Characterizing the clinical implementation of a novel activation-repolarization metric to identify targets for catheter ablation of ventricular tachycardias using computational models

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Computer-aided detection of arrhythmogenic sites in post-ischemic ventricular tachycardia

Nowadays, catheter-based ablation in patients with post-ischemic ventricular tachycardia (VT) is performed in arrhythmogenic sites identified by electrophysiologists by visual inspection during electroanatomic mapping. This work aims to present the development of machine learning tools aiming at supporting clinicians in the identification of arrhythmogenic sites by exploiting innovative features that belong to different domains. This study included 1584 bipolar electrograms from nine patients affected by post-ischemic VT. Different features were extracted in the time, time scale, frequency, and spatial domains and used to train different supervised classifiers. Classification results showed high performance, revealing robustness across the different classifiers in terms of accuracy, true positive, and false positive rates. The combination of multi-domain features with the ensemble tree is the most effective solution, exhibiting accuracies above 93% in the 10-time 10-fold cross-validation and 84% in the leave-one-subject-out validation. Results confirmed the effectiveness of the proposed features and their potential use in a computer-aided system for the detection of arrhythmogenic sites. This work demonstrates for the first time the usefulness of supervised machine learning for the detection of arrhythmogenic sites in post-ischemic VT patients, thus enabling the development of computer-aided systems to reduce operator dependence and errors, thereby possibly improving clinical outcomes.

Retrospective Window of Interest Annotation Provides New Insights Into Functional Channels in Ventricular Tachycardia Substrate

BACKGROUND

Accurate annotation of local activation time is crucial in the functional assessment of ventricular tachycardia (VT) substrate. A major limitation of modern mapping systems is the standard prospective window of interest (sWOI) is limited to 490 to 500 milliseconds, preventing annotation of very late potentials (LPs). A novel retrospective window of interest (rWOI), which allows annotation of all diastolic potentials, was used to assess the functional VT substrate.

OBJECTIVES

This study sought to investigate the utility of a novel rWOI, which allows accurate visualization and annotation of all LPs during VT substrate mapping.

METHODS

Patients with high-density VT substrate maps and a defined isthmus were included. All electrograms were manually annotated to latest activation using a novel rWOI. Reannotated substrate maps were correlated to critical sites, with areas of late activation examined. Propagation patterns were examined to assess the functional aspects of the VT substrate.

RESULTS

Forty-eight cases were identified with 1,820 ± 826 points per map. Using the novel rWOI, 31 maps (65%) demonstrated LPs beyond the sWOI limit. Two distinct patterns of channel activation were seen during substrate mapping: 1) functional block with unidirectional conduction into the channel (76%); and 2) wave front collision within the channel (24%). In addition, a novel marker termed the zone of early and late crowding was studied in the rWOI substrate maps and found to have a higher positive predictive value (85%) than traditional deceleration zones (69%) for detecting critical sites of re-entry.

CONCLUSIONS

The standard WOI of contemporary mapping systems is arbitrarily limited and results in important very late potentials being excluded from annotation. Future versions of electroanatomical mapping systems should provide longer WOIs for accurate local activation time annotation.

Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications

Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From this foundation, the authors summarize recent advances in whole-heart ventricular arrhythmia modeling. Efforts in gaining mechanistic insights into ventricular arrhythmias are discussed, in addition to other applications of models such as the assessment of novel therapeutics. The review emphasizes the unique benefits of computational modeling that allow for insights that are not obtainable by contemporary experimental or clinical means. Additionally, the clinical impact of modeling is explored, demonstrating how patient care is influenced by the information gained from ventricular arrhythmia models. The authors conclude with future perspectives about the direction of whole-heart ventricular arrhythmia modeling, outlining how advances in neural network methodologies hold the potential to reduce computational expense and permit for efficient whole-heart modeling.

Dynamic spatial dispersion of repolarization is present in regions critical for ischemic ventricular tachycardia ablation

BACKGROUND

The presence of dynamic substrate changes may facilitate functional block and reentry in ventricular tachycardia (VT).

OBJECTIVE

We aimed to study dynamic ventricular repolarization changes in critical regions of the VT circuit during sensed single extrastimulus pacing known as the Sense Protocol (SP).

METHODS

Twenty patients (aged 67 ± 9 years, 17 male) underwent VT ablation. A bipolar voltage map was obtained during sinus rhythm (SR) and right ventricular SP pacing at 20 ms above ventricular effective refractory period. Ventricular repolarization maps were constructed. Ventricular repolarization time (RT) was calculated from unipolar electrogram T waves, using the Wyatt method, as the dV/dtmax of the unipolar T wave. Entrainment or pace mapping confirmed critical sites for ablation.

RESULTS

The median global repolarization range (max-min RT per patient) was 166 ms (interquartile range [IQR] 143-181 ms) during SR mapping vs 208 ms (IQR 182-234) during SP mapping (P = .0003 vs intrinsic rhythm). Regions of late potentials (LP) had a longer RT during SP mapping compared to regions without LP (mean 394 ± 40 ms vs 342 ± 25 ms, P < .001). In paired regions of normal myocardium there was no significant spatial dispersion of repolarization (SDR)/10 mm2 during SP mapping vs SR mapping (SDR 11 ± 6 ms vs 10 ± 6 ms, P = .54). SDR/10 mm2 was greater in critical areas of the VT circuit during SP mapping 63 ± 29 ms vs SR mapping 16 ± 9 ms (P < .001).

CONCLUSION

Ventricular repolarization is prolonged in regions of LP and increases dynamically, resulting in dynamic SDR in critical areas of the VT circuit. These dynamic substrate changes may be an important factor that facilitates VT circuits.

Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling

BACKGROUND

Identification of targets for ablation of post-infarction ventricular tachycardias (VTs) remains challenging, often requiring arrhythmia induction to delineate the reentrant circuit. This carries a risk for the patient and may not be feasible. Substrate mapping has emerged as a safer strategy to uncover arrhythmogenic regions. However, VT recurrence remains common.

GOAL

To use computer simulations to assess the ability of different substrate mapping approaches to identify VT exit sites.

METHODS

A 3D computational model of the porcine post-infarction heart was constructed to simulate VT and paced rhythm. Electroanatomical maps were constructed based on endocardial electrogram features and the reentry vulnerability index (RVI - a metric combining activation (AT) and repolarization timings to identify tissue susceptibility to reentry). Since scar transmurality in our model was not homogeneous, parameters derived from all signals (including dense scar regions) were used in the analysis. Potential ablation targets obtained from each electroanatomical map during pacing were compared to the exit site detected during VT mapping.

RESULTS

Simulation data showed that voltage cut-offs applied to bipolar electrograms could delineate the scar, but not the VT circuit. Electrogram fractionation had the highest correlation with scar transmurality. The RVI identified regions closest to VT exit site but was outperformed by AT gradients combined with voltage cut-offs. The performance of all metrics was affected by pacing location.

CONCLUSIONS

Substrate mapping could provide information about the infarct, but the directional dependency on activation should be considered. Activation-repolarization metrics have utility in safely identifying VT targets, even with non-transmural scars.

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

BACKGROUND

Pace-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.

METHOD

Six 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.

RESULTS

Our 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.

CONCLUSIONS

In-silico pace-mapping can be used along with EGMs from implanted devices to localise VT ablation targets in pre-procedural planning.

Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Patient-specific computer simulations can be a powerful tool in clinical applications, helping in diagnostics and the development of new treatments. However, its practical use depends on the reliability of the models. The construction of cardiac simulations involves several steps with inherent uncertainties, including model parameters, the generation of personalized geometry and fibre orientation assignment, which are semi-manual processes subject to errors. Thus, it is important to quantify how these uncertainties impact model predictions. The present work performs uncertainty quantification and sensitivity analyses to assess the variability in important quantities of interest (QoI). Clinical quantities are analysed in terms of overall variability and to identify which parameters are the major contributors. The analyses are performed for simulations of the left ventricle function during the entire cardiac cycle. Uncertainties are incorporated in several model parameters, including regional wall thickness, fibre orientation, passive material parameters, active stress and the circulatory model. The results show that the QoI are very sensitive to active stress, wall thickness and fibre direction, where ejection fraction and ventricular torsion are the most impacted outputs. Thus, to improve the precision of models of cardiac mechanics, new methods should be considered to decrease uncertainties associated with geometrical reconstruction, estimation of active stress and of fibre orientation. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Evaluation of the reentry vulnerability index to predict ventricular tachycardia circuits using high-density contact mapping

Background

Identifying arrhythmogenic sites to improve ventricular tachycardia (VT) ablation outcomes remains unresolved. The reentry vulnerability index (RVI) combines activation and repolarization timings to identify sites critical for reentrant arrhythmia initiation without inducing VT.

Objective

The purpose of this study was to provide the first assessment of RVI’s capability to identify VT sites of origin using high-density contact mapping and comparison with other activation-repolarization markers of functional substrate.

Methods

Eighteen VT ablation patients (16 male; 72% ischemic) were studied. Unipolar electrograms were recorded during ventricular pacing and analyzed offline. Activation time (AT), activation–recovery interval (ARI), and repolarization time (RT) were measured. Vulnerability to reentry was mapped based on RVI and spatial distribution of AT, ARI, and RT. The distance from sites identified as vulnerable to reentry to the VT site of origin was measured, with distances <10 mm and >20 mm indicating accurate and inaccurate localization, respectively.

Results

The origins of 18 VTs (6 entrainment, 12 pace-mapping) were identified. RVI maps included 1012 (408–2098) (median, 1st–3rd quartiles) points per patient. RVI accurately localized 72.2% VT sites of origin, with median distance of 5.1 (3.2–10.1) mm. Inaccurate localization was significantly less frequent for RVI than AT (5.6% vs 33.3%; odds ratio 0.12; P = .035). Compared to RVI, distance to VT sites of origin was significantly larger for sites showing prolonged RT and ARI and were nonsignificantly larger for sites showing highest AT and ARI gradients.

Conclusion

RVI identifies vulnerable regions closest to VT sites of origin. Activation-repolarization metrics may improve VT substrate delineation and inform novel ablation strategies.

Factors Promoting Conduction Slowing as Substrates for Block and Reentry in Infarcted Hearts

The development of effective and safe therapies for scar-related ventricular tachycardias requires a detailed understanding of the mechanisms underlying the conduction block that initiates electrical re-entries associated with these arrhythmias. Conduction block has been often associated with electrophysiological changes that prolong action potential duration (APD) within the border zone (BZ) of chronically infarcted hearts. However, experimental evidence suggests that remodeling processes promoting conduction slowing as opposed to APD prolongation mark the chronic phase. In this context, the substrate for the initial block at the mouth of an isthmus/diastolic channel leading to ventricular tachycardia is unclear. The goal of this study was to determine whether electrophysiological parameters associated with conduction slowing can cause block and re-entry in the BZ. In silico experiments were conducted on two-dimensional idealized infarct tissue as well as on a cohort of postinfarction porcine left ventricular models constructed from ex vivo magnetic resonance imaging scans. Functional conduction slowing in the BZ was modeled by reducing sodium current density, whereas structural conduction slowing was represented by decreasing tissue conductivity and including fibrosis. The arrhythmogenic potential of APD prolongation was also tested as a basis for comparison. Within all models, the combination of reduced sodium current with structural remodeling more often degenerated into re-entry and, if so, was more likely to be sustained for more cycles. Although re-entries were also detected in experiments with prolonged APD, they were often not sustained because of the subsequent block caused by long-lasting repolarization. Functional and structural conditions associated with slow conduction rather than APD prolongation form a potent substrate for arrhythmogenesis at the isthmus/BZ of chronically infarcted hearts. Reduced excitability led to block while slow conduction shortened the wavelength of propagation, facilitating the sustenance of re-entries. These findings provide important insights for models of patient-specific risk stratification and therapy planning.