Distinct Substrates of Idiopathic Ventricular Fibrillation Revealed by Arrhythmia Characteristics on Implantable Cardioverter-Defibrillator.

BACKGROUND: Idiopathic ventricular fibrillation (IVF) can be associated with undetected distinct conditions such as microstructural cardiomyopathic alterations (MiCM) or Purkinje (Purk) activities with structurally normal hearts. OBJECTIVE: This study sought to evaluate the characteristics of recurrent VF recorded on implantable defibrillator electrograms, associated with these substrates. METHODS: This was a multicenter collaboration study. At 32 centers, we selected patients with an initial diagnosis of IVF and recurrent arrhythmia at follow-up without antiarrhythmic drugs, in whom mapping demonstrated Purk or MiCM substrate. We analyzed variables related to previous ectopy, sinus rate preceding VF, trigger, and initial VF cycle lengths. Logistic regression with cross validation was used to evaluate the performance of criteria to discriminate Purk or MiCM substrates. RESULTS: Among 95 patients (35 women, age 35 ± 11 years) meeting the inclusion criteria, IVF was associated with MiCM in 41 and Purk in 54 patients. A total of 117 arrhythmia recurrences including 91% VF were recorded on defibrillator. Three variables were mostly discriminant. Sinus tachycardia (≤570 ms) was more frequent in MiCM (35.9% vs 13.4%, P = 0.014) whereas short-coupled (<350 ms) triggers were most frequent in Purk-related VF (95.5% vs 23.1%, P = 0.001), which also had shorter VFCLs (182 ± 15 ms vs 215 ± 24 ms, P < 0.001).The multivariable combination provided the highest prediction (accuracy = 0.93 ± 0.05, range 0.833-1.000), discriminating 81% of IVF substrates with a high probability (>80%). Ectopy were inconsistently present before VF. CONCLUSIONS: Characteristics of arrhythmia recurrences on implantable cardioverter- defibrillator provide phenotypic markers of the distinct and hidden substrates underlying IVF. These findings have significant clinical and genetic implications.

Hypersynchrony in sarcomeric hypertrophic cardiomyopathy: description and mechanistic approach using multimodal electro-mechanical non-invasive cartography (HSYNC study).

Background: Little is known about left ventricular (LV) sequences of contraction and electrical activation in hypertrophic cardiomyopathy (HCM). A better understanding of the underlying relation between mechanical and electrical activation may allow the identification of predictive response criteria to right ventricular DDD pacing in obstructive patients. Objective: To describe LV mechanical and electrical activation sequences in HCM patients compared to controls. Materials and methods: We prospectively studied, in 40 HCM patients (20 obstructive and 20 non-obstructive) and 20 healthy controls: (1) mechanical activation using echocardiography at rest and cardiac magnetic resonance imaging, (2) electrical activation using 3-dimensional electrocardiographic mapping (ECM). Results: In echocardiography, healthy controls had a physiological apex-to-base delay (ABD) during contraction (23.8 ± 16.2 ms). Among the 40 HCM patients, 18 HCM patients presented a loss of this ABD (<10 ms, defining hypersynchrony) more frequently than controls (45% vs. 5%, p = 0.017). These patients had a lower LV end-diastolic volume (71.4 ± 9.7 ml/m2 vs. 82.4 ± 14.8 ml/m2, p = 0.01), lower native T1 values (988 ± 32 ms vs. 1,028 ± 39 ms, p = 0.001) and tended to have lower LV mass (80.7 ± 23.7 g/m2 vs. 94.5 ± 25.3 g/m2, p = 0.08) compared with HCM patients that had a physiological contraction sequence. There was no significant relation between ABD and LV outflow tract obstruction. While HCM patients with a physiological contraction sequence presented an ECM close to those encountered in controls, patients with a loss of ABD presented a particular pattern of ECM with the first potential more frequently occurring in the postero-basal region. Conclusion: The LV contraction sequence can be modified in HCM patients, with a loss of the physiological ABD, and is associated with smaller LV dimensions and a particular pattern of ECM. Further research is needed to determine whether this pattern is related to an electrical substrate or is the consequence of the hypertrophied heart's specific geometry. Clinical trial registration: ClinicalTrial.gov: NCT02559726.

Expert opinion on mexiletine treatment in adult patients with myotonic dystrophy.

In France, mexiletine - a class I antiarrhythmic drug - can be prescribed for the symptomatic treatment of myotonia of the skeletal muscles in adult patients with myotonic dystrophy under a compassionate use programme. Mexiletine is used according to its summary of product characteristics, which describes its use for myotonia treatment in adult patients with non-dystrophic myotonia, a different neuromuscular condition without cardiac involvement. A cardiac assessment is required prior to initiation and throughout treatment due to potential proarrhythmic effects. The presence of conduction system disease, the most common cardiac manifestation of myotonic dystrophy, mandates repeated cardiac evaluations in patients with this condition, and becomes even more important when they are given mexiletine. A group of experts, including three neurologists and five cardiologists from French neuromuscular reference centres, were involved in a task force to develop a treatment algorithm to guide mexiletine use in myotonic dystrophy. The recommendations are based on data from a literature review of the safety of mexiletine-treated patients with myotonic dystrophy, the compassionate use protocol for mexiletine and the personal clinical experience of the experts. The main conclusion of the expert group is that, although existing safety data in mexiletine-treated patients with myotonic dystrophy are reassuring, cardiac assessments should be reinforced in such patients compared with mexiletine-treated patients with non-dystrophic myotonia. This expert opinion to guide mexiletine treatment in patients with myotonic dystrophy should help to reduce the risk of severe adverse events and facilitate interactions between specialists involved in the routine care of patients with myotonic dystrophy.

Position paper on sustainability in cardiac pacing and electrophysiology from the Working Group of Cardiac Pacing and Electrophysiology of the French Society of Cardiology.

Sustainability in healthcare, particularly within the domain of cardiac electrophysiology, assumes paramount importance for the near future. The escalating environmental constraints encountered necessitate a proactive approach. This position paper aims to raise awareness among physicians, spark critical inquiry and identify potential solutions to enhance the sustainability of our practice. Reprocessing of single-use medical devices has emerged as a potential solution to mitigate the environmental impact of electrophysiology procedures, while also offering economic advantages. However, reprocessing remains unauthorized in certain countries. In regions where it is possible, stringent regulatory standards must be adhered to, to ensure patient safety. It is essential that healthcare professionals, policymakers and manufacturers collaborate to drive innovation, explore sustainable practices and ensure that patient care remains uncompromised in the face of environmental challenges. Ambitious national/international programmes of disease prevention should be the cornerstone of the strategy. It is equally vital to implement immediate actions, as delineated in this position paper, to bring about tangible change quickly.

Local VA index for the differential diagnosis of supraventricular tachycardia.

BACKGROUND: Differentiating between atypical atrioventricular nodal reentrant tachycardia (AVNRT) and orthodromic reciprocating tachycardia utilizing a septal accessory pathway is a complex challenge. OBJECTIVE: The purpose of this study was to describe the "local VA index," a straightforward method based on signals from the coronary sinus catheter, to distinguish between these arrhythmias during tachycardia and entrainment. The ventriculoatrial (VA) interval on the coronary sinus catheter is measured during tachycardia and entrainment, at the site of earliest atrial activity. The difference between these 2 situations defines the "local VA index." We also propose a mechanism to clarify the limitations of historical pacing maneuvers, such as postpacing interval minus tachycardia cycle length (PPI-TCL) and stimulus-atrial interval minus ventriculoatrial interval (SA-VA), by examining nodal decrement and intraventricular conduction delay. METHODS: In a retrospective study of 75 patients referred for supraventricular tachycardia evaluation, 37 were diagnosed with atrioventricular reentrant tachycardia (AVRT) with orthodromic reciprocating tachycardia, and 38 with AVNRT (27 typical, 11 atypical). RESULTS: In comparison to AVRT patients, AVNRT patients exhibited longer PPI-TCL (176 ± 47 ms vs 113 ± 42 ms; P <.01) and SA-VA (138 ± 47 ms vs 64 ± 28 ms; P <.01). The AVRT group had mean local VA index of -1 ± 13 ms, whereas the AVNRT group had a significantly longer index of 91 ± 46 ms (P <.01). An optimal threshold for differentiation was a local VA index of 40 ms. Importantly, there was no significant correlation between pacing cycle length and nodal decrement as well as intraventricular delay related to pathway location. This interindividual variability might explain misleading interpretations of PPI-TCL and SA-VA. CONCLUSION: This novel approach is advantageous because of its simplicity and effectiveness, requiring only 2 diagnostic catheters. A local VA interval difference <40 ms provides a clear distinction for AVRT.

Triggers of Ventricular Fibrillation in Patients With Inferolateral J-Wave Syndrome.

BACKGROUND: There are few data on ventricular fibrillation (VF) initiation in patients with inferolateral J waves. OBJECTIVES: This multicenter study investigated the characteristics of triggers initiating spontaneous VF in inferolateral J-wave syndrome. METHODS: A total of 31 patients (age 37 ± 14 years, 24 male) with spontaneous VF episodes associated with inferolateral J waves were evaluated to determine the origin and characteristics of triggers. The J-wave pattern was recorded in inferior leads in 11 patients, lateral leads in 3, and inferolateral leads in 17. RESULTS: The VF triggers (n = 37) exhibited varying QRS durations (176 ± 21 milliseconds, range 119-219 milliseconds) and coupling intervals (339 ± 46 milliseconds, range 250-508 milliseconds) with a right (70%) or left (30%) bundle branch block (BBB) pattern. Trigger patterns were associated with J-wave location: left BBB triggers with inferior J waves and right BBB triggers with lateral J waves. Electrophysiologic study was performed for 22 VF triggers in 19 patients. They originated from the left or right Purkinje system in 6 and from the ventricular myocardium in 10 and were undetermined in 6. Purkinje vs myocardial triggers showed distinct electrocardiographic characteristics in coupling interval and QRS-complex duration and morphology. Abnormal epicardial substrate associated with fragmented electrograms was identified in 9 patients, with triggers originating from the same region in 7 patients. Catheter ablation resulted in VF suppression in 15 patients (79%). CONCLUSIONS: VF initiation in inferolateral J-wave syndrome is associated with significant individual heterogeneity in trigger characteristics. Myocardial triggers have electrocardiographic features distinct from Purkinje triggers, and their origin often colocalizes with an abnormal epicardial substrate.

Cardiac structure discontinuities revealed by ex-vivo microstructural characterization. A focus on the basal inferoseptal left ventricle region.

BACKGROUND: While the microstructure of the left ventricle (LV) has been largely described, only a few studies investigated the right ventricular insertion point (RVIP). It was accepted that the aggregate cardiomyocytes organization was much more complex due to the intersection of the ventricular cavities but a precise structural characterization in the human heart was lacking even if clinical phenotypes related to right ventricular wall stress or arrhythmia were observed in this region. METHODS: MRI-derived anatomical imaging (150 µm3) and diffusion tensor imaging (600 µm3) were performed in large mammalian whole hearts (human: N = 5, sheep: N = 5). Fractional anisotropy, aggregate cardiomyocytes orientations and tractography were compared within both species. Aggregate cardiomyocytes orientation on one ex-vivo sheep whole heart was then computed using structure tensor imaging (STI) from 21 µm isotropic acquisition acquired with micro computed tomography (MicroCT) imaging. Macroscopic and histological examination were performed. Lastly, experimental cardiomyocytes orientation distribution was then compared to the usual rule-based model using electrophysiological (EP) modeling. Electrical activity was modeled with the monodomain formulation. RESULTS: The RVIP at the level of the inferior ventricular septum presented a unique arrangement of aggregate cardiomyocytes. An abrupt, mid-myocardial change in cardiomyocytes orientation was observed, delimiting a triangle-shaped region, present in both sheep and human hearts. FA's histogram distribution (mean ± std: 0.29 ± 0.06) of the identified region as well as the main dimension (22.2 mm ± 5.6 mm) was found homogeneous across samples and species. Averaged volume is 0.34 cm3 ± 0.15 cm3. Both local activation time (LAT) and morphology of pseudo-ECGs were strongly impacted with delayed LAT and change in peak-to-peak amplitude in the simulated wedge model. CONCLUSION: The study was the first to describe the 3D cardiomyocytes architecture of the basal inferoseptal left ventricle region in human hearts and identify the presence of a well-organized aggregate cardiomyocytes arrangement and cardiac structural discontinuities. The results might offer a better appreciation of clinical phenotypes like RVIP-late gadolinium enhancement or uncommon idiopathic ventricular arrhythmias (VA) originating from this region.

Efficient Patient-Specific Simulations of Ventricular Tachycardia Based on Computed Tomography-Defined Wall Thickness Heterogeneity.

BACKGROUND: Electrophysiological mapping of ventricular tachycardia (VT) is tedious and poorly reproducible. Substrate analysis on imaging cannot explicitly display VT circuits. OBJECTIVES: This study sought to introduce a computed tomography-based model personalization approach, allowing for the simulation of postinfarction VT in a clinically compatible time frame. METHODS: In 10 patients (age 65 ± 11 years, 9 male) referred for post-VT ablation, computed tomography-derived wall thickness maps were registered to 25 electroanatomical maps (sinus rhythm, paced, and VT). The relationship between wall thickness and electrophysiological characteristics (activation-recovery interval) was analyzed. Wall thickness was then employed to parameterize a fast and tractable organ-scale wave propagation model. Pacing protocols were simulated from multiple sites to test VT induction in silico. In silico VTs were compared to VT circuits mapped clinically. RESULTS: Clinically, 6 different VTs could be induced with detailed maps in 9 patients. The proposed model allowed for fast simulation (median: 6 min/pacing site). Simulations of steady pacing (600 milliseconds) from 100 different sites/patient never triggered any arrhythmia. Applying S1-S2 or S1-S2-S3 induction schemes allowed for the induction of in silico VTs in the 9 of 10 patients who were clinically inducible. The patient who was not inducible clinically was also noninducible in silico. A total of 42 different VTs were simulated (4.2 ± 2 per patient). Six in silico VTs matched a VT circuit mapped clinically. CONCLUSIONS: The proposed framework allows for personalized simulations in a matter of hours. In 6 of 9 patients, simulations show re-entrant patterns matching intracardiac recordings.

Abnormal Atrial Potentials Recorded During Sinus Rhythm or Pacing Represent Substrates for Reentrant Atrial Tachycardia.

BACKGROUND: Abnormal atrial potentials (AAPs) recorded during sinus rhythm/atrial pacing may indicate areas of slow conduction capable of supporting reentrant atrial tachycardia (AT). Therefore, we sought to examine the relationship between AAPs and AT circuits. METHODS: One hundred twenty-three reentrant ATs in 104 patients were analyzed. AAPs, consisting of fragmented potentials and split potentials, were assessed using the Rhythmia LUMIPOINT algorithm. RESULTS: There was 93±13% overlap between areas with AAPs during sinus rhythm/atrial pacing and areas of slow conduction along the reentry circuit during AT. The cumulative area of AAPs was smaller in patients with localized-reentrant ATs compared with anatomic macro-reentrant ATs (20.0 [14.6-30.5] versus 28.9 [21.8-35.6] cm2; P=0.021). Patients with perimitral ATs had larger areas of AAPs on the lateral wall whereas patients with roof-dependent ATs had larger areas of AAPs on the roof and posterior wall (P≤0.018 for all comparisons). The patchy scar that was associated with localized-reentrant AT exhibited a larger area of AAPs at its periphery than the scar that did not participate in localized-reentrant AT (3.1 [2.4-4.5] versus 1.0 [0.7-1.6] cm2; P<0.001). CONCLUSIONS: AAPs recorded during sinus rhythm/atrial pacing are associated with areas of slow conduction during reentrant AT. The burden and distribution of AAPs may provide actionable insights into AT circuit features, including in cases in which ATs are difficult to map.

Electrophysiologic Determinants of Isoelectric Intervals on Surface Electrocardiograms During Atrial Tachycardia: Insights From High-Density Mapping.

BACKGROUND: Substrate abnormalities can alter atrial activation during atrial tachycardias (ATs) thereby influencing AT-wave morphology on the surface electrocardiogram. OBJECTIVES: This study sought to identify determinants of isoelectric intervals during ATs with complex atrial activation patterns. METHODS: High-density activation maps of 126 ATs were studied. To assess the impact of the activated atrial surface on the presence of isoelectric intervals, this study measured the minimum activated area throughout the AT cycle, defined as the smallest activated area within a 50-millisecond period, by using signal processing algorithms (LUMIPOINT). RESULTS: ATs with isoelectric intervals (P-wave ATs) included 23 macro-re-entrant ATs (40%), 26 localized-re-entrant ATs (46%), and 8 focal ATs (14%), whereas those without included 46 macro-re-entrant ATs (67%), 21 localized-re-entrant ATs (30%), and 2 focal ATs (3%). Multivariable regression identified smaller minimum activated area and larger very low voltage area as independent predictors of P-wave ATs (OR: 0.732; 95% CI: 0.644-0.831; P < 0.001; and OR: 1.042; 95% CI: 1.006-1.080; P = 0.023, respectively). The minimum activated area with the cutoff value of 10 cm2 provided the highest predictive accuracy for P-wave ATs with sensitivity, specificity, and positive and negative predictive values of 96%, 97%, 97%, and 95%, respectively. In re-entrant ATs, smaller minimum activated area was associated with lower minimum conduction velocity within the circuit and fewer areas of delayed conduction outside of the circuit (standardized ß: 0.524; 95% CI: 0.373-0.675; P < 0.001; and standardized ß: 0.353; 95% CI: 0.198-0.508; P < 0.001, respectively). CONCLUSIONS: Reduced atrial activation area and voltage were associated with isoelectric intervals during ATs.

Impact of filter configurations on bipolar EGMs: An optimal filter setting for identifying VT substrates.

BACKGROUND: The impact of filtering on bipolar electrograms (EGMs) has not been systematically examined. We tried to clarify the optimal filter configuration for ventricular tachycardia (VT) ablation. METHODS: Fifteen patients with VT were included. Eight different filter configurations were prospectively created for the distal bipoles of the ablation catheter: 1.0-250, 10-250, 100-250, 30-50, 30-100, 30-250, 30-500, and 30-1000 Hz. Pre-ablation stable EGMs with good contact (contact force > 10 g) were analyzed. Baseline fluctuation, baseline noise, bipolar peak-to-peak voltage, and presence of local abnormal ventricular activity (LAVA) were compared between different filter configurations. RESULTS: In total, 2276 EGMs with multiple bipolar configurations in 246 sites in scar and border areas were analyzed. Baseline fluctuation was only observed in the high-pass filter of (HPF) ≤ 10 Hz (p < .001). Noise level was lowest at 30-50 Hz (0.018 [0.012-0.029] mV), increased as the low-pass filter (LPF) extended, and was highest at 30-1000 Hz (0.047 [0.041-0.061] mV) (p < .001). Conversely, the HPF did not affect the noise level at ≤30 Hz. As the HPF extended to 100 Hz, bipolar voltages significantly decreased (p < .001), but were not affected when the LPF was extended to ≥100 Hz. LAVAs were most frequently detected at 30-250 Hz (207/246; 84.2%) and 30-500 Hz (208/246; 84.6%), followed by 30-1000 Hz (205/246; 83.3%), but frequently missed at LPF ≤ 100 Hz or HPF ≤ 10 Hz (p < .001). A 50-Hz notch-filter reduced the bipolar voltage by 43.9% and LAVA-detection by 34.5% (p < .0001). CONCLUSION: Bipolar EGMs are strongly affected by filter settings in scar/border areas. In all, 30-250 or 30-500 Hz may be the best configuration, minimizing the baseline fluctuation, baseline noise, and detecting LAVAs. Not applying the 50-Hz notch filter may be beneficial to avoid missing VT substrate.

Left Ventricular Abnormal Substrate in Brugada Syndrome.

BACKGROUND: Slow-conductive structural abnormalities located in the epicardium of the right ventricle (RV) underlie Brugada syndrome (BrS). The extent of such substrate in the left ventricle (LV) has not been investigated. OBJECTIVES: This study sought to characterize the extent of epicardial substrate abnormalities in BrS. METHODS: We evaluated 22 consecutive patients (mean age 46 ± 11 years, 21 male) referred for recurrent ventricular arrhythmias (mean 10 ± 13 episodes) in the setting of BrS. The patients underwent clinical investigations and wide genetic screening to identify SCN5A mutations and common risk variants. High-density biventricular epicardial mapping was performed to detect prolonged (>70 ms) fragmented electrograms, indicating abnormal substrate area. RESULTS: All patients presented with abnormal substrate in the epicardial anterior RV (27 ± 11 cm2). Abnormal substrate was also identified on the LV epicardium in 10 patients (45%), 9 at baseline and 1 after ajmaline infusion, covering 15 ± 11 cm2. Of these, 4 had severe LV fascicular blocks. Patients with LV substrate had a longer history of arrhythmia (11.4 ± 6.7 years vs 4.3 ± 4.3 years; P = 0.003), longer PR (217 ± 24 ms vs 171 ± 14 ms; P < 0.001) and HV (60 ± 12 ms vs 46 ± 5 ms; P = 0.005) intervals, and abnormal substrate also extending into the inferior RV (100% vs 33%; P = 0.001). SCN5A mutation was present in 70% of patients with LV substrate (vs 25%; P = 0.035). SCN5A BrS patients with recurrent ventricular arrhythmias present a higher polygenic risk score compared with a nonselected BrS population (median of differences: -0.86; 95% CI: -1.48 to -0.27; P = 0.02). CONCLUSIONS: A subset of patients with BrS present an abnormal substrate extending onto the LV epicardium and inferior RV that is associated with SCN5A mutations and multigenic variants.

Detailed analysis of tachycardia cycle length aids diagnosis of the mechanism and location of atrial tachycardias.

AIMS: Although the mechanism of an atrial tachycardia (AT) can usually be elucidated using modern high-resolution mapping systems, it would be helpful if the AT mechanism and circuit could be predicted before initiating mapping. OBJECTIVE: We examined if the information gathered from the cycle length (CL) of the tachycardia can help predict the AT-mechanism and its localization. METHODS: One hundred and thirty-eight activation maps of ATs including eight focal-ATs, 94 macroreentrant-ATs, and 36 localized-ATs in 95 patients were retrospectively reviewed. Maximal CL (MCL) and minimal CL (mCL) over a minute period were measured via a decapolar catheter in the coronary sinus. CL-variation and beat-by-beat CL-alternation were examined. Additionally, the CL-respiration correlation was analysed by the RhythmiaTM system. : Both MCL and mCL were significantly shorter in macroreentrant-ATs [MCL = 288 (253-348) ms, P = 0.0001; mCL = 283 (243-341) ms, P = 0.0012], and also shorter in localized-ATs [MCL = 314 (261-349) ms, P = 0.0016; mCL = 295 (248-340) ms, P = 0.0047] compared to focal-ATs [MCL = 506 (421-555) ms, mCL = 427 (347-508) ms]. An absolute CL-variation (MCL-mCL) < 24 ms significantly differentiated re-entrant ATs from focal-ATs with a sensitivity = 96.9%, specificity = 100%, positive predictive value (PPV) = 100%, and negative predictive value (NPV) = 66.7%. The beat-by-beat CL-alternation was observed in 10/138 (7.2%), all of which showed the re-entrant mechanism, meaning that beat-by-beat CL-alternation was the strong sign of re-entrant mechanism (PPV = 100%). Although the CL-respiration correlation was observed in 28/138 (20.3%) of ATs, this was predominantly in right-atrium (RA)-ATs (24/41, 85.7%), rather than left atrium (LA)-ATs (4/97, 4.1%). A positive CL-respiration correlation highly predicted RA-ATs (PPV = 85.7%), and negative CL-respiration correlation probably suggested LA-ATs (NPV = 84.5%). CONCLUSION: Detailed analysis of the tachycardia CL helps predict the AT-mechanism and the active AT chamber before an initial mapping.

Omnipolar versus bipolar mapping to guide ventricular tachycardia ablation.

BACKGROUND: Omnipolar technology (OT) was recently proposed to generate electroanatomic voltage maps with orientation-independent electrograms. We describe the first cohort of patients undergoing ventricular tachycardia (VT) ablation guided by OT. OBJECTIVE: The purpose of this study was to compare omnipolar and bipolar high-density maps with regard to voltage amplitude, late potential (LP) annotation, and isochronal late activation mapping distribution. METHODS: A total of 24 patients (16 [66%] ischemic cardiomyopathy and 12 [50%] redo cases) underwent VT ablation under OT guidance. Twenty-seven sinus rhythm substrate maps and 10 VT activation maps were analyzed. Omnipolar and bipolar (HD Wave Solution algorithm, Abbott, Abbott Park, IL) voltages were compared. Areas of LPs were correlated with the VT isthmus areas, and late electrogram misannotation was evaluated. Deceleration zones based on isochronal late activation maps were analyzed by 2 blinded operators and compared to the VT isthmuses. RESULTS: OT maps had higher point density (13.8 points/cm2 vs 8.0 points/cm2). Omnipolar points had 7.1% higher voltages than bipolar points within areas of dense scar and border zone. The number of misannotated points was significantly lower for OT maps (6.8% vs 21.9%; P = .01), showing comparable sensitivity (53% vs 59%) but higher specificity (79% vs 63%). The sensitivity and specificity of detection of the VT isthmus in the deceleration zones were, respectively, 75% and 65% for OT and 35% and 55% for bipolar mapping. At 8.4 months, 71% freedom from VT recurrence was achieved. CONCLUSION: OT is a valuable tool for guiding VT ablation, providing more accurate identification of LPs and isochronal crowding due to slightly higher voltages.

Artificial intelligence for detection of ventricular oversensing: Machine learning approaches for noise detection within nonsustained ventricular tachycardia episodes remotely transmitted by pacemakers and implantable cardioverter-defibrillators.

BACKGROUND: Pacemakers (PMs) and implantable cardioverter-defibrillators (ICDs) increasingly automatically record and remotely transmit nonsustained ventricular tachycardia (NSVT) episodes, which may reveal ventricular oversensing. OBJECTIVES: We aimed to develop and validate a machine learning algorithm that accurately classifies NSVT episodes transmitted by PMs and ICDs in order to lighten health care workload burden and improve patient safety. METHODS: PMs or ICDs (Boston Scientific, St Paul, MN) from 4 French hospitals with ≥1 transmitted NSVT episode were split into 3 subgroups: training set, validation set, and test set. Each NSVT episode was labeled as either physiological or nonphysiological. Four machine learning algorithms-2DTF-CNN, 2D-DenseNet, 2DTF-VGG, and 1D-AgResNet-were developed using training and validation data sets. Accuracies of the classifiers were compared with an analysis of the remote monitoring team of the Bordeaux University Hospital using F2 scores (favoring sensitivity over predictive positive value) using an independent test set. RESULTS: A total of 807 devices transmitted 10,471 NSVT recordings (82% ICD; 18% PM), of which 87 devices (10.8%) transmitted 544 NSVT recordings with nonphysiological signals. The classification by the remote monitoring team resulted in an F2 score of 0.932 (sensitivity 95%; specificity 99%) The 4 machine learning algorithms showed high and comparable F2 scores (2DTF-CNN: 0.914; 2D-DenseNet: 0.906; 2DTF-VGG: 0.863; 1D-AgResNet: 0.791), and only 1D-AgResNet had significantly different labeling from that of the remote monitoring team. CONCLUSION: Machine learning algorithms were accurate in detecting nonphysiological signals within electrograms transmitted by PMs and ICDs. An artificial intelligence approach may render remote monitoring less resourceful and improve patient safety.