Author + information
- Received November 6, 2018
- Revision received January 8, 2019
- Accepted January 17, 2019
- Published online April 15, 2019.
- Claire A. Martin, PhDa,b,c,d,∗ (, )
- Masateru Takigawa, PhDa,b,c,
- Ruairidh Martin, MPhila,b,c,e,
- Philippe Maury, MDf,
- Christian Meyer, MDg,
- Tom Wong, MDh,
- Rui Shi, MDh,
- Parag Gajendragadkar, MPhild,
- Antonio Frontera, PhDa,b,c,
- Ghassen Cheniti, MDa,b,c,
- Nathaniel Thompson, MDa,b,c,
- Takeshi Kitamura, MDa,b,c,
- Konstantinos Vlachos, MDa,b,c,
- Michael Wolf, MDa,b,c,
- Felix Bourier, MDa,b,c,
- Anna Lam, MDa,b,c,
- Josselin Duchâteau, PhDa,b,c,
- Grégoire Massoullié, MDa,b,c,
- Thomas Pambrun, MDa,b,c,
- Arnaud Denis, MDa,b,c,
- Nicolas Derval, MDa,b,c,
- Mélèze Hocini, MDa,b,c,
- Michel Haïssaguerre, MDa,b,c,
- Pierre Jaïs, MDa,b,c and
- Frédéric Sacher, PhDa,b,c
- aElectrophysiology and Ablation Unit, Bordeaux University Hospital (Centre Hospitalier Universitaire [CHU]), Pessac, France
- bInstitut Hospitalo-Universitaire (IHU), LIRYC, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac- Bordeaux, France
- cUniversité Bordeaux, Institut National de la Santé et de la Recherche Médicale U1045, Bordeaux, France
- dDepartment of Electrophysiology, Royal Papworth Hospital National Health Service Foundation Trust, Cambridge, United Kingdom
- eDepartment of Cardiology, Newcastle University, Newcastle, United Kingdom
- fUnité Inserm U 1048, University Hospital Rangueil, Toulouse, France
- gDepartment of Cardiology, University Medical Center Hamburg—Eppendorf, Hamburg, Germany
- hDepartment of Electrophysiology, Brompton Hospital, London, United Kingdom
- ↵∗Address for correspondence:
Dr. Claire A. Martin, IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-/ Bordeaux University Hospital (CHU), Electrophysiology and Ablation Unit/Université Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, F-33000, Bordeaux, France/ 33600 Pessac-Bordeaux, France.
Objectives This study reports the use of a novel “Lumipoint” algorithm in ventricular tachycardia (VT) ablation.
Background Automatic mapping systems aid rapid acquisition of activation maps. However, they may annotate farfield rather than nearfield signal in low voltage areas, making maps difficult to interpret. The Lumipoint algorithm analyzes the complete electrogram tracing and therefore includes nearfield signals in its analysis.
Methods Twenty-two patients with ischemic cardiomyopathy and 5 with dilated cardiomyopathy underwent mapping using the ultra-high density Rhythmia system. Lumipoint algorithms were applied retrospectively.
Results In all left ventricular substrate maps, changing the window of interest to the post-QRS phase automatically identified late potentials. In 25 of 27 left ventricular VT activation maps, a minimum spatial window of interest correctly identified the VT isthmus as seen by the manually annotated map, entrainment, and response to ablation. In 6 maps, the algorithm identified the isthmus where the standard automatically annotated map did not.
Conclusions The Lumipoint algorithm automatically highlights areas with electrograms having specific characteristics or timings. This can identify late and fractionated potentials and regions that exhibit discontinuous activation, as well as the isthmus of a VT circuit. These features may enhance human interpretation of the electrogram signals during a case, particularly where the circuit lies in partial scar with low amplitude nearfield signals and potentially allow a more targeted ablation strategy.
Catheter ablation of complex arrhythmias is challenging. Current recurrence rates for ventricular tachycardia (VT) in the setting of structural heart disease lie at approximately 50% at 5-year follow-up (1). Mapping has been greatly aided by the development of automatic systems that allow the rapid acquisition of activation and substrate maps (2). However, these algorithms may annotate the farfield rather than the nearfield signal, especially in areas of low voltage, thus rendering maps difficult to interpret (3). Manual reannotation to the nearfield signal is time-consuming and may not be feasible in real time.
A novel set of “Lumipoint” algorithms (Boston Scientific, Marlborough, Massachusetts) have been recently developed that analyzes the complete electrogram tracing to determine activity at each location and therefore includes nearfield signals in its analysis. A window of interest may be used to highlight regions of the map that activate within a certain time within the cycle. This feature may be used in a variety of ways to enhance interpretation of electrograms to aid comprehension of the map and therefore potentially focus ablation strategy. We report use of this feature in VT ablation.
The research was approved by local ethics committees. Prior written informed consent to participate was obtained from all participants. Twenty-two patients with ischemic cardiomyopathy (ICM) (group 1) and 5 with dilated cardiomyopathy (DCM) (group 2) undergoing VT ablation were included.
A quadripolar catheter was placed in the right ventricular apex, and a decapolar catheter was placed in the coronary sinus. Access was gained to the endocardial left ventricular (LV) cavity through either an anterograde transseptal approach or a retrograde aortic approach, depending on clinical factors. If the clinical VT or the pre-procedural imaging suggested an epicardial circuit, epicardial access was performed using the Sosa method.
Mapping was performed using the ultra-high density Rhythmia system, with Orion mapping catheter (Boston Scientific). The following beat acceptance criteria were used: 1) electrocardiographic morphology match; 2) time stability of electrograms; 3) respiratory stability; and 4) a maximal distance of electrode to anatomical shell of 2 mm. Bipolar electrograms were filtered at 30 and 300 Hz and unipolar electrograms at 1 and 300 Hz, without a notch filter.
Substrate mapping was performed either in sinus rhythm (SR), with atrial pacing from the proximal electrode of the coronary sinus catheter at 600 ms or with pacing at 600 ms from the RV apex. VT was then induced by programmed stimulation and an activation map made of any sustained and hemodynamically stable circuits. The VT isthmus location was confirmed by entrainment mapping and/or pace mapping and subsequently by response to ablation.
Radiofrequency ablation was delivered with open-irrigated catheter (30 to 50 W endocardially and 25 to 35 W epicardially) until targeted sites were rendered electrically inexcitable with pacing at 10 mA with 2-ms pulse width output. The critical isthmuses of the VT were ablated, followed by regions of local abnormal ventricular activity (LAVA). Endpoints were VT isthmus ablation, LAVA elimination, and VT noninducibility.
Patients were followed up at 1, 3, and 6 months and every 6 months thereafter. Implantable cardioverter-defibrillators were followed through remote monitoring. History, electrocardiogram, and Holter monitoring were taken in symptomatic patients without implantable cardioverter-defibrillators. Any documented VT sustaining ≥30 s or terminated by appropriate implantable cardioverter-defibrillator therapy (anti-tachycardia pacing or shock) was considered a recurrence.
Maps were analyzed retrospectively using a noncommercial version of the Rhythmia software. Signals >0.02 mV (twice laboratory noise level) were annotated. Activation maps during VT and SR/pacing were annotated to the high-frequency nearfield bipolar signals. Areas of scar (defined as <0.8 mV and dense scar as <0.2 mV (4)) and of LAVA were annotated on each substrate map. Late activation was defined as that occurring after the QRS interval. LAVA were defined as sharp high-frequency ventricular potentials, occurring anytime during or after the farfield ventricular electrogram and distinct from it, in SR or pacing (5).
Lumipoint algorithms were then applied. In addition to voltage and activation time annotation, each electrogram was processed to detect all activity. This results in a continuous trace that reflects the presence of deflections for each time point and provides the basis for further inspection. As the first step in the analysis, an “activation search” feature was applied to all LV maps (Figures 1A to 1E). This feature uses an adjustable time-of-interest period within the mapping window. Superimposed onto the current voltage or activation map, the tool highlights regions of the map that contain electrograms that show activity in the time of interest. An electrogram with activity in the time of interest is highlighted regardless of the electrogram’s activation time annotation. This was applied to all LV substrate maps, with a time-of-interest period covering the post-QRS phase, to highlight late potentials. A “complex activation” feature was then employed to the substrate maps; this highlights regions of the map that both activate within the time-of-interest period and exhibit multiple components of activation. The number of components necessary to cause an electrogram to be highlighted is adjustable. The “group reannotation” feature was then employed, which automatically annotates a deflection within the time-of-interest period as the activation time for highlighted electrograms (Figures 1F and 1G).
The “activation search” feature was then applied to all VT activation maps acquired during the live case and before manual annotation. The “Skyline” graph feature was enabled, which reflects the size of the depolarizing region throughout the mapping window. It computes the surface area associated with active electrograms for each moment in time as a fraction of the total surface area of the map. Following a hypothesis that the isthmus of the VT circuit will colocalize with the region of the map with the smallest activation region, the window of interest of the activation search tool was placed over the trough of the Skyline graph. In this way, the putative isthmus of the circuit was identified (Figure 2, Online Video 1). This feature was then applied to the same maps after they had been manually reannotated to the nearfield signal where necessary.
Continuous variables are presented as mean ± SD for normally distributed data and median and interquartile range for non-normally distributed data. Continuous variables were compared using analysis of variance. Categorical variables were expressed as counts or proportions. Analyses and comparisons of continuous data were performed using analysis of variance, whereas the Fisher exact test was used to compare categorical data. A 2-sided probability level of <0.05 was considered significant. All calculations were performed using SPSS version 20.0 (IBM Software, Armonk, New York).
Patient and procedure information
Twenty-two patients with ICM and 5 with DCM from 4 centers were recruited. All 27 patients underwent endocardial mapping; 5 patients also underwent epicardial mapping (3 with DCM, 2 with ICM). A retrograde approach was used in 12 patients and a transseptal approach in 15. Twelve cases were redo procedures. Twenty-five of 27 cases were successful acutely in that VT was noninducible at the end. There were no complications. Patient and procedural demographics are summarized in Table 1. There were no significant differences between ICM and DCM cohorts except the proportion of cases that used an epicardial approach.
Use of activation search feature in substrate maps
Twenty-two SR/paced maps from the ICM patients and 5 SR/paced maps from the DCM patients were analyzed using the activation search feature to highlight the post-QRS timing region. In all 27 cases, the algorithm identified regions of late potentials overlapping LAVA annotated manually with a 71.7 ± 7.0% overlap (72.7 ± 6.5%, n = 22 in ICM, and 67.2 ± 7.5%, n= 5 in DCM; p = 0.12) (Figures 3B, 4A, and 4B⇓⇓, Online Video 2). The algorithm was able to identify late potentials in all 5 epicardial maps (Figure 3B). The complex activation search feature, with the window of interest set in the post-QRS period and set to highlight electrograms with at least 9 deflections identified a subset of late potentials with fractionated signals. In all 27 cases, including all 5 epicardial maps, this overlapped with regions where LAVA were annotated manually with an 82.6 ± 7.9% overlap (83.6 ± 7.5%, n = 22 in ICM, and 78.3 ± 9.0%, n = 5 in DCM; p = 0.18) (Figure 4C). The highlighted regions overlapped with the VT isthmus as demonstrated on the corresponding VT activation map in all 27 cases, both endocardially and epicardially.
The group reannotation feature was employed to annotate the highlighted electrograms to the late activation time window (Figures 4D to 4F). In all 27 cases, including all 5 epicardial maps, the algorithm correctly reannotated the signals. In 22 of 27 (81%) (18 of 22, 82% in ICM, and 4 of 5, 80% in DCM), the region of late activation overlapped with the VT isthmus.
Use of activation search feature in activation maps
Twenty-three LV VT activation maps from group 1 (1 patient had 2 tachycardias; 2 were epicardial maps) and 5 LV VT activation maps from group 2 (3 were epicardial maps) were analyzed by moving the activation search window to the minimum of the Skyline graph. In 26 LV maps (21 ICM, 5 DCM), including all epicardial maps, the algorithm correctly highlighted the VT isthmus (Figures 2, 3A, 4G, and 4H, Online Videos 1 and 3). This was identified by 1) the manually annotated activation map (n = 26), 2) entrainment and pace mapping (n = 24), and 3) response to ablation with VT terminating on ablation (n = 4) or when ablated in SR/paced rhythm, no VT being inducible post-procedure (n = 26). In the 26 LV maps where the isthmus was identified, the mean distance from the area highlighted by the algorithm to that demonstrated on the annotated activation map was 2.2 ± 1.7 cm (2.2 ± 1.9 cm, n = 21 in ICM, 2.4 ± 1.1 cm, n = 5 in DCM; p = 0.79). In all maps, there was farfield annotation in areas of low voltage.
In 6 maps (5 from group 1, 1 from group 2), the isthmus lay in a zone in which the farfield component had largely been initially annotated. Being independent of activation time annotation, the activation search feature identified the isthmus where the automatically annotated map did not clearly indicate it (Figure 5, Online Videos 4 and 5). In 4 of these cases, initial unsuccessful ablation lesions based on the unannotated map were in a different location to where the isthmus was subsequently identified using the algorithm.
In the remaining 2 LV maps (both ICM) where the algorithm failed to identify the critical isthmus, entrainment and further examination of the map, including manual annotation where necessary, demonstrated that the isthmus was not endocardial (Figure 6A). An epicardial approach was not undertaken for clinical reasons. We also noted that in 7 of 27 VT activation maps (26%), at least 1 blind loop was present. In 4 of these cases, the algorithm also highlighted this loop, but entrainment was able to differentiate this from the true isthmus (Figure 6B, Online Video 6).
The novel Lumipoint algorithm set allows maps to be automatically reannotated within specific windows of interest. Specifically it highlights: all potentials lying within a certain timing window of interest; fractionated potentials with components lying within a certain timing window of interest; regions of the map that correspond to a minimum amount of activating tissue (Central Illustration).
Post-infarct VT is associated with channels of surviving myocardium within scar, characterized by fractionated and low-amplitude signals. Conventional automated algorithms experience difficulties differentiating the delayed local signal of conduction within the scar from the initial farfield signal generated by surrounding healthy tissue. Adjustment of the voltage threshold has been used to identify channels of preserved myocardium within scar, but because voltage is annotated to the electrogram peak, these regions are usually formed based on farfield signal (6). Manual tagging of abnormal potentials or manual adjustment of activation time can highlight local activation through scar, but these manual procedures are challenging with high-density point collection. A case report has previously used the ability to change the window of interest to automatically map His potentials (7), and this technique can be generalized to other phases of the cycle. Adjusting the mapping window post-QRS phase has been used to find sites of late activation (8).
However, annotation of a single activation time is suboptimal at sites with fractionated or multiple late potentials (9). The Lumipoint algorithm has the advantage of using signal information across the whole mapping window rather than only the peak signal. In highlighting regions with activity in the post-QRS phase of a substrate map, a late potential map can be automatically generated, which corresponds well with manual annotation. Furthermore, specific areas showing late and fractionated signals can be automatically annotated using the complex activation search feature. This has the potential to allow more rapid mapping, as points do not have to be manually annotated, and reduces the risk of missing some regions.
Previous attempts have been made to use information generated from the whole electrogram trace to aid differentiation of nearfield from farfield signals. Ripple mapping displays each electrogram as a dynamic bar on the cardiac surface and may aid visualization of conduction channels within the ventricular scar (10), but this technique requires experience to interpret the resultant maps.
The Lumipoint algorithm may also identify the putative isthmus of a VT circuit by highlighting the region of the map corresponding to a minimum of activating tissue. VT circuits are often found to occur in regions of partial or even dense scar (11). In these cases, where the circuit has low amplitude nearfield signals, the farfield signal is often automatically annotated, which may mask the true isthmus. This algorithm may aid delineation of the isthmus to guide ablation without manual reannotation.
The algorithm is based solely on anatomical and timing characteristics of the circuit; it will therefore identify any region where the electrogram timing falls within a narrow geographical area. This may also occur with blind loops, and therefore entrainment mapping is still required to differentiate these regions once the algorithm has identified a putative isthmus.
Whereas the majority of our cases were ischemic in etiology, we did also examine substrate and activation maps of patients with DCM. We found that the Lumipoint algorithms worked equally well in annotating late and fractionated potentials and in identifying the VT isthmus as for ICM. The epicardium may play a critical role in providing substrate for re-entrant circuits, especially in DCM. The Lumipoint algorithms were able to demonstrate lack of critical isthmus endocardially and identify the isthmus epicardially in these patients.
We have chosen to apply the algorithms to a series of VT ablation cases. However, the algorithms could equally be used for ablation of other rhythms such as atrial tachycardia. This is the subject of ongoing work by our group.
The case series represents a selection that has relatively stable mappable VT, with a relatively long cycle length. These patients tend to have relatively large macro re-entrant tachycardia circuits. However, the principles that the algorithms use can be applied to any set of electrograms, whether this be macro-re-entrant, micro-re-entrant, or focal.
As these algorithms were applied retrospectively, we cannot provide data that these algorithms improve detection of arrhythmia substrate or conduction gaps. We report the first worldwide use of these algorithms, and as such, this was a limited first-in-man feasibility study with relatively small patient numbers. Further clinical evaluation is necessary to validate these findings and to use these algorithms prospectively to assess whether they may improve the outcome of ablation procedures.
The Lumipoint algorithm automatically highlights areas with electrograms having specific characteristics or timings. This can identify late and fractionated potentials and regions that exhibit discontinuous activation, as well as the isthmus of a VT circuit. These features may enhance human interpretation of the electrogram signals during a case, particularly where the circuit lies in partial scar with low amplitude nearfield signals and potentially allow a more targeted ablation strategy.
COMPETENCY IN MEDICAL KNOWLEDGE: The novel Lumipoint algorithm set allows maps to be automatically reannotated within specific windows of interest to identify late and/or fractionated potentials, as well as the putative isthmuses of re-entrant circuits.
TRANSLATIONAL OUTLOOK: These features may act to enhance human interpretation of the electrogram signals during a case and therefore allow easier and quicker comprehension of maps and decision making regarding ablation strategy.
This research was supported by IHU LIRYC grant ANR-10-IAHU-04. Dr. Meyer has received speaking honoraria from Boston Scientific and Abbott; and has served on the advisory board of Biosense Webster. Drs. Derval, Denis, Jaïs, and Sacher, have received modest consulting fees and speaking honoraria from Boston Scientific. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
All authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the JACC: Clinical Electrophysiology author instructions page.
- Abbreviations and Acronyms
- dilated cardiomyopathy
- ischemic cardiomyopathy
- local abnormal ventricular activity
- left ventricle
- sinus rhythm
- ventricular tachycardia
- Received November 6, 2018.
- Revision received January 8, 2019.
- Accepted January 17, 2019.
- 2019 American College of Cardiology Foundation
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