In situ procedure for high-efficiency computational modeling of atrial fibrillation reflecting personal anatomy, fiber orientation, fibrosis, and electrophysiology

Clinical usefulness of digital twin guided virtual amiodarone test in patients with atrial fibrillation ablation

It would be clinically valuable if the efficacy of antiarrhythmic drugs could be simulated in advance. We developed a digital twin to predict amiodarone efficacy in high-risk atrial fibrillation (AF) patients post-ablation. Virtual left atrium models were created from computed tomography and electroanatomical maps to simulate AF and evaluate its response to varying amiodarone concentrations. As the amiodarone concentration increased in the virtual setting, action potential duration lengthened, peak upstroke velocities decreased, and virtual AF termination became more frequent. Patients were classified into effective (those with virtually terminated AF at therapeutic doses) and ineffective groups. The one-year clinical outcomes after AF ablation showed significantly better results in the effective group compared to the ineffective group, with AF recurrence rates of 20.8% vs. 45.1% (log-rank p = 0.031, adjusted hazard ratio, 0.37 [0.14-0.98]; p = 0.046). This study highlights the potential of a digital twin-guided approach in predicting amiodarone's effectiveness and improving personalized AF management. Clinical Trial Registration Name: The Evaluation for Prognostic Factors After Catheter Ablation of Atrial Fibrillation: Cohort Study, Registration number: NCT02138695. The date of registration: 2014-05. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02138695.

Anti- and pro-fibrillatory effects of pulmonary vein isolation gaps in human atrial fibrillation digital twins

Although pulmonary vein isolation (PVI) gaps and extrapulmonary vein triggers contribute to recurrence after atrial fibrillation (AF) ablation, their precise mechanisms remain unproven. Our study assessed the impact of PVI gaps on rhythm outcomes using a human AF digital twin. We included 50 patients (76.0% with persistent AF) who underwent catheter ablation with a realistic AF digital twin by integrating computed tomography and electroanatomical mapping. We evaluated the final rhythm status, including AF and atrial tachycardia (AT), across 600 AF episodes, considering factors including PVI level, PVI gap number, and pacing locations. Our findings revealed that antral PVI had a significantly lower ratio of AF at the final rhythm (28% vs. 56%, p = 0.002) than ostial PVI. Increasing PVI gap numbers correlated with an increased ratio of AF at the final rhythm (p < 0.001). Extra-PV induction yielded a higher ratio of AF at the final rhythm than internal PV induction (77.5% vs. 59.0%, p < 0.001). In conclusion, our human AF digital twin model helped assess AF maintenance mechanisms. Clinical trial registration: https://www.clinicaltrials.gov ; Unique identifier: NCT02138695.

Fiber Organization Has Little Effect on Electrical Activation Patterns During Focal Arrhythmias in the Left Atrium

Over the past two decades there has been a steady trend towards the development of realistic models of cardiac conduction with increasing levels of detail. However, making models more realistic complicates their personalization and use in clinical practice due to limited availability of tissue and cellular scale data. One such limitation is obtaining information about myocardial fiber organization in the clinical setting. In this study, we investigated a chimeric model of the left atrium utilizing clinically derived patient-specific atrial geometry and a realistic, yet foreign for a given patient fiber organization. We discovered that even significant variability of fiber organization had a relatively small effect on the spatio-temporal activation pattern during regular pacing. For a given pacing site, the activation maps were very similar across all fiber organizations tested.

Fiber Organization has Little Effect on Electrical Activation Patterns during Focal Arrhythmias in the Left Atrium

Over the past two decades there has been a steady trend towards the development of realistic models of cardiac conduction with increasing levels of detail. However, making models more realistic complicates their personalization and use in clinical practice due to limited availability of tissue and cellular scale data. One such limitation is obtaining information about myocardial fiber organization in the clinical setting. In this study, we investigated a chimeric model of the left atrium utilizing clinically derived patient-specific atrial geometry and a realistic, yet foreign for a given patient fiber organization. We discovered that even significant variability of fiber organization had a relatively small effect on the spatio-temporal activation pattern during regular pacing. For a given pacing site, the activation maps were very similar across all fiber organizations tested.

Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence

AIMS

The long-term success rate of ablation therapy is still sub-optimal in patients with persistent atrial fibrillation (AF), mostly due to arrhythmia recurrence originating from arrhythmogenic sites outside the pulmonary veins. Computational modelling provides a framework to integrate and augment clinical data, potentially enabling the patient-specific identification of AF mechanisms and of the optimal ablation sites. We developed a technology to tailor ablations in anatomical and functional digital atrial twins of patients with persistent AF aiming to identify the most successful ablation strategy.

METHODS AND RESULTS

Twenty-nine patient-specific computational models integrating clinical information from tomographic imaging and electro-anatomical activation time and voltage maps were generated. Areas sustaining AF were identified by a personalized induction protocol at multiple locations. State-of-the-art anatomical and substrate ablation strategies were compared with our proposed Personalized Ablation Lines (PersonAL) plan, which consists of iteratively targeting emergent high dominant frequency (HDF) regions, to identify the optimal ablation strategy. Localized ablations were connected to the closest non-conductive barrier to prevent recurrence of AF or atrial tachycardia. The first application of the HDF strategy had a success of >98% and isolated only 5-6% of the left atrial myocardium. In contrast, conventional ablation strategies targeting anatomical or structural substrate resulted in isolation of up to 20% of left atrial myocardium. After a second iteration of the HDF strategy, no further arrhythmia episode could be induced in any of the patient-specific models.

CONCLUSION

The novel PersonAL in silico technology allows to unveil all AF-perpetuating areas and personalize ablation by leveraging atrial digital twins.

Clinical Usefulness of Virtual Ablation Guided Catheter Ablation of Atrial Fibrillation Targeting Restitution Parameter-Guided Catheter Ablation: CUVIA-REGAB Prospective Randomized Study

BACKGROUND AND OBJECTIVES

We investigated whether extra-pulmonary vein (PV) ablation targeting a high maximal slope of the action potential duration restitution curve (Smax) improves the rhythm outcome of persistent atrial fibrillation (PeAF) ablation.

METHODS

In this open-label, multi-center, randomized, and controlled trial, 178 PeAF patients were randomized with 1:1 ratio to computational modeling-guided virtual Smax ablation (V-Smax) or empirical ablation (E-ABL) groups. Smax maps were generated by computational modeling based on atrial substrate maps acquired during clinical procedures in sinus rhythm. Smax maps were generated during the clinical PV isolation (PVI). The V-Smax group underwent an additional extra-PV ablation after PVI targeting the virtual high Smax sites.

RESULTS

After a mean follow-up period of 12.3±5.2 months, the clinical recurrence rates (25.6% vs. 23.9% in the V-Smax and the E-ABL group, p=0.880) or recurrence appearing as atrial tachycardia (11.1% vs. 5.7%, p=0.169) did not differ between the 2 groups. The post-ablation cardioversion rate was higher in the V-Smax group than E-ABL group (14.4% vs. 5.7%, p=0.027). Among antiarrhythmic drug-free patients (n=129), the AF freedom rate was 78.7% in the V-Smax group and 80.9% in the E-ABL group (p=0.776). The total procedure time was longer in the V-Smax group (p=0.008), but no significant difference was found in the major complication rates (p=0.497) between the groups.

CONCLUSIONS

Unlike a dominant frequency ablation, the computational modeling-guided V-Smax ablation did not improve the rhythm outcome of the PeAF ablation and had a longer procedure time.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02558699.

An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias

Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.

Ablation and antiarrhythmic drug effects on PITX2+/− deficient atrial fibrillation: A computational modeling study

Introduction

Atrial fibrillation (AF) is a heritable disease, and the paired-like homeodomain transcription factor 2 (PITX2) gene is highly associated with AF. We explored the differences in the circumferential pulmonary vein isolation (CPVI), which is the cornerstone procedure for AF catheter ablation, additional high dominant frequency (DF) site ablation, and antiarrhythmic drug (AAD) effects according to the patient genotype (wild-type and PITX2+/− deficient) using computational modeling.

Methods

We included 25 patients with AF (68% men, 59.8 ± 9.8 years of age, 32% paroxysmal AF) who underwent AF catheter ablation to develop a realistic computational AF model. The ion currents for baseline AF and the amiodarone, dronedarone, and flecainide AADs according to the patient genotype (wild type and PITX2+/− deficient) were defined by relevant publications. We tested the virtual CPVI (V-CPVI) with and without DF ablation (±DFA) and three virtual AADs (V-AADs, amiodarone, dronedarone, and flecainide) and evaluated the AF defragmentation rates (AF termination or changes to regular atrial tachycardia (AT), DF, and maximal slope of the action potential duration restitution curves (Smax), which indicates the vulnerability of wave-breaks.

Results

At the baseline AF, mean DF (p = 0.003), and Smax (p &lt; 0.001) were significantly lower in PITX2+/− deficient patients than wild-type patients. In the overall AF episodes, V-CPVI (±DFA) resulted in a higher AF defragmentation relative to V-AADs (65 vs. 42%, p &lt; 0.001) without changing the DF or Smax. Although a PITX2+/− deficiency did not affect the AF defragmentation rate after the V-CPVI (±DFA), V-AADs had a higher AF defragmentation rate (p = 0.014), lower DF (p &lt; 0.001), and lower Smax (p = 0.001) in PITX2+/− deficient AF than in wild-type patients. In the clinical setting, the PITX2+/− genetic risk score did not affect the AF ablation rhythm outcome (Log-rank p = 0.273).

Conclusion

Consistent with previous clinical studies, the V-CPVI had effective anti-AF effects regardless of the PITX2 genotype, whereas V-AADs exhibited more significant defragmentation or wave-dynamic change in the PITX2+/− deficient patients.

A Review of Healthy and Fibrotic Myocardium Microstructure Modeling and Corresponding Intracardiac Electrograms

Computational simulations of cardiac electrophysiology provide detailed information on the depolarization phenomena at different spatial and temporal scales. With the development of new hardware and software, in silico experiments have gained more importance in cardiac electrophysiology research. For plane waves in healthy tissue, in vivo and in silico electrograms at the surface of the tissue demonstrate symmetric morphology and high peak-to-peak amplitude. Simulations provided insight into the factors that alter the morphology and amplitude of the electrograms. The situation is more complex in remodeled tissue with fibrotic infiltrations. Clinically, different changes including fractionation of the signal, extended duration and reduced amplitude have been described. In silico, numerous approaches have been proposed to represent the pathological changes on different spatial and functional scales. Different modeling approaches can reproduce distinct subsets of the clinically observed electrogram phenomena. This review provides an overview of how different modeling approaches to incorporate fibrotic and structural remodeling affect the electrogram and highlights open challenges to be addressed in future research.

Anti-atrial Fibrillation Effects of Pulmonary Vein Isolation With or Without Ablation Gaps: A Computational Modeling Study

Background

Although pulmonary vein isolation (PVI) gaps contribute to recurrence after atrial fibrillation (AF) catheter ablation, the mechanism is unclear. We used realistic computational human AF modeling to explore the AF wave-dynamic changes of PVI with gaps (PVI-gaps).

Methods

We included 40 patients (80% male, 61.0 ± 9.8 years old, 92.5% persistent AF) who underwent AF catheter ablation to develop our realistic computational AF model. We compared the effects of a complete PVI (CPVI) and PVI-gap (2-mm × 4) on the AF wave-dynamics by evaluating the dominant frequency (DF), spatial change of DF, maximal slope of the action potential duration restitution curve (Smax), and AF defragmentation rate (termination or change to atrial tachycardia), and tested the effects of additional virtual interventions and flecainide on ongoing AF with PVI-gaps.

Results

Compared with the baseline AF, CPVIs significantly reduced extra-PV DFs (p < 0.001), but PVI-gaps did not. COV-DFs were greater after CPVIs than PVI-gaps (p < 0.001). Neither CPVIs nor PVI-gaps changed the mean Smax. CPVIs resulted in higher AF defragmentation rates (80%) than PVI-gaps (12.5%, p < 0.001). In ongoing AF after PVI-gaps, the AF defragmentation rates after a wave-breaking gap ablation, extra-PV DF ablation, or flecainide were 60.0, 34.3, and 25.7%, respectively (p = 0.010).

Conclusion

CPVIs effectively reduced the DF, increased its spatial heterogeneity in extra-PV areas, and offered better anti-AF effects than extra-PV DF ablation or additional flecainide in PVI-gap conditions.

Restitution Slope Affects the Outcome of Dominant Frequency Ablation in Persistent Atrial Fibrillation: CUVIA-AF2 Post-Hoc Analysis Based on Computational Modeling Study

Introduction

Although the dominant frequency (DF) localizes the reentrant drivers and the maximal slope of the action potential duration (APD) restitution curve (Smax) reflects the tendency of the wave-break, their interaction has never been studied. We hypothesized that DF ablation has different effects on atrial fibrillation (AF) depending on Smax.

Methods

We studied the DF and Smax in 25 realistic human persistent AF model samples (68% male, 60 ± 10 years old). Virtual AF was induced by ramp pacing measuring Smax, followed by spatiotemporal DF evaluation for 34 s. We assessed the DF ablation effect depending on Smax in both computational modeling and a previous clinical trial, CUVIA-AF (170 patients with persistent AF, 70.6% male, 60 ± 11 years old).

Results

Mean DF had an inverse relationship with Smax regardless of AF acquisition timing (p &lt; 0.001). Virtual DF ablations increased the defragmentation rate compared to pulmonary vein isolation (PVI) alone (p = 0.015), especially at Smax &lt;1 (61.5 vs. 7.7%, p = 0.011). In post-DF ablation defragmentation episodes, DF was significantly higher (p = 0.002), and Smax was lower (p = 0.003) than in episodes without defragmentation. In the post-hoc analysis of CUVIA-AF2, we replicated the inverse relationship between Smax and DF (r = −0.47, p &lt; 0.001), and we observed better rhythm outcomes of clinical DF ablations in addition to a PVI than of empirical PVI at Smax &lt;1 [hazard ratio 0.45, 95% CI (0.22–0.89), p = 0.022; log-rank p = 0.021] but not at ≥ 1 (log-rank p = 0.177).

Conclusion

We found an inverse relationship between DF and Smax and the outcome of DF ablation after PVI was superior at the condition with Smax &lt;1 in both in-silico and clinical trials.

Clinical Outcomes of Computational Virtual Mapping-Guided Catheter Ablation in Patients With Persistent Atrial Fibrillation: A Multicenter Prospective Randomized Clinical Trial

Background: Clinical recurrence after atrial fibrillation catheter ablation (AFCA) still remains high in patients with persistent AF (PeAF). We investigated whether an extra-pulmonary vein (PV) ablation targeting the dominant frequency (DF) extracted from electroanatomical map–integrated AF computational modeling improves the AFCA rhythm outcome in patients with PeAF.

Methods: In this open-label, randomized, multi-center, controlled trial, 170 patients with PeAF were randomized at a 1:1 ratio to the computational modeling-guided virtual DF (V-DF) ablation and empirical PV isolation (E-PVI) groups. We generated a virtual dominant frequency (DF) map based on the atrial substrate map obtained during the clinical AF ablation procedure using computational modeling. This simulation was possible within the time of the PVI procedure. V-DF group underwent extra-PV V-DF ablation in addition to PVI, but DF information was not notified to the operators from the core lab in the E-PVI group.

Results: After a mean follow-up period of 16.3 ± 5.3 months, the clinical recurrence rate was significantly lower in the V-DF than with E-PVI group (P = 0.018, log-rank). Recurrences appearing as atrial tachycardias (P = 0.145) and the cardioversion rates (P = 0.362) did not significantly differ between the groups. At the final follow-up, sinus rhythm was maintained without any AADs in 74.7% in the V-DF group and 48.2% in the E-PVI group (P < 0.001). No significant difference was found in the major complication rates (P = 0.489) or total procedure time (P = 0.513) between the groups. The V-DF ablation was independently associated with a reduced AF recurrence after AFCA [hazard ratio: 0.51 (95% confidence interval: 0.30–0.88); P = 0.016].

Conclusions: The computational modeling-guided V-DF ablation improved the rhythm outcome of AFCA in patients with PeAF.

Clinical Trial Registration: Clinical Research Information Service, CRIS identifier: KCT0003613.

Computational modeling of atrial fibrillation

With the aging society, the prevalence of atrial fibrillation (AF) continues to increase. Nevertheless, there are still limitations in antiarrhythmic drugs (AAD) or catheter interventions for AF. If it is possible to predict the outcome of AF management according to various AADs or ablation lesion sets through computational modeling, it will be of great clinical help. AF computational modeling has been utilized for in-silico arrhythmia research and enabled high-density entire chamber mapping, reproducible condition control, virtual intervention, not possible clinically or experimentally, in-depth mechanistic research. With the recent development of computer science and technology, more sophisticated and faster computational modeling has become available for clinical application. In particular, it can be applied to determine the extra-PV target of persistent AF catheter ablation or to select the AAD with the best effect. AF computational modeling combined with artificial intelligence is expected to contribute to precision medicine for more diverse uses in the future. Therefore, in this review, we will deal with the history, development, and various applications of computation modeling.

Current progress of computational modeling for guiding clinical atrial fibrillation ablation

Atrial fibrillation (AF) is one of the most common arrhythmias, associated with high morbidity, mortality, and healthcare costs, and it places a significant burden on both individuals and society. Anti-arrhythmic drugs are the most commonly used strategy for treating AF. However, drug therapy faces challenges because of its limited efficacy and potential side effects. Catheter ablation is widely used as an alternative treatment for AF. Nevertheless, because the mechanism of AF is not fully understood, the recurrence rate after ablation remains high. In addition, the outcomes of ablation can vary significantly between medical institutions and patients, especially for persistent AF. Therefore, the issue of which ablation strategy is optimal is still far from settled. Computational modeling has the advantages of repeatable operation, low cost, freedom from risk, and complete control, and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance. This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF, from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation. Finally, we summarize current developments and challenges and provide our perspectives and suggestions for future directions.

Spatial Changes in the Atrial Fibrillation Wave-Dynamics After Using Antiarrhythmic Drugs: A Computational Modeling Study

Background: We previously reported that a computational modeling-guided antiarrhythmic drug (AAD) test was feasible for evaluating multiple AADs in patients with atrial fibrillation (AF). We explored the anti-AF mechanisms of AADs and spatial change in the AF wave-dynamics by a realistic computational model. Methods: We used realistic computational modeling of 25 AF patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal AF) reflecting the anatomy, histology, and electrophysiology of the left atrium (LA) to characterize the effects of five AADs (amiodarone, sotalol, dronedarone, flecainide, and propafenone). We evaluated the spatial change in the AF wave-dynamics by measuring the mean dominant frequency (DF) and its coefficient of variation [dominant frequency-coefficient of variation (DF-COV)] in 10 segments of the LA. The mean DF and DF-COV were compared according to the pulmonary vein (PV) vs. extra-PV, maximal slope of the restitution curves (Smax), and defragmentation of AF. Results: The mean DF decreased after the administration of AADs in the dose dependent manner (p < 0.001). Under AADs, the DF was significantly lower (p < 0.001) and COV-DF higher (p = 0.003) in the PV than extra-PV region. The mean DF was significantly lower at a high Smax (≥1.4) than a lower Smax condition under AADs. During the episodes of AF defragmentation, the mean DF was lower (p < 0.001), but the COV-DF was higher (p < 0.001) than that in those without defragmentation. Conclusions: The DF reduction with AADs is predominant in the PVs and during a high Smax condition and causes AF termination or defragmentation during a lower DF and spatially unstable (higher DF-COV) condition.

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model. Our new model parametrization is then adopted to predict the formation and self-sustainment of localized reentries characterizing atrial fibrillation, by numerically simulating the onset of ectopic beats from the pulmonary veins. We investigate the paroxysmal and the persistent form of AF starting from electro-anatomical maps of two patients. The model's response to stimulation shows how substrate characteristics play a key role in inducing and sustaining these arrhythmias. Localized reentries are less frequent and less stable in case of paroxysmal AF, while they tend to anchor themselves in areas affected by severe slow conduction in case of persistent AF.

Model Systems for Addressing Mechanism of Arrhythmogenesis in Cardiac Repair

PURPOSE OF REVIEW

Cardiac cell-based therapy represents a promising approach for cardiac repair. However, one of the main challenges is cardiac arrhythmias associated with stem cell transplantation. The current review summarizes the recent progress in model systems for addressing mechanisms of arrhythmogenesis in cardiac repair.

RECENT FINDINGS

Animal models have been extensively developed for mechanistic studies of cardiac arrhythmogenesis. Advances in human induced pluripotent stem cells (hiPSCs), patient-specific disease models, tissue engineering, and gene editing have greatly enhanced our ability to probe the mechanistic bases of cardiac arrhythmias. Additionally, recent development in multiscale computational studies and machine learning provides yet another powerful tool to quantitatively decipher the mechanisms of cardiac arrhythmias. Advancing efforts towards the integrations of experimental and computational studies are critical to gain insights into novel mitigation strategies for cardiac arrhythmias in cell-based therapy.

Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2 ^+/--deficient AF conditions by realistic in silico AF modeling. Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2 ^+/- deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications. Results: We compared the wild-type and PITX2 ^+/- deficiency in terms of the action potential duration (APD₉₀), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2 ^+/--deficient model exhibited a shorter APD₉₀ (p < 0.001), a lower Smax (p < 0.001), mean DF (p = 0.012), PS number (p < 0.001), and a longer AF cycle length (AFCL, p = 0.011). Five V-AADs changed the electrophysiology in a dose-dependent manner. AAD-induced AFCL lengthening (p < 0.001) and reductions in the CV (p = 0.033), peak DF (p < 0.001), and PS number (p < 0.001) were more significant in PITX2 ^+/--deficient than wild-type AF. PITX2 ^+/--deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018). Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.

Accuracy and clinical feasibility of 3D-myocardial thickness map measured by cardiac computed tomogram

Background

Although myocardial thickness is an important variable for therapeutic catheter ablation of cardiac arrhythmias, quantification of wall thickness has been overlooked. We developed a software (AMBER) that measures 3D-myocardial thickness using a cardiac computed tomogram (CT) image, verified its accuracy, and tested its clinical feasibility.

Methods

We generated 3D-thickness maps by calculating wall thickness (WT) from the CT images of 120 patients’ hearts and a 3D-phantom model (PhM). The initial vector field of the Laplace equation was oriented to calculate WT with the field lines derived from the 3D mesh. We demonstrate the robustness of the Laplace WT algorithm by comparing with the real thickness of 3D-PhM, echocardiographically measured left ventricular (LV) WT, and regional left atrial (LA) WT reported from previous studies. We conducted a pilot case of catheter ablation for atrial fibrillation (AF) utilizing real-time LAWT map-guided radiofrequency (RF) energy titration.

Results

AMBER 3D-WT had excellent correlations with the real thickness of the PhM (R = 0.968, p < 0.001) and echocardiographically measured LVWT in 10 patients (R = 0.656, p = 0.007). AMBER 3D-LAWT (n = 120) showed a relatively good match with 12 previously reported regional LAWT. We successfully conducted pilot AF ablation utilizing AMBER 3D-LAWT map-guided real-time RF energy titration.

Conclusion

We developed and verified an AMBER 3D-cardiac thickness map measured by cardiac CT images for LAWT and LVWT, and tested its feasibility for RF energy titration during clinical catheter ablation.