Deriving the Bidomain Model of Cardiac Electrophysiology From a Cell-Based Model; Properties and Comparisons

The bidomain model is considered to be the gold standard for numerical simulation of the electrophysiology of cardiac tissue. The model provides important insights into the conduction properties of the electrochemical wave traversing the cardiac muscle in every heartbeat. However, in normal resolution, the model represents the average over a large number of cardiomyocytes, and more accurate models based on representations of all individual cells have therefore been introduced in order to gain insight into the conduction properties close to the myocytes. The more accurate model considered here is referred to as the EMI model since both the extracellular space (E), the cell membrane (M) and the intracellular space (I) are explicitly represented in the model. Here, we show that the bidomain model can be derived from the cell-based EMI model and we thus reveal the close relation between the two models, and obtain an indication of the error introduced in the approximation. Also, we present numerical simulations comparing the results of the two models and thereby highlight both similarities and differences between the models. We observe that the deviations between the solutions of the models become larger for larger cell sizes. Furthermore, we observe that the bidomain model provides solutions that are very similar to the EMI model when conductive properties of the tissue are in the normal range, but large deviations are present when the resistance between cardiomyocytes is increased.

Wavelet Packet Analysis of ECG Signals to Understand the Effect of Cannabis Abuse on Cardiac Electrophysiology of Indian Women Working in Paddy Fields

This chapter is aimed at identifying the variation in the cardiac electrophysiology due to the abuse of the cannabis products (bhang) in a non-invasive manner. ECG signals were acquired from 25 Indian women working in the paddy fields. Amongst them, 10 women regularly abused bhang and the rest 15 women never abused bhang. The ECG signals were preprocessed and subjected to wavelet packet decomposition (WPD) up to the level 3 using db04 wavelet. Ninety-six statistical features were extracted from the wavelet packet coefficients and analyzed using linear and non-linear statistical methods. The results suggested a variation in the cardiac electrophysiology due to the abuse of bhang. Artificial neural networks (ANNs), namely, radial basis function (RBF) and multilayer perceptron (MLP) were able to classify the ECG signals with an accuracy of ≥95%. This supported the hypothesis that abuse of bhang may alter the cardiac electrophysiology. The results of the study may be used to increase awareness among people to avoid the abuse of cannabis products.

Shared Decision-Making in Cardiac Electrophysiology Procedures and Arrhythmia Management

Shared decision-making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision-making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.

35 Electrophysiology and electrostimulation: experience

In the last 50 years, cardiac electrophysiology has undergone rapid technological development which has led to a numerical increase in both patients who have been able to benefit from the therapies of rediscovery and rhythm control, and of the devices. The activity of an electrophysiology and electrostimulation room is based on the intensive use of ionizing radiation even if electrophysiology studies, ablation, and cryoablation techniques have benefited from the support of computerized electroanatomical mapping systems with consequent dose reduction. Over the years, the instruments to be managed inside the room have increased both in complexity and numerically. Starting from the biventricular PM, we go through the implantation of subcutaneous defibrillators up to the transseptal ablations. Patient management requires additional skills that each member of the team must possess. Continuous training and updates are of fundamental importance. The purpose of this work is our experience based on the activity now more 10 years.

Safe electrophysiologic profile of dexmedetomidine in different experimental arrhythmia models

Previous studies suggest an impact of dexmedetomidine on cardiac electrophysiology. However, experimental data is sparse. Therefore, purpose of this study was to investigate the influence of dexmedetomidine on different experimental models of proarrhythmia. 50 rabbit hearts were explanted and retrogradely perfused. The first group (n = 12) was treated with dexmedetomidine in ascending concentrations (3, 5 and 10 µM). Dexmedetomidine did not substantially alter action potential duration (APD) but reduced spatial dispersion of repolarization (SDR) and rendered the action potentials rectangular, resulting in no proarrhythmia. In further 12 hearts, erythromycin (300 µM) was administered to simulate long-QT-syndrome-2 (LQT2). Additional treatment with dexmedetomidine reduced SDR, thereby suppressing torsade de pointes. In the third group (n = 14), 0.5 µM veratridine was added to reduce the repolarization reserve. Further administration of dexmedetomidine did not influence APD, SDR or the occurrence of arrhythmias. In the last group (n = 12), a combination of acetylcholine (1 µM) and isoproterenol (1 µM) was used to facilitate atrial fibrillation. Additional treatment with dexmedetomidine prolonged the atrial APD but did not reduce AF episodes. In this study, dexmedetomidine did not significantly alter cardiac repolarization duration and was not proarrhythmic in different models of ventricular and atrial arrhythmias. Of note, dexmedetomidine might be antiarrhythmic in acquired LQT2 by reducing SDR.