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1

Meijer, Charles, Hae-Won Uh, and Said el Bouhaddani. "Digital Twins in Healthcare: Methodological Challenges and Opportunities." Journal of Personalized Medicine 13, no. 10 (2023): 1522. http://dx.doi.org/10.3390/jpm13101522.

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One of the most promising advancements in healthcare is the application of digital twin technology, offering valuable applications in monitoring, diagnosis, and development of treatment strategies tailored to individual patients. Furthermore, digital twins could also be helpful in finding novel treatment targets and predicting the effects of drugs and other chemical substances in development. In this review article, we consider digital twins as virtual counterparts of real human patients. The primary aim of this narrative review is to give an in-depth look into the various data sources and met
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Palmer, Sarah Jane. "The age of digital twins in cardiac healthcare." British Journal of Cardiac Nursing 20, no. 4 (2025): 1–4. https://doi.org/10.12968/bjca.2025.0014.

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Ammar, Mohamed, and Hamed Al-Raweshidy. "Integration of Digital Twins and Artificial Intelligence for Classifying Cardiac Ischemia." Journal on Artificial Intelligence 5 (2023): 195–218. http://dx.doi.org/10.32604/jai.2023.045199.

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Zappon, Elena, Matthias A. F. Gsell, Karli Gillette, and Gernot Plank. "Quantifying anatomically-based in-silico electrocardiogram variability for cardiac digital twins." Computers in Biology and Medicine 189 (May 2025): 109930. https://doi.org/10.1016/j.compbiomed.2025.109930.

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Ugurlu, Devran, Shuang Qian, Elliot Fairweather, et al. "Cardiac digital twins at scale from MRI: Open tools and representative models from ~ 55000 UK Biobank participants." PLOS One 20, no. 7 (2025): e0327158. https://doi.org/10.1371/journal.pone.0327158.

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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. We describe an automatic open-source pipeline for creating patient-specific left and right ventricular meshes from
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Sánchez, Jorge, Inés Llorente-Lipe, Cristian Barrios Espinosa, et al. "Enhancing premature ventricular contraction localization through electrocardiographic imaging and cardiac digital twins." Computers in Biology and Medicine 190 (May 2025): 109994. https://doi.org/10.1016/j.compbiomed.2025.109994.

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7

Xu, Jun, and Fei Wang. "Cardiac Mechano-Electrical-Fluid Interaction: A Brief Review of Recent Advances." Eng 6, no. 8 (2025): 168. https://doi.org/10.3390/eng6080168.

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This review investigates recent developments in cardiac mechano-electrical-fluid interaction (MEFI) modeling, with a focus on multiphysics simulation platforms and digital twin frameworks developed between 2015 and 2025. The purpose of the study is to assess how computational modeling methods—particularly finite element and immersed boundary techniques, monolithic and partitioned coupling schemes, and artificial intelligence (AI)-enhanced surrogate modeling—capture the integrated dynamics of cardiac electrophysiology, tissue mechanics, and hemodynamics. The goal is to evaluate the translationa
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Qian, Shuang, Devran Ugurlu, Elliot Fairweather, et al. "Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization." Nature Cardiovascular Research 4, no. 5 (2025): 624–36. https://doi.org/10.1038/s44161-025-00650-0.

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Abstract 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. We show here that sex-specific differences in QRS duration were fully explained by myocardial anatomy whil
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Jung, Alexander, Matthias A. F. Gsell, Christoph M. Augustin, and Gernot Plank. "An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics—A Multi-Fidelity Approach for Personalising Active Mechanics." Mathematics 10, no. 5 (2022): 823. http://dx.doi.org/10.3390/math10050823.

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Personalised computer models of cardiac function, referred to as cardiac digital twins, are envisioned to play an important role in clinical precision therapies of cardiovascular diseases. A major obstacle hampering clinical translation involves the significant computational costs involved in the personalisation of biophysically detailed mechanistic models that require the identification of high-dimensional parameter vectors. An important aspect to identify in electromechanics (EM) models are active mechanics parameters that govern cardiac contraction and relaxation. In this study, we present
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Rudnicka, Zofia, Klaudia Proniewska, Mark Perkins, and Agnieszka Pregowska. "Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review." Electronics 13, no. 5 (2024): 866. http://dx.doi.org/10.3390/electronics13050866.

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Recently, significant efforts have been made to create Health Digital Twins (HDTs), Digital Twins for clinical applications. Heart modeling is one of the fastest-growing fields, which favors the effective application of HDTs. The clinical application of HDTs will be increasingly widespread in the future of healthcare services and has huge potential to form part of mainstream medicine. However, it requires the development of both models and algorithms for the analysis of medical data, and advances in Artificial Intelligence (AI)-based algorithms have already revolutionized image segmentation pr
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Li, Lei, Hannah Smith, Yilin Lyu, et al. "Personalized topology-informed localization of standard 12-lead ECG electrode placement from incomplete cardiac MRIs for efficient cardiac digital twins." Medical Image Analysis 101 (April 2025): 103472. https://doi.org/10.1016/j.media.2025.103472.

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12

Avanzato, Roberta, Francesco Beritelli, Alfio Lombardo, and Carmelo Ricci. "Heart DT: Monitoring and Preventing Cardiac Pathologies Using AI and IoT Sensors." Future Internet 15, no. 7 (2023): 223. http://dx.doi.org/10.3390/fi15070223.

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Today’s healthcare facilities require new digital tools to cope with the rapidly increasing demand for technology that can support healthcare operators. The advancement of technology is leading to the pervasive use of IoT devices in daily life, capable of acquiring biomedical and biometric parameters, and providing an opportunity to activate new tools for the medical community. Digital twins (DTs) are a form of technology that are gaining more prominence in these scenarios. Many scientific research papers in the literature are combining artificial intelligence (AI) with DTs. In this work, we p
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Strocchi, Marina, Stefano Longobardi, Christoph M. Augustin, et al. "Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators." PLOS Computational Biology 19, no. 6 (2023): e1011257. http://dx.doi.org/10.1371/journal.pcbi.1011257.

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Cardiac pump function arises from a series of highly orchestrated events across multiple scales. Computational electromechanics can encode these events in physics-constrained models. However, the large number of parameters in these models has made the systematic study of the link between cellular, tissue, and organ scale parameters to whole heart physiology challenging. A patient-specific anatomical heart model, or digital twin, was created. Cellular ionic dynamics and contraction were simulated with the Courtemanche-Land and the ToR-ORd-Land models for the atria and the ventricles, respective
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Gillette, Karli, Matthias A. F. Gsell, Anton J. Prassl, et al. "A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs." Medical Image Analysis 71 (July 2021): 102080. http://dx.doi.org/10.1016/j.media.2021.102080.

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15

Sánchez Arciniegas, Jorge P., Inés Llorente Lipe, Andreu M. Climent, and María S. Guillem. "PO-05-032 ENHANCED ELECTROCARDIOGRAPHIC IMAGING WITH CARDIAC DIGITAL TWINS FOR THE LOCATION OF PREMATURE VENTRICULAR CONTRACTION." Heart Rhythm 21, no. 5 (2024): S565. http://dx.doi.org/10.1016/j.hrthm.2024.03.1428.

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Vivarelli, Cecilia, Eugenio Mattei, Federica Ricci, Sara D'Eramo, and Giovanni Calcagnini. "A Tool for the Assessment of Electromagnetic Compatibility in Active Implantable Devices: The Pacemaker Physical Twin." Bioengineering 12, no. 7 (2025): 689. https://doi.org/10.3390/bioengineering12070689.

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Background: The increasing use of technologies operating between 10 and 200 kHz, such as RFID, wireless power transfer systems, and induction cooktops, raises concerns about electromagnetic interference (EMI) with cardiac implantable electronic devices (CIEDs). The mechanisms of interaction within this frequency range have been only partially addressed by both the scientific and regulatory communities. Methods: A physical twin of a pacemaker/implantable defibrillator (PM/ICD) was developed to experimentally assess voltages induced at the input stage by low-to-mid-frequency magnetic fields. The
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Nesterova, T. M., V. Yu Kabak, D. S. Lebedev, and O. E. Solovyova. "Mathematical models and artificial intelligence for studying the ventricular dyssynchrony and improving the effectiveness of cardiac resynchronization therapy." Russian Journal of Cardiology 29, no. 4S (2024): 6194. https://doi.org/10.15829/1560-4071-2024-6194.

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The review is devoted to the current status of artificial intelligence (AI), mathematical modeling (MM) and their combination in the analysis of cardiac dyssynchrony mechanisms and its treatment using cardiac resynchronization therapy (CRT). Recent articles and reviews demonstrate the high promise of AI and MM in personalized medicine, but also identify existing obstacles to their implementation in clinical practice. The works discussed are devoted to a number of topical problems of clinical cardiology as follows: analysis of phenotypes of patients with cardiac dyssynchrony, search for novel p
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Bartusik-Aebisher, Dorota, Kacper Rogóż, and David Aebisher. "Artificial Intelligence and ECG: A New Frontier in Cardiac Diagnostics and Prevention." Biomedicines 13, no. 7 (2025): 1685. https://doi.org/10.3390/biomedicines13071685.

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Objectives: With the growing importance of mobile technology and artificial intelligence (AI) in healthcare, the development of automated cardiac diagnostic systems has gained strategic significance. This review aims to summarize the current state of knowledge on the use of AI in the analysis of electrocardiographic (ECG) signals obtained from wearable devices, particularly smartwatches, and to outline perspectives for future clinical applications. Methods: A narrative literature review was conducted using PubMed, Web of Science, and Scopus databases. The search focused on combinations of keyw
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Bayer, Jennifer, Christoph Hintermüller, Hermann Blessberger, and Clemens Steinwender. "ECG Electrode Localization: 3D DS Camera System for Use in Diverse Clinical Environments." Sensors 23, no. 12 (2023): 5552. http://dx.doi.org/10.3390/s23125552.

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Models of the human body representing digital twins of patients have attracted increasing interest in clinical research for the delivery of personalized diagnoses and treatments to patients. For example, noninvasive cardiac imaging models are used to localize the origin of cardiac arrhythmias and myocardial infarctions. The precise knowledge of a few hundred electrocardiogram (ECG) electrode positions is essential for their diagnostic value. Smaller positional errors are obtained when extracting the sensor positions, along with the anatomical information, for example, from X-ray Computed Tomog
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Galappaththige, Suran, Richard A. Gray, Caroline Mendonca Costa, Steven Niederer, and Pras Pathmanathan. "Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar." PLOS Computational Biology 18, no. 10 (2022): e1010541. http://dx.doi.org/10.1371/journal.pcbi.1010541.

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Reliable and robust simulation of individual patients using patient-specific models (PSMs) is one of the next frontiers for modeling and simulation (M&S) in healthcare. PSMs, which form the basis of digital twins, can be employed as clinical tools to, for example, assess disease state, predict response to therapy, or optimize therapy. They may also be used to construct virtual cohorts of patients, for in silico evaluation of medical product safety and/or performance. Methods and frameworks have recently been proposed for evaluating the credibility of M&S in healthcare applications. How
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Cook, Amanda. "Twin Reversed Arterial Perfusion (TRAP) Sequence: A Rare Case Report of an “Acardiac” Twin." Canadian Journal of Medical Sonography 11, no. 1 (2020): 5–12. http://dx.doi.org/10.3138/cjms.v11i1.5.

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A 32 year-old-pregnant female, presented to the labour and delivery department with contractions and leaking fluid. A vaginal mass was noted on digital examination. Obstetrical ultrasound demonstrated a twin pregnancy with a normal male fetus and a dysmorphic fetus with cardiac activity. Cesarean section was performed due to premature rupture of membranes (PROM) and ultrasound findings. A normal live male infant was delivered, required minimal neonatal care, and is healthy to date. A non-viable anomalous twin and the shared placenta was sent for autopsy. Pathology diagnosis was twin reversed a
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Kumar D, Ajith. "Augmented Vision-Enabled Digital Twin System for Real-Time ICU Patient Monitoring and Emergency Response." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem46582.

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Abstract: This project introduces a real-time health monitoring system for ICU emergency patients, leveraging Digital Twin (DT) technology integrated with Augmented Vision (AV). The proposed system enables early screening and rapid identification of high-risk individuals using a unique DT-based AV code assigned to each patient. Upon hospital admission for critical conditions such as cardiac or pulmonary emergencies, patients receive wearable biomedical sensors and an AV code printout, which facilitates swift ICU admission. The sensor data is continuously uploaded to a centralized server via Io
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Grandits, Thomas, Karli Gillette, Gernot Plank, and Simone Pezzuto. "Accurate and efficient cardiac digital twin from surface ECGs: Insights into identifiability of ventricular conduction system." Medical Image Analysis 105 (October 2025): 103641. https://doi.org/10.1016/j.media.2025.103641.

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Zheng, Tianbao, Luca Azzolin, Jorge Sánchez, Olaf Dössel, and Axel Loewe. "An automate pipeline for generating fiber orientation and region annotation in patient specific atrial models." Current Directions in Biomedical Engineering 7, no. 2 (2021): 136–39. http://dx.doi.org/10.1515/cdbme-2021-2035.

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Abstract Modeling the 'digital twin' of a patient's heart has gained traction in the last years and helps to understand the pathogenic mechanisms of cardiovascular disease to pave the way for personalized therapies. Although a 3D patient-specific model (PSM) can be obtained from computed tomography (CT) or magnetic resonance imaging (MRI), the fiber orientation of cardiac muscle, which significantly affects the electrophysiological and mechanical characteristics of the heart, can hardly be obtained in vivo. Several approaches have been suggested to solve this problem. However, most of them req
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Laudenschlager, Sebastian, Samuel Schofield, Nicolas Drysdale, et al. "Estimation of pulmonary vascular resistance for Glenn physiology." PLOS ONE 19, no. 7 (2024): e0307890. http://dx.doi.org/10.1371/journal.pone.0307890.

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Children with single ventricle heart disease typically require a series of three operations, (1) Norwood, (2) Glenn, and (3) Fontan, which ultimately results in complete separation of the pulmonary and systemic circuits to improve pulmonary/systemic circulation. In the last stage, the Fontan operation, the inferior vena cava (IVC) is connected to the pulmonary arteries (PAs), allowing the remainder of deoxygenated blood to passively flow to the pulmonary circuit. It is hypothesized that optimizing the Fontan anatomy would lead to decreased power loss and more balanced hepatic flow distribution
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Herrero Martin, C., J. Reventos-Presmanes, J. B. Guichard, et al. "Generation of cardiac digital twins based on noninvasive cardiac mapping." Europace 25, Supplement_1 (2023). http://dx.doi.org/10.1093/europace/euad122.643.

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Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Generalitat Valenciana Grants Ministerio de Ciencia, Innovación y Universidades Background Personalized cardiac digital twins have been proposed as a clinical tool to plan ablation strategies during cardiac arrhythmias. However, these personalization frameworks normally rely on invasive recordings which limits their clinical applicability. Electrocardiographic Imaging (ECGI) is a mapping technique that allows the reconstruction of global cardiac activity non-invasively. Purpose Evaluate the applicability
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Cluitmans, Matthijs J. M., Gernot Plank, and Jordi Heijman. "Digitale Zwillinge in der kardialen Elektrophysiologie – aktueller Entwicklungsstand und kommende Herausforderungen." Herzschrittmachertherapie + Elektrophysiologie, April 12, 2024. http://dx.doi.org/10.1007/s00399-024-01014-0.

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AbstractCardiac arrhythmias remain a major cause of death and disability. Current antiarrhythmic therapies are effective to only a limited extent, likely in large part due to their mechanism-independent approach. Precision cardiology aims to deliver targeted therapy for an individual patient to maximize efficacy and minimize adverse effects. In-silico digital twins have emerged as a promising strategy to realize the vision of precision cardiology. While there is no uniform definition of a digital twin, it typically employs digital tools, including simulations of mechanistic computer models, ba
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Lippert, M., K. A. Dumont, S. Birkeland, et al. "Cardiac anatomic digital twins - findings from a single national centre." European Heart Journal - Digital Health, September 18, 2024. http://dx.doi.org/10.1093/ehjdh/ztae070.

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Abstract Aims New three-dimensional cardiac visualisation technologies are increasingly employed for anatomic digital twins in preoperative planning. However, the role and influence of extended reality (virtual, augmented, or mixed) within heart team settings remain unclear. We aimed to assess the impact of mixed reality visualisation of the intracardiac anatomy on surgical decision-making in patients with complex heart defects. Methods and Results Between September 2020 and December 2022, we recruited 50 patients and generated anatomic digital twins and visualized them in mixed reality. These
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Thangaraj, Phyllis M., Sean H. Benson, Evangelos K. Oikonomou, Folkert W. Asselbergs, and Rohan Khera. "Cardiovascular care with digital twin technology in the era of generative artificial intelligence." European Heart Journal, September 26, 2024. http://dx.doi.org/10.1093/eurheartj/ehae619.

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Abstract Digital twins, which are in silico replications of an individual and its environment, have advanced clinical decision-making and prognostication in cardiovascular medicine. The technology enables personalized simulations of clinical scenarios, prediction of disease risk, and strategies for clinical trial augmentation. Current applications of cardiovascular digital twins have integrated multi-modal data into mechanistic and statistical models to build physiologically accurate cardiac replicas to enhance disease phenotyping, enrich diagnostic workflows, and optimize procedural planning.
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Molero Alabau, R., R. Moreno-Lopez, A. Cano-Cabanero, et al. "Enhanced identification of atrial arrhythmic triggers using cardiac digital twins generated from imageless electrocardiographic imaging." Europace 27, Supplement_1 (2025). https://doi.org/10.1093/europace/euaf085.051.

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Abstract Introduction Atrial arrhythmias, such as atrial fibrillation, are often triggered by ectopic beats. Conventional Electrocardiographic Imaging (ECGI) has proven effective for mapping ectopic foci on the epicardium; however, it relies on CT scans and often struggles to accurately identify the Earliest Activation Site (EAS), especially in the septal regions due to spatial constraints of ECGI. Purpose This study aims to enhance the detection of the EAS for ectopic atrial beats by utilizing ECGI-Twins, generated through artificial intelligence to identify the cardiac digital twin that best
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Morotti, Stefano. "Precision cardiac electrophysiology: toward digital twins and beyond." Journal of Precision Medicine: Health and Disease, June 2025, 100009. https://doi.org/10.1016/j.premed.2025.100009.

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Waight, Michael C., Adityo Prakosa, Anthony C. Li, et al. "Personalized Heart Digital Twins Detect Substrate Abnormalities in Scar-Dependent Ventricular Tachycardia." Circulation, January 6, 2025. https://doi.org/10.1161/circulationaha.124.070526.

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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. We present the first prospective analysis of digital twin technology in predicting critical substrate abnormalities in VT. METHODS: Heart dig
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Ložek, Miroslav, Jan Kovanda, Peter Kubuš, et al. "How to assess and treat right ventricular electromechanical dyssynchrony in post-repair tetralogy of Fallot: insights from imaging, invasive studies and computational modelling." Europace, January 24, 2024. http://dx.doi.org/10.1093/europace/euae024.

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Abstract Right bundle branch block (RBBB) and resulting RV electromechanical discoordination are thought to play a role in the disease process of subpulmonary right ventricular (RV) dysfunction that frequently occur post-repair tetralogy of Fallot. We sought to describe this disease entity, the role of pulmonary re-valvulation and the potential added value of RV cardiac resynchronization therapy (RV-CRT). Two patients with repaired tetralogy of Fallot, complete right bundle branch block, pulmonary regurgitation and significantly decreased RV function underwent echocardiography, cardiac magneti
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Salvador, Matteo, Marina Strocchi, Francesco Regazzoni, et al. "Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations." npj Digital Medicine 7, no. 1 (2024). http://dx.doi.org/10.1038/s41746-024-01084-x.

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AbstractCardiac 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. We use Latent Neural Ordinary Differential Equations (LNODEs) to learn the pressure-volume dynamics of a heart failure patient. Our surrogate model is trained from 400 simulations while accounting for 43 parameters describing cell-to-organ card
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Gonzalez-Martin, P., M. Webber, F. Chan, et al. "A pipeline for developing digital cardiac twins integrating cardiovascular magnetic resonance and electrocardiographic imaging: results from the MyoFit46 study." European Heart Journal 45, Supplement_1 (2024). http://dx.doi.org/10.1093/eurheartj/ehae666.3508.

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Abstract Background Personalised cardiovascular medicine uses multimodal screening and diagnostic tools, spanning from organ to tissue to molecular levels, to generate a complex and detailed patient phenotype. Cardiac digital twins are powerful tools capable of merging and explore these multimodal data by developing virtual, mechanistic and predictive versions of the patient's heart. State-of-the-art pipelines are mainly based on artificial intelligence and optimization process to replicate clinical data and not used it as an input. We present a proof-of-principle pipeline for building digital
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Li, Lei, Julia Camps, Blanca Rodriguez, and Vicente Grau. "Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey." IEEE Reviews in Biomedical Engineering, 2024, 1–19. http://dx.doi.org/10.1109/rbme.2024.3486439.

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Qian, S., D. Ugurlu, E. Fairweather, et al. "Cardiac digital twins of the adult population: linking electrophysiological functions to anatomy." Europace 25, Supplement_1 (2023). http://dx.doi.org/10.1093/europace/euad122.591.

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Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This project is supported by the Wellcome Trust and EPSRC Centre for Medical Engineering. Background QRS duration derived from 12-lead ECGs provides an estimate of the ventricular depolarization time and is an important metric to assess cardiac function. The QRS duration is determined in part by the combination of heart size and conduction velocity (CV). Differences in QRS duration in terms of gender, body mass index (BMI) and age have been well-documented, however, the re
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Abd Elaziz, Mohamed, Mohammed A. A. Al‐qaness, Abdelghani Dahou, et al. "Digital twins in healthcare: Applications, technologies, simulations, and future trends." WIREs Data Mining and Knowledge Discovery, September 6, 2024. http://dx.doi.org/10.1002/widm.1559.

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AbstractThe healthcare industry has witnessed significant interest in applying DTs (DTs), due to technological advancements. DTs are virtual replicas of physical entities that adapt to real‐time data, enabling predictions of their physical counterparts. DT technology enhances understanding of disease occurrence, enabling more accurate diagnoses and treatments. Integrating emerging technologies like big data, cloud computing, Virtual Reality (VR), and internet‐of‐things (IoT) provides a solid foundation for DT implementation in healthcare. However, defining DTs within the healthcare context sti
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Gillette, Karli, Matthias A. F. Gsell, Julien Bouyssier, et al. "Automated Framework for the Inclusion of a His–Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology." Annals of Biomedical Engineering, August 24, 2021. http://dx.doi.org/10.1007/s10439-021-02825-9.

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AbstractPersonalized models of cardiac electrophysiology (EP) that match clinical observation with high fidelity, referred to as cardiac digital twins (CDTs), show promise as a tool for tailoring cardiac precision therapies. Building CDTs of cardiac EP relies on the ability of models to replicate the ventricular activation sequence under a broad range of conditions. Of pivotal importance is the His–Purkinje system (HPS) within the ventricles. Workflows for the generation and incorporation of HPS models are needed for use in cardiac digital twinning pipelines that aim to minimize the misfit bet
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Hwang, T., O. Kwon, B. Lim, et al. "Clinical application of virtual antiarrhythmic drug test using digital twins in patients who recurred atrial fibrillation after catheter ablation." Europace 25, Supplement_1 (2023). http://dx.doi.org/10.1093/europace/euad122.076.

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Abstract Funding Acknowledgements Type of funding sources: None. Background We previously reported a proof-of-concept study that digital twins can test antiarrhythmic drug (AAD) effects on atrial fibrillation (AF) after integrating the patients’ cardiac CT imaging and electroanatomical map (EAM). In this study, we evaluated the reproducibility of the virtual AAD test (V-AAD) in the clinical setting in patients who recurred after AF catheter ablation (AFCA) and took AADs. Methods This single-center retrospective study included 232 patients (71.6% male, 60.5±10.2 years of age, 40.9% paroxysmal A
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Viola, Francesco, Giulio Del Corso, Ruggero De Paulis, and Roberto Verzicco. "GPU accelerated digital twins of the human heart open new routes for cardiovascular research." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-023-34098-8.

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AbstractThe recruitment of patients for rare or complex cardiovascular diseases is a bottleneck for clinical trials and digital twins of the human heart have recently been proposed as a viable alternative. In this paper we present an unprecedented cardiovascular computer model which, relying on the latest GPU-acceleration technologies, replicates the full multi-physics dynamics of the human heart within a few hours per heartbeat. This opens the way to extensive simulation campaigns to study the response of synthetic cohorts of patients to cardiovascular disorders, novel prosthetic devices or s
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Schuijt, Eva, Daniel Scherr, Gernot Plank, Ulrich Schotten, and Jordi Heijman. "Evolution in electrophysiology 100 years after Einthoven: translational and computational innovations in rhythm control of atrial fibrillation." Europace, December 27, 2024. https://doi.org/10.1093/europace/euae304.

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Abstract In 1924, the Dutch physiologist Willem Einthoven received the Nobel Prize in Physiology or Medicine for his discovery of the mechanism of the electrocardiogram (ECG). Anno 2024, the ECG is commonly used as a diagnostic tool in cardiology. In the paper ‘Le Télécardiogramme’, Einthoven described the first recording of the now most common cardiac arrhythmia: atrial fibrillation (AF). Treatment of AF includes rhythm control, aiming to alleviate symptoms and improve quality of life. Recent studies found that early rhythm control might additionally improve clinical outcomes. However, curren
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43

O’Hara, Ryan P., Audrey Lacy, Adityo Prakosa, et al. "Cardiac MRI Oversampling in Heart Digital Twins Improves Preprocedure Ventricular Tachycardia Identification in Postinfarction Patients." JACC: Clinical Electrophysiology, June 2024. http://dx.doi.org/10.1016/j.jacep.2024.04.032.

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44

Li, Lei, Julia Camps, Zhinuo Wang, et al. "Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference." IEEE Transactions on Medical Imaging, 2024, 1. http://dx.doi.org/10.1109/tmi.2024.3367409.

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45

Karli, GIllette, A.F. Gsell Matthias, Bouyssier Julien, et al. "Automated Framework for the Inclusion of a His–Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology." May 17, 2023. https://doi.org/10.5281/zenodo.7944267.

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This piece of work was originally published in the <em>Annals of Biomedical Engineering </em>(Volume 49:12).&nbsp;A title page is included with proper acknowledgements stated that &quot;This project 18HLT07 MedalCare has received funding from the EMPIR programme co-financed by the Participating States and from the European Union&rsquo;s Horizon 2020 research and innovation programme.&quot;
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46

Karli, Gillette, A.F. Gsell Matthias, J. Prassl Anton, et al. "A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs." May 17, 2023. https://doi.org/10.5281/zenodo.7944373.

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This piece of work was originally published in the <em>Medical Image Analysis</em> (Volume 71, 2021).&nbsp;A title page is included with proper acknowledgements stated that &quot;This project 18HLT07 MedalCare has received funding from the EMPIR programme co-financed by the Participating States and from the European Union&rsquo;s Horizon 2020 research and innovation programme.&quot;
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de Lepper, Anouk G. W., Carlijn M. A. Buck, Marcel van ‘t Veer, Wouter Huberts, Frans N. van de Vosse, and Lukas R. C. Dekker. "From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy." Journal of The Royal Society Interface 19, no. 194 (2022). http://dx.doi.org/10.1098/rsif.2022.0317.

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Survivors of myocardial infarction are at risk of life-threatening ventricular tachycardias (VTs) later in their lives. Current guidelines for implantable cardioverter defibrillators (ICDs) implantation to prevent VT-related sudden cardiac death is solely based on symptoms and left ventricular ejection fraction. Catheter ablation of scar-related VTs is performed following ICD therapy, reducing VTs, painful shocks, anxiety, depression and worsening heart failure. We postulate that better prediction of the occurrence and circuit of VT, will improve identification of patients at risk for VT and b
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48

Zhang, Yingnan, Kelly Zhang, Adityo Prakosa, et al. "Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins." eLife 12 (October 18, 2023). http://dx.doi.org/10.7554/elife.88865.3.

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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. This approach integrates
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Xing, Xiaodan, Javier Del Ser, Yinzhe Wu, et al. "HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis." IEEE Journal of Biomedical and Health Informatics, 2022, 1. http://dx.doi.org/10.1109/jbhi.2022.3158897.

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Roopnarinesingh, Ricardo, Debanjan Mukherjee, Sreeparna Majee, Kelly Cao, Leon Rinkel, and Jonathan Coutinho. "Abstract TP388: Integrating standard-of-care clinical stroke workup within in silico embolic stroke models for etiology disambiguation." Stroke 56, Suppl_1 (2025). https://doi.org/10.1161/str.56.suppl_1.tp388.

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Introduction: Embolic Stroke of Undetermined Source (ESUS) accounts for a critical proportion of all ischemic strokes. Disambiguating embolism etiology is important to improve treatment efficacy and reduce recurrent events. Patient-specific in silico models can shed valuable insights on embolus source-destination mapping. This requires reliable and accurate pre/post-stroke hemodynamic models, which benefit from integrating multiple modes of patient information from imaging and clinical records. This is a major state-of-the-art challenge. Here, we present a workflow for multi-modal data integra
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