Representation of women in cardiovascular disease management: a systematic analysis of ESC guidelines.

Objective: Sex differences play a critical role in the presentation, progression and treatment outcomes of cardiac diseases. However, historical male predominance in clinical studies has led to disparities in evidence supporting care for both sexes. Clinical guidelines are essential for cardiovascular care, shaping practice and influencing patient outcomes.

Integrating imaging and invasive pressure data into a multi-scale whole-heart model.

Cardiovascular diseases are the leading cause of death. Clinical data used to decide treatment are hard to integrate and interpret, making optimal treatment selection difficult. Personalised models can be used to integrate clinical data into a physics and physiology-constrained framework, but their clinical application faces limitations due to complex calibration and validation.

Three-dimensional left atrial strain from retrospective gated computed tomography: Comparison with speckle-tracking echocardiography in patients with aortic stenosis.

Background: Three-dimensional (3D) left atrial (LA) deformation assessment beyond the two-dimensional (2D) apical views circumvents atrial foreshortening and can be quantified from four-dimensional (4D) retrospective gated computed tomography (CT) using novel feature tracking methods. However, the consistency between CT-derived 3D and echocardiographic 2D peak left atrial longitudinal strain (PALS) has not been reported. We aimed to compare CT-derived 3D and echocardiographic 2D PALS in patients undergoing transcatheter aortic valve implantation (TAVI).

Rhythm control benefits left ventricular function compared with rate control in patients with atrial fibrillation: A computational study.

Background: Atrial fibrillation (AF) alters heart rate, rhythm regularity, and atrial contraction, which may contribute to an increased risk of heart failure. Although rate and rhythm control target different aspects of these disturbances, their specific effects on left ventricular (LV) function remain unclear.

Objective: The purpose of this study was to predict the independent and combined contribution of heart rate, rhythm regularity, and atrial contraction to LV function in patients with AF.

Cardiac digital twins: a tool to investigate the function and treatment of the diabetic heart.

Diabetes increases the risk of cardiovascular disease (CVD) due to its multi-scale and diverse effects on cardiomyocyte metabolism and function, the circulation, and the kidneys. The complex relationship between organ systems affected by diabetes and associated comorbidities leads to challenges in estimating cardiovascular risk and stratifying optimal treatment strategies at the individual patient level. Most recently, sodium-glucose transport protein 2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP1) receptor agonists have been shown to offer substantial cardiac benefits.

Cardiac digital twins at scale from MRI: Open tools and representative models from ~ 55000 UK Biobank participants.

A cardiac digital twin is a virtual replica of a patient's heart for screening, diagnosis, prognosis, risk assessment, and treatment planning of cardiovascular diseases. This requires an anatomically accurate patient-specific 3D structural representation of the heart, suitable for electro-mechanical simulations or study of disease mechanisms. However, generation of cardiac digital twins at scale is demanding and there are no public repositories of models across demographic groups.

Is regional atrial strain a useful surrogate of regional atrial fibrosis in atrial cardiomyopathy?

Aims: To determine whether atrial biomechanics measured using 3D regional strain, left atrial volume (LAV), and left atrial emptying fraction (LAEF) are associated with atrial fibrosis in patients with suspected atrial cardiomyopathy.

Methods And Results: Cardiovascular magnetic resonance (CMR) was performed in atrial fibrillation (AF) patients ( = 47). Healthy volunteer ( = 41) and familial dilated cardiomyopathy (DCM) ( = 31) cohorts were acquired for normalization and validation, respectively.

Developing cardiac biomechanical models beyond the clinic: modeling stressors of daily life.

There is growing motivation to exploit computational biomechanical modeling of the heart as a predictive tool to support clinical diagnoses and therapies. Existing patient-specific cardiac models often rely on data collected under highly standardized conditions in hospitals. However, disease progression and therapy responses often depend on stressors, encountered in daily life, that cannot be captured in a traditional clinical setting.

Effect of leadless left ventricular endocardial and left bundle branch area pacing on biventricular repolarization metrics.

Background: Cardiac resynchronization therapy (CRT) delivered with left ventricular (LV) epicardial pacing may increase arrhythmic risk through detrimental effects on ventricular repolarization. Leadless LV endocardial CRT including leadless left bundle branch area pacing (LBBAP) may mitigate this by preserving a more physiological transmural activation pattern.

Objective: This study aimed to evaluate the effect of leadless LV endocardial and leadless LBBAP on repolarization metrics derived from electrocardiographic imaging (ECGi).

An in silico guide for ventriculo-ventricular delay programming for left bundle branch-optimized cardiac resynchronization therapy.

Aims: Left bundle branch pacing (LBBP)-optimized cardiac resynchronization therapy (LOT-CRT) can improve left ventricular (LV) activation when LBBP alone or conventional biventricular pacing are ineffective. However, the optimal programming settings for ventriculo-ventricular delay (VVD) for LOT-CRT are unknown. We aim to investigate how to optimally program VVD for LOT-CRT in the presence of various LV conduction substrates using computational modelling.

Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.

Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncovering multi-scale insights tied to these mechanisms. In this study, we constructed 3,461 CDTs from the UK Biobank and another 359 from an ischemic heart disease (IHD) cohort, using cardiac magnetic resonance images and electrocardiograms.

Probabilistic Richardson extrapolation.

For over a century, extrapolation methods have provided a powerful tool to improve the convergence order of a numerical method. However, these tools are not well-suited to modern computer codes, where multiple continua are discretized and convergence orders are not easily analysed. To address this challenge, we present a probabilistic perspective on Richardson extrapolation, a point of view that unifies classical extrapolation methods with modern multi-fidelity modelling, and handles uncertain convergence orders by allowing these to be statistically estimated.

In silico pace mapping identifies pacing sites more accurately than inverse body surface potential mapping.

Background: Electrocardiographic imaging (ECGi) is a noninvasive technique for ventricular tachycardia ablation planning. However, it is limited to reconstructing epicardial surface activation. In silico pace mapping combines a personalized computational model with clinical electrocardiograms (ECGs) to generate a virtual 3-dimensional pace map.

Optimizing outcomes from cardiac resynchronization therapy: what do recent data and insights say?

Introduction: Cardiac Resynchronization Therapy (CRT) is an effective treatment for heart failure (HF) in approximately two-thirds of recipients, with a third remaining CRT 'non-responders.' There is an increasing body of evidence exploring the reasons behind non-response, as well as ways to preempt or counteract it.

Areas Covered: This review will examine the most recent evidence regarding optimizing outcomes from CRT, as well as explore whether traditional CRT indeed remains the best first-line therapy for electrical resynchronization in HF.

From bits to bedside: entering the age of digital twins in cardiac electrophysiology.

This State of the Future Review describes and discusses the potential transformative power of digital twins in cardiac electrophysiology. In this 'big picture' approach, we explore the evolution of mechanistic modelling based digital twins, their current and immediate clinical applications, and envision a future where continuous updates, advanced calibration, and seamless data integration redefine clinical practice of cardiac electrophysiology. Our aim is to inspire researchers and clinicians to embrace the extraordinary possibilities that digital twins offer in the pursuit of precision medicine.

Noninvasive assessment of hydroquinidine effect in Brugada syndrome (QUIET BrS).

Background: Hydroquinidine reduces arrhythmic events in patients with Brugada syndrome (BrS). The mechanism by which it exerts antiarrhythmic benefit and its electrophysiological effects on BrS substrate remain incompletely understood.

Objective: This study aimed to determine the effect of hydroquinidine on ventricular depolarization and repolarization in patients with BrS in vivo.

Optimizing electrical efficacy of leadless cardiac resynchronization therapy and leadless left ventricular septal pacing: Insights on left and right ventricular activation from electrocardiographic imaging.

Background: Leadless cardiac resynchronization therapy (CRT) is an emerging heart failure treatment. An implanted electrode delivers lateral or septal endocardial left ventricular (LV) pacing (LVP) upon detection of a right ventricular (RV) pacing stimulus from a coimplanted device, thus generating biventricular pacing (BiVP). Electrical efficacy data regarding this therapy, particularly leadless LV septal pacing (LVSP) for potential conduction system capture, are limited.

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations.

Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-based methods can make the creation of fast and accurate whole-heart digital twins feasible.

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways.

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation.

Developing Cardiac Digital Twins at Scale: Insights from Personalised Myocardial Conduction Velocity.

Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology-constrained representations, enabling inference of multi-scale properties tied to these mechanisms. We constructed 3464 anatomically-accurate CDTs using cardiac magnetic resonance images from UK biobank and personalised their myocardial conduction velocities (CVs) from electrocardiograms (ECG), through an automated framework.

A Semi-automatic Pipeline for Generation of Large Cohorts of Four-Chamber Heart Meshes.

Computational models for cardiac electro-mechanics have been increasingly used to further understand heart function. Small cohort and single patient computational studies provide useful insight into cardiac pathophysiology and response to therapy. However, these smaller studies have limited capability to capture the high level of anatomical variability seen in cardiology patients.

Computational Modelling Enabling In Silico Trials for Cardiac Physiologic Pacing.

Conduction system pacing (CSP) has the potential to achieve physiological-paced activation by pacing the ventricular conduction system. Before CSP is adopted in standard clinical practice, large, randomised, and multi-centre trials are required to investigate CSP safety and efficacy compared to standard biventricular pacing (BVP). Furthermore, there are unanswered questions about pacing thresholds required to achieve optimal pacing delivery while preventing device battery draining, and about which patient groups are more likely to benefit from CSP rather than BVP.

Managing arrhythmia in cardiac resynchronisation therapy.

Arrhythmia is an extremely common finding in patients receiving cardiac resynchronisation therapy (CRT). Despite this, in the majority of randomised trials testing CRT efficacy, patients with a recent history of arrhythmia were excluded. Most of our knowledge into the management of arrhythmia in CRT is therefore based on arrhythmia trials in the heart failure (HF) population, rather than from trials dedicated to the CRT population.

Left bundle branch area pacing reduces epicardial dispersion of repolarization compared with biventricular cardiac resynchronization therapy.

Background: Biventricular endocardial pacing (BiV-endo) and left bundle branch area pacing (LBBAP) are novel methods of delivering cardiac resynchronization therapy. These techniques are associated with improved activation times and acute hemodynamic response compared with conventional biventricular epicardial pacing (BiV-epi); however, the effects on repolarization and arrhythmic risk are unknown.

Objective: The purpose of this study was to compare the effects of temporary BiV-epi, BiV-endo, and LBBAP on epicardial left ventricular (LV) repolarization using electrocardiographic imaging (ECGi).