Lluís Mont

Background and Aims: MODULAR ATP is an ongoing trial assessing the efficacy of a subcutaneous implantable cardioverter defibrillator (S-ICD) in communication with a leadless pacemaker (LP) that can deliver bradycardia pacing and antitachycardia pacing. The objective of this study was to assess safety and pacing performance of the investigational LP. Methods: The study enrolled patients with an ICD indication and at high risk for monomorphic ventricular tachycardia. Pacemaker dependent patients were excluded. Primary safety endpoint 2 was the percentage of patients free from major LP-related complications at 12 months. The secondary effectiveness endpoint assessed the rate response performance of the LP under workload. Parameters related to the pacing performance were also measured. Results: In 297 patients, the mean age was 59±12 years, the mean left ventricular ejection fraction was 35.3±13.1%, and 17.5% were female. LP implant was attempted in 286 patients and was successful in 100%. The major LP-related complication free rate at 12 months was 97.2% (one-sided 97.5% LCL 94.5%), surpassing the performance goal of 81%. There were no LP-related complications following Implant. For the secondary effectiveness endpoint, the slope of the normalized sensor rate versus the normalized workload was 0.96 (95% LCL 0.91, 95% UCL 1.02), within the performance goal range of 0.65-1.35. At 12 months, 96.8% of patients had a pacing capture threshold ≤ 2V @ 0.4ms pulse width. Conclusions: The performance of the modular pacing-defibrillator system at one year demonstrated a low complication rate and reliable pacing functionality.

Background: Optimization of biventricular pacing for cardiac resynchronization therapy (CRT) with fusion (fusion‐optimized intervals method) has been shown to improve left ventricular remodeling. However, information on programming the atrioventricular (AV) interval during left bundle branch pacing (LBBP) is scarce. Objective: Assess with electrocardiographic imaging (ECGI) the electrical benefit of optimization of the AV interval during LBBP. Methods: Retrospective analysis of prospectively collected data. Pilot study including patients who received LBBP with CRT indication, normal AV conduction, sinus rhythm, and left bundle branch block. ECGI was used to obtain non‐invasive activation maps, ventricular activation times, and QRS widths during the optimization of the AV interval. Results: A total of 10 patients who received LBBP were included. Median age was 62 years (57–74 years), 40% were women, 20% had ischemic cardiomyopathy, and baseline LVEF was 29% (23%–36%). The baseline median QRS duration was 178 ms (168–187 ms), with a left ventricular activation time (LVAT) of 99 ms (90–109 ms), a right ventricular activation time (RVAT) of 42 ms (34–71 ms), and a total ventricular activation time (TAT) of 111 ms (105–131 ms). A non‐tailored AV programming showed a QRS measured from intrinsic deflection of 142 ms (137–149 ms); when a tailored AV was programmed, the median QRS decreased to 124 ms (116–130 ms). Ventricular activation times showed shortening with a tailored approach. Conclusion: AV interval adjustment during left bundle branch pacing may result in better resynchronization.

Introduction: Electrogram peak‐to‐peak voltage depends on atrial wall structure and mapping configuration. We evaluated the relationship between computed tomography–derived atrial wall thickness, intramyocardial fat, myocardial muscle thickness, and electrogram voltage obtained with omnipolar, bipolar, and unipolar mapping. Methods: Consecutive patients undergoing left atrial mapping during atrial fibrillation or atypical atrial flutter ablation were retrospectively included. Pre‐procedural contrast‐enhanced CT was processed with ADAS 3D to quantify left atrial wall thickness and intramyocardial fat infiltration, from which myocardial muscle thickness was derived. High‐density electroanatomical maps were spatially co‐registered with CT. Associations between anatomical parameters and peak‐to‐peak voltage were assessed, stratifying by rhythm stability. Results: Twenty patients were included. In stable rhythms, left atrial wall thickness correlated positively with voltage for all configurations, strongest for unipolar ( β = 0.38) and omnipolar ( β = 0.23) vs. bipolar mapping ( β = 0.13) (BP–UP p < 0.0001; BP–OT p < 0.01). Intramyocardial fat showed the strongest inverse association with omnipolar ( β = –0.39), compared with bipolar ( β = –0.14) and unipolar ( β = –0.01; p ≤ 0.02). After excluding fat, muscle thickness correlated positively with OT ( β = 0.30) and UP ( β = 0.30), exceeding BP ( β = 0.14; p < 0.0001). In unstable rhythms, associations were attenuated but OT remained most responsive to fat ( β = –0.20) and muscle thickness ( β = 0.11) (both p < 0.01). Conclusions: Myocardial muscle thickness is the main determinant of local atrial voltage, while intramyocardial fat contributes to voltage attenuation. OT provides the most consistent assessment of atrial wall composition, particularly under rhythm instability.

Purpose: Atrial fibrillation (AF) is both influenced by and contributes to atrial structural remodelling, including atrial enlargement and fibrosis. In this work, we aimed to understand how differences in atrial anatomy affect AF inducibility and dynamics, both without and with fibrosis, through in silico models. Methods: Atrial wall anatomies from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) were used to generate personalised models. Detailed intra- and inter-atrial structures (pectinate muscles, Bachmann’s bundle, fossa ovalis, coronary sinus, and fibre orientations) were mapped onto patient-specific atrial anatomies through a novel strategy using universal atrial coordinates and a highly detailed reference model. Patient-specific endomysial fibrosis was incorporated based on LGE-MRI. We quantified AF and macro-reentrant atrial tachycardia (MRAT) initiation rates in models with and without fibrosis, comparing reentry dynamics using renewal theory. Results: We generated personalised models of 10 patients, all but one with low-fibrotic content (Utah stages ≤ 2). Anatomical variability did not significantly affect AF initiation rates in both non-fibrotic (54.0 ± 13.7%, p = 0.43) and fibrotic models (53.5 ± 15.3%, p = 0.37). For AF + MRAT, initiation rates varied significantly among fibrotic models ( p = 0.04) but not among non-fibrotic ones ( p = 0.14). Reentry formation rates varied significantly across anatomies both with and without fibrosis ( p < 0.04). With fibrosis, reentry destruction rates also varied significantly ( p < 0.02). The number of simultaneous reentries varied significantly across patient anatomies ( p < 0.001 without fibrosis, p < 0.05 with fibrosis), with fibrosis altering reentry counts in 2 patients ( p < 0.02). Conclusion: Atrial anatomy influenced patient-specific variability in AF reentry dynamics, while fibrosis played a limited modifying role in this low-fibrotic cohort.