Adityo Prakosa

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is a severe genetic heart disease that predominantly affects young athletic individuals and carries a high risk of ventricular tachycardia (VT) and sudden cardiac death. Catheter-based radiofrequency ablation is the state-of-the-art treatment for VT; however, its effectiveness in ARVC is limited by high recurrence rates. This study aims to develop a personalized approach to improve ablation outcomes in ARVC. We developed a non-invasive digital twin-based framework, termed GenDIRECT, that simulates cardiac electrical activity on patient-specific heart models to predict the optimal VT ablation targets. This retrospective study included 30 patients with ARVC of two common ARVC genotypes (GE and PKP2). Among them, 25 underwent a single clinical ablation, and 5 had repeat ablation within 12 months of the initial ablation. Predicted targets were compared with clinically delivered ablation lesions in patients who underwent initial and/or repeat procedures. Here, we show that GenDIRECT-predicted ablation targets closely align with clinical ablation lesions (Dice score = 89.47%) in patients with successful initial procedures (n = 25) and are associated with significantly smaller lesion volumes (p = 5.39*10^-5). In patients with VT recurrence requiring repeat procedures (n = 5), predicted targets correspond to the combined lesions from both initial and repeat ablations. GenDIRECT-guided ablation targets eliminate VT inducibility in all simulations. GenDIRECT has the potential to guide clinical VT ablation procedures in ARVC by identifying comprehensive patient-specific targets. This approach may improve procedural efficacy, reduce arrhythmia recurrence, and decrease the need for repeat ablation and subsequent hospitalizations.

Persistent atrial fibrillation (PsAF) is often refractory to pulmonary vein isolation, a well-established AF treatment, owing to the fibrosis-remodeled substrates sustaining reentries. Three-dimensional fibrosis distribution and atrial adiposity have been found to be essential contributors to PsAF arrhythmogenesis. We aimed to utilize late gadolinium enhancement (LGE)-MRI-derived personalized heart digital twins (DTs)—a recent promising tool for non-invasively assessing patient arrhythmogenesis—as well as contrast-enhanced cardiac computed tomography (CCT) images and electroanatomic maps (EAMs) to investigate relationships between fibrosis distribution, including endo–epi differences, adiposity infiltration, and electrophysiological abnormalities, and their influence on PsAF arrhythmogenic substrate. DTs incorporating fibrosis distribution were generated from consecutive PsAF patients’ LGE-MRIs. Using rapid pacing, potential locations attracting reentries (LRs) were identified in DTs. CCTs were used to segment adipose tissue within pericardial sac and evaluate the distance from endocardial surface to closest adipose tissue (DEnCA). Bipolar- and unipolar-low-voltage area fractions (LVFs) were extracted from EAMs. Volumetric fibrosis fraction (FF) and surface FF on endocardial and epicardial surfaces at LRs and non-LRs were analyzed in relation to DEnCA and LVF. In 22 patients, adipose tissue volume correlated with BMI and CHA₂DS₂-VASc and, together with atrial-FF, predicted number of LRs. At LRs and non-LRs, while volumetric-FF was the sole determinant of LR classification, volumetric-FF correlated with endocardium-predominant fibrosis and bipolar-LVF. Endocardium-predominant fibrosis was independently linked to DEnCA. This study highlights the complex interactions between structural features, such as three-dimensional fibrosis distribution and atrial adiposity infiltration, electrophysiological features, and PsAF arrhythmogenesis.

Aims: Arrhythmogenic fibrotic substrates facilitate reentrant activity in the atria, contributing to the perpetuation of atrial fibrillation (AF). Catheter ablation may disrupt existing reentrant pathways but can also create new ones. This longitudinal study aimed to assess whether post-ablation AF recurrence is associated with incomplete elimination of native arrhythmogenic substrates or emergence of new arrhythmogenic substrates created by ablation lesions, addressing important questions in current AF management: why some patients experience recurrence post-ablation while others do not, and whether ablation lesions themselves contribute to post-ablation arrhythmogenesis. Methods and results: Biatrial digital twins (DTs) derived from pre- and post-ablation contrast-enhanced magnetic resonance imaging were used to evaluate the arrhythmogenic propensity of the fibrotic substrate—quantified by potential reentry-sites (PRs) and a vulnerability index (VI) reflecting reentry inducibility. Pre- and post-ablation DT pairs were generated for 11 patients who experienced AF recurrence (R-DTs) and 11 who did not (N-DTs). In total, 58 pre-ablation PRs and 32 post-ablation PRs were detected, with a nearly even distribution of PRs between the left atrium (LA) and right atrium (RA) both pre- and post-ablation. Pre-ablation VI was similar between N-DTs and R-DTs; however, post-ablation VI was significantly higher in R-DTs (P = 0.015). N-DTs exhibited a marked reduction in PRs following ablation, whereas R-DTs did not (P = 0.017). Both groups had few residual PRs from pre- to post-ablation, but R-DTs had many newly emergent PRs. In R-DTs, emergent PRs in the RA were accompanied by a post-ablation increase in RA fibrotic burden. In the LA, where lesions were delivered, all post-ablation reentries anchored around ablation-induced scar (ScAReentries). ScAReentries were significantly more inducible than those occurring within fibrotic substrate and were nearly three times more prevalent in R-DTs, accounting for the elevated post-ablation VI. Conclusion: In DTs, emergent PRs in both atria underlie AF recurrence post-ablation, with ablation itself creating some PRs of high arrhythmogenic propensity.

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is a severe genetic heart disease that predominantly affects young athletic individuals and carries a high risk of ventricular tachycardia (VT) and sudden cardiac death. Although catheter-based radiofrequency ablation is the state-of-the-art treatment for VT, its success in ARVC is limited by high recurrence rates. Here, we present Genotype-specific Digital-twin Ablation Targeting (GenDIRECT), a personalized, non-invasive technology that predicts, prior to the clinical procedure, the optimal VT ablation targets using patient-specific heart digital twins. The GenDIRECT-predicted target set is devised to eliminate, with minimum lesion size, the ability of the ARVC ventricles to sustain any reentrant arrhythmias. Comparison of GenDIRECT target lesions with the clinical ablation lesions demonstrated excellent co-localization in both ARVC patients who had undergone index ablation and in those with redo procedures many months later, regardless of genotype. Thus, should GenDIRECT be used to guide clinical procedures, it is expected that existing VTs will be terminated, and post-ablation arrhythmias will be prevented, thereby increasing the efficacy of the ablation procedure and reducing redo procedures and re-hospitalization.

BACKGROUND: Atrial fibrillation (AF) is a progressive disease involving both structural and functional remodeling. Although over the past decade, digital twin-guided therapy has been proposed and applied, accounting for cardiomyocyte functional remodeling remains challenging. We aimed to investigate the contribution of functional remodeling at the cellular level to AF pathogenesis in patients with fibrotic remodeling and to develop novel techniques to predict the location of reentrant drivers. METHODS: To investigate the contribution of cell-scale functional remodeling to AF pathogenesis under the conditions of fibrotic remodeling, we combined 3-dimensional atrial digital twins with pathology-specific single-cell models. The latter were developed using recordings in myocytes isolated from patients in sinus rhythm, paroxysmal, postoperative, and persistent AF. To quantify AF dynamics in the digital twins, we developed a novel algorithm for locating reentrant drivers by backtracking the conduction velocity field from the wavebreak regions. RESULTS: We demonstrate that our novel algorithm is at least 700× faster than the traditional phase singularity analysis. The inducibility of simulated AF was not pathology-dependent, but pathological models demonstrate a more extensive arrhythmogenic substrate than the sinus rhythm. We observed a correlation between wavebreak probability and fibrosis density, with the highest regression slope for the persistent AF model and the lowest for the sinus rhythm model. CONCLUSIONS: AF driver locations in atrial fibrotic substrates depend on electrophysiological remodeling; differences between pathology-specific models are explained by differences in wavebreak patterns. Specifically, reentrant drivers tend to dwell in the regions with the highest wavebreak probability.

BACKGROUND: Catheter ablation of scar-dependent ventricular tachycardia (VT) is frequently hampered by hemodynamic instability, long procedure duration, and high recurrence rates. Magnetic resonance imaging-based personalized heart digital twins may overcome these challenges by noninvasively predicting VT circuits and optimum ablation lesion sites. In this combined clinical and digital twin study, we investigated the relationship between digital twin-predicted VTs and optimum ablation lesion sets with their invasively mapped counterparts during clinical VT ablation. METHODS: A total of 18 patients with scar-dependent VT underwent digital twin creation based on preprocedural, contrast-enhanced cardiac magnetic resonance imaging. Using rapid pacing protocols, VT was simulated and ablation targets were derived that would terminate all possible VTs in the models. Patients subsequently underwent invasive VT ablation, including targeting of diastolic activity and optimum entrainment sites. Digital twin-predicted VT circuits and ablation lesions were compared with their invasive clinical counterparts. RESULTS: Forty-three clinical VTs and 92 digital twin VTs were induced. Diastolic activity was seen in 16 of 43 (37.2%) clinical VTs. Sensitivity, specificity, positive predictive, and negative predictive values for the detection of critical VT sites by digital twins were 81.3%, 83.8%, 21.7%, and 98.8%, respectively. At an American Heart Association-segment level, agreement between clinical VT critical sites and digital twin primary predicted sites was moderate, with a κ coefficient of 0.46 (±0.32; P ≤0.001). Termination of VT with ablation was achieved at a digital twin-predicted site in 4 of 5 (80%) cases where attempted. A total of 426 of 709 (60.1%) lesions were within 5 mm of a predicted target site. In total, 54.0% (±28.9%) of the digital twin-predicted area was ablated per patient based on conventional mapping criteria. CONCLUSIONS: Heart digital twin VT circuits and ablation targets accurately predict many features of their respective clinical counterparts but have some limitations in spatial resolution. Our findings demonstrate the significant potential of digital twin technology in guiding catheter ablation for scar-dependent VT.

BACKGROUND: Current outcomes from catheter ablation for scar-dependent ventricular tachycardia (VT) are limited by high recurrence rates and long procedure durations. Personalized heart digital twin technology presents a noninvasive method of predicting critical substrate in VT, and its integration into clinical VT ablation offers a promising solution. The accuracy of the predictions of digital twins to detect invasive substrate abnormalities is unknown. We present the first prospective analysis of digital twin technology in predicting critical substrate abnormalities in VT. METHODS: Heart digital twin models were created from 18 patients with scar-dependent VT undergoing catheter ablation. Contrast-enhanced cardiac magnetic resonance images were used to reconstruct finite-element meshes, onto which regional electrophysiological properties were applied. Rapid-pacing protocols were used to induce VTs and to define the VT circuits. Predicted optimum ablation sites to terminate all VTs in the models were identified. Invasive substrate mapping was performed, and the digital twins were merged with the electroanatomical map. Electrogram abnormalities and regions of conduction slowing were compared between digital twin–predicted sites and nonpredicted areas. RESULTS: Electrogram abnormalities were significantly more frequent in digital twin–predicted sites compared with nonpredicted sites (468/1029 [45.5%] versus 519/1611 [32.2%]; P P <0.001). Digital twins correctly identified 21 of 26 (80.8%) deceleration zones seen on isochronal late activation mapping. CONCLUSIONS: Digital twin–predicted sites display a higher prevalence of abnormal and prolonged electrograms compared with nonpredicted sites and accurately identify regions of conduction slowing. Digital twin technology may help improve substrate-based VT ablation. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04632394.

Background and Aims: Life-threatening arrhythmias are a well-established consequence of reduced cardiac sodium current (INa). Gene therapy approaches to increase INa have demonstrated potential benefits to prevent arrhythmias. However, the development of such therapies is hampered by the large size of sodium channels. In this study, SCN10A-short (S10s), a short transcript encoding the carboxy-terminal domain of the human neuronal sodium channel, was evaluated as a gene therapy target to increase INa and prevent arrhythmias. Methods: Adeno-associated viral vector overexpressing S10s was injected into wild type and Scn5a-haploinsufficient mice on which patch-clamp studies, optical mapping, electrocardiogram analyses, and ischaemia reperfusion were performed. In vitro and in silico studies were conducted to further explore the effect of S10s gene therapy in the context of human hearts. Results: Cardiac S10s overexpression increased cellular INa, maximal action potential upstroke velocity, and action potential amplitude in Scn5a-haploinsufficient cardiomyocytes. S10s gene therapy rescues conduction slowing in Scn5a-haploinsufficient mice and prevented ventricular tachycardia induced by ischaemia-reperfusion in wild type mice. S10s overexpression increased maximal action potential upstroke velocity in human inducible pluripotent stem cell-derived cardiomyocytes and prevented inducible arrhythmias in simulated human heart models. Conclusions: S10s gene therapy may be effective to treat cardiac conduction abnormalities and associated arrhythmias.

Atrial fibrillation (AF), the most common heart rhythm disorder, may cause stroke and heart failure. For patients with persistent AF with fibrosis proliferation, the standard AF treatment—pulmonary vein isolation—has poor outcomes, necessitating redo procedures, owing to insufficient understanding of what constitutes good targets in fibrotic substrates. Here we present a prospective clinical and personalized digital twin study that characterizes the arrhythmogenic properties of persistent AF substrates and uncovers locations possessing rotor-attracting capabilities. Among these, a portion needs to be ablated to render the substrate not inducible for rotors, but the rest (37%) lose rotor-attracting capabilities when another location is ablated. Leveraging digital twin mechanistic insights, we suggest ablation targets that eliminate arrhythmia propensity with minimum lesions while also minimizing the risk of iatrogenic tachycardia and AF recurrence. Our findings provide further evidence regarding the appropriate substrate ablation targets in persistent AF, opening the door for effective strategies to mitigate patients’ AF burden.