Jack M. Rogers

Estimation of conduction velocity vector fields from epicardial mapping data

An automated method to estimate vector fields of propagation velocity from observed epicardial extracellular potentials is introduced. The method relies on fitting polynomial surfaces T(x,y) to the space-time (x,y,t) coordinates of activity, Both speed and direction of propagation are computed from the gradient of the local polynomial surface. The components of velocity, which are total derivatives, are expressed in terms of the partial derivatives which comprise the gradient of T. The method was validated on two-dimensional (2-D) simulations of propagation and then applied to cardiac mapping data. Conduction velocity was estimated at multiple epicardial locations during sinus rhythm, pacing, and ventricular fibrillation (VF) in pigs. Data were obtained via a 528-channel mapping system from 23/spl times/22 and 24/spl times/21 arrays of unipolar electrodes sutured to the right ventricular epicardium. Velocity estimates are displayed as vector fields and are used to characterize propagation qualitatively and quantitatively during both simple and complex rhythms.

Incidence, Evolution, and Spatial Distribution of Functional Reentry During Ventricular Fibrillation in Pigs

Functional reentry has been hypothesized to be an underlying mechanism of ventricular fibrillation (VF); however, its contribution to activation patterns during fully developed VF is unclear. We applied new quantitative pattern analysis techniques to mapping data acquired from a 21 x 24 unipolar electrode array (2-mm spacing) located on the ventricular epicardium of 7 open-chest, unsupported pigs. Data epochs 4 seconds long beginning 1, 10, 20, 30, and 40 seconds after electrical induction were analyzed. Reentrant circuits were automatically identified and quantified. We found that 2.3% of activation pathways could unambiguously be classified as reentrant. From scaling analysis, an additional 28% of the pathways may also have been reentrant. Reentry was short-lived with 1.5+/-1.5 (mean+/-SD) complete cycles per circuit. The fraction of reentrant pathways, number of cycles per circuit, cycle duration, and area and perimeter of the cores all increased significantly as VF progressed. Core drift speed decreased significantly. Neither the orientation of the cores nor the direction of drift was well predicted by the epicardial fiber orientation (r2=0.108 and 0.138, respectively, by linear regression). Reentrant circuits were clustered in regions of the epicardium. We conclude the following: (1) Epicardial reentry is relatively uncommon and short-lived during VF, suggesting either that sustained reentry is transmural or that mechanisms governing sustained reentry are relatively unimportant to the dynamics of VF. (2) Reentrant circuits become more common, larger, and longer-lived as VF progresses, which may explain a recently observed increase in VF organization during the first minute of VF. (3) The conditions necessary to induce and sustain reentry are distributed nonuniformly.

Evolution of activation patterns during long-duration ventricular fibrillation in pigs

Quantitative analysis has demonstrated five temporal stages of activation during the first 10 min of ventricular fibrillation (VF) in dogs. To determine whether these stages exist in another species, we applied the same analysis to the first 10 min of VF recorded in vivo from two 504-electrode arrays, one each on left anterior and posterior ventricular epicardium in six anesthetized pigs. The following descriptors were continuously quantified: 1) number of wavefronts, 2) wavefront fractionations, 3) wavefront collisions, 4) repeatability, 5) multiplicity index, 6) wavefront conduction velocity, 7) activation rate, 8) mean area activated by the wavefronts, 9) negative peak rate of voltage change, 10) incidence of breakthrough/foci, 11) incidence of block, and 12) incidence of reentry. Cluster analysis of these descriptors divided VF into four stages (stages i-iv). The values of most descriptors increased during stage i (1-22 s after VF induction), changed quickly to values indicating greater organization during stage ii (23-39 s), decreased steadily during stage iii (40-187 s), and remained relatively unchanged during stage iv (188-600 s). The epicardium still activated during stage iv instead of becoming silent as in dogs. In conclusion, during the first 10 min, VF activation can be divided into four stages in pigs instead of five stages as in dogs. Following a 16-s period during the first minute of VF when activation became more organized, all parameters exhibited progressive decreased organization. Further studies are warranted to determine whether these changes, particularly the increased organization of stage ii, have clinical consequences, such as alteration in defibrillation efficacy.

Phase Mapping of Cardiac Fibrillation

Received January 25, 2009; accepted October 6, 2009. Phase is a descriptor that tracks the progression of a defined region of myocardium through the action potential and has been demonstrated to be an effective parameter in analyzing spatiotemporal changes during fibrillation. In this review, the basic principles behind phase mapping are presented mainly in the context of ventricular fibrillation (VF), atrial fibrillation (AF), and fibrillation from experimental monolayer data. During fibrillation, the phase distribution changes over time, depending on activation patterns. Analyzing these phase patterns provides us insight into the fibrillatory dynamics and helps clarify the mechanisms of cardiac fibrillation and modulation by interventions. Winfree1 introduced the phase analysis to study cardiac fibrillation in the late eighties. This time-encoding technique deals with a scenario where the activation periods are the same over the surface being mapped. To deal with the scenario of varying activation period over the mapped surface (common in animal and human fibrillation models), Gray et al2,3⇓ introduced the state-space encoding concept from nonlinear dynamics. In analyzing spatiotemporal phase maps constructed from electric or optical mapping of the surface of heart during VF, points around which the phase progresses through a complete cycle from −π to +π are of great interest. At these points, the phase becomes indeterminate and the activation wave fronts hinge to these points and rotate around them in an organized fashion. These points in the phase map are called phase singularity (PS) points. Bray et al4 developed a procedure to locate PS points in a phase map. Nash et al5 used phase mapping to study the entire ventricular epicardium of human hearts with a sock containing 256 unipolar contact electrodes. The development of this phase mapping tool has led to better understanding of fibrillation dynamics as evidenced by the …

Activation Patterns of Purkinje Fibers During Long-Duration Ventricular Fibrillation in an Isolated Canine Heart Model

Background— The roles of Purkinje fibers (PFs) and focal wave fronts, if any, in the maintenance of ventricular fibrillation (VF) are unknown. If PFs are involved in VF maintenance, it should be possible to map wave fronts propagating from PFs into the working ventricular myocardium during VF. If wave fronts ever arise focally during VF, it should be possible to map them appearing de novo. Methods and Results— Six canine hearts were isolated, and the left main coronary artery was cannulated and perfused. The left ventricular cavity was exposed, which allowed direct endocardial mapping of the anterior papillary muscle insertion. Nonperfused VF was induced, and 6 segments of data, each 5 seconds long, were analyzed during 10 minutes of VF. During 36 segments of data that were analyzed, 1018 PF or focal wave fronts of activation were identified. In 534 wave fronts, activation was mapped propagating from working ventricular myocardium to PF. In 142 wave fronts, activation was mapped propagating from PF to working ventricular myocardium. In 342 wave fronts, activation was mapped arising focally. More than 1 of these 3 patterns could occur in the same wave front. Conclusions— PFs are highly active throughout the first 10 minutes of VF. In addition to retrograde propagation from the working ventricular myocardium to PFs, antegrade propagation occurs from PFs to working ventricular myocardium, which suggests PFs are important in VF maintenance. Prior plunge needle recordings in dogs indicate activation propagates from the endocardium toward the epicardium after 1 minute of VF, which suggests that focal sites on the endocardium may represent foci and not breakthrough. If so, in addition to reentry, abnormal automaticity or triggered activity may also occur during VF.

Recurrent wavefront morphologies: A method for quantifying the complexity of epicardial activation patterns

We have developed a method for quantifying the complexity of activation patterns observed during ventricular fibrillation (VF) that is based on our previously reported methodology for decomposing epicardial mapping data into a set of isolated wavefronts. One-half second datasets are acquired from a 21×24 array of unipolar electrodes (1 mm spacing), and the wavefronts are isolated. A correlation technique is used to compute the similarity between all possible pairs of the isolated wavefronts. From these data, the wavefronts are sorted into clusters, each of which represents a recurring wavefront morphology. We define multiplicity (M) as the number of clusters needed to account for 90% of the total activations in the VF episode.M measures the complexity of the rhythm. In repetitive patterns (e.g., sinus rhythm),M=1, indicating that the same morphology repeatedly activates the mapped region. Typically, in VF,M>1, with larger numbers representing more complex, disorganized patterns. As an example, we computedM at 5, 10, 15, and 20 sec after electrical induction of VF in six pigs.M decreased significantly (p<0.001), suggesting increasing organization during this period.

Chemical ablation of the Purkinje system causes early termination and activation rate slowing of long-duration ventricular fibrillation in dogs

Endocardial mapping has suggested that Purkinje fibers may play a role in the maintenance of long-duration ventricular fibrillation (LDVF). To determine the influence of Purkinje fibers on LDVF, we chemically ablated the Purkinje system with Lugol solution and recorded endocardial and transmural activation during LDVF. Dog hearts were isolated and perfused, and the ventricular endocardium was exposed and treated with Lugol solution (n = 6) or normal Tyrode solution as a control (n = 6). The left anterior papillary muscle endocardium was mapped with a 504-electrode (21 x 24) plaque with electrodes spaced 1 mm apart. Transmural activation was recorded with a six-electrode plunge needle on each side of the plaque. Ventricular fibrillation (VF) was induced, and perfusion was halted. LDVF spontaneously terminated sooner in Lugol-ablated hearts than in control hearts (4.9 +/- 1.5 vs. 9.2 +/- 3.2 min, P = 0.01). After termination of VF, both the control and Lugol hearts were typically excitable, but only short episodes of VF could be reinduced. Endocardial activation rates were similar during the first 2 min of LDVF for Lugol-ablated and control hearts but were significantly slower in Lugol hearts by 3 min. In control hearts, the endocardium activated more rapidly than the epicardium after 4 min of LDVF with wave fronts propagating most often from the endocardium to epicardium. No difference in transmural activation rate or wave front direction was observed in Lugol hearts. Ablation of the subendocardium hastens VF spontaneous termination and alters VF activation sequences, suggesting that Purkinje fibers are important in the maintenance of LDVF.

A quantitative framework for analyzing epicardial activation patterns during ventricular fibrillation

Few techniques have been developed for deriving quantitative measures of activation patterns during ventricular fibrillation (VF). Such measures have many potential applications, for example, assessing the effects of time, drugs, or electrical interventions. We have developed a new framework for quantifying VF patterns as mapped from an array of ≈500 unipolar electrodes. Individual activation wavefronts are isolated from one another using an algorithm that groups together adjacent active electrogram samples (dV/dt <−0.5 V/sec). Contacts between wavefronts are detected; these include fractionations, in which a single wavefront breaks into multiple wavefronts, and collisions, in which multiple wavefronts coalesce to form a new wavefront. The timing and contact relationships between wavefronts are summarized as a directed graph. From this model of the VF episode, we derive several parameters: number of wavefronts number of fractionations, number of collisions, mean wavefront size, mean area swept out, and mean duration. As an example of this analysis, we computed these parameters in six open-chest pigs at 5, 10, 15, and 20 sec after electrical induction of VF. The number of wavefronts and the number of collisions decreased, whereas the mean wavefront size and mean area swept out increased during this period. These results are consistent with previous studies showing a recovery of organization during the first minute of VF.

Locally Propagated Activation Immediately After Internal Defibrillation

BACKGROUND Electrical mapping studies indicate an interval of 40 to 100 ms between a defibrillation shock and the earliest activation that propagates globally over the ventricles (globally propagated activation, GPA). This study determined whether activation occurs during this interval but propagates only locally before being blocked (locally propagated activation, LPA). METHODS AND RESULTS In five anesthetized pigs, the heart was exposed and a 504-electrode sock with 4-mm interelectrode spacing was pulled over the ventricles. Ten biphasic shocks of a strength near the defibrillation threshold (DFT) were delivered via intracardiac catheter electrodes, and epicardial activation sequences were mapped before and after attempted defibrillation. Local activation was defined as dV/dt < or =-0.5 V/s. Postshock activation times and wave-front interaction patterns were determined with an animated display of dV/dt at each electrode in a computer representation of the ventricular epicardium. LPAs were observed after 40 of the 50 shocks. A total of 173 LPA regions were observed, each of which involved 2+/-2 (mean+/-SD) electrodes. LPAs were observed after both successful and failed shocks but occurred earlier (P<.0001) after failed (35+/-8 ms) than successful (41+/-16 ms) shocks, although the times at which the GPA appeared were not significantly different. On reaching the LPA region, the GPA front either propagated through it (n=135) or was blocked (n=38). The time from the onset of the LPA until the GPA front propagated to reach the LPA region was shorter (P<.01) when the GPA front was blocked (32+/-12 ms) than when it propagated through the LPA region (63+/-20 ms). CONCLUSIONS LPAs exist after successful and failed shocks near the DFT. Thus, the time from the shock to the GPA is not totally electrically silent.

Three-dimensional surface reconstruction and panoramic optical mapping of large hearts

Optical mapping of electrical activity from the surface of the heart is a powerful tool for studying complex arrhythmias. However, a limitation of traditional optical mapping is that the mapped region is restricted to the field of view of the sensor, which makes it difficult to track electrical waves as they drift in and out of view. To address this, we developed an optical system that panoramically maps epicardial electrical activity in three dimensions. The system was engineered to accomodate hearts comparable in size to human hearts. It is comprised of a surface scanner that measures epicardial geometry and a panoramic fluorescence imaging system that records electrical activity. Custom software texture maps the electrical data onto a reconstructed epicardial surface. The result is a high resolution, spatially contiguous, mapping dataset. In addition, the three-dimensional positions of the recording sites are known, making it possible to accurately measure parameters that require geometric information, such as propagation velocity. In this paper, we describe the system and demonstrate it by mapping a swine heart.