Personalized Heart Digital Twins Detect Substrate Abnormalities in Scar-Dependent Ventricular Tachycardia.

Background: Current outcomes from catheter ablation for scar-dependent ventricular tachycardia (VT) are limited by high recurrence rates and long procedure durations. Personalized heart digital twin technology presents a noninvasive method of predicting critical substrate in VT, and its integration into clinical VT ablation offers a promising solution. The accuracy of the predictions of digital twins to detect invasive substrate abnormalities is unknown.

12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.

Background And Purpose: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This study aims to evaluate the efficacy of a deep learning model applied to 12‑lead ECGs for non-invasively predicting the presence of LVAs, potentially guiding pre-ablation strategies and improving patient outcomes.

Methods: A retrospective analysis was conducted on 204 AF patients, who underwent catheter ablation.

A scalable framework for learning the geometry-dependent solution operators of partial differential equations.

Solving partial differential equations (PDEs) using numerical methods is a ubiquitous task in engineering and medicine. However, the computational costs can be prohibitively high when many-query evaluations of PDE solutions on multiple geometries are needed. Here we aim to address this challenge by introducing Diffeomorphic Mapping Operator Learning (DIMON), a generic artificial intelligence framework that learns geometry-dependent solution operators of different types of PDE on a variety of geometries.

Atrial fibrillation nomenclature, definitions, and mechanisms: Position paper from the international Working Group of the Signal Summit.

The international Working Group of the Signal Summit is a consortium of experts in the field of cardiac electrophysiology dedicated to advancing knowledge on understanding and clinical application of signal recording and processing techniques. In 2023, the working group met in Reykjavik, Iceland, and laid the foundation for this manuscript. Atrial fibrillation (AF) is the most common arrhythmia in adults, with a rapidly increasing prevalence worldwide.

Defining myocardial fiber bundle architecture in atrial digital twins.

A key component in developing atrial digital twins (ADT) - virtual representations of patients' atria - is the accurate prescription of myocardial fibers which are essential for the tissue characterization. Due to the difficulty of reconstructing atrial fibers from medical imaging, a widely used strategy for fiber generation in ADT relies on mathematical models. Existing methodologies utilze semi-automatic approaches, are tailored to specific morphologies, and lack rigorous validation against imaging fiber data.

Unipolar voltage electroanatomic mapping detects structural atrial remodeling identified by LGE-MRI.

Background: In atrial fibrillation (AF) management, understanding left atrial (LA) substrate is crucial. While both electroanatomic mapping (EAM) and late gadolinium enhancement magnetic resonance imaging (LGE-MRI) are accepted methods for assessing the atrial substrate and are associated with ablation outcome, recent findings have highlighted discrepancies between low-voltage areas (LVAs) in EAM and LGE areas.

Objective: The purpose of this study was to explore the relationship between LGE regions and unipolar and bipolar LVAs using multipolar high-density mapping.

Optimizing the Distribution of Ablation Lesions to Prevent Postablation Atrial Tachycardia: A Personalized Digital-Twin Study.

Background: Although targeting atrial fibrillation (AF) drivers and substrates has been used as an effective adjunctive ablation strategy for patients with persistent AF (PsAF), it can result in iatrogenic scar-related atrial tachycardia (iAT) requiring additional ablation. Personalized atrial digital twins (DTs) have been used preprocedurally to devise ablation targeting that eliminate the fibrotic substrate arrhythmogenic propensity and could potentially be used to predict and prevent postablation iAT.

Objectives: In this study, the authors sought to explore possible alternative configurations of ablation lesions that could prevent iAT occurrence with the use of biatrial DTs of prospectively enrolled PsAF patients.

Assessing the arrhythmogenic propensity of fibrotic substrate using digital twins to inform a mechanisms-based atrial fibrillation ablation strategy.

Atrial fibrillation (AF), the most common heart rhythm disorder, may cause stroke and heart failure. For patients with persistent AF with fibrosis proliferation, the standard AF treatment-pulmonary vein isolation-has poor outcomes, necessitating redo procedures, owing to insufficient understanding of what constitutes good targets in fibrotic substrates. Here we present a prospective clinical and personalized digital twin study that characterizes the arrhythmogenic properties of persistent AF substrates and uncovers locations possessing rotor-attracting capabilities.

Cardiac MRI Oversampling in Heart Digital Twins Improves Preprocedure Ventricular Tachycardia Identification in Postinfarction Patients.

Background: Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients after myocardial infarction. Radiofrequency catheter ablation (RFA) is a modestly effective treatment of VT, but it has limitations and risks. Cardiac magnetic resonance (CMR)-based heart digital twins have emerged as a useful tool for identifying VT circuits for RFA treatment planning.

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data.

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations.

Elastic shape analysis for unsupervised clustering of left atrial appendage morphology.

Morphological variations in the left atrial appendage (LAA) are associated with different levels of ischemic stroke risk for patients with atrial fibrillation (AF). Studying LAA morphology can elucidate mechanisms behind this association and lead to the development of advanced stroke risk stratification tools. However, current categorical descriptions of LAA morphologies are qualitative in nature, and inconsistent across studies, which impedes advancements in our understanding of stroke pathogenesis in AF.

Understanding the Utility of Endocardial Electrocardiographic Imaging in Epi-Endocardial Mapping of 3D Reentrant Circuits.

Background: Studies of VT mechanisms are largely based on a 2D portrait of reentrant circuits on one surface of the heart. This oversimplifies the 3D circuit that involves the depth of the myocardium. Simultaneous epicardial and endocardial (epi-endo) mapping was shown to facilitate a 3D delineation of VT circuits, which is however difficult via invasive mapping.

Digital twins in medicine.

Medical digital twins, which are potentially vital for personalized medicine, have become a recent focus in medical research. Here we present an overview of the state of the art in medical digital twin development, especially in oncology and cardiology, where it is most advanced. We discuss major challenges, such as data integration and privacy, and provide an outlook on future advancements.

Slow blood-flow in the left atrial appendage is associated with stroke in atrial fibrillation patients.

Background: Atrial fibrillation (AF) patients are at high risk of stroke with ∼90% clots originating from the left atrial appendage (LAA). Clinical understanding of blood-flow based parameters and their potential association with stroke for AF patients remains poorly understood. We hypothesize that slow blood-flow either in the LA or the LAA could lead to the formation of blood clots and is associated with stroke for AF patients.

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data.

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHADS-VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations.

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.

Up digital and personal: How heart digital twins can transform heart patient care.

Precision medicine is the vision of health care where therapy is tailored to each patient. As part of this vision, digital twinning technology promises to deliver a digital representation of organs or even patients by using tools capable of simulating personal health conditions and predicting patient or disease trajectories on the basis of relationships learned both from data and from biophysics knowledge. Such virtual replicas would update themselves with data from monitoring devices and medical tests and assessments, reflecting dynamically the changes in our health conditions and the responses to treatment.

Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes.

Association of epicardial and intramyocardial fat with ventricular arrhythmias.

Background: Among patients with ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), myocardial fibrosis is associated with an increased risk for ventricular arrhythmia (VA). Growing evidence suggests that myocardial fat contributes to ventricular arrhythmogenesis. However, little is known about the volume and distribution of epicardial adipose tissue and intramyocardial fat and their relationship with VAs.

Twenty-five years of research in cardiac imaging in electrophysiology procedures for atrial and ventricular arrhythmias.

Catheter ablation is nowadays considered the treatment of choice for numerous cardiac arrhythmias in different clinical scenarios. Fluoroscopy has traditionally been the primary imaging modality for catheter ablation, providing real-time visualization of catheter navigation. However, its limitations, such as inadequate soft tissue visualization and exposure to ionizing radiation, have prompted the integration of alternative imaging modalities.

Risk of Arrhythmic Death in Patients With Nonischemic Cardiomyopathy: JACC Review Topic of the Week.

Nonischemic cardiomyopathy (NICM) is common and patients are at significant risk for early mortality secondary to ventricular arrhythmias. Current guidelines recommend implantable cardioverter-defibrillator (ICD) therapy to decrease sudden cardiac death (SCD) in patients with heart failure and reduced left ventricular ejection fraction. However, in randomized clinical trials comprised solely of patients with NICM, primary prevention ICDs did not confer significant mortality benefit.