Ventricular Tachycardia Ablation Targets Research Articles

Determining physiological VT ablation targets in the era of early VT ablation

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Professor Nanthakumar is a recipient of the Mid-career Investigator Award from the Heart & Stroke Foundation of Ontario. Background Ablation targets in the era of early ventricular tachycardia (VT) ablation will likely be driven by substrate-based physiological target approaches rather than activation mapping. Decrement evoked potentials (DeEP) have been co-localized to the diastolic VT circuit and are used as a method to perform VT ablation when VT cannot or should not be induced.1 Traditionally these potentials are evoked by a single extrastimulus. The incremental utility of a second extrastimulus in detecting these potentials has not been evaluated. Purpose We studied the utility of the second extra stimulus (S3) in detecting substrate ablation over the first extra stimulus (S2) following a drivetrain (S1) of 8 beats at 600ms. Methods DeEP was measured as the time difference between the pacing stimulus and the nearfield local activation delay on the bipolar electrogram during the S1 drivetrain and after the S2 or S3 respectively. Decrement of ≥10ms was considered a positive DeEP site. A total of 157 sites from 6 patients with VT were analysed. The incremental value of S3-induced DeEP was compared to the S2-induced DeEP. Results The mean decrement was significantly greater on the S3 compared to the S2 (41.8±35.6ms for S3 vs 25.8±20.4ms for S2, P <0.0001). The mean incremental value of the S3 was 15.9ms (95% CI, 11.5-20.3ms). From the 157 intracardiac electrograms studied, 79.1% had a positive DeEP with S2 alone. At the same electrode locations, an additional S3 evoked DeEP in 82.2% of sites. Conclusion When physiological substrate is present on the first extra stimulus, the second extra stimulus magnifies the identification of the target. However, we found in our study that the second extrastimulus uncovered a hidden arrhythmogenic substrate in only 3.1% additional mapped sites. Consequently, the utility of the second extrastimulus in identification of hidden substrate needs to be balanced with the risk of induction of potentially unstable rhythms.

A method to identify which patients will have VT substrate ablation targets prior to ablation procedure

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Dr Nanthakumar is a recipient of the Mid-career Investigator Award from the Heart & Stroke Foundation of Ontario Background Recent trials in ventricular tachycardia (VT) ablation suggest that early ablation could reduce VT burden. A method to predict which patients will have substrate ablation targets based on non-invasive testing prior to the procedure does not exist and could be of value in selecting ideal patients for early VT substrate ablation. Decrement-evoked potential (DeEP) mapping is used to identify VT substrate ablation targets.1 A method for predicting which patients would have DeEP targets on a pre-ablation 12-lead ECG has not yet been developed. Objective To develop a metric to predict the presence of physiological substrate VT ablation targets from the 12-lead ECG. Method 22 electrophysiology (EP) lab VT cases that had undergone DeEP mapping were extracted from the CARTO® 3 system and were analysed retrospectively. For each case, DeEP was calculated by subtracting last component of the nearfield evoked response in the pacing train (S1) from the latest component of the nearfield evoked decremented response of the extra stimulus (S2). By inference, 12-lead ECG prediction was calculated by subtracting the width of the 12-lead surface ECG envelope of S1 from the width of the 12-lead ECG envelope of S2. Cases were divided into three categories: - Cases displaying intracardiac DeEP between 0-10ms – no ablation targets - Cases displaying intracardiac DeEP between 10-50ms – DeEP positive - Cases displaying intracardiac DeEP >50ms – prominent DeEP present Results Out of the 22 cases, 8 were characterised as no ablation targets, 12 as DeEP positive, and 2 as prominent DeEP present. The 12-lead surface ECG measurement means were 3.5±4.6ms for the no ablation target group, 23.2±9.1ms for positive DeEP group, and 80.9±8.1ms for prominent DeEP group. The surface ECG decrement was significantly different P<0.0001 between the three groups. Consequently, we propose that ECG QRS widening of envelope width of 20ms or more may indicate the presence of DeEP targets during invasive mapping. Conclusion It may be possible to detect which patients will have substrate ablation targets based on 12-lead ECG, prior to the VT ablation procedure. Additionally, this prediction rule, based on its association with arrhythmogenic potentials, may be able to predict which ambulatory patients who have not had manifest VT, may be prone to develop VT thus help identify early VT ablation candidates. This concept should be validated in larger data sets and is ideal for training and testing using surface ECG envelopes with artificial intelligence algorithms.

PO-04-190 LONG TERM OUTCOMES OF VENTRICULAR TACHYCARDIA ABLATION IN DESMOPLAKIN ARRHYTHMOGENIC CARDIOMYOPATHY – A MULTICENTER STUDY

Desmoplakin (DSP) pathogenic/likely pathogenic (P/LP) variants have been associated with the development of highly arrhyhtmogenic phenotypes of the spectrum of the arrhythmogenic cardiomyopathy (DSP-ACM). Data addressing arrhythmic outcomes after ventricular tachycardia (VT) ablation in patients (pts) with DSP-ACM are scarce. To report on long-term outcomes of pts with DSP-ACM undergoing VT-ablation All pts with P/LP DSP variant at 8 tertiary academic institutions in North America and Europe undergoing VT ablation were included in the study. Demographic, clinical, and instrumental data, as well as all arrhythmic events including per patient rates of VA episodes/year were collected. Sustained ventricular arrhythmia (VA) episodes (defined as a combination of sustained VT, proper implantable cardioverter defibrillator (ICD) intervention, and ventricular fibrillation episodes) after index procedure were the primary outcome of the study and reported with Kaplan Meyer curves. A per-pt pre- and post- VT ablation paired comparison of VA episodes/year rates was performed as well. Nineteen DSP-ACM pts (29 [25–36] y.o.; 68.4% male; 94.7% probands) referred for VT ablation were included. At the time of index procedures, all patients had a highly arrhythmic profile with a high PVC burden and over 30 different VT morphologies (56.6% right bundle branch block (BBBB); 26.6% left BBB; 16.8% unknown)(Table1). VT ablation targets were located in the LV in 7/19 pts, the RV in 7/19 pts, and both ventricles in 5/19 pts. An epicardial ablation was needed in 14/19 pts. Over a median follow-up of 27 [20–72] months, 10/19 (52.6%) pts experienced recurrent VA episodes (Figure1-PanelA). A significant reduction in per-patient event/year pre- and post- VT ablation was observed (0.50 0.25–0.94] vs 0.14 [0–0.40]; Matched Pair Wilcoxon p=0.009) (Figure1-Panel B). VT ablation in DSP-ACM is effective in significantly reducing the VA burden of the disease. However, it is not uncommon for pts to experience VA recurrences during follow up.

Evaluation of a deep learning-enabled automated computational heart modelling workflow for personalized assessment of ventricular arrhythmias.

Personalized, image-based computational heart modelling is a powerful technology that can be used to improve patient-specific arrhythmia risk stratification and ventricular tachycardia (VT) ablation targeting. However, most state-of-the-art methods still require manual interactions by expert users. The goal of this study is to evaluate the feasibility of an automated, deep learning-based workflow for reconstructing personalized computational electrophysiological heart models to guide patient-specific treatment of VT. Contrast-enhanced computed tomography (CE-CT) images with expert ventricular myocardium segmentations were acquired from 111 patients across five cohorts from three different institutions. A deep convolutional neural network (CNN) for segmenting left ventricular myocardium from CE-CT was developed, trained and evaluated. From both CNN-based and expert segmentations in a subset of patients, personalized electrophysiological heart models were reconstructed and rapid pacing was used to induce VTs. CNN-based and expert segmentations were more concordant in the middle myocardium than in the heart's base or apex. Wavefront propagation during pacing was similar between CNN-based and original heart models. Between most sets of heart models, VT inducibility was the same, the number of induced VTs was strongly correlated, and VT circuits co-localized. Our results demonstrate that personalized computational heart models reconstructed from deep learning-based segmentations even with a small training set size can predict similar VT inducibility and circuit locations as those from expertly-derived heart models. Hence, a user-independent, automated framework for simulating arrhythmias in personalized heart models could feasibly be used in clinical settings to aid VT risk stratification and guide VT ablation therapy. KEY POINTS: Personalized electrophysiological heart modelling can aid in patient-specific ventricular tachycardia (VT) risk stratification and VT ablation targeting. Current state-of-the-art, image-based heart models for VT prediction require expert-dependent, manual interactions that may not be accessible across clinical settings. In this study, we develop an automated, deep learning-based workflow for reconstructing personalized heart models capable of simulating arrhythmias and compare its predictions with that of expert-generated heart models. The number and location of VTs was similar between heart models generated from the deep learning-based workflow and expert-generated heart models. These results demonstrate the feasibility of using an automated computational heart modelling workflow to aid in VT therapeutics and has implications for generalizing personalized computational heart technology to a broad range of clinical centres.

Automated Identification of Ventricular Tachycardia Ablation Targets: Multicenter Validation and Workflow Characterization.

Decrement evoked potentials (EPs) (DeEPs) constitute an accepted method to identify physiological ventricular tachycardia (VT) ablation targets without inducing VT. The feasibility of automated software (SW) in the detection of arrhythmogenic VT substrate has been documented. However, multicenter validation of automated SW and workflow has yet to be characterized. The objective of this study was to describe the functionality of a novel DeEP SW (Biosense Webster, Diamond Bar, CA, USA) and evaluate the independent performance of the automated algorithm using multicenter data. VT ablation cases were performed in the catheterization laboratory and retrospectively analyzed using the DeEP SW. The algorithm indicated and mapped DeEPs by first identifying capture in surface electrocardiograms (ECGs). Once capture was confirmed, the EPs of S1 paces were detected. The algorithm checked for the stability of S1 EPs by comparing the last 3 of the 8 morphologies and attributing standard deviation values. The extra-stimulus EP was then detected by comparing it to the S1 EP. Once detected, the DeEP value was computed from the extra-stimulus and displayed as a sphere on a voltage map. A total of 5,885 DeEP signals were extracted from 21 substrate mapping cases conducted at 3 different centers (in Spain, Canada, and Australia). A gold standard was established from ECGs manually marked by subject experts. Once the algorithm was deployed, 91.6% of S2 algorithm markings coincided with the gold standard, 1.9% were false-positives, and 0.1% were false-negatives. Also, 6.4% were non-specific DeEP detections. In conclusion, the automated DeEP algorithm identifies and displays DeEP points, revealing VT substrates in a multicenter validation study. The automation of identification and mapping display is expected to improve efficiency.

In-silico pace-mapping using a detailed whole torso model and implanted electronic device electrograms for more efficient ablation planning

BackgroundPace-mapping is a commonly used electrophysiological (EP) procedure which aims to identify exit sites of ventricular tachycardia (VT) by matching ventricular activation patterns (assessed by QRS morphology) at specific pacing locations with activation during VT. However, long procedure durations and the need for VT induction render this technique non-optimal.To demonstrate the potential of in-silico pace-mapping, using stored electrogram (EGM) recordings of clinical VT from implanted devices to guide pre-procedural ablation planning. MethodSix scar-related VT episodes were simulated in a 3D torso model reconstructed from computed tomography (CT) imaging data, including three different infarct anatomies mapped from infarcted porcine imaging data. In-silico pace-mapping was performed to localise VT exit sites and isthmuses by using 12-lead electrocardiogram (ECG) signals and different combinations of EGM sensing vectors from implanted devices, through the creation of conventional correlation maps and reference-less maps. ResultsOur in-silico platform was successful in identifying VT exit sites for a variety of different VT morphologies from both ECG correlation maps and corresponding EGM maps, with the latter dependent upon the number of sensing vectors used. We also showed the added utility of both ECG and EGM reference-less pace-mapping for the identification of slow-conducting isthmuses, uncovering the optimal algorithm parameters. Finally, EGM-based pace-mapping was shown to be more dependent upon the mapped surface (epicardial/endocardial), relative to the VT origin. ConclusionsIn-silico pace-mapping can be used along with EGMs from implanted devices to localise VT ablation targets in pre-procedural planning.

668Principal component analysis can identify ventricular regions with highest variability in the arrhythmogenic substrate of ventricular tachycardia patients

Abstract Introduction Left ventricle (LV) substrate can be characterized by imaging modalities providing physiological variables (tissue perfusion, ischemia, etc.) grouped in a complex dataset. Principal Component Analysis (PCA) can identify the dataset variables that best explain its variance. Variables linked to substrate arrhythmogenicity will lead PCA to identify LV regions most influenced by the variables on a LV 3D geometry. Purpose To evaluate whether regions identified by PCA correspond to regions targeted by physicians in a ventricular tachycardia (VT) ablation procedure. Methods Ischemic VT subjects underwent SPECT/CT perfusion imaging (rest and stress) prior to LV voltage mapping with the cardiac mapping system. Co-registration allowed projection of ablation sites onto SPECT/CT geometries. PCA retrospectively analyzed the following dataset: tissue perfusion (rest and stress), tissue ischemia and the local (1cm2 sub-regions) stress-rest difference for: 1) standard deviation (STD) and 2) skewness (Skew). PCA components (PCAc) explaining ≥85% of the total variance were plotted on the LV 3D geometry to display regions highly influenced by the dataset variables (see figure below). Results Ten subjects (9 males, 66 ± 8 years old, LVEF 37 ± 11%) underwent co-registration. In 7/10 subjects, tissue perfusion (in PCAc#1) and ischemia (in PCAc#2) were most influential on LV regions variance. Ischemia and low perfusion (≤40%) areas equaled 32 ± 19 % of the LV with 21 ± 23% of these areas highly involved in the arrhythmogenic substrate (≥75% of explained LV variance). The location of 63 ± 18% of ablation sites were <1 cm from areas explaining ≥50% of LV variance. Conclusion Preliminary results showed that PCA can synthesize the influence of different perfusion derived variables, like tissue perfusion and ischemia, used in SPECT/CT imaging of the LV. Further analysis is needed to confirm whether this could be used to select VT ablation targets. Abstract Figure.

Does Ventricular Tachycardia Ablation Targeting Local Abnormal Ventricular Activity Elimination Reduce Ventricular Fibrillation Incidence?

Various strategies for ablation of ventricular tachycardia (VT) have been described, but their impact on ventricular fibrillation (VF) is largely unknown. The aim of our study was to assess the effect of substrate-based VT ablation targeting local abnormal ventricular activity (LAVA) on recurrent VF events in patients with structural heart disease. A retrospective 2-center study was performed on patients with structural heart disease and both VT and VF, with incident VT ablation procedures targeting LAVAs. Generalized estimating equations with a Poisson loglinear model were used to assess the impact of catheter ablation on VF episodes. The change in VF events before and after catheter ablation was compared with matched controls without ablation. From a total of 686 patients with an incident VT ablation procedure targeting LAVAs, 21 patients (age, 57±14 years; left ventricular ejection fraction, 30±10%) had both VT and VF and met inclusion criteria. A total of 80 VF events were recorded in the implantable cardioverter-defibrillator logs the 6 months preceding ablation. Complete and partial LAVA elimination was achieved in 11 (52%) and 10 (48%) patients, respectively. Catheter ablation was associated with a highly significant reduction in VF recurrences (P<0.0001), which were limited to 3 (14%) patients at 6 months. The total number of VF events thereby decreased from 80 to 3, from a median of 1.0 (range, 1-29) to 0.0 (range, 0-1) in the 6 months before and after ablation, respectively. The reduction in VF events was significantly greater in patients with catheter ablation compared with 21 matched controls during 6-month periods following and preceding a baseline assessment (Poisson β-coefficient, 1.39; P=0.0003). Substrate-guided VT ablation targeting LAVAs may be associated with a significant reduction in recurrent VF, suggesting that VT and VF share overlapping arrhythmogenic substrates in patients with structural heart disease.

5203Ablation of scar-related ventricular tachycardia: paced electrogram feature analysis (PEFA) is a novel and effective substrate based strategy

Abstract Background Ablation of scar related ventricular tachycardia (VT) has been shown to be superior to escalation of drug therapy. However, the incremental benefit remains modest, with 42% experiencing recurrent shocks and 64% appropriate anti-tachycardia pacing (ATP) in the VANISH study. Improved ablation strategies are needed. Paced electrogram feature analysis (PEFA) is a novel substrate based ablation technique. Purpose To investigate the effectiveness of the PEFA based VT ablation technique. Methods A single centre, prospective study. Consecutive cases of scar related VT that had an implantable cardiac defibrillator (ICD) and no prior ablations were recruited. Close coupled pacing was performed at the right ventricular apex and the VT isthmus(es) identified on high density mapping catheters by increased electrogram (EGM) duration and latency. A algorithm was developed to identify the latest EGM component after the S2 pacing artefact,. This millisecond value was displayed on the geometry as a colour (PEFA map) (St Jude Ensite Precision Electroanatomic Mapping). PEFA identified VT isthmus sites were targeted for ablation (Figure 1). Follow up ICD interrogation data was utilized to assess for VT recurrence. Results A total of 20 patients were recruited. These comprised ischaemic cardiomyopathy (CM) (17/20), dilated CM (2/20), and arrhythmogenic CM (1/20), male (18/20), and endocardial only approach (19/20). Mean age was 64.3±11.3 years, ejection fraction 24.4% ± 14.4, and ablation time was 1989.9±1078.1 seconds. Non-inducibility was demonstrated at the end of the case in 18/20. A class I or III anti-arrhythmic drug was continued in 50%. VT recurred in three cases (Day 28,30,55). One death occurred following a stroke on day 181. Mean follow up was 437.5±231.7 days. Figure 1 Conclusion This is the largest study to date on PEFA based VT ablation, the first to include non-ischaemic aetiologies, and reports a longer mean follow up. A high proportion of cases were non-inducible, and low VT recurrence rates were observed. PEFA appears to be a promising tool to guide VT ablation targets. Acknowledgement/Funding This research was funded in part by the Canadian Institute for Health Research (139080) and a grant from St. Jude Medical.

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs’ 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients.

Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia.

Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Catheter-based radiofrequency ablation of cardiac tissue has achieved only modest efficacy, owing to the inaccurate identification of ablation targets by current electrical mapping techniques, which can lead to extensive lesions and to a prolonged, poorly tolerated procedure. Here we show that personalized virtual-heart technology based on cardiac imaging and computational modelling can identify optimal infarct-related VT ablation targets in retrospective animal (5 swine) and human studies (21 patients) and in a prospective feasibility study (5 patients). We first assessed in retrospective studies (one of which included a proportion of clinical images with artifacts) the capability of the technology to determine the minimum-size ablation targets for eradicating all VTs. In the prospective study, VT sites predicted by the technology were targeted directly, without relying on prior electrical mapping. The approach could improve infarct-related VT ablation guidance, where accurate identification of patient-specific optimal targets could be achieved on a personalized virtual heart prior to the clinical procedure.

Imaging of patients with implanted devices and arrhythmia

Expanding implantable cardioverter-defibrillator (ICD) indications and significant morbidity and mortality reduction benefits have resulted in a large number of routine ICD implants with appropriate ICD shocks for ventricular arrhythmias. The side-effects and lack of long-term efficacy of antiarrhythmics have made ventricular tachycardia (VT) ablation an increasingly attractive treatment option. Although cardiac magnetic resonance imaging (CMR) is considered the gold standard technique for imaging of myocardial fibrosis to diagnose and guide VT ablation targets in patients with cardiac arrhythmia, safety concerns and significant artifacts from the devices significantly limit the application of CMR. We discuss how to decrease artifact from cardiac devices and the role of a modified inversion pulse late gadolinium enhancement (LGE) CMR sequence as a useful tool in this setting, and we review techniques, safety protocols and limitations from the perspective of our institution’s experience.