로써, 거의 동시다발적으로 좌우심실의 수축이 일어나게 된다. 심실의 전기적 흥분이 전파되는 경로상에서 문제가 있거나 동시성이 깨어질 경우에 인공 심박조율기를 이식하여 인공적으로 심조율을 하게 된다. 일반적으로 인공 심장재동기화를시행할때, 심실전극도자는접근성의용이로일반적으로 우심실에 이식한다[1]. 그러나 의료장비 및 시술기술의 발전으로 우심실뿐 만 아니라 좌심실이나 심첨 등에도 이식을 할 수 있게 되었고, 우심실이 아닌 다른 부위에서 인공 심조율기를 이식하여 시행함으로써 어떠한 심장역학적 변화가 있는지를 알아보고자 하는 실험들이 시도되었다[2,3]. 최근 일부 연구에서 보면 우심실이 아닌 좌심실에서 인위적으로 조율을 하였을 때 심박출량의 개선을 보인다는 보고도 있었다[4]. 그러나 실험적 방법에 의한 결과들은대부분 심장기능을 가늠하는 직접적인 지표(심박출량, 압력-부피관계, 심장에 부여되는 기계적응력 및 에너지소모량 등)가 아니라 심전도 또는 혈관계의 혈압과 같은 간접적인 지표들이다. 현재 의료측정장비의 기술로는 아직까지 위와 같은 지표들을 측정하는 것은 불가능하다. 이의 대안으로 심장모델링 기술을 이용한 컴퓨터 시뮬레

Outflow cannulation site of left ventricular assist device(LVAD) chosen by considering anatomical structure of thoracic cavity and vascular system. Though outflow cannulation site influences blood perfusion at each branch, there is no standard rule or quantitative data. In this study, we computed the amount of blood perfusion at each arterial branch numerically according to outflow cannulation sites(ascending aorta, aortic arch, descending aorta). We generated computational meshes to the three-dimensionally reconstructed arterial system. Clinically measured arterial pressure were used for inlet boundary condition, porous media were applied to mimic blood flow resistance. Blood perfusion through left common carotid artery was 2.5 times higher than other cases, and that through right common carotid artery was 1.1 times higher than other branches. Although this is simulation study, will be useful reference data for the clinical study of LVAD which considers blood perfusion efficiency.

Using a three-dimensional electromechanical model of the canine ventricles with dyssynchronous heart failure, we investigated the relationship between severity of valve regurgitation and ventricular mechanical responses. The results demonstrated that end-systolic tension in the septum and left ventricular free wall was significantly lower under the condition of mitral regurgitation (MR) than under aortic regurgitation (AR). Stroke work in AR was higher than that in MR. On the other hand, the difference in stroke volume between the two conditions was not significant, indicating that AR may cause worse pumping efficiency than MR in terms of consumed energy and performed work.

Background and aims Although it is important to analyze the hemodynamic factors related to the right ventricle (RV) after left ventricular assist device (LVAD) implantation, previous studies have focused only on the alteration of the ventricular shape and lack quantitative analysis of the various hemodynamic parameters. Therefore, we quantitatively analyzed various hemodynamic parameters related to the RV under normal, heart failure (HF), and HF incorporated with continuous flow LVAD therapy by using a computational model. Methods In this study, we combined a three-dimensional finite element electromechanical model of ventricles, which is based on human ventricular morphology captured by magnetic resonance imaging (MRI) with a lumped model of the circulatory system and continuous flow LVAD function in order to construct an integrated model of an LVAD implanted-cardiovascular system. To induce systolic dysfunction, the magnitude of the calcium transient function under HF condition was reduced to 70% of the normal value, and the time constant was reduced by 30% of the normal value. Results Under the HF condition, the left ventricular end systolic pressure decreased, the left ventricular end diastolic pressure increased, and the pressure in the right atrium (RA), RV, and pulmonary artery (PA) increased compared with the normal condition. The LVAD therapy decreased the end-systolic pressure of the LV by 41%, RA by 29%, RV by 53%, and PA by 71%, but increased the right ventricular ejection fraction by 52% and cardiac output by 40%, while the stroke work was reduced by 67% compared with the HF condition without LVAD. The end-systolic ventricular tension and strain decreased with the LVAD treatment. Conclusion LVAD enhances CO and mechanical unloading of the LV as well as those of the RV and prevents pulmonary hypertension which can be induced by HF.

Background and aims Although studies on the relation between arrhythmias and the action potential duration (APD) have been carried out, most of them are based only on electrophysiological factors of the heart and lack experiments that consider cardiac mechanical and electromechanical characteristics. Therefore, we conducted this study to clarify the relevance of the shortening of APD of a cell in relation to the mechanical contraction activity of the heart and the associated risk of arrhythmia. Methods The human ventricular model used in this study has two dynamic characteristics: electrophysiological conduction and mechanical contraction. The model simulating electrophysiological characteristics was consisted of lumped parameter circuit that can mimic the phenomenon of ion exchange through the cell membrane of myocyte and consisted of 214,319 tetrahedral finite elements. In contrast, the model simulating mechanical contraction characteristics was constructed to mimic cardiac contraction by means of the crossbridge of a myofilament and consisted of 14,720 hermite-based finite elements to represent a natural 3D curve of the cardiac surface. First, we performed a single cell simulation and the electrophysiological simulation according to the change of the APD by changing the electrical conductivity of the I Ks channel. Thus, we confirmed the correlation between APD and intracellular Ca2+ concentration. Then, we compared mechanical response through mechanical simulation using Ca2+ data from electrical simulation. Results The APD and the sum of the intracellular Ca2+ concentrations showed a positive correlation. The shortened APD reduced the conduction wavelength of ventricular cells by shortening the plateau and early repolarization in myocardial cells. The decrease in APD reduced ventricular pumping efficiency by more than 60% as compared with the normal group (normal conditions). This change is caused by the decline of ventricular output owing to reduced ATP consumption during the crossbridge of myofilaments and decreased tension. Conclusion The shortening of APD owing to increased electrical conductivity of a protein channel on myocardial cells likely decreases the wavelength and the pumping efficiency of the ventricles. Additionally, it may increase tissue sensitivity to ventricular fibrillation, including reentry, and cause symptoms such as dyspnea and dizziness.

Genetic factors play an important role in the pathogenesis of atrial flutter (AF). Although mutation in KCNQ1 has been widely correlated with AF, the mechanism by which mutation promotes AF remains poorly understood. The purpose of this study was to investigate the proarrhythmic effect of V241F KCNQ1 mutation in human atrium using the electrophysiological model of human atrium. Using 2D and 3D cardiac electrophysiological models that incorporate the Courtemanche human atrial model, we simulated electrical conduction through atrial tissue and compared spiral wave dynamics under the wild-type and V241F KCNQ1 conditions. In 2D and 3D simulation, V241F KCNQ1 showed a stable and persistent wave without spiral break-up, whereas the wild-type wave was less stable, resulting in early self-termination. According to the results, we concluded that compared to the wild type, the electrical activity of the V241F KCNQ1 mutation is more likely to sustain spiral wave.

따라서 LVAD 처방의 장단점을 고려하여, 적절한 시기에 치료를 시작하는 것이 매우 중요하다. 특히 심실회복을 목표로 LVAD 치료를 시작하는 환Key Words: Left Ventricular Assist Device(좌심실보조장치), Ventricular Unloading(심실부하감소), Finite Element Model(유한요소감소모델), ATP Consumption(수축성 ATP소모율) 초록: 좌심실보조장치(LVAD)가 심실부하감소에 미치는 영향을 극대화 하기 위해, 심실보조장치 치료를 위한 최적의 심부전 심각도 단계를 찾는 것은 중요하다. 우리는 심부전 정도에 따른 LVAD 의 박동효율을 이론적으로 예측하였다. 우리는 혈관시스템의 6컴파트먼트의 Wind-kessel 모델과 연동된 심실의 삼차원 유한요소모델을 사용하였다. 이 모델을 이용하여, LVAD 치료 하에서 심부전의 정도에 따라 심실의 수축성 ATP 소모율, 좌심실압력, 심박출량, 심박출 분획, 1회심박출량 등과 같은 심장응답을 예측하였다. LVAD 치료 중에 에너지학적 부하조건을 암시하는 수축성 ATP 소모율은 5 단계 심부전 조건에서 가장 크게 감소하였다. 따라서, 우리는 LVAD 를 회복으로의 가교로서 고려하고 있을 때, 심부전 5 단계에서 LVAD 치료를 시작하는 것이 가장 적절하다는 결론을 내린다. Abstract: In order to maximize the effect of left ventricular assist device (LVAD) on ventricular unloading, the therapy should be begun at appropriate level of heart failure severity. We predicted pumping efficacy of LVAD according to the severity of heart failure theoretically. We used 3 dimensional finite element model of ventricle coupled with 6 Wind-kessel compartmental model of vascular system. Using the computational model, we predicted cardiac responses such as contractile ATP consumption of ventricle, left ventricular pressure, cardiac output, ejection fraction, and stroke work according to the severity of ventricular systolic dysfunction under the treatments of continuous LVAD. Contractile ATP consumption, which indicates the ventricular energetic loading condition decreased maximally at the 5

Intra-aortic balloon pump (IABP) is normally contraindicated in significant aortic regurgitation (AR). It causes and aggravates pre-existing AR while performing well in the event of mitral regurgitation (MR). Indirect parameters, such as the mean systolic pressure, product of heart rate and peak systolic pressure, and pressure-volume are used to quantify the effect of IABP on ventricular workload. However, to date, no studies have directly quantified the reduction in workload with IABP. The goal of this study is to examine the effect of IABP therapy on ventricular mechanics under valvular insufficiency by using a computational model of the heart. For this purpose, the 3D electromechanical model of the failing ventricles used in previous studies was coupled with a lumped parameter model of valvular regurgitation and the IABP-treated vascular system. The IABP therapy was disturbed in terms of reducing the myocardial tension generation and contractile ATP consumption by valvular regurgitation, particularly in the AR condition. The IABP worsened the problem of ventricular expansion induced as a result of the regurgitated blood volume during the diastole under the AR condition. The IABP reduced the LV stroke work in the AR, MR, and no regurgitation conditions. Therefore, the IABP helped the ventricle to pump blood and reduced the ventricular workload. In conclusion, the IABP partially performed its role in the MR condition. However, it was disturbed by the AR and worsened the cardiovascular responses that followed the AR. Therefore, this study computationally proved the reason for the clinical contraindication of IABP in AR patients.

The detection of alpha-fetoprotein (AFP) in plasma is important in the diagnosis of hepatocellular carcinoma (HCC) in humans. We developed a biosensor to detect AFP in HCC patient plasma and in a phosphate buffer saline (PBS) solution using a graphene field-effect transistor (G-FET). The G-FET was functionalized with 1-pyrenebutyric acid N-hydroxysuccinimide ester (PBASE) for immobilization of an anti-AFP antibody. AFP was detected by assessing the shift in the voltage of the Dirac point (&Delta, VDirac) after binding of AFP to the anti-AFP-immobilized G-FET channel surface. This anti-AFP-immobilized G-FET biosensor was able to detect AFP at a concentration of 0.1 ng mL&minus, 1 in PBS, and the detection sensitivity was 16.91 mV. In HCC patient plasma, the biosensor was able to detect AFP at a concentration of 12.9 ng mL&minus, 1, with a detection sensitivity of 5.68 mV. The sensitivity (&Delta, VDirac) depended on the concentration of AFP in either PBS or HCC patient plasma. These data suggest that G-FET biosensors could have practical applications in diagnostics.

Atrial fibrillation (AF) is related to mutations at the genetic level. This includes mutations in genes that encode KCNQ1, a subunit of the I Ks channel. Here, we investigate the mechanism of gain-of-function in I Ks towards the occurrence of AF. We used the Courtemanche–Ramirez–Nattel (CRN) human atrial cell model (Am J Physiol Heart Circ Physiol 275:H301–H321, 1998) and applied the modification proposed by Hasegawa et al. (Heart Rhythm 11:67–75, 2014) to fit the behavior of I Ks due to the G229D mutation in KCNQ1 under a heterozygous mutant form. This was incorporated into two-(2D) and three-dimensional (3D) tissue models, where the mutation sustained a reentrant wave. However, under the wild-type condition, the reentrant wave terminated before the end of our simulations (in 2D, the spiral wave terminated before 10 s, while in 3D, the spiral wave terminated before 13 s). Sustained reentry under the mutation conditions also resulted in a spiral wave breakup in the 3D model, which was sustained until the end of the simulation (20 s), indicating AF.

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

Wearable ubiquitous biomedical applications, such as ECG monitors, can generate dynamic noise as a person moves. However, the source of this noise is not clear. We postulated that the dynamic ECG noise has two causes: the change in displacement of the heart during motion and the change in the electrical impedance of the skin-gel interface due to motion-induced deformation of the skin-gel interface. Using a three-dimensional electrophysiological heart model coupled with a torso model, dynamic noise was simulated, while the displacement of the heart was changed in the vertical and horizontal directions, independently and while the skin-gel interface was deformed during motion. To determine the deformation rate of the skin and sol-gel layers, motion-induced deformation of the two layers was simulated using a three-dimensional finite element method.

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

Left ventricular-assist devices (LVADs) are used to supply blood to the body of patients with heart failure. Pressure unloading is greater for counter-pulsating LVADs than for continuous LVADs. However, several clinical trials have demonstrated that myocardial recovery is similar for both types of LVAD. This study examined the contractile energy consumption of the myocardium with continuous and counter-pulsating LVAD support to ascertain the effect of the different LVADs on myocardial recovery. We used a three-dimensional electromechanical model of canine ventricles, with models of the circulatory system and an LVAD. We compared the left ventricular peak pressure (LVPP) and contractile ATP consumption between pulsatile and continuous LVADs. With the continuous and counter-pulsating LVAD, the LVPP decreased to 46 and 10%, respectively, and contractile ATP consumption decreased to 60 and 50%. The small difference between the contractile ATP consumption of these two types of LVAD may explain the comparable effects of the two types on myocardial recovery.

Background/Aim: We previously developed the cold dialysate regeneration system (CDRS) for use in daily home hemodialysis (HD). This study evaluates the long-term efficacy of the CDRS using a mathematical method. Method: HD with the CDRS was simulated using a method that integrates the mass-transfer model and the dialyzer solute kinetics model with a newly proposed model of CDRS function. Results: We mathematically assessed the long-term efficacy of HD with the CDRS. The weekly treatment time required for HD with the CDRS was reduced significantly using the daily dialysis method; it required only an 11% longer treatment time to obtain the corrected equivalent renal clearance and a 14% shorter time for the standard Kt/V, compared with thrice weekly treatment with conventional HD. Conclusion: By developing a mathematical model to test the long-term efficacy of the new CDRS, we showed that HD with the CDRS is an efficient means of daily home hemodialysis therapy.

We evaluated the quantitative contribution of pulsatile flow to ultrafiltration (UF) in terms of fluid power, membrane stretch, and reduction of membrane layering. An in vitro comparison of the UF rate using pulsatile and roller pumps was performed with distilled water and bovine whole blood. The mean transmembrane pressure (TMPm) and UF rate were higher with the pulsatile pump for the same mean flow rate: 6.6 mm Hg and 21.1 mL/min higher on average for distilled water and 34.2 mm Hg and 31.4 mL/min higher on average for blood. The average UF rate was 8.4 mL/min higher with the pulsatile pump for the same TMPm with bovine blood. However, the relationship between the UF rate and the TMPm was independent of the flow configuration for distilled water. We showed that the higher UF rate in the pulsatile pump is mainly due to greater fluid power and reduction of membrane layering, while the membrane stretch was not an important factor.