F.J. Claydon

The potential gradient field created by epicardial defibrillation electrodes in dogs.

Knowledge of the potential gradient field created by defibrillation electrodes is important for the understanding and improvement of defibrillation. To obtain this knowledge by direct measurements, potentials were recorded from 60 epicardial, eight septal, and 36 right ventricular transmural electrodes in six open-chest dogs while 1 to 2 V shocks were given through defibrillation electrodes on the right atrium and left ventricular apex (RA. V) and on the right and left ventricles (RV .LV). The potential gradient field across the ventricles was calculated for these low voltages. Ventricular fibrillation was electrically induced, and ventricular activation patterns were recorded after delivering high-voltage shocks just below the defibrillation threshold. With the low-voltage shocks, the potential gradient field was very uneven, with the highest gradient near the epicardial defibrillation electrodes and the weakest gradient distant from the defibrillation electrodes for both RA. V and RV .LV combinations. The mean ratio of the highest to the lowest measured gradient over the entire ventricular epicardium was 19.4 +/- 8.1 SD for the RA. V combination and 14.4 +/- 3.4 for the RV .LV combination. For both defibrillation electrode combinations, the earliest sites of activation after unsuccessful shocks just below the defibrillation threshold were located in areas where the potential gradient was weak for the low-voltage shocks. We conclude that there is a markedly uneven distribution of potential gradients for epicardial defibrillation electrodes with most of the voltage drop occurring near the electrodes, the potential gradient field is significant because it determines where shocks fail to halt fibrillation, and determination of the potential gradient field should lead to the development of improved electrode locations for defibrillation.

A volume conductor model of the thorax for the study of defibrillation fields

The authors develop a physiologically realistic volume conductor model for calculating epicardial potentials during transthoracic stimulation. The objective of the study is to measure cardiac potentials during a transthoracic stimulus and compare the measurements to calculated epicardial potentials obtained from the model. The results for all four stimulus configurations (anterior-posterior, neck-waist, precordial, and right-left) on the torso consistently yield correlation coefficients of about 0.90 and RMS errors of 47% between calculated and measured epicardial potentials for a homogeneous torso. Incorporating the effects of the skeletal muscle layer improves the agreement, i.e., correlation coefficients increase to about 0.914 and RMS errors decrease to about 42%. At the same time, the lungs and heart have little influence on the agreement between measured and calculated epicardial potentials. The results of the study demonstrate the importance of the skeletal muscle layer in physiologically realistic volume conductor models.<<ETX>>

Defibrillation Efficacy of Different Electrode Placements in a Human Thorax Model

The objective of this study was to measure the defibrillation threshold (DFT) associated with different electrode placements using a three‐dimensional anatomically realistic finite element model of the human thorax. Coil electrodes (Endotak DSP, model 125, Guidant/CPI) were placed in the RV apex along the lateral wall (RV), withdrawn 10 mm away from the RV apex along the lateral wall (RVprox), in the RV apex along the anterior septum (RVseptal), and in the SVC. An active pulse generator (can) was placed in the subcutaneous prepectoral space. Five electrode configurations were studied: RV → SVC, RVprox→ SVC, RVSEPTAL→SVC, RV →Can, and RV →SVC+Can. DFTs are defined as the energy required to produce a potential gradient of at least 5 V/cm in 95% of the ventricular myocardium. DFTs for RV → SVC, RVPROX→ SVC, RVseptal→ SVC, RV → Can, and RV → SVC + Can were 10, 16, 7, 9, and 6 J, respectively. The DFTs measured at each configuration fell within one standard deviation of the mean DFTs reported in clinical studies using the Endotak leads. The relative changes in DFT among electrode configurations also compared favorably. This computer model allows measurements of DFT or other defibrillation parameters with several different electrode configurations saving time and cost of clinical studies.

Measurement of defibrillation shock potential distributions and activation sequences of the heart in three dimensions

The authors note that knowledge of the extracellular potential gradient field of the defibrillation shock and the cardiac-tissue response to the shock should lead to better understanding of the mechanism of defibrillation and stimulate improvement of defibrillation techniques. By measuring the potential distribution of the defibrillation shock throughout the heart and the location of the recording electrodes, the potential gradient field may be calculated. By recording local electrograms throughout the heart immediately before and after the shock, the tissue response to the shock can be evaluated. >

Classification of Heart Tissue from Bipolar and Unipolar Intramural Potentials

The purpose of this study is to evaluate how well bipolar and intramural potentials are able to classify the state of the myocardium (normal or infarcted) proximal to the electrode recording sites. Nine mongrel dogs with anterior myocardial infarcts were used to generate a database for the study. Classification of the myocardium as normal or infarcted was attempted from potentials recorded in and around the infarcted region using electrodes within plunge needles. In addition to the potentials, the database contains the locations of the plunge needles, the grossly visible borders of the infarcts, and the epicardium and endocardium of both ventricles.

Membrane polarization induced in the myocardium by defibrillation fields: an idealized 3-D finite element bidomain/monodomain torso model

This study develops a three-dimensional finite element torso model with bidomain myocardium to simulate the transmembrane potential (TMP) of the heart induced by defibrillation fields. The inhomogeneities of the torso are modeled as eccentric spherical volumes with both the curvature and the rotation features of cardiac fibers incorporated in the myocardial region. The numerical computation of the finite element bidomain myocardial model is validated by a semianalytic solution. The simulations show that rotation of fiber orientation through the depth of the myocardial wall changes the pattern of polarization and decreases the amount of cardiac tissue polarized compared to the idealized analytic model with no fiber rotation incorporated. The TMP induced by transthoracic and transvenous defibrillation fields are calculated and visualized. The TMP is quantified by a continuous measure of the percentage of myocardial mass above a potential gradient threshold. Using this measure, the root mean square differences in TMP distribution produced by reversing the electrode polarity for anterior-posterior and transvenous electrode configurations are 13.6 and 28.6%, respectively. These results support the claim that a bidomain model of the heart predicts a change of defibrillation threshold with reversed electrode polarity.

Effects of myocardial infarction on cardiac electrical field properties using a numerical expansion technique.

This study was undertaken to quantify basic cardiac electrical field properties using the Karhounen-Loeve (K-L) numerical expansion technique after experimental myocardial infarction. Transmural anterior myocardial infarction was produced in seven dogs by injection of liquid latex into the anterior descending artery; posterior myocardial infarction was produced in five dogs by injection of the circumflex artery. Body surface potentials from 84 electrodes were recorded during sinus rhythm prior to and 1 week after infarction. Electrical field properties during the QRS, ST, and QRST intervals were computed by the K-L method based upon areas calculated for each lead. The ratio of the sum of magnitude of the first three eigenvectors to the sum of all computed eigenvectors expressed as a percentage was used as a measure analogous to field dipolarity. Values before infarction were high during the QRS (97.1% +/- 2.0%, mean +/- 1SD), ST (96.0% +/- 5.1%), and QRST (97.7% +/- 2.7%) intervals, with no significant difference between the three periods. After infarction, the ratio during QRS decreased significantly, with lower values after posterior (61.9% +/- 11.7%) than after anterior (91.1% +/- 6.0%) infarction (p less than 0.001). Values during ST and QRST intervals were not significantly changed by infarction. Spatial patterns of the first eigenvector indicated that the derived QRS area electric field is directed away from the myocardial lesion for both anterior and posterior infarcts. Thus, experimental myocardial infarction produces significant changes in cardiac electrical field properties as measured by the K-L technique.

Extracting isovolumes from three-dimensional torso geometry using PROLOG

Three-dimensional (3D) finite element torso models are widely used to simulate defibrillation field quantities, such as potential, gradient and current density. These quantities are computed at spatial nodes that comprise the torso model. These spatial nodes typically number between 10/sup 5/ and 10/sup 6/, which makes the comprehension of torso defibrillation simulation output difficult. Therefore, the objective of this study is to rapidly prototype software to extract a subset of the geometric model of the torso for visualization in which the nodal information associated with the geometry of the model meets a specified threshold value (e.g., minimum gradient). The data extraction software is implemented in PROLOG, which is used to correlate the coordinate, structural and nodal data of the torso model. A PROLOG-based environment has been developed and is used to rapidly design and test new methods for sorting, collecting and optimizing data extractions from defibrillation simulations in a human torso model for subsequent visualization.

Effects of cardiac anisotropy on modeling transvenous defibrillation in the human thorax

The objective of this study is to determine the effects of cardiac tissue anisotropy on transvenous defibrillation fields in a human torso model. The study is implemented with a physiologically realistic 3-D finite element model of the human thorax. The model computes potential and potential gradient distributions within the heart from a knowledge of defibrillation shock strength, defibrillation electrode location, and the relative conductivities of the interior thorax. Coil electrodes were placed in the right ventricular cavity and the superior vena cava. Results are compared between a model with an isotropic myocardium and a model with an anisotropic myocardium. Comparison of the potential and potential gradient distributions within the myocardium between the isotropic and anisotropic models yielded root mean square errors of 4.9% and 19.%, respectively, and correlation coefficients of 0.999 and 0.981, respectively. These results indicate that cardiac anisotropy and fiber orientation do not significantly affect transvenous defibrillation fields.

Spatial effects from bipolar current injection in 3D myocardium: implications for conductivity measurements

This study aims at predicting the spatial extent of the polarization in myocardium (surface and in-depth patterns) resulting from bipolar current injection. The three-dimensional effects resulting from transmural fiber rotation and unequal anisotropy ratio for the intra- and extracellular domain are modeled using a 3D finite element bidomain model. Circular current and voltage electrodes with different radii and distance between them are considered. The authors assess the accuracy of the idealized models, applied in combination with the four electrode technique for interpretation of conductivity measurements in myocardium, in the presence of transmural rotation. Based on the spatial sensitivity of the extracellular and transmembrane potential fields to the underlying conductivity tensors the authors recommend an alternative placement of the sensing electrodes for standard electrical or optical measurements.