Using the Surface Electrocardiogram to Localize the Origin of Idiopathic Ventricular Tachycardia

A "two-step classification" machine learning method for non-invasive localization of premature ventricular contraction origins based on 12-lead ECG

BACKGROUND

Premature ventricular contraction (PVC) is a type of cardiac arrhythmia that originates from ectopic pacemaker in the ventricles. The localization of the origin of PVC is essential for successful catheter ablation. However, most studies on non-invasive PVC localization focus on elaborate localization in specific regions of the ventricle. This study aims to propose a machine learning algorithm based on 12-lead electrocardiogram (ECG) data that can improve the accuracy of PVC localization in the whole ventricle.

METHODS

We collected 12-lead ECG data from 249 patients with spontaneous or pacing-induced PVCs. The ventricle was divided into 11 segments. In this paper, we propose a machine learning method consisting of two consecutive classification steps. In the first classification step, each PVC beat was labeled to one of the 11 ventricular segments using six features, including a newly proposed morphological feature called "Peak_index." Four machine learning methods were tested for comparative multi-classification performance and the best classifier result was kept to the next step. In the second classification step, a binary classifier was trained using a smaller combination of features to further differentiate segments that are easily confused.

RESULTS

The Peak_index as a proposed new classification feature combined with other features is suitable for whole ventricle classification by machine learning methods. The test accuracy of the first classification reached 75.87%. It is shown that a second classification for confusable categories can improve the classification results. After the second classification, the test accuracy reached 76.84%, and when a sample classified into adjacent segments was considered correct, the test "rank accuracy" was improved to 93.49%. The binary classification corrected 10% of the confused samples.

CONCLUSION

This paper proposes a "two-step classification" method to localize the origin of PVC beats into the 11 regions of the ventricle using non-invasive 12-lead ECG. It is expected to be a promising technique to be used in clinical settings to help guide ablation procedures.

Electrocardiographic characteristics of right-bundle-branch-block premature ventricular complexes predicting absence of left ventricular scar in athletes with apparently structural normal heart

AIMS

Left ventricular scar is an arrhythmic substrate that may be missed by echocardiography and diagnosed only by cardiac magnetic resonance (CMR), which is a time-consuming and expensive imaging modality. Premature ventricular complexes (PVCs) with a right-bundle-branch-block (RBBB) pattern are independent predictors of late gadolinium enhancement (LGE) but their positive predictive value is low. We studied which electrocardiographic features of PVCs with an RBBB pattern are associated with a higher probability of the absence of an underlying LGE.

METHODS

The study included 121 athletes (36 ± 16 years; 48.8% men) with monomorphic PVCs with an RBBB configuration and normal standard clinical investigations who underwent CMR. LGE was identified in 35 patients (29%), predominantly in those with PVCs with a superior/intermediate axis (SA-IntA) compared to inferior axis (IA) (38% vs. 10%, P = 0.002). Among patients with SA-IntA morphology, the contemporary presence of qR pattern in lead aVR and V1 was exclusively found in patients without LGE at CMR (51.0% vs. 0%, P < 0.0001). Among patients with IA, the absence of LGE correlated to a narrow ectopic QRS (145 ± 16 vs. 184 ± 27 msec, P < 0.001).

CONCLUSIONS

Among athletes with apparently idiopathic PVCs with a RBBB configuration, the presence of a concealed LGE at CMR was documented in 29% of cases, mostly in those with a SA-IntA. In our experience, the contemporary presence of qR pattern in lead aVR and V1 in PVCs with RBBB/SA-IntA morphology or, on the other hand, a relatively narrow QRS in PVCs with an IA, predicted absence of LGE.

Idiopathic Ventricular Tachycardia

Idiopathic ventricular tachycardia (VT) is an important cause of morbidity and less commonly, mortality in patients with structurally normal hearts. Appropriate diagnosis and management are predicated on an understanding of the mechanism, relevant cardiac anatomy, and associated ECG signatures. Catheter ablation is a viable strategy to adequately treat and potentially provide a cure in patients that are intolerant to medications or when these are ineffective. In this review, we discuss special approaches and considerations for effective and safe ablation of VT arising from the right ventricular outflow tract, left ventricular outflow tract, left ventricular fascicles, papillary muscles, and moderator band.

Best Practices for the Catheter Ablation of Ventricular Arrhythmias

Techniques for catheter ablation have evolved to effectively treat a range of ventricular arrhythmias. Pre-operative electrocardiographic and cardiac imaging data are very useful in understanding the arrhythmogenic substrate and can guide mapping and ablation. In this review, we focus on best practices for catheter ablation, with emphasis on tailoring ablation strategies, based on the presence or absence of structural heart disease, underlying clinical status, and hemodynamic stability of the ventricular arrhythmia. We discuss steps to make ablation safe and prevent complications, and techniques to improve the efficacy of ablation, including optimal use of electroanatomical mapping algorithms, energy delivery, intracardiac echocardiography, and selective use of mechanical circulatory support.

The value of QRS onset of the outflow tract PVC in V1 and V2 leads recorded in fourth, third, and second intercostal spaces to differentiate main origins of premature ventricular contraction—A prospective cohort study

Background

Electrocardiography (ECG) is now proposed as a simple and cost‐effective tool to determine the location of arrhythmias before ablation. We aimed to examine the value of the QRS onset of outflow tract PVC in V1 and V2 leads recorded in fourth, third, and second intercostal spaces to differentiate two main origins for premature ventricular contraction (PVC) including right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT).

Methods

In this prospective cohort study, a total of 58 patients were studied, from whom a surface ECG was obtained using V1 and V2 leads in the fourth, third, and second intercostal spaces. ECG and Electrophysiology studie (EPS) data were then recorded and compared to determine the sensitivity and specificity of QRS onset in locating arrhythmias. The reciever operating characterictic (ROC) curve analysis was applied to test diagnostic performance.

Results

Based on the time of PVC initiation in each of the V1 and V2 leads in the fourth intercostal space, if PVC is recorded earlier in the V1 lead, its source in 95.8% of the patients is RVOT and if PVC preceded the V2 lead, 70.59% of the patients had PVC from LVOT. Comparing of QRS onset in V1 and V2 leadsrecorded from third% and and second intercostal spaces had considerable sensitivity and specificity to determine the origin of the outflow tract PVC (81.82 and 94.12%, respectively)

Conclusion

Simultaneous recording of outflow tract PVCs from second third and fourth intercostal spaces and comparing their onset can determine the left and right outflow tract PVCs with high sensitivity and specificity.

A High-Precision Deep Learning Algorithm to Localize Idiopathic Ventricular Arrhythmias

Background: An accurate prediction of ventricular arrhythmia (VA) origins can optimize the strategy of ablation, and facilitate the procedure. Objective: This study aimed to develop a machine learning model from surface ECG to predict VA origins. Methods: We obtained 3628 waves of ventricular premature complex (VPC) from 731 patients. We chose to include all signal information from 12 ECG leads for model input. A model is composed of two groups of convolutional neural network (CNN) layers. We chose around 13% of all the data for model testing and 10% for validation. Results: In the first step, we trained a model for binary classification of VA source from the left or right side of the chamber with an area under the curve (AUC) of 0.963. With a threshold of 0.739, the sensitivity and specification are 90.7% and 92.3% for identifying left side VA. Then, we obtained the second model for predicting VA from the LV summit with AUC is 0.998. With a threshold of 0.739, the sensitivity and specificity are 100% and 98% for the LV summit. Conclusions: Our machine learning algorithm of surface ECG facilitates the localization of VPC, especially for the LV summit, which might optimize the ablation strategy.

Ventricular tachycardia originating from the His bundle: A case report

BACKGROUND

Ventricular tachycardia (VT) commonly occurs among patients with heart failure and can even cause sudden cardiac death. VT originating from the His bundle branch has been rarely reported. We present the case of a patient with VT from the His bundle branch.

CASE SUMMARY

A 58-year-old female complained of paroxysmal palpitations and dizziness for approximately 6 mo. She had a history of fatty liver and cholecystitis, and carotid atherosclerosis could not be excluded from the ultrasound results. An evaluation of the electrocardiogram obtained after admission showed spontaneous conversion between two different morphologies. The possible electrophysiologic mechanism suggested that the dual-source VT originated from the same source, the His bundle branch. Finally, the His bundle branch was ablated, and a dual-chamber pacemaker was inserted into the patient’s heart. No further VT occurred during the 3-year follow-up after hospital discharge.

CONCLUSION

The diagnosis of VT originating from the His bundle is rare and difficult to establish. The results of this study showed VT originating from the His bundle based on a careful evaluation of the electrocardiogram, and the diagnosis was confirmed by an intracardiac electrophysiologic examination.

Flecainide in Ventricular Arrhythmias: From Old Myths to New Perspectives

Flecainide is an IC antiarrhythmic drug (AAD) that received in 1984 Food and Drug Administration approval for the treatment of sustained ventricular tachycardia (VT) and subsequently for rhythm control of atrial fibrillation (AF). Currently, flecainide is mainly employed for sinus rhythm maintenance in AF and the treatment of idiopathic ventricular arrhythmias (IVA) in absence of ischaemic and structural heart disease on the basis of CAST data. Recent studies enrolling patients with different structural heart diseases demonstrated good effectiveness and safety profile of flecainide. The purpose of this review is to assess current evidence for appropriate and safe use of flecainide, 30 years after CAST data, in the light of new diagnostic and therapeutic tools in the field of ischaemic and non-ischaemic heart disease.

Prospective Multicenter Assessment of a New Intraprocedural Automated System for Localizing Idiopathic Ventricular Arrhythmia Origins

OBJECTIVES

The objective of this study was to present a new system, the Automatic Arrhythmia Origin Localization (AAOL) system, which used incomplete electroanatomic mapping (EAM) for localization of idiopathic ventricular arrhythmia (IVA) origin on the patient-specific geometry of left ventricular, right ventricular, and neighboring vessels. The study assessed the accuracy of the system in localizing IVA source sites on cardiac structures where pace mapping is challenging.

BACKGROUND

An intraprocedural automated site of origin localization system was previously developed to identify the origin of early left ventricular activation by using 12-lead electrocardiograms (ECGs). However, it has limitations, as it could not identify the site of origin in the right ventricle and relied on acquiring a complete EAM.

METHODS

Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The new system combined 3-lead (III, V₂, and V₆) 120-ms QRS integrals and patient-specific EAM geometry with pace mapping to predict the site of earliest ventricular activation. The predicted site was projected onto EAM geometry.

RESULTS

Twenty-three IVA origin sites were clinically identified by activation mapping and/or pace mapping (8, right ventricle; 15, left ventricle, including 8 from the posteromedial papillary muscle, 2 from the aortic root, and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs.

CONCLUSIONS

The new intraprocedural AAOL system achieved accurate localization of IVA origin in ventricles and neighboring vessels, which could facilitate ablation procedures for patients with IVAs.

<p>Park Algorithm as Predictor of Premature Ventricular Contraction Origin in Three‐Dimensional Mapping Electrophysiological Studies</p>

Purpose

In the past few years, premature ventricular contraction (PVC) has attracted immense attention, both in patients with or without structural heart disease. Despite the technological advancement, no guiding tools are currently available to assist in the prediction of origin of PVC using a 12‐lead electrocardiogram (ECG) before electrophysiology and ablation procedures. Park and co‐workers compiled the existing algorithms for the morphology of ECG from the literature and generated a single algorithm based on specific features of ECG for the prediction of PVC origin. The Park algorithm is limited to idiopathic PVC and has not been evaluated clinically. In the present study, the Park algorithm was used to predict PVC origin in patients with or without structural heart disease and compared with the gold standard examination based on three-dimensional electrophysiological mapping studies.

Patients and Methods

A cross‐sectional study employing ECG data and electrophysiology study (EPS) reports from patients’ medical records at Integrated Heart Center Wahidin Sudirohusodo Hospital, Makassar, Indonesia was conducted. The study was performed from April 2018 to June 2019 with a total of 31 samples; however, four samples were excluded during the EPS.

Results

In the present study, the incidence of structural heart disease was 45.2%. The suitability of the Park algorithm for electrophysiological evaluation was 85.2%, both in the case of PVC with and/or without structural heart disease. The prediction of the origin of PVC in the right or left heart using the Park algorithm showed a sensitivity of 95%, specificity of 100%, positive predictive value of 100%, negative predictive value of 87.5%, and accuracy of 96%.

Conclusion

The findings of the study suggest significant accuracy of the Park algorithm in the prediction of location of origin of PVC. High sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the Park algorithm highlight its suitability to be used for determining the location of PVC origin in the right or left heart.

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Electrocardiographic interpretation in athletes

Participation in regular exercise of moderate intensity is associated with a plethora of systemic benefits, including a reduction in risk factors for coronary atherosclerosis; however, intensive exercise may paradoxically culminate in sudden cardiac arrest among individuals harboring arrhythmogenic substrates. The precise mechanism for arrhythmogenesis is likely multifactorial, however, surges in catecholamines, electrolyte shifts, acid-base disturbances, increased core temperature and demand myocardial ischemia are potential contributors. Although most deaths occur in middle aged and older males with atherosclerotic coronary artery disease, a significant proportion also affect young athletes with inherited or congenital cardiac abnormalities. The impact of such catastrophes on society, particularly when a young high-profile athlete is affected could be considered a justified reason for identifying individuals who may be at risk. Given the rarity of deaths in young athletes, only the simplest screening test, such as the 12-lead electrocardiography (ECG) may be considered to be cost effective. The ECG is effective for detecting serious electrical diseases in young athletes such as congenital electrical accessory pathways and ion channel diseases but can also identify athletes with potential life-threatening structural diseases such as hypertrophic and arrhythmogenic cardiomyopathy. One of the concerns about ECG screening is that regular intensive exercise results in several physiological alterations in cardiac structure and function that are reflected on the athlete's ECG. Sinus bradycardia, first-degree atrioventricular block, incomplete right bundle branch block, minor J-point elevation and large QRS voltages are common. Conversely, some repolarization anomalies affecting the ST segment, T waves and QT interval may overlap with patterns observed in patients with serious cardiac diseases. The situation is complicated further because age, sex and ethnicity of the athletes also influence the ECG and there is a risk that erroneous interpretation could have serious consequences. This review will describe the normal electrical patterns of the "athlete's heart" and provide insights into differentiation physiological electrical patterns from those observed in serious cardiac disease.

A hybrid machine learning approach to localizing the origin of ventricular tachycardia using 12-lead electrocardiograms

BACKGROUND

Machine learning models may help localize the site of origin of ventricular tachycardia (VT) using 12-lead electrocardiograms. However, population-based models suffer from inter-subject anatomical variations within ECG data, while patient-specific models face the open challenge of what pacing data to collect for training.

METHODS

This study presents and validates the first hybrid model that combines population and patient-specific machine learning for rapid "computer-guided pace-mapping". A population-based deep learning model was first trained offline to disentangle inter-subject variations and regionalize the site of VT origin. Given a new patient with a target VT, an on-line patient-specific model -- after being initialized by the population-based prediction -- was then built in real time by actively suggesting where to pace next and improving the prediction with each added pacing data, progressively guiding pace-mapping towards the site of VT origin.

RESULTS

The population model was trained on pace-mapping data from 38 patients and the patient-specific model was subsequently tuned on one patient. The resulting hybrid model was tested on a separate cohort of eight patients in localizing 1) 193 LV endocardial pacing sites, and 2) nine VTs with clinically determined exit sites. The hybrid model achieved a localization error of 5.3 ± 2.6 mm using 5.4 ± 2.5 pacing sites in localizing LV pacing sites, achieving a significantly higher accuracy with a significantly smaller amount of training sites in comparison to models without active guidance.

CONCLUSION

The presented hybrid model has the potential to assist rapid pace-mapping of interventional targets in VT.

Electrocardiographic characteristics of idiopathic ventricular arrhythmias based on anatomy

Idiopathic ventricular arrhythmia (IVA) is a term used to describe a spectrum of ventricular arrhythmia without structural heart disease (SHD). IVAs contain premature ventricular contractions (PVCs), nonsustained monomorphic ventricular tachycardia (VT), and sustained VT. Electrocardiography is a fundamental and important tool to diagnose and localize IVAs. More detailed, IVAs originating from different origins exhibit characterized ECGs due to their specific anatomic backgrounds. As catheter ablation becomes widely used to eliminate these arrhythmias, its high success rate is based on accurate localization of their origins. Therefore, these ECG characteristics show great importance for precise localization of their origins and subsequently successful ablation. This review aims to sum up ECG characteristics of IVAs based on anatomy and give brief introduction of mechanisms and treatment of IVAs.

Abnormal ECG Findings in Athletes: Clinical Evaluation and Considerations

PURPOSE OF REVIEW

Pre-participation cardiovascular evaluation with electrocardiography is normal practice for most sporting bodies. Awareness about sudden cardiac death in athletes and recognizing how screening can help identify vulnerable athletes have empowered different sporting disciplines to invest in the wellbeing of their athletes.

RECENT FINDINGS

Discerning physiological electrical alterations due to athletic training from those representing cardiac pathology may be challenging. The mode of investigation of affected athletes is dependent on the electrical anomaly and the disease(s) in question. This review will highlight specific pathological ECG patterns that warrant assessment and surveillance, together with an in-depth review of the recommended algorithm for evaluation.

Premature ventricular complexes: diagnostic and therapeutic considerations in clinical practice : A state-of-the-art review by the American College of Cardiology Electrophysiology Council

Premature ventricular complexes (PVCs) are common arrhythmias in the clinical setting. PVCs in the structurally normal heart are usually benign, but in the presence of structural heart disease (SHD), they may indicate increased risk of sudden death. High PVC burden may induce cardiomyopathy and left ventricular (LV) dysfunction or worsen underlying cardiomyopathy. Sometimes PVCs may be a marker of underlying pathophysiologic process such as myocarditis. Identification of PVC burden is important, since cardiomyopathy and LV dysfunction can reverse after catheter ablation or pharmacological suppression. This state-of-the-art review discusses pathophysiology, clinical manifestations, how to differentiate benign and malignant PVCs, PVCs in the structurally normal heart, underlying SHD, diagnostic procedures (physical examination, electrocardiogram, ambulatory monitoring, exercise testing, echocardiography, cardiac magnetic resonance imaging, coronary angiography, electrophysiology study), and treatment (lifestyle modification, electrolyte imbalance, medical, and catheter ablation).

Twelve-lead electrocardiographic localization of idiopathic premature ventricular contraction origins

The major sites of origins of idiopathic ventricular arrhythmias have been elucidated. Idiopathic ventricular arrhythmias most often present as premature ventricular contractions (PVCs) with a focal mechanism, and commonly occur without structural heart disease. Idiopathic ventricular arrhythmias usually originate from specific anatomical structures, commonly endocardial but sometimes epicardial and exhibit characteristic electrocardiograms (ECGs) based on their anatomical background. There are general and specific ECG characteristics that can localize the site of idiopathic PVC origins. The general ECG characteristics include the bundle branch block pattern, axis, QRS polarity in lead V6, QRS duration, precordial transition, maximal deflection index, and so forth. They can roughly localize the site of idiopathic PVC origins. Several major sites of idiopathic PVC origins are located close to each other, and specific ECG characteristics are helpful for localizing the site of origins more accurately in those PVCs. Twelve-lead surface ECG algorithms usually can localize the site of idiopathic PVC origins with a high accuracy, but their accuracy can be limited by the patients' physique, heart rotation, specific conduction properties, presence of structural heart disease, and so forth. This review describes an overview of the approaches to the 12-lead surface ECG localization of idiopathic PVCs, and also discusses their caveats and limitations.

Sequential Factorized Autoencoder for Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms

OBJECTIVE

This work presents a novel approach to handle the inter-subject variations existing in the population analysis of ECG, applied for localizing the origin of ventricular tachycardia (VT) from 12-lead electrocardiograms (ECGs).

METHODS

The presented method involves a factor disentangling sequential autoencoder (f-SAE) - realized in both long short-term memory (LSTM) and gated recurrent unit (GRU) networks - to learn to disentangle the inter-subject variations from the factor relating to the location of origin of VT. To perform such disentanglement, a pair-wise contrastive loss is introduced.

RESULTS

The presented methods are evaluated on ECG dataset with 1012 distinct pacing sites collected from scar-related VT patients during routine pace-mapping procedures. Experiments demonstrate that, for classifying the origin of VT into the predefined segments, the presented f-SAE improves the classification accuracy by 8.94% from using prescribed QRS features, by 1.5% from the supervised deep CNN network, and 5.15% from the standard SAE without factor disentanglement. Similarly, when predicting the coordinates of the VT origin, the presented f-SAE improves the performance by 2.25 mm from using prescribed QRS features, by 1.18 mm from the supervised deep CNN network and 1.6 mm from the standard SAE.

CONCLUSION

These results demonstrate the importance as well as the feasibility of the presented f-SAE approach for separating inter-subject variations when using 12-lead ECG to localize the origin of VT.

SIGNIFICANCE

This work suggests the important research direction to deal with the well-known challenge posed by inter-subject variations during population analysis from ECG signals.

Idiopathic basal crux ventricular arrhythmias with left bundle branch block and superior axis: A comparison with inferior-septal valvular arrhythmias

INTRODUCTION

Left bundle branch block (LBBB) with superior axis is common in patients with idiopathic-ventricular arrhythmia (VA) originating from the tricuspid annulus (TA) and rarely from the cardiac basal crux and mitral annulus (MA). We described the electrocardiography and electrophysiological findings of idiopathic-VA presenting with LBBB and superior axis.

METHODS AND RESULTS

We described 42 idiopathic-VA patients who had an LBBB and superior axis; 15 basal crux-VA, 17 TA-VA, and 10 MA-VA. No patient had a structural heart disease. Among patients with idiopathic-VA referred for ablation, we investigated the electrocardiogram and clinical characteristics of basal crux-VA as compared with other LBBB and superior axis-VA. The left ventricular ejection fraction with MA-VA was significantly lower in comparison with basal crux-VA (P = .01). All patients had a positive R wave in lead I and aVL. The maximum deflection index with basal crux-VA was significantly higher in comparison with TA-VA or MA-VA (P = .01). Patients with basal crux-VA presented with QS wave in lead II more frequently as compared with TA-VA or MA-VA (P = .001). All MA-VA patients had Rs wave in V6, and basal crux-VA, and TA-VA patients had a monophasic R wave or Rs wave in V6. Basal crux-VA patients underwent ablation in the middle cardiac vein (MCV) or coronary sinus (success rate: 94%, recurrence rate: 6%).

CONCLUSIONS

We could distinguish basal crux-VA, TA-VA, and MA-VA, using a combination of clinical and electrocardiographic findings. These findings might be useful for counseling patients about an ablation strategy. Ablation via the MCV is effective for eliminating basal crux-VA.

Learning Domain Shift in Simulated and Clinical Data: Localizing the Origin of Ventricular Activation From 12-Lead Electrocardiograms

Building a data-driven model to localize the origin of ventricular activation from 12-lead electrocardiograms (ECG) requires addressing the challenge of large anatomical and physiological variations across individuals. The alternative of a patient-specific model is, however, difficult to implement in clinical practice because the training data must be obtained through invasive procedures. In this paper, we present a novel approach that overcomes this problem of the scarcity of clinical data by transferring the knowledge from a large set of patient-specific simulation data while utilizing domain adaptation to address the discrepancy between the simulation and clinical data. The method that we have developed quantifies non-uniformly distributed simulation errors, which are then incorporated into the process of domain adaptation in the context of both classification and regression. This yields a quantitative model that, with the addition of 12-lead ECG data from each patient, provides progressively improved patient-specific localizations of the origin of ventricular activation. We evaluated the performance of the presented method in localizing 75 pacing sites on three in-vivo premature ventricular contraction (PVC) patients. We found that the presented model showed an improvement in localization accuracy relative to a model trained on clinical ECG data alone or a model trained on combined simulation and clinical data without considering domain shift. Furthermore, we demonstrated the ability of the presented model to improve the real-time prediction of the origin of ventricular activation with each added clinical ECG data, progressively guiding the clinician towards the target site.

Segmented radial cardiac MRI during arrhythmia using retrospective electrocardiogram and respiratory gating

PURPOSE

To improve segmented cardiac MRI image quality during arrhythmia.

METHODS

Electrocardiogram (ECG) and respiratory waveforms were recorded during imaging. Imaging readouts were retrospectively classified into heartbeat-types based on the RR interval of the current and preceding beats, QRS morphology, and respiratory phase. Image data were sorted by these classifiers to generate separate cine images of different heartbeat-types during sinus rhythm and arrhythmia. A simulation study evaluated the efficiency of K-space sampling over a range of heart rhythms, heart rates, and respiratory rates. In vivo imaging was performed in volunteers with sinus rhythm, swine with arrhythmia simulated by pacing, and a human subject with spontaneous premature beats.

RESULTS

K-space sampling uniformity and image quality incrementally improve with additional occurrences of the desired normal sinus or arrhythmia heartbeat-type. To approach the image quality of breath-hold imaging, sufficiently restrictive gating parameters are required. Compared with real-time imaging, retrospective gated images had reduced noise and improved sharpness while maintaining desired cine temporal resolution. Variations of cardiac function between arrhythmia heartbeats could be observed in arrhythmia imaging cases that are not captured by conventional segmented imaging.

CONCLUSION

Retrospective ECG and respiratory gating permits imaging of various heartbeats during arrhythmia with fewer resolution restrictions compared to real-time imaging. For a fixed imaging time, imaging quality depends on frequency of the imaged heartbeat-type. Imaging additional heartbeats permits incremental improvement in image quality.

Ventricular Arrhythmias in the Patient with a Structurally Normal Heart

Ventricular arrhythmias (VAs) are among the most common cardiac rhythm disturbances encountered in clinical practice. Patients presenting with frequent ventricular ectopy or sustained ventricular tachycardia represent a challenging and worrisome clinical scenario for many practitioners because of concerning symptoms, frequent associated acute hemodynamic compromise, and the adverse prognostic implications inherent to these cases. While an underlying structural or functional cardiac abnormality, metabolic derangement, or medication toxicity is often readily apparent, many patients have no obvious underlying condition, despite a comprehensive diagnostic evaluation. Such patients are diagnosed as having an idiopathic VA, which is a label with specific implications regarding arrhythmia origin, prognosis, and potential for pharmacologic and invasive management. Further, a subset of patients with otherwise benign idiopathic ventricular ectopy can present with polymorphic ventricular tachycardia and ventricular fibrillation, adding a layer of complexity to a clinical syndrome previously felt to have a benign clinical course. Thus, this review seeks to highlight the most common types of idiopathic VAs with a focus on their prognostic implications, underlying electrophysiologic mechanisms, unique electrocardiographic signatures, and considerations for invasive electrophysiologic study and catheter ablation. We further address some of the data regarding idiopathic ventricular fibrillation with respect to the heterogeneous nature of this diagnosis.

Idiopathic Ventricular Premature Contraction and Ventricular Tachycardia: Distribution of the Origin, Diagnostic Algorithm, and Catheter Ablation

Idiopathic ventricular premature contractions (VPCs), defined as VPCs in the absence of obvious structural heart disease, are one of the common types of arrhythmia in clinical practice. They are sometimes complicated with non-sustained ventricular tachycardia (VT), and/or sustained VT with almost same QRS morphology in 12 leads ECG. Idiopathic VT (IVT) commonly occurs by focal mechanisms and the origins are distributed in a variety of sites in both ventricles. In this article, the clinical characteristics of IVT/IVPCs, the diagnostic algorithm, and how to ablate them will be reviewed.

Electrocardiographic morphology of multiple ventricular arrhythmias originating from the right ventricular outflow tract: inverse correlation of the amplitude in the inferior leads and anatomic height of the origin

It is unclear whether the electrocardiogram amplitude in the inferior leads (Amp-I) can always predict the height of the origin of right ventricular outflow tract arrhythmias (RVOT-VAs). We analyzed patients who received catheter ablation of multiple RVOT-VAs in the same session in our hospital from 2011 to 2016. Two distinguished RVOT-VAs, those with anatomically higher origins (HOs) and lower origins (LOs), were identified and compared to measure the longitudinal distance. Amp-I was uniquely determined for each OTVA as the highest amplitude in leads II, III, and aVF and compared between the HO-VAs and LO-VAs. In total, out of 187 patients who underwent catheter ablation of RVOT-VAs, 9 (4.8%) had multiple right OTVAs successfully treated. Four cases (Group A) had HO-VAs (10.8 ± 5.3 mm from an LO) with a lower Amp-I (1.28 ± 0.46 mV) than the LO-VAs (1.81 ± 0.59 mV), whereas the other 4 patients (Group B) had HO-VAs with a higher Amp-I (1.91 ± 0.23 mV) than the LO-VAs (1.26 ± 0.35 mV). In Group A, all HO-VAs originated from the lateral free wall and had notched R waves in the inferior leads, whereas all LOs with higher Amp-Is were located on the septum. In one patient, the HO and LO were at almost the same height, while a VA from a lateral origin had lower notched R waves in the inferior leads. A divided excitation from high lateral origins may result in not only QRS notching, but also a reduction in the QRS amplitude. In patients harboring multiple RVOT-VAs, VAs arising from the high lateral free wall could have lower Amp-Is than VAs from low septal origins.

Noninvasive epicardial and endocardial mapping of premature ventricular contractions

Aims

The aim of the present study was to estimate the accuracy of a novel non-invasive epicardial and endocardial electrophysiology system (NEEES) for mapping ectopic ventricular depolarizations.

Methods and results

The study enrolled 20 patients with monomorphic premature ventricular contractions (PVCs) or ventricular tachycardia (VT). All patients underwent pre-procedural computed tomography or magnetic resonance imaging of the heart and torso. Radiographic data were semi-automatically processed by the NEEES to reconstruct a realistic 3D model of the heart and torso. In the electrophysiology laboratory, body-surface electrodes were connected to the NEEES followed by unipolar EKG recordings during episodes of PVC/VT. The body-surface EKG data were processed by the NEEES using its inverse-problem solution software in combination with anatomical data from the heart and torso. The earliest site of activation as denoted on the NEEES 3D heart model was compared with the PVC/VT origin using a 3D electroanatomical mapping system. The site of successful catheter ablation served as final confirmation. A total of 21 PVC/VT morphologies were analysed and ablated. The chamber of interest was correctly diagnosed non-invasively in 20 of 21 (95%) PVC/VT cases. In 18 of the 21 (86%) cases, the correct ventricular segment was diagnosed. Catheter ablation resulted in acute success in 19 of the 20 (95%) patients, whereas 1 patient underwent successful surgical ablation. During 6 months of follow-up, 19 of the 20 (95%) patients were free from recurrence off antiarrhythmic drugs.

Conclusion

The NEEES accurately identified the site of PVC/VT origin. Knowledge of the potential site of the PVC/VT origin may aid the physician in planning a successful ablation strategy.

Spectrum of Ventricular Arrhythmias Arising from Papillary Muscle in the Structurally Normal Heart

Papillary muscle is an endocavitary structure that can give rise to ventricular arrhythmias in a structurally normal heart. Its manifestation is generally benign. The papillary muscle's complex anatomy and the presence of intermixed Purkinje fibers can create a substrate for idiopathic ventricular fibrillation. Although differentiating ventricular arrhythmias originating from the papillary muscle and the fascicles is challenging and not always possible, the distinction may be helpful for planning ablation. The propensity for difficulty with ablation of papillary arrhythmias results in a variable success rate. Improvement in techniques to stabilize the catheter, use of imaging, and methods of energy delivery are required to improve ablation outcomes.

Recurrent AICD shocks in a 60-year-old man

CLINICAL INTRODUCTION

We present the case of a 60-year-old man with history of non-ischaemic cardiomyopathy with left ventricular ejection fraction of 40%. His baseline surface 12-lead ECG shows sinus rhythm with PR interval of 170 ms, no evidence of pre-excitation and a normal QT interval. He had a single-chamber automated implantable cardiac defibrillator (AICD) inserted for sustained wide complex tachycardia associated with palpitations. Subsequently, he presented with recurrent shocks from the AICD coming on at rest despite treatment with amiodarone. He did not experience any significant cardiovascular symptoms except for mild palpitations. There were no reversible causes found for his arrhythmia. Figure 1 shows the device EGM of the event leading to the shock.

QUESTION

What is the tachycardia that caused the AICD shock? (figure 1) Atrial fibrillation (AF) with pre-excitationVentricular fibrillation (VF)Multiform ventricular tachycardia (VT)Atrial tachycardia (AT) with bundle branch blockTorsades de Pointes (TdP).

The QRS morphology pattern in V5R is a novel and simple parameter for differentiating the origin of idiopathic outflow tract ventricular arrhythmias

AIMS

There are many reports on the ECG characteristics of idiopathic outflow tract ventricular arrhythmias (OT-VAs) to predict their origin. However, differentiating near regions using 12-lead ECGs is still complicated. The synthesized 18-lead ECG derived from the 12-lead ECG can provide virtual waveforms of the right-sided chest leads (V3R, V4R, and V5R) and back leads (V7, V8, and V9). The aim of this study was to develop a simple and useful parameter for differentiating OT-VA origins using the 18-lead ECG.

METHODS AND RESULTS

We studied 28 and 73 patients with idiopathic VAs in a pacemapping study and validation cohort, respectively. In the pacemapping study, several sites out of five different sites were paced in each patient: the anterior and posterior right ventricular OT (RVOT-ant and RVOT-post), right and left coronary cusps (RCC and LCC), and junction of both cusps (RLJ). The 18-lead ECGs during pacemapping among the five sites were compared for establishing a simple parameter to predict VA origins. A novel parameter using 18-lead ECGs was tested prospectively in 73 patients. In the pacemapping study, the dominant QRS morphology pattern in the synthesized V5R significantly differed among those sites (RVOT-ant:Rs, RVOT-post:rS, RCC:QS, RLJ:qR, and LCC:R). The patients in the validation cohort were divided into five groups depending on those QRS morphology patterns during VAs in the synthesized V5R. Each V5R QRS morphology pattern could predict a precise origin of the OT-VAs with an overall accuracy of 75%.

CONCLUSION

The QRS morphology pattern in V5R was a simple and useful parameter for differentiating detailed OT-VA origins.