Author + information
- Received March 15, 2016
- Revision received September 29, 2016
- Accepted October 18, 2016
- Published online January 16, 2017.
- Julien Seitz, MDa,∗ (, )
- Clément Bars, MDa,b,
- Guillaume Théodore, MDc,
- Sylvain Beurtheret, MDa,
- Nicolas Lellouche, MD, PhDd,
- Michel Bremondy, MDa,
- Ange Ferracci, MDa,
- Jacques Faure, MDa,
- Guillaume Penarandae,
- Masatoshi Yamazaki, MD, PhDf,
- Uma Mahesh R. Avula, MDf,
- Laurence Curel, MSa,
- Sabrina Siamea,
- Omer Berenfeld, PhDf,
- André Pisapia, MDa and
- Jérôme Kalifa, MD, PhDf
- aUnité de Rythmologie Interventionnelle, Hôpital Saint Joseph Marseille, France
- bService de Cardiologie, Institut Mutualiste Montsouris, Paris, France
- cService de Cardiologie, CHU, Nice, France
- dService de Cardiologie, CHU Henri Mondor, Creteil, France
- eDépartement Statistique, Laboratoire Alphabio, Marseille, France
- fCenter for Arrhythmia Research, Cardiovascular Research Center, Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, Michigan
- ↵∗Reprint requests and correspondence:
Dr. Julien Seitz, Hôpital Saint Joseph, Unité de Rythmologie Interventionnelle, Service de Cardiologie, 26 Boulevard de Louvain, 13008 Marseille, France.
Background The use of intracardiac electrograms to guide atrial fibrillation (AF) ablation has yielded conflicting results.
Objectives The authors evaluated the usefulness of spatiotemporal dispersion, a visually recognizable electric footprint of AF drivers, for the ablation of all forms of AF.
Methods The authors prospectively enrolled 105 patients admitted for AF ablation. AF was sequentially mapped in both atria with a 20-pole PentaRay catheter. The authors tagged and ablated only regions displaying electrogram dispersion during AF. Results were compared to a validation set in which a conventional ablation approach was used (pulmonary vein isolation/stepwise approach). To establish the mechanism underlying spatiotemporal dispersion of AF electrograms, the authors conducted realistic numerical simulations of AF drivers in a 2-dimensional model and optical mapping of ovine atrial scar-related AF.
Results Ablation at dispersion areas terminated AF in 95% of the 105 patients. After ablation of 17 ± 10% of the left atrial surface and 18 months of follow-up, the atrial arrhythmia recurrence rate was 15% after 1.4 ± 0.5 procedures per patient versus 41% in the validation set after 1.5 ± 0.5 procedures per patient (arrhythmia free-survival: 85% vs. 59%; log-rank p < 0.001). Compared with the validation set, radiofrequency times (49 ± 21 min vs. 85 ± 34.5 min; p = 0.001) and procedure times (168 ± 42 min vs. 230 ± 67 min; p < 0.0001) were shorter. In simulations and optical mapping experiments, virtual PentaRay recordings demonstrated that electrogram dispersion is mostly recorded in the vicinity of a driver.
Conclusions The clustering of intracardiac electrograms exhibiting spatiotemporal dispersion is indicative of AF drivers. Their ablation allows for a nonextensive and patient-tailored approach to AF ablation. (Substrate Ablation Guided by High Density Mapping in Atrial Fibrillation [SUBSTRATE HD]; NCT02093949)
Visual appraisal of the sequence and morphology of intracardiac electrograms sufficiently guides ablation of most ventricular and atrial arrhythmias. Atrial fibrillation (AF) is an exception to this paradigm. The targeting of complex fractionated electrograms (CFAE) as stand-alone or adjunctive ablation therapy has yielded variable results (1–8). Although some have reported good results when targeting CFAEs (6–8), a growing number of reports found little advantage in targeting CFAEs after having isolated the pulmonary veins (PVs) (1–5). CFAE ablation is usually guided by recording fractionated electrograms at the tip of a single intracardiac electrode. Multiple studies have suggested that multipolar electrode–obtained CFAEs provide added value beyond single electrode–recorded CFAEs by enabling classification of CFAEs as “active” or “passive” (9–11). The authors of these studies specifically noted that fractionation occurring in a nonsimultaneous fashion at neighboring electrode locations (time dispersion) and organized in well-defined clusters (spatial dispersion) may indicate the presence of an underlying source of AF (9–12). Recently, it was suggested that such multielectrode electrogram clusters might help in guiding ablation (11,13).
Previously, it was shown that intracardiac electrogram analysis might enable the visualization of AF drivers (14,15). It is unclear, however, whether multipolar electrogram signatures can serve as surrogates for the presence of drivers. The purpose of this pilot study was to describe a visually recognizable intracardiac electrogram abnormality that can identify regions of AF drivers and represent effective target sites for ablation of paroxysmal or persistent AF.
The hypothesis underlying this study is that electrograms recorded simultaneously by a multipolar catheter displaying both spatial and temporal dispersion areas are indicative of AF drivers, regardless of whether these electrograms are fractionated or not. In Figure 1A, we present the typical feature of abnormal multipolar electrograms associated with AF drivers: the spatiotemporal dispersion of electrical activation. Figures 1B and 2 show examples of fractionated and nonfractionated single-bipole and multipolar electrograms recorded in dispersion regions.
Between September 2013 and July 2014, 126 patients with drug-refractory symptomatic AF were prospectively enrolled at 3 centers (Hopital St-Joseph, Marseille; Institut Mutualiste Monsouris, Paris; and Centre Hospitalier Universitaire, Nice). Ablations were performed independently by 7 electrophysiologists. The validation set included a cohort of patients with symptomatic drug-refractory AF who underwent ablation using a conventional approach. From a database of 98 patients ablated conventionally (pulmonary vein isolation [PVI]/stepwise approach) between November 2008 and March 2010, 47 controls were selected based on these clinical characteristics at the time of the procedure: sex, presence of structural heart disease, and duration of continuous AF. The only exclusion criterion in the study and validation set was a prior AF ablation procedure. The study was approved by the institutional ethics committees, and all patients provided signed informed consent.
In addition to the following information, details regarding this study’s methods are in the Online Appendix.
Protocols and mapping
In the study population, only dispersion areas were ablated. For patients in sinus rhythm (SR) at the procedure’s outset, AF was induced by rapid atrial pacing using the coronary sinus (CS) catheter (500 and 180 ms). If AF was not inducible, isoproterenol (baseline dose 2.4 mg/h, increased in 0.2-mg increments to obtain a sinus rate >100 beats/min) was infused. A reference AF cycle length (AFCL) value was calculated as the average of 2 consecutive measurements of 10 cycle lengths (CLs) either in the left atrial (LA) or right atrial (RA) appendages (Online Figure 1). The Online Appendix includes details on the validation set ablation procedure.
Baseline mapping in both atria was performed during AF with the PentaRay multispline catheter (Biosense Webster, Diamond Bar, California) (Figure 1A) sequentially positioned in various regions of the RA and LA. At each location, the catheter was maintained in a stable position for a minimum of 2.5 s. The operator looked for dispersion areas (electrograms exhibiting both time and spatial dispersion). Where dispersion was found and/or the catheter was not stable for 2.5 s, acquisitions were repeated.
Dispersion areas were defined as clusters of electrograms, either fractionated or nonfractionated, that displayed interelectrode time and space dispersion at a minimum of 3 adjacent bipoles such that activation spread over all the AFCL (Figures 1A and 1B). At each bipole in a dispersion area, 1 or more of the following fractionated or nonfractionated electrogram morphologies were found (Figure 1B): 1) continuous, low-voltage fractionated electrograms (“continuously fractionated signal”); 2) bursts of fractionated electrograms (“trains of fractionation”); 3) fast nonfractionated electrograms (AFCL <120 ms; “rapid fires”); and 4) slow nonfractionated electrograms (AFCL >120 ms). Representative multipolar electrogram dispersion and nondispersion regions (Figure 2) illustrated that fractionated electrograms were found in both dispersion and nondispersion regions.
We used a single transseptal sheath. Once initial biatrial mapping with the PentaRay catheter was obtained, there was no further analysis/evaluation performed either visually or quantitatively on electrograms recorded with the ablation catheter.
Radiofrequency (RF) energy was applied (10 to 45 W) at any atrial location including the PV antrum and the CS, whereas no ablation was performed inside the PVs. A contact force of 7 g was considered a minimum to deliver RF energy at any location. The power was adjusted to a range of 10 to 25 W when the ablation catheter was inside the CS, near a PV ostium, or on the posterior LA wall. The endpoint of ablation of areas of dispersion was AF termination defined as conversion to SR or a stable atrial tachycardia (AT) (15). Post-ablation ATs were mapped and ablated until conversion to SR. If AF did not terminate after ablation of the pre-selected dispersion area regions, a new multielectrode sequential map was performed (remapping). If 2 ablated areas were very close (<1 cm), they were connected by RF applications. Neither PV isolation nor linear ablation was performed.
After restoring SR by ablation, AF reinducibility was tested by rapid atrial pacing (500 to 180 ms) in the proximal and distal CS with the addition of isoproterenol to induce AF when necessary. When ablation at dispersion regions led to rhythm regularization into AT before all dispersion regions had been ablated, the AT was mapped and ablated.
For patients in the validation set with paroxysmal AF, antral PVI was performed. For patients with persistent AF, ablation using the stepwise approach (16) was performed (details in the Online Appendix).
In 90 patients, the location of dispersion regions—as tagged on the 3-dimensional biatrial electroanatomic maps—was sorted according to biatrial segmentation as previously reported (15). The total surface area occupied by dispersion regions and the surface area of the ablated regions were measured from the electroanatomic maps in 43 patients. Biatrial surface was calculated after excluding areas pertaining to the mitral and tricuspid annuli, the vena cavas, and the PVs.
We evaluated inter- and intraobserver variability of the dispersion visual detection and the temporal stability of the spatial distribution of dispersion regions. (See the Online Appendix for methods.)
All patients were instructed to contact the study center if they experienced palpitations or any other symptoms suggestive of recurrent AF and to discontinue antiarrhythmic drug (AAD) therapy in the absence of symptoms after a 3-month blanking period. They also had follow-up visits and 24-h Holter monitors at 3, 6, 12, and 18 months. In a subgroup of 20 patients, the rhythm was monitored with 7-day Holter monitors (n = 18) or the memory functions of pacemakers and internal cardiac defibrillators (n = 2). Patients with recurrent AF or AT—defined as arrhythmia episodes >30 s after the blanking period—were offered a second ablation procedure. For redo procedures, the ablation protocol was similar to the one described for the study group.
The primary short-term efficacy endpoint was AF termination. Secondary short-term efficacy endpoints were conversion to SR and post-ablation AF noninducibility. At the end of the 18-month follow-up period, our primary long-term efficacy endpoint was AF recurrence rate after a single procedure (with or without AAD therapy). Secondary long-term efficacy endpoints included: AF/AT recurrence rate after 1 procedure (with or without AAD therapy); AF/AT recurrence rate after 1 or more procedures (with or without AAD therapy); AF recurrence rate and AF/AT recurrence rate in the absence of AAD therapy (Online Appendix).
We analyzed AT mechanisms and locations in a subset of 21 patients in whom post-ablation tachycardias occurred during the index procedure or during the follow-up.
We sought to compare the surface area occupied by CFAEs, classically used as ablation targets, with a dispersion region. We generated automatic fractionation maps (“auto-CFAEs”) with the CARTO setting “SCI 30-40” (17) (CARTO, Biosense Webster), with 30 and 40 ms as lower and upper limits, respectively. In 40 regions (2 dispersion areas and 2 nondispersed regions in 10 patients), we calculated the auto-CFAEs surface area/dispersion surface area ratio and the auto-CFAEs surface area/nondispersion surface area ratio.
To examine the mechanisms of spatiotemporal dispersion in AF driver regions, we analyzed intracardiac electrograms in dispersion and nondispersion areas, which were the tagged and untagged regions, respectively. We also conducted numerical simulations and isolated ovine heart experiments to generate pseudomultipolar recordings in driver and bystander regions (Online Appendix).
Categorical variables are expressed as n (%), and numerical variables as mean ± SD or median (interquartile range [IQR]). Categorical variables were compared using the chi-square test or Fisher exact test as appropriate. Continuous numerical data were compared using the Wilcoxon rank sum test or Brown-Mood median test as appropriate.
Survival analyses were performed to compare endpoints at the end of follow-up: Kaplan Meier estimates for AF rates after a single procedure; AF/AT rates after a single procedure; and AF/AT rates after ≥1 procedures (with or without AAD therapy) (Online Appendix). Kaplan-Meier survival curves were assessed and compared using log-rank tests. The time recorded was the time needed for the event of interest to occur (failure to achieve freedom from AF or freedom from AF and AT). The outcome was unknown in patients who did not reach the event before the end of follow-up (i.e., an 18-month follow-up), in patients lost to follow-up, and in patients who died during follow-up. In all such cases, time of follow-up was recorded and interpreted as censored data. Pairwise Cox hazards regression was used to compare survival of dispersion area subgroups (paroxysmal, persistent, and longstanding persistent). A 2-sided p value < 0.05 indicated statistical significance. All statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary, North Carolina).
Between September 2013 and July 2014, 126 consecutive patients with AF were prospectively enrolled at 3 centers. Eighteen patients were excluded because of previous AF ablation, and 3 patients when an LA appendage thrombus was detected before ablation. In total, 105 patients were enrolled and compared to a validation set of 47 patients (Table 1).
Mapping and analysis
Before ablation, the RA and LA appendage reference CLs were 179 ms (IQR: 177 to 206 ms) and 182 ms (IQR: 164 to 203 ms), respectively. The mapping times and number of acquisition points per patient in the RA and LA were 7 min (IQR: 5 to 9 min) and 12 min (IQR: 10 to 15 min) and 491 (IQR: 325 to 704) points and 882 (IQR: 673 to 1,110) points, respectively.
Maps with representative dispersion areas in 3 patients with paroxysmal, persistent, and longstanding persistent AF illustrated that dispersion areas were formed by a variable number of electrograms (Figures 3A to 3C) and were patient- and AF type-dependent. There was an average of 5 ± 1.5 dispersion areas per patient, and each dispersion area spanned an average of 5 ± 2 cm2 (Table 2). Dispersion areas covered a significantly larger surface area in patients with longstanding persistent AF than patients with paroxysmal or persistent AF. Dispersion area locations are in Table 3.
The visual analysis of the 4 operators was completely concordant in 94.3% of the analyzed electrograms (interobserver variability equal to 6.7%). The intraobserver variability of the visual analysis was 2 ± 2% (5%, 1.7%, 1.7%, and 0%, respectively for each operator).
We observed a high degree of temporal stability in the spatial distribution of dispersion regions, regardless of whether the repeat mapping was performed by the same or a distinct ablationist (detailed results are presented in the Online Appendix, Online Figure 2).
Ablation was performed in both the LA and RA in 51% of patients, with the procedural outcome seen in Figure 4 and Online Figure 3. In the remaining patients, ablation was only performed in the LA. AF terminated in 100 of 105 (95%) patients. In patients in “spontaneous” AF at the procedure outset, AF termination was obtained in 60 (92%). By comparison, AF termination was obtained in all patients in whom AF was pace-induced (n = 40; p = 0.15). Of note, there were 25 of 65 (33.8%) patients with spontaneous AF on AADs versus 12 of 40 (30.0%) with induced AF on AADs (p = 0.68). AF termination was obtained with 20 (IQR: 10 to 37) min of RF energy and 46 (IQR: 21 to 72) min after the first RF application either by conversion directly to SR (15%) or conversion to AT (85%) (Figure 4A). Overall, 77% of patients converted to SR via ablation.
Post-ablation AF inducibility was tested in 61 (58.6%) patients. Noninducibility of AF and AT was achieved in 44 (72%) of those tested. An average of 1.93 ± 1 ATs were ablated (Figure 4A). No major complications occurred. Three patients experienced minor groin bleeding. RF time to terminate AF was significantly longer in longstanding persistent AF versus both paroxysmal and persistent AF (p = 0.0004) (Figure 4B). The procedure time to terminate AF was significantly longer in longstanding persistent AF versus paroxysmal AF (p = 0.007) (Figure 4B). For total procedure and RF times, there was no difference between AF types (Figure 4C).
In the validation set, AF termination and SR conversion rates were significantly lower (Figure 4D). Also, the overall average procedure, RF energy, and fluoroscopy times were significantly longer in the control group: 230 ± 67 min versus 168 ± 42 min (p < 0.0001); 85 ± 35 min versus 49 ± 21 min (p = 0.0001); and 78 ± 25 min versus 15 ± 13 min (p < 0.0001), respectively (Figure 4E, Online Table 1). RF energy times for paroxysmal AF ablation were similar between the study population and the validation set (Online Table 1).
The area that was ablated represented 10 ± 5% of the overall biatrial area and 17 ± 10% of the LA area. Notably, the areas ablated in paroxysmal and persistent AF patients were comparable, but the area ablated in patients with longstanding persistent AF was significantly larger (Table 2).
Ninety-six patients (91.4%) in the study population completed 18-month follow-up. Of the 9 (8.6%) who did not, 1 patient died 2 months before the end of follow-up (myocardial infarction), and 8 were lost to follow-up because of relocation. Their mean follow-up time was 10 ± 3 months. In the validation set, 3 patients dropped out during the blanking period (1 died of heart failure and 2 relocated). All other patients completed 18-month follow-up.
The single-procedural AF and AF/AT recurrence rates after 18 months were significantly lower in the study population compared with the validation set (11% vs. 58%; log-rank p < 0.001; and 45% vs. 64%; log-rank p = 0.026, respectively). AF-free (89% vs. 42%; log-rank p < 0.001) and AF/AT-free survival rates (55% vs. 36%; log-rank p = 0.026) also were significant (Figure 5A). The multiple-procedural arrhythmia recurrence rates were also lower in the study population at the end of the follow-up: 15% versus 41% (log-rank p < 0.001) as were AF/AT-free survival rates (85% vs. 59%; log-rank p < 0.001). (Figure 5B, Online Figures 4 and 5 show data from 7-day Holter-monitoring.) Importantly, there were comparable rates of patients using AADs in the study group versus the validation set (44% vs. 43%; p = 0.9).
After 1 procedure, there were no differences in AF recurrence or AF/AT recurrence rates between the paroxysmal, persistent, and longstanding persistent groups: respectively, 21%, 8%, and 10% (log-rank p = 0.24) and 29%, 53%, and 43% (log-rank p = 0.15). After 1.4 ± 0.5 procedures per patient, there also were no differences in AF/AT recurrence rates between the paroxysmal, persistent, and longstanding persistent groups, respectively: 17%, 16%, and 13%; log-rank p = 0.9. Redo procedures were performed for organized ATs in 75.6% of patients. Redo procedures were significantly shorter in duration than the index procedures and required less RF and fluoroscopy times (Table 4). Except for 1 pericardial effusion, no major complications were noted after the redo procedures.
We then compared key patient and procedural characteristics between patients who were “spontaneously” in AF at the beginning of the procedure (no pacing maneuver) versus those in whom AF had been pace-induced. For pace-induced and “spontaneous” AF patients, respectively, LA volumes were 143 ± 31 ml versus 181 ± 46 ml (p < 0.0001); RF time to terminate AF 19.8 ± 16.2 min versus 29.4 ± 20.4 min (p = 0.02); total RF times 43 ± 19.7 min versus 52.3 ± 21.5 min (p = 0.01); and rates of AF termination, 100% and 92% (p = 0.15). However, after 18-months follow-up and an average of 1.4 procedures in both subgroups, there was a similar rate of AF/AT recurrence between “spontaneous” AF and pace-induced AF (14% vs. 18%, respectively; log-rank p = 0.44). We observed no statistical difference in outcomes at the end of the follow-up between patients on and off AADs: single-procedure AF recurrence rate was 13% for those on versus 10% for those off drugs (log-rank p = 0.62); the single-procedure AF/AT recurrence rate was 46% for those on versus 44% for those off drugs (log-rank p = 0.71); and the AF/AT recurrence rates after 1 or more procedures was 15% in patients on or off drugs (log-rank p = 1.00).
In 21 patients, we counted 44 distinct ATs (2.2 ± 1.3 AT per patient): 22 were macro–re-entries (peritricuspid, perimitral, or LA roof flutters) and 22 were localized AT (focal or micro–re-entries). Of these 44 ATs, only 5 (11.4%) originated from dispersion regions that had just been ablated, whereas 39 (88.6%) were either macro–re-entries or localized ATs arising from locations not previously ablated. Importantly, 17 of 22 localized ATs arose from dispersion regions not previously ablated (Online Figure 6).
We analyzed long-term AT recurrences after the index AF ablation procedure. We focused our analysis on determining whether the AT that occurred arose from the dispersion regions that were targeted during the index procedure (dispersion-index regions) or from nondispersion regions (nondispersion-index regions), which were not ablated. During follow-up, 11 AT ablation procedures were conducted. Of 18 distinct recurrent ATs, 11 (61%) originated from nondispersion-index regions as follows: 6 macro–re-entries previously ablated at nondispersion regions such as the mitral isthmus or the roof, relapsed presumably because of conduction recovery of ablation lines; 4 macro–re-entries not present during the index case; and 1 focal tachycardia from a nondispersion-index region. Additionally, 3 (16.6%) originated from within a dispersion-index region and 4 (22%) were found in close vicinity of a dispersion-index region (<1 cm).
The ratios of surface area of CFAEs automatically detected to the surface area of dispersion regions and to the surface area of regions not displaying dispersion were 72 ± 25% and 27 ± 15%, respectively (Figure 6A, Online Figure 7).
Dispersion area abnormal electrograms exhibited a higher occurrence of single-bipole fractionated continuous signals (Figure 6B), a reduced voltage (Figure 6C), a significantly shorter CL (Figure 6D), and a dispersion duration that spanned most of the AFCL (Figures 6E and 6F). Additionally, a mean of 8.1 ± 3.5 rotations per 2.5 s occurred in dispersion areas (Figure 6G).
Figure 7 depicts simulated pseudo-multipolar electrograms obtained after positioning a virtual PentaRay either at the center or at periphery of the driver (here a rotor) (Figures 7A to 7C, Online Video 1). In comparing Figure 7A and 7B, striking differences in the features of the virtual PentaRay electrograms can be seen. When the virtual catheter hovered over the center of the driver, virtual bipolar electrograms exhibited a fast frequency of excitation. Also, the time distribution of the electrograms was such that either branch of the PentaRay was activated in asynchrony with the other branches. Consequently, the virtual electrogram time-series spanned most of the AFCL. The overall visual impression was one of successive electrode-to-electrode and branch-to-branch activations. At the driver periphery, the frequency of activation was reduced and impulses were nonrotational or planar-like. As a result, either branch of the PentaRay was activated in relative synchrony with the other branches (Figure 7B). The visual impression was one of successive beats separated by quiescence.
Figure 7C shows an AF driver initiated in a pseudofibrotic substrate. In this setting, driver impulses propagated within a highly heterogeneous substrate. The virtual PentaRay then generated unique multipolar pseudoelectrogram features. Throughout the 2-dimensional sheet, multiple regions contributed to a slowing down of the rotational impulse. Although there was no impulse block, the driver’s wavefront experienced markedly slow and heterogeneous conduction. This resulted in beat-to-beat changes in wave directionality. Such disturbances translated into lengthened and fractionated depolarization pseudoelectrograms (Figure 7C), reminiscent of the features of dispersion areas in patients. Here, the numerical and experimental data predicted that such drivers should yield electrograms with significantly greater temporal and spatial dispersion than drivers spinning within relatively homogeneous media.
Figures 8A and 8B included pseudomultipolar electrograms generated from optical movies during AF induced in an isolated LA scar (Online Appendix). The PentaRay-like single-pixel time series was obtained in the region of the LA myocardial infarct border zone where a driver was anchored after initiation by burst pacing (Online Video 2). For comparison, we presented PentaRay-like single-pixel time series obtained at the RA where nonrotational and planar-like waves propagated (Online Video 2). Similar to the differences seen in the simulations, fractionated multipolar pseudoelectrograms exhibited a high degree of spatiotemporal dispersion when recorded in the vicinity of a driver (Figure 8B, right). In the RA bystander region, however, waves were planar-like and pseudoelectrograms were nearly simultaneous (Figure 8B, left).
These aspects evoked the dispersion areas and nontagged multipolar electrogram aspects recorded in patients. Furthermore, the time series of maximal voltage absolute values at any of the bipoles shown in the right panels of Figures 7 and 8 illustrated that the time of electrical quiescence of pseudo-multipolar electrograms obtained in the vicinity of a driver—that is, low <0.2 mV voltage absolute values at any of the bipoles—was drastically reduced in comparison with the time of electrical quiescence of pseudomultipolar electrograms from bystander regions. Collectively, our simulations and optical mapping studies suggested that dispersion areas may be regarded as electrogram footprints of active electrical sources of AF propagating in a heterogeneous atrial muscle.
Our main findings are as follows: 1) spatiotemporal dispersion of electrograms represented an electrical footprint of waves emanating from rapid fibrillatory drivers and propagating within a heterogeneous atrial muscle; and 2) the clustering of intracardiac electrograms exhibiting spatiotemporal dispersion may guide a wholly patient-tailored ablation of all types of AF.
This pilot study’s results demonstrated that electrogram dispersion detected by direct visualization of electrograms recorded simultaneously with a splined, multielectrode catheter is a marker of AF drivers. We recorded regions exhibiting spatiotemporal electrogram dispersion and targeted such regions in the absence of PVI or any other anatomy-based ablation. With 44% of patients on AADs, preliminary results showed that our approach allowed for efficacious, nonextensive, and wholly patient-tailored ablation of all AF types. Application of 20 min of RF energy resulted in a 95% rate of AF termination and 89% of patients free from AF after a single procedure, which continued during 18 months of follow-up. The AF/AT-free survival rate was 55% after 1 procedure and 85% after ∼1.4 procedures per patient.
This study offers insight into why CFAEs might represent worthy ablation targets in some hands (6–8), but not in others (1–5). Successful outcomes after ablating CFAEs might be explained by the fact that fractionated electrograms represent a majority of the surface area in driver regions (Figure 6A), which exhibit spatial and temporal dispersion. Conversely, fractionated electrograms can also be found in bystander regions that do not exhibit dispersion (Figures 2C and 6A, Online Figure 7). We showed that CFAEs located in nondispersion regions represented most of the CFAE surface area. About 30% of the surface area in dispersion regions were sites of nonfractionated electrograms (Figure 6A). Altogether, we presented evidence that dispersion ablation might overlap with conventional CFAE ablation when CFAEs are spatially clustered. Also, our numerical and experimental data strongly suggested that dispersion regions correspond to driver regions, which may be identified either on the endocardial or epicardial sides of the atrial wall. Future works implementing advanced mapping simultaneously to multipolar electrode recordings are needed to examine the degree of overlap between driver and dispersion regions.
Our contribution aligns well with Narayan et al. (14) and Jadidi et al. (18) in that they suggested that patient-tailored, mechanism-based ablation may yield valuable results. We envision such studies, including our own, as building blocks of a collaborative effort that may lead to an efficacious patient-tailored ablation approach. In the study by Narayan et al. (14) the ablation time for reaching the short-term endpoint of AF termination or ≥10% AF slowing was 31.8 min (IQR: 22.1 to 71.5 min) and 18.5 min (IQR: 7.9 to 24.5 min) in the focal impulse and rotor modulation–blinded and the focal impulse and rotor modulation groups, respectively. After PVI, ablation times increased to 52.1 ± 17.8 min and 57.8 ± 22.8 min, respectively. Jadidi et al. (18) showed that PVI as the initial ablation approach was achieved after a mean of 28 ± 11 min. Among patients in whom PVI did not terminate AF, selective atrial ablation at low-voltage, dispersion-like regions terminated persistent AF after 11 ± 9 min of RF. Ablation of the remaining ATs required an additional 12 ± 9 min, producing an RF time of 23 ± 11 min in addition to PVI, resulting in a grand total of 44 ± 19 min of RF (18). The main difference, however, with the present work was the percentage of the overall ablation time dedicated to patient-tailored ablation. This represented about one-third the overall ablation time reported by Narayan et al. (14) and one-half that reported by Jadidi et al. (18). Therefore, we feel that the most novel aspect of our approach was that it represented an approach that is entirely patient-tailored (Central Illustration).
The comparison with a validation set provided further evidence that dispersion ablation was comparable to a more conventional ablation approach (Figures 4 and 5, Online Table 1). Finally, after dispersion ablation, the majority (75.6%) of recurrences were organized AT and not AF. ATs were simpler to ablate as demonstrated by the reduced procedure time and the higher SR conversion rate during redo ablation (Table 4). We believe such a high proportion of AT/AF recurrences might be the basis for our highly satisfactory long-term outcomes: 85% of patients free from any arrhythmia after ∼1.4 procedures per patient in a population with 77% of persistent and longstanding AF.
We conducted numerical simulations and experiments to examine the mechanisms by which regions harboring spatiotemporal dispersion of electrograms are key to AF perpetuation. Both our experiments and numerical simulations showed that pseudomultipolar electrograms exhibiting dispersion were uniquely recorded in the vicinity of drivers (Figures 7 and 8). Such results illustrated that the simultaneous presence of time and spatial dispersion of abnormal electrograms represents regions where the wavefront shape is highly curved and where impulse propagation of waves emanating from drivers is impaired. This also corroborates previous findings that continuously fractionated electrograms, which could be dispersed electrograms, have been recorded in rotor regions (15) or in regions critical to AF maintenance (6–8). Importantly, our results demonstrated that dispersion of multipolar electrograms highly depends on both the source’s frequency of activation and its underlying atrial substrate (Figures 7 and 8). We previously reported that beat-to-beat changes in wavefront directionality and impulse velocity produced fractionation in the immediate vicinity of a rotor at the boundary of the maximal dominant frequency domain (19). This was expected because several studies had emphasized that electrogram fractionation is highly frequency-dependent (11,19–21). In particular, Spach et al. (20) presented that electrogram fractionation that occurs during transversal impulse propagation might also manifest in the longitudinal direction at shorter CLs (frequency-dependent space dispersion). Here, our results corroborated these findings in showing that spatiotemporal dispersion of multipolar electrograms is frequency dependent. Therefore, our results also validated the studies that indicated that high dominant frequency may be used as a surrogate for AF source localization (22–24).
The fact that post-ablation ATs predominantly arise from nonablated dispersion regions suggests the unmasking of AT drivers after some degree of substrate modification. Although a plausible scenario, it is unclear how ablation may prevent fibrillatory conduction of waves emanating from the (subsequent) AT drivers while, at the same time, reducing the overall frequency of activation. This would suggest that a single ablation application could produce effect on an AT driver as well as on distant waves emanating from it. A possible alternative scenario: post-ablation ATs arising from nonablated dispersion regions pre-exist but as secondary or co-primary drivers, and once 1 or more drivers have been ablated, the arrhythmic activity may only be maintained by slower drivers. These may only rise to dominance once their faster counterpart, located in a distinct dispersion region, has been ablated.
We further demonstrated that interstitial fibrosis was key to the observation of spatiotemporal dispersion of electrograms during AF. Previously, we and others had reported that fractionated electrograms may be recorded in regards of rotors propagating within a fibrotic atrium (24,25). Here, we showed that a driver initiated within a fibrotic atrium (Figure 7C) yielded a significantly larger temporal and spatial electrogram dispersion than the one produced by a driver propagating within a more homogeneous medium (Figure 7B). As we have previously shown (24), the presence of fibrotic, millimeter-sized obstacles (1 to 7 mm2) is sufficient to anchor re-entries characterized by a CL that depends on the obstacle size. Therefore, in the context of extensive fibrosis, the term rotor, which might be understood as an “entirely functional” re-entry, may be interchangeable with terms such as micro–re-entry or re-entry that also are AF drivers. Overall, these results agree with recent atrial structural imaging reports, which have presented that the atria of patients undergoing AF are highly fibrotic, and that electrogram fractionation occurs in regions of patchy fibrosis (26–28).
The nonrandomized design of this pilot study limited our conclusions in comparing techniques. An evaluation of dispersion area ablation in a larger patient population using a randomized study design is warranted. Also, in patients in SR at the outset of the procedure and in whom AF is initiated by pacing maneuvers, the assumption should be that RF ablation may lead to a serendipitous termination. In general, procedural endpoints such as AF termination, SR conversion, or AF noninducibility need to be interpreted with caution. Besides, their value as procedural predictors of long-term outcome will need to be rigorously investigated.
We did not check whether PVs were isolated. Therefore, we cannot state that some of the PVs were not unintentionally isolated. In 13 additional patients, in whom we only performed dispersion ablation, only 2 of 52 PVs were isolated unintentionally.
The computer simulations were performed in a 2-dimensional model; a more realistic 3-dimensional model of AF and fibrosis would yield more realistic electrograms. Finally, to avoid prolonged procedures and comply with institutional requirements, we made the collegial decision to withhold inducibility maneuvers after 2 h.
We presented the first demonstration that the clustering of intracardiac electrograms exhibiting spatiotemporal dispersion allows for a wholly patient-tailored ablation of all types of AF.
COMPETENCY IN PATIENT CARE AND PROCEDURAL SKILLS: Spatiotemporal dispersion of multipolar electrograms recorded during catheter ablation is a signature of electrical drivers of atrial fibrillation in the left and right atria. Ablation at these locations often eliminates AF.
TRANSLATIONAL OUTLOOK: Additional research is needed to assess the long-term outcomes of ablation procedures guided by automated software that identities spatiotemporal electrogram dispersion in patients with various patterns and durations of AF in specific patient populations.
The authors thank their colleagues for their scientific input, in particular Drs. Fred Morady, Hakan Oral, José Jalife, Alexandre Maluski, Eloi Marijon, and Julien Mancini. The authors also thank Fanny Desmettre, Julia Legrand, Alexandrine Lozupone, Camille Metzdorff, Joseph Ajoury, Alexandre Masse, and Kamila Djouadi for their technical assistance. Special thanks to Donovan C. Jr. for his drawings and his support.
For an expanded Methods section as well as supplemental figures, tables, and videos with legends, please see the online version of this article.
The study was not funded by industry and received no financial support. Dr. Yamazaki was supported by Grant-in-Aid for Scientific Research (C) 15K09077 and Joint International Research grant 15KK0341. Dr. Seitz has received speaker fees and honoraria as a consultant from Biosense Webster; has received speaker fees from St. Jude Medical and Medtronic; and owns shares of Volta Medical. Dr. Bars has received speaker fees and honoraria as a consultant from Biosense Webster; and owns shares of Volta Medical. Dr. Theodore has received honoraria as a consultant from Biotronik, Boston Scientific, St. Jude Medical, and Medtronic. Prof. Lellouche has received speaker fees from Medtronic. Dr. Bremondy has received honoraria as study investigator from St. Jude Medical for the STAR AF II trial study. Drs. Ferracci and Faure have received honoraria from St. Jude Medical as consultants. Dr. Berenfeld has received grants and donations from Medtronic and St. Jude Medical; is a consultant for Acutus Medical; and has equity in and is a senior officer of Rhythm Solutions. Dr. Pisapia has received honoraria as a consultant for the STAR AF II trial from St. Jude Medical; and speaker fees from Medtronic. Dr. Kalifa is coinvestigator on a project sponsored by Medtronic; and owns shares of Volta Medical. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- antiarrhythmic drug
- atrial fibrillation
- atrial fibrillation cycle length
- atrial tachycardia
- complex fractionated atrial electrogram
- cycle length
- coronary sinus
- interquartile range
- left atrial/atrium
- pulmonary vein
- pulmonary vein isolation
- right atrial/atrium
- sinus rhythm
- voltage absolute value
- Received March 15, 2016.
- Revision received September 29, 2016.
- Accepted October 18, 2016.
- American College of Cardiology Foundation
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