Machine Learning Identifies Arrhythmogenic Features of QRS Fragmentation in Human Cardiomyopathy: Implications for Improving Risk Stratification.

Background: Heterogeneous ventricular activation can provide the substrate for ventricular arrhythmias (VA), but its manifestation on the electrocardiogram (ECG) as a risk stratifier is not well-defined.

Objective: To characterize the spatiotemporal features of QRS peaks that best predict VA in patients with cardiomyopathy (CM) using machine learning (ML).

Methods: Prospectively enrolled CM patients with prophylactic defibrillators (n=95) underwent digital, high-resolution ECG recordings during intrinsic rhythm and ventricular pacing at 100 to 120 beats/min.

P-Wave Duration/Amplitude Ratio Quantifies Atrial Low-Voltage Area and Predicts Atrial Arrhythmia Recurrence After Pulmonary Vein Isolation.

Background: Atrial low-voltage areas (LVAs) in patients with atrial fibrillation increase the risk of atrial arrhythmia (AA) recurrence after pulmonary vein isolation (PVI). Contemporary LVA prediction scores (DR-FLASH, APPLE) do not include P-wave metrics. We aimed to evaluate the utility of P-wave duration/amplitude ratio (PWR) in quantifying LVA and predicting AA recurrence after PVI.

Automated Quantification of Abnormal QRS Peaks From High-Resolution ECGs Predicts Late Ventricular Arrhythmias in Hypertrophic Cardiomyopathy: A 5-Year Prospective Multicenter Study.

Background Patients with hypertrophic cardiomyopathy (HCM) are at risk of ventricular arrhythmia (VA) attributed to abnormal electrical activation arising from myocardial fibrosis and myocyte disarray. We sought to quantify intra-QRS peaks (QRSp) in high-resolution ECGs as a measure of abnormal activation to predict late VA in patients with HCM. Methods and Results Prospectively enrolled patients with HCM (n=143, age 53±14 years) with prophylactic implantable cardioverter-defibrillators had 3-minute, high-resolution (1024 Hz), digital 12-lead ECGs recorded during intrinsic rhythm.

Use of Wearable Technology and Deep Learning to Improve the Diagnosis of Brugada Syndrome.

Background: The diagnosis of Brugada syndrome by 12-lead electrocardiography (ECG) is challenging because the diagnostic type 1 pattern is often transient.

Objectives: This study sought to improve Brugada syndrome diagnosis by using deep learning (DL) to continuously monitor for Brugada type 1 in 24-hour ambulatory 12-lead ECGs (Holters).

Methods: A convolutional neural network was trained to classify Brugada type 1.

Microvolt QRS Alternans in Hypertrophic Cardiomyopathy: A Novel Risk Marker of Late Ventricular Arrhythmias.

Background Unlike T-wave alternans (TWA), the relation between QRS alternans (QRSA) and ventricular arrhythmia (VA) risk has not been evaluated in hypertrophic cardiomyopathy (HCM). We assessed microvolt QRSA/TWA in relation to HCM risk factors and late VA outcomes in HCM. Methods and Results Prospectively enrolled patients with HCM (n=130) with prophylactic implantable cardioverter-defibrillators underwent digital 12-lead ECG recordings during ventricular pacing (100-120 beats/min).

Deep Learning Classification of Unipolar Electrograms in Human Atrial Fibrillation: Application in Focal Source Mapping.

Focal sources are potential targets for atrial fibrillation (AF) catheter ablation, but they can be time-consuming and challenging to identify when unipolar electrograms (EGM) are numerous and complex. Our aim was to apply deep learning (DL) to raw unipolar EGMs in order to automate putative focal sources detection. We included 78 patients from the Focal Source and Trigger (FaST) randomized controlled trial that evaluated the efficacy of adjunctive FaST ablation compared to pulmonary vein isolation alone in reducing AF recurrence.

Unipolar electrogram-based voltage mapping with far-field cancellation to improve detection of abnormal atrial substrate during atrial fibrillation.

Introduction: An important substrate for atrial fibrillation (AF) is fibrotic atrial myopathy. Identifying low voltage, myopathic regions during AF using traditional bipolar voltage mapping is limited by the directional dependency of wave propagation. Our objective was to evaluate directionally independent unipolar voltage mapping, but with far-field cancellation, to identify low-voltage regions during AF.

Predicting Survival After VA-ECMO for Refractory Cardiogenic Shock: Validating the SAVE Score.

Background: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is used increasingly to support patients who are in cardiogenic shock. Due to the risk of complications, prediction models may aid in identifying patients who would benefit most from VA-ECMO. One such model is the Survival After Veno-Arterial Extracorporeal Membrane Oxygenation (SAVE) score.

Focal and pseudo/rotational activations in human atrial fibrillation defined with automated periodicity mapping.

Introduction: Defining atrial fibrillation (AF) wave propagation is challenging unless local signal features are discrete or periodic. Periodic focal or rotational activity may identify AF drivers. Our objective was to characterize AF propagation at sites with periodic activation to evaluate the prevalence and relationship between focal and rotational activation.

Microvolt QRS Alternans Without Microvolt T-Wave Alternans in Human Cardiomyopathy: A Novel Risk Marker of Late Ventricular Arrhythmias.

Background Action potential alternans can induce ventricular tachyarrhythmias and manifest on the surface ECG as T-wave alternans (TWA) and QRS alternans (QRSA). We sought to evaluate microvolt QRSA in cardiomyopathy patients in relation to TWA and ventricular tachyarrhythmia outcomes. Methods and Results Prospectively enrolled cardiomyopathy patients (n=100) with prophylactic defibrillators had 12-lead ECGs recorded during ventricular pacing from 100 to 120 beats/min.

Focal source and trigger mapping in atrial fibrillation: Randomized controlled trial evaluating a novel adjunctive ablation strategy.

Background: Intraoperative mapping has demonstrated focal activations during human atrial fibrillation (AF). These putative AF sources can manifest sustained periodic bipolar and unipolar QS electrograms (EGMs). We have automated the detection of these EGM features using our validated Focal Source and Trigger (FaST) computational algorithm.

Quantification of abnormal QRS peaks predicts response to cardiac resynchronization therapy and tracks structural remodeling.

Background: Although QRS duration (QRSd) is an important determinant of cardiac resynchronization therapy (CRT) response, non-responder rates remain high. QRS fragmentation can also reflect electrical dyssynchrony. We hypothesized that quantification of abnormal QRS peaks (QRSp) would predict CRT response.

Body surface distribution of T wave alternans is modulated by heart rate and ventricular activation sequence in patients with cardiomyopathy.

Background: T wave alternans (TWA) is an electrocardiographic marker of heightened sudden death risk from ventricular tachyarrhythmias in patients with cardiomyopathy. TWA is evaluated from the 12-lead electrocardiogram, Frank lead, or Holter lead recordings, however these clinical lead configurations will not record TWA from adjacent regions of the body torso.

Objective: We tested the hypothesis that changing heart rate or ventricular activation may alter the body surface distribution of TWA such that the clinical ECG leads fail to detect TWA in some patients; thereby producing a false-negative test.

Differential pacing from two sites to diagnose risk of ventricular arrhythmia and death.

Background: QRS abnormalities may not be apparent in sinus rhythm in electrically stable cardiomyopathy patients who can have quiescent but highly arrhythmogenic substrate. Here, we test the hypothesis that differential changes in QRS construction during right-ventricular apex pacing (RVP) as opposed to atrial pacing (AP) will identify latent substrate for ventricular arrhythmias (VA) and death.

Methods: Forty patients with cardiomyopathy free of VA underwent baseline 114-electrode body-surface electrocardiogram during AP (100 beats per minute [bpm]) and RVP (100 and 120 bpm).

Reduced T wave alternans in heart failure responders to cardiac resynchronization therapy: Evidence of electrical remodeling.

Background: T-wave alternans (TWA), a marker of electrical instability, can be modulated by cardiac resynchronization therapy (CRT). The relationship between TWA and heart failure response to CRT has not been clearly defined.

Methods And Results: In 40-patients (age 65±11 years, left ventricular ejection-fraction [LVEF] 23±7%), TWA was evaluated prospectively at median of 2 months (baseline) and 8 months (follow-up) post-CRT implant.

Spatial Relationships of Complex Fractionated Atrial Electrograms and Continuous Electrical Activity to Focal Electrical Sources: Implications for Substrate Ablation in Human Atrial Fibrillation.

Objectives: This study sought to evaluate the spatial relationships of focal electrical sources (FSs) to complex fractionated atrial electrograms (CFAE) and continuous electrical activity (CEA).

Background: Fractionated atrial electrograms have been associated with atrial fibrillation (AF) drivers in computational studies and represent ablation targets in the management of persistent AF.

Methods: We included a subset of 66 patients (age: 63 [56, 67] years, 69% persistent AF) with electroanatomic data from the SELECT AF (Selective complex fractionated atrial electrograms targeting for atrial fibrillation) randomized control trial that compared the efficacy of CFAE with CEA ablation in AF patients undergoing pulmonary vein antral ablation.

Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With Cardiomyopathy.

Background: Cardiomyopathy patients are at risk of sudden death, typically from scar-related abnormalities of electrical activation that promote ventricular tachyarrhythmias. Abnormal intra-QRS peaks may provide a measure of altered activation. We hypothesized that quantification of such QRS peaks (QRSp) in high-resolution ECGs would predict arrhythmic events in implantable cardioverter-defibrillator (ICD)-eligible cardiomyopathy patients.

Identification and annotation of multiple periodic pulse trains using dominant frequency and graph search: Applications in atrial fibrillation rotor detection.

Biological signals, such as intracardiac electrograms during atrial fibrillation (AF), can contain multiple periodic components or peaks. We propose a method for identifying individual periodic peak trains in signals containing multiple such periodic sequences. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activation set or peaks of interest.

An algorithm for rotor tracking in atrial fibrillation using graph search-based periodic peak detection.

Rotors are rotating electrical waves that may sustain atrial fibrillation (AF); thereby providing therapeutic targets for catheter ablation. We propose a method for identifying rotors from circular catheter recordings of bipolar intracardiac electrograms (EGM) during AF. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activations or peaks of interest in each bipolar EGM recorded by a multipolar circular catheter.

Hierarchical Schema for Identifying Focal Electrical Sources During Human Atrial Fibrillation: Implications for Catheter-Based Atrial Substrate Ablation.

Objectives: The study sought to localize focal sources (FS) during atrial fibrillation (AF) using periodic component analysis (PiCA) and QS unipolar electrogram (EGM) morphology based on the assumption that periodic activation with centrifugal propagation is inherent to a FS.

Background: The localization of FS maintaining AF remains challenging, due to limitations in conventional time-frequency domain analysis. This is relevant to identifying targets for AF substrate ablation.

Rapid Device-Detected Nonsustained Ventricular Tachycardia in the Risk Stratification of Hypertrophic Cardiomyopathy.

Background: Nonsustained ventricular tachycardia (NSVT) detected by ambulatory Holter (Holter NSVT) is a major risk factor for sudden cardiac death in hypertrophic cardiomyopathy (HCM). We hypothesized that the prognostic utility of Holter NSVT in HCM would improve with prolonged monitoring and a higher heart rate cut-off for detection.

Methods: We enrolled 60 patients (44 ± 14 years) with HCM, who had a prophylactic implantable cardioverter defibrillator (ICD).

High-resolution 3D scar imaging using a novel late iodine enhancement multidetector CT protocol to guide ventricular tachycardia catheter ablation.

Scar delineation with late gadolinium-enhanced MRI can direct VT substrate mapping and ablation, but imaging is poor and relatively contraindicated in the majority of patients with ICDs. We present a case of scar definition using late iodine-enhanced multidetector CT in a patient with ischemic cardiomyopathy and multiple ICD shocks for VT. CT images were acquired using a novel intracoronary contrast delivery protocol which provided high-resolution subendocardial scar visualization.

Relationship of bipolar and unipolar electrogram voltage to scar transmurality and composition derived by magnetic resonance imaging in patients with nonischemic cardiomyopathy undergoing VT ablation.

Background: Bipolar voltage mapping has a role in defining endocardial-based scar in postinfarct patients undergoing ventricular tachycardia catheter ablation. The utility of bipolar and unipolar voltages in characterizing scar has not been evaluated in patients with nonischemic cardiomyopathy.

Objective: To relate left ventricular (LV) endocardial bipolar and unipolar voltages in these patients to scar transmurality (endocardial vs nonendocardial) and composition (homogeneous core vs heterogeneous gray).