Statistical accuracy of a moving equivalent dipole method to identify sites of origin of cardiac electrical activation

While radio frequency (RF) catheter ablation (RCA) procedures for treating ventricular arrhythmias have evolved significantly over the past several years, the use of RCA has been limited to treating slow ventricular tachycardias (VTs). In this paper, we present preliminary results from computer and animal studies to evaluate the accuracy of an algorithm that uses the single equivalent moving dipole (SEMD) model in an infinite homogeneous volume conductor to guide the RF catheter to the site of origin of the arrhythmia. Our method involves measuring body surface electrocardiographic (ECG) signals generated by arrhythmic activity and by bipolar current pulses emanating from a catheter tip, and representing each of them by a SEMD model source at each instant of the cardiac cycle, thus enabling rapid repositioning of the catheter tip requiring only a few cycles of the arrhythmia. We found that the SEMD model accurately reproduced body surface ECG signals with a correlation coefficients > 0.95. We used a variety of methods to estimate the uncertainty of the SEMD parameters due to measurement noise and found that at the time when the arrhythmia is mostly localized during the cardiac cycle, the estimates of the uncertainty of the spatial SEMD parameters (from ECG signals) are between 1 and 3 mm. We used pacing data from spatially separated epicardial sites in a swine model as surrogates for focal ventricular arrhythmic sources and found that the spatial SEMD estimates of the two pacing sites agreed with both their physical separation and orientation with respect to each other. In conclusion, our algorithm to estimate the SEMD parameters from body surface ECG can potentially be a useful method for rapidly positioning the catheter tip to the arrhythmic focus during an RCA procedure.     

Mechanism of Abnormal Sarcoplasmic Reticulum Calcium Release in Canine Left-Ventricular Myocytes Results in Cellular Alternans

Electrocardiographic alternans are known to predispose to increased susceptibility to life threatening arrhythmias and sudden cardiac death. While deficiencies in Ca²⁺ transport processes have been implicated in the genesis of cellular alternans, the underlying mechanisms have been elusive, and are the goal of this study. A novel reverse engineering approach that applies a simultaneous action potential (AP) and [Ca²⁺ ]i clamp of experimentally obtained data, to a previously described left-ventricular canine myocyte model, is employed to isolate the molecular and cellular mechanisms underlying cardiac alternans. The model-derived sarcoplasmic reticulum (SR) Ca²⁺ in control beats (102.1 plusmn 12.9 nM, n = 639 ), although larger, is not statistically significantly different as compared to beats corresponding to small [Ca²⁺ ]_i (99.3 plusmn 35.4 nM, n = 310, p = NS), but is significantly smaller as compared to beats corresponding to large [Ca²⁺ ]_i (122.6 plusmn 31.0 nM, n = 311, p<0.000001) during alternans. The model indicates that the increased SR Ca²⁺ in these beats triggers multiple ryanodine receptor (RyR) channel openings and delayed Ca²⁺ release that subsequently triggers an inward depolarizing current, a subthreshold early after depolarization, and AP prolongation. In conclusion, the results presented in this study support the idea that aberrant RyR openings on alternate beats are responsible for the [Ca²⁺ ]_i alternans-type oscillations, which, in turn, give rise to AP alternans.     

Linear and nonlinear system identification of autonomic heart-ratemodulation

The authors' findings show that system identification provides a useful, noninvasive, and quantitative means for evaluating cardiovascular regulatory mechanisms. With combinations of linear and nonlinear identification, new insights about the cardiovascular regulatory dynamics were obtained. System identification provides a new way of studying and monitoring cardiovascular function. Instead of just studying the signals generated by the cardiovascular regulatory system, the signals are analyzed to characterize quantitatively the mechanisms that generate them. System identification is a type of “inverse modeling”in which the physiologic signals are used to create a model of cardiovascular regulation for the specific individual from whom the data are obtained. As such, system identification would appear to be a desirable means for evaluating effects of physiologic alterations resulting from pharmacological interventions, changes in environment such as changes in gravitational field, physiologic stresses such as hypoxia and exercise, and disease processes. System identification may also prove to be an attractive means to study closed-loop regulation in other physiologic systems, ranging in size from biochemical pathways to intact multi-organ systems