ArticleeLife2022
Personalized computational heart models with T1-mapped fibrotic remodeling predict sudden death risk in patients with hypertrophic cardiomyopathy.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Fibro-Inflammatory Signaling, Fibrosis, and Microvascular Ischemia as Convergent Translational Substrates of Sudden Cardiac Death in Hypertrophic Cardiomyopathy: A Systematic Review.Journal of cardiovascular translational research · 2026Pooled it
- The Hodgkin-Huxley-Katz Prize Lecture: Heart digital twins: A new paradigm in arrhythmia medicine.The Journal of physiology · 2026Article
- Myocardial Fibrosis in Hypertrophic Cardiomyopathy: Leveraging Quantitative Imaging and Artificial Intelligence for Precision Management.Reviews in cardiovascular medicine · 2026Review
- Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.The Journal of physiology · 2026Review
- Body surface potential driven personalisation of electrophysiological digital twins in hypertrophic cardiomyopathy.PLoS computational biology · 2026Article
- Genotype-specific digital twins for arrhythmia ablation targeting in arrhythmogenic right ventricular cardiomyopathy.Communications medicine · 2026Article
- Models of cardiomyocyte-non-myocyte electrical interactions.The Journal of physiology · 2026Review
- A case of hypertrophic cardiomyopathy with untoward outcome.The British journal of cardiology · 2026Article
- Genotype-specific Digital Twins for Arrhythmia Ablation Targeting in Arrhythmogenic Right Ventricular Cardiomyopathy.Research square · 2025Article
- Late gadolinium enhancement imaging and sudden cardiac death.European heart journal · 2025Review
- Article
- Comparative analysis of the ten Tusscher and Tomek human ventricular cell models at cellular, tissue, and organ levels: Implications for post-infarct ventricular tachycardia simulation.Physiological reports · 2025Article
- Multimodal AI to forecast arrhythmic death in hypertrophic cardiomyopathy.Nature cardiovascular research · 2025Article
- Personalized Heart Digital Twins Detect Substrate Abnormalities in Scar-Dependent Ventricular Tachycardia.Circulation · 2025Observational
- Digital twins as global learning health and disease models for preventive and personalized medicine.Genome medicine · 2025Review
- Medical Digital Twin: A Review on Technical Principles and Clinical Applications.Journal of clinical medicine · 2025Review
- Computational Medicine: What Electrophysiologists Should Know to Stay Ahead of the Curve.Current cardiology reports · 2024Review
- Cardiovascular care with digital twin technology in the era of generative artificial intelligence.European heart journal · 2024Review
- In silico evaluation of cell therapy in acute versus chronic infarction: role of automaticity, heterogeneity and Purkinje in human.Scientific reports · 2024Article
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
Hypertrophic cardiomyopathy (HCM) is associated with risk of sudden cardiac death (SCD) due to ventricular arrhythmias (VAs) arising from the proliferation of fibrosis in the heart. Current clinical risk stratification criteria inadequately identify at-risk patients in need of primary prevention of VA. Here, we use mechanistic computational modeling of the heart to analyze how HCM-specific remodeling promotes arrhythmogenesis and to develop a personalized strategy to forecast risk of VAs in these patients. We combine contrast-enhanced cardiac magnetic resonance imaging and T1 mapping data to construct digital replicas of HCM patient hearts that represent the patient-specific distribution of focal and diffuse fibrosis and evaluate the substrate propensity to VA. Our analysis indicates that the presence of diffuse fibrosis, which is rarely assessed in these patients, increases arrhythmogenic propensity. In forecasting future VA events in HCM patients, the imaging-based computational heart approach achieved 84.6%, 76.9%, and 80.1% sensitivity, specificity, and accuracy, respectively, and significantly outperformed current clinical risk predictors. This novel VA risk assessment may have the potential to prevent SCD and help deploy primary prevention appropriately in HCM patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.