Cuiwei Yang

Investigation of Atrial Vulnerability by Analysis of the Sinus Node EG From Atrial Fibrillation Models Using a Phase Synchronization Method

Atrial fibrillation (AF) can result in life-threatening arrhythmia, and a clinically convenient means for detecting vulnerability remains elusive. We investigated atrial vulnerability by analyzing the sinus electrogram (EG) from AF animal models using a phase synchronization method. Using acetylcholine (ACh)-induced acute canine AF models (n = 4), a total of 128 electrical leads were attached to the surface of the anterior and posterior atria, and the pulmonary veins to form an electrocardiological mapping system. ACh was injected at varying concentrations with ladder-type adjustments. Sinus EGs and induced AF EGs that pertain to specific ACh concentrations were recorded. We hypothesize that the atrial vulnerability may be correlated with the Shannon entropy (SE) of the phase difference matrix that is extracted from the sinus EG. Our research suggests that the combination of SE with the synchronization method enables the sinus node EG to be analyzed and used to estimate atrial vulnerability.

Implementation of a novel interpolating method to epicardial potential mapping for atrial fibrillation study

Epicardial potential mapping is an efficient way to visualize the potential distribution on the epicardial surface. We found in our previous study, that the traditional linear interpolation used for the epicardial mapping may cause errors and distortions in reconstruction of the electric activities on the epicardial surface especially during the atrial fibrillation. In this study, we devoted on the implementation of a 3D interpolating method, and verified it in comparison with another interpolating method as well as studying of the mechanism of vagal atrial fibrillation (AF). In case studying, we analyzed the epicardial data from seven canine cardiac models using this method and found the macro-re-entry during the sustainable AF is more likely due to the dispersion of refractoriness in the myocardium and does not demonstrated the focal patterns at the beginning of AF. This indicated that the electrophysiological characteristics of myocardium might have been changed during the paroxysmal atrial fibrillation (PAF).

Analysis of epicardial mapping electrogram of sustained atrial fibrillation based on shannon entropy

The mechanisms of sustained atrial fibrillation (AF) are not well understood. And predicting the development of AF is a problem of great clinical interest. This paper proposed an AF analysis method by evaluating, based on Shannon entropy, the complexity of atrial activation in various AF stages. The first step was to preprocess and characterize electrograms. Then, Shannon entropy analysis and statistical analysis were applied to find the significance of interval entropy in sustained AF. Study results proved that interval entropy presented a degressive tendency in the process of sustained AF and some sites with high activation frequency but low entropy was possibly related to ectopic driver of AF.

Decreasing the Defibrillation Energy by Optimizing the Pulse Duration of Electrical Shock

Low energy defibrillation can not only save the power of the device (especially the ICD) but also lighten the damage to the patients. This paper investigates the method to decrease the defibrillation energy by optimizing the pulse duration of electrical shock. The defibrillation threshold is one of the main parameter to evaluate the defibrillation dosage. In this paper, the defibrillation threshold corresponding to the pulse duration is analysed and studied through 7 animal trails by an appropriative defibrillator designed by ourselves.The defibrillation thresholds are changing along with the changing of the pulse duration and existing optimal pulse duration that corresponding to the lowest defibrillation threshold. Although this optimal pulse duration is not so steady under different conditions in our animal trails but it showed a nice possibility to decrease the defibrillation energy by optimizing the pulse duration.

Development of Epicardial Mapping System for Studying Atrial Fibrillation

Epicardial mapping system is an important tool for studying electrophysiological characteristics of atrial fibrillation (AF). AF is the most common arrhythmia and is becoming more prevalent each year. Most in vivo experimental research on AF is performed by simultaneous epicardial mapping technique. An epicardial mapping system is developed to record electrical activities from 128 sites at the same time, with a spacing of 3.5-5.0 mm. The initial purpose of this research is to display the electrical signals on the whole-atrial epicardial surface and store these data for subsequent analysis. 128 unipolar electrodes arranged in eight flexible patches were adopted to detect signal on the surface of whole atrium. Each electrode patch was designed to adaptable to the corresponding epicardial surface of canine atrium. The system contained an amplifier with 128 isolated channels and a data acquisition card based on USB communication. Random acquisition duration of interested data during sinus or AF rhythm could be recorded. Animal tests were operated on four mongrel dogs, in which two were models of chronic AF. Result shows that this system can perform successfully in a surgical setting. This system may be a special and portable tool for whole-atrium epicardial mapping and therefore useful for studying AF.

A New System for Whole-atrial Epicardial Mapping

Epicardial mapping system is an important tool in the study and treatment of cardiac arrhythmias. Surgical therapy has been applied to eliminate atrial fibrillation (AF) for almost two decades, but there is still little effect on the treatment of AF in respect that the mechanism of AF is still unknown. Further investigation into the electrophysiological properties in AF is required to develop an appropriate treatment, though radiofrequency ablation has opened the new era of therapies for AF. Nevertheless, the sequential epicardial mapping for whole-atrium will increase the benefit to understand electrical mechanism during AF. The purpose of our research is to detect the electrical activity on the atrial surface and therefore find the optimal technique or ablation procedures to prevent AF. Animal tests were operated on ten dogs in which chronic AF had been induced. In experiment whole-atrial electrodes were located on the atrial surface after the heart had been exposed. Fach 20-second sampling data during sinus or atrial fibrillation rhythm were recorded and stored for analysis. Three-dimensional dynamic maps are presented clearly and the activity of sinus or AF rhythm can be seen quite differently. The active isopotential map can display the dynamic electrical conduction of the atria as a movie. This study demonstrates the flexibility of the system in AF research

Predicting atrial fibrillation inducibility in a canine model by multi-threshold spectra of the recurrence complex network

The purpose of this study is to predict atrial fibrillation (AF) from epicardial signals by investigating the recurrence property of atrial activity dynamic system before AF. A novel scheme is proposed to predict AF by using multi-threshold spectra of the recurrence complex network. Firstly, epicardial signals are transformed into the recurrence complex network to quantify structural properties of the recurrence in the phase space. Spectral parameters with multi-threshold are used to characterize the global structure of the network. Then the feature sequential forward searching algorithm and mutual information based Maximum Relevance Minimum Redundancy criterion are used to find the optimal feature set. Finally, a support vector machine is used to predict the occurrence of AF. This method is assessed on the pre-AF epicardial signals of canine which includes the normal group A (no further AF will happen), the mild group B (the following AF time is less than 180s) and the severe group C (the following AF time is more than 180s). 25 optimal features are selected out of 180 features from each sample. With these features, sensitivity, specificity and accuracy are 99.40%, 99.70% and 99.60%, respectively, which are the best among the recurrence based methods. The results suggest that the proposed method can predict AF accurately and thus can be prospectively used in the postoperative evaluation.

Dynamic Epicardial Mapping Using 3D Emulation

Dynamic epicardial mapping is an important tool in cardiac electrophysiology. This article brings forward a method for 3D dynamic modeling used in epicardial mapping system. Firstly, 3DMAX was used to create a 3D heart model and an .ase file was stored. Secondly, OpenGL was applied to display this model in users window interface. When electrodes and amplifiers sampled new data, the electrode which had the minimum euler distance to each vertex of 3D model was calculated, thus an interpolate triangle was formed by combining another two adjacent electrodes. The voltage value of each vertex was obtained by using a new linear interpolation based on grads calculation. This method was proved to be feasible in animal experiments. Electrical activity could be investigated directly in a cardiac cycle through this 3D model. This model can also reflect the conduction process of depolarization in complex arrhythmia such as atrial fibrillation. This method is appropriate for any real-time 3D dynamic field modeling, which has an array of regular measure points.

The 64/176-channel epicardial mapping system used in basic research and clinic diagnoses the complex arrhythmias

When heart is in ventricular fibrillation or atrial fibrillation, its electrical activities are very complex not only on spatial distribution but also on temporal variation. It is very difficult to find out its rules by traditional points by points mapping method. The 64/176-channel epicardial mapping system developed by Fudan University can be used to study the complex arrhythmias and has acquired some interesting results from the animal trials.

A preliminary study on atrial epicardial mapping signals based on Graph Theory

In order to get a better understanding of atrial fibrillation, we introduced a method based on Graph Theory to interpret the relations of different parts of the atria. Atrial electrograms under sinus rhythm and atrial fibrillation were collected from eight living mongrel dogs with cholinergic AF model. These epicardial signals were acquired from 95 unipolar electrodes attached to the surface of the atria and four pulmonary veins. Then, we analyzed the electrode correlations using Graph Theory. The topology, the connectivity and the parameters of graphs during different rhythms were studied. Our results showed that the connectivity of graphs varied from sinus rhythm to atrial fibrillation and there were parameter gradients in various parts of the atria. The results provide spatial insight into the interaction between different parts of the atria and the method may have its potential for studying atrial fibrillation.