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Sel K, Osman D, Zare F, Masoumi Shahrbabak S, Brattain L, Hahn JO, Inan OT, Mukkamala R, Palmer J, Paydarfar D, Pettigrew RI, Quyyumi AA, Telfer B, Jafari R. Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact. J Am Heart Assoc 2024; 13:e031981. [PMID: 39087582 DOI: 10.1161/jaha.123.031981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
The past several decades have seen rapid advances in diagnosis and treatment of cardiovascular diseases and stroke, enabled by technological breakthroughs in imaging, genomics, and physiological monitoring, coupled with therapeutic interventions. We now face the challenge of how to (1) rapidly process large, complex multimodal and multiscale medical measurements; (2) map all available data streams to the trajectories of disease states over the patient's lifetime; and (3) apply this information for optimal clinical interventions and outcomes. Here we review new advances that may address these challenges using digital twin technology to fulfill the promise of personalized cardiovascular medical practice. Rooted in engineering mechanics and manufacturing, the digital twin is a virtual representation engineered to model and simulate its physical counterpart. Recent breakthroughs in scientific computation, artificial intelligence, and sensor technology have enabled rapid bidirectional interactions between the virtual-physical counterparts with measurements of the physical twin that inform and improve its virtual twin, which in turn provide updated virtual projections of disease trajectories and anticipated clinical outcomes. Verification, validation, and uncertainty quantification builds confidence and trust by clinicians and patients in the digital twin and establishes boundaries for the use of simulations in cardiovascular medicine. Mechanistic physiological models form the fundamental building blocks of the personalized digital twin that continuously forecast optimal management of cardiovascular health using individualized data streams. We present exemplars from the existing body of literature pertaining to mechanistic model development for cardiovascular dynamics and summarize existing technical challenges and opportunities pertaining to the foundation of a digital twin.
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Affiliation(s)
- Kaan Sel
- Laboratory for Information & Decision Systems (LIDS) Massachusetts Institute of Technology Cambridge MA USA
| | - Deen Osman
- Department of Electrical and Computer Engineering Texas A&M University College Station TX USA
| | - Fatemeh Zare
- Department of Electrical and Computer Engineering Texas A&M University College Station TX USA
| | | | - Laura Brattain
- Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA
| | - Jin-Oh Hahn
- Department of Mechanical Engineering University of Maryland College Park MD USA
| | - Omer T Inan
- School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA
| | - Ramakrishna Mukkamala
- Department of Bioengineering and Anesthesiology and Perioperative Medicine University of Pittsburgh Pittsburgh PA USA
| | - Jeffrey Palmer
- Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA
| | - David Paydarfar
- Department of Neurology The University of Texas at Austin Dell Medical School Austin TX USA
| | | | - Arshed A Quyyumi
- Emory Clinical Cardiovascular Research Institute, Division of Cardiology, Department of Medicine Emory University School of Medicine Atlanta GA USA
| | - Brian Telfer
- Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA
| | - Roozbeh Jafari
- Laboratory for Information & Decision Systems (LIDS) Massachusetts Institute of Technology Cambridge MA USA
- Department of Electrical and Computer Engineering Texas A&M University College Station TX USA
- Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA
- School of Engineering Medicine Texas A&M University Houston TX USA
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Trayanova NA, Lyon A, Shade J, Heijman J. Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation. Physiol Rev 2024; 104:1265-1333. [PMID: 38153307 PMCID: PMC11381036 DOI: 10.1152/physrev.00017.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023] Open
Abstract
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. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.
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Affiliation(s)
- Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aurore Lyon
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of Heart and Lungs, Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Julie Shade
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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Dasí A, Nagel C, Pope MTB, Wijesurendra RS, Betts TR, Sachetto R, Loewe A, Bueno-Orovio A, Rodriguez B. In Silico TRials guide optimal stratification of ATrIal FIbrillation patients to Catheter Ablation and pharmacological medicaTION: the i-STRATIFICATION study. Europace 2024; 26:euae150. [PMID: 38870348 PMCID: PMC11184207 DOI: 10.1093/europace/euae150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 05/23/2024] [Indexed: 06/15/2024] Open
Abstract
AIMS Patients with persistent atrial fibrillation (AF) experience 50% recurrence despite pulmonary vein isolation (PVI), and no consensus is established for secondary treatments. The aim of our i-STRATIFICATION study is to provide evidence for stratifying patients with AF recurrence after PVI to optimal pharmacological and ablation therapies, through in silico trials. METHODS AND RESULTS A cohort of 800 virtual patients, with variability in atrial anatomy, electrophysiology, and tissue structure (low-voltage areas, LVAs), was developed and validated against clinical data from ionic currents to electrocardiogram. Virtual patients presenting AF post-PVI underwent 12 secondary treatments. Sustained AF developed in 522 virtual patients after PVI. Second ablation procedures involving left atrial ablation alone showed 55% efficacy, only succeeding in the small right atria (<60 mL). When additional cavo-tricuspid isthmus ablation was considered, Marshall-PLAN sufficed (66% efficacy) for the small left atria (<90 mL). For the bigger left atria, a more aggressive ablation approach was required, such as anterior mitral line (75% efficacy) or posterior wall isolation plus mitral isthmus ablation (77% efficacy). Virtual patients with LVAs greatly benefited from LVA ablation in the left and right atria (100% efficacy). Conversely, in the absence of LVAs, synergistic ablation and pharmacotherapy could terminate AF. In the absence of ablation, the patient's ionic current substrate modulated the response to antiarrhythmic drugs, being the inward currents critical for optimal stratification to amiodarone or vernakalant. CONCLUSION In silico trials identify optimal strategies for AF treatment based on virtual patient characteristics, evidencing the power of human modelling and simulation as a clinical assisting tool.
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Affiliation(s)
- Albert Dasí
- Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QD, UK
| | - Claudia Nagel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Michael T B Pope
- Department of Cardiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Department for Human Development and Health, University of Southampton, Southampton, UK
| | - Rohan S Wijesurendra
- Department of Cardiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Timothy R Betts
- Department of Cardiology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Rafael Sachetto
- Departamento de Ciência da Computação, Universidade Federal de São João del Rei, São João del Rei, MG, Brazil
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Alfonso Bueno-Orovio
- Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QD, UK
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, Oxford OX1 3QD, UK
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Martínez Díaz P, Sánchez J, Fitzen N, Ravens U, Dössel O, Loewe A. The right atrium affects in silico arrhythmia vulnerability in both atria. Heart Rhythm 2024; 21:799-805. [PMID: 38301854 DOI: 10.1016/j.hrthm.2024.01.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/18/2024] [Accepted: 01/24/2024] [Indexed: 02/03/2024]
Affiliation(s)
- Patricia Martínez Díaz
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Jorge Sánchez
- Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Valencia, Spain
| | - Nikola Fitzen
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Ursula Ravens
- Institute for Experimental Cardiovascular Medicine, Universitätsklinikum Freiburg, Freiburg, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
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Jaffery OA, Melki L, Slabaugh G, Good WW, Roney CH. A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data. Arrhythm Electrophysiol Rev 2024; 13:e08. [PMID: 38807744 PMCID: PMC11131150 DOI: 10.15420/aer.2023.25] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/27/2023] [Indexed: 05/30/2024] Open
Abstract
Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested. However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.
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Affiliation(s)
- Ovais A Jaffery
- School of Engineering and Materials Science, Queen Mary University of London London, UK
| | - Lea Melki
- R&D Algorithms, Acutus Medical Carlsbad, CA, US
| | - Gregory Slabaugh
- Digital Environment Research Institute, Queen Mary University of London London, UK
| | | | - Caroline H Roney
- School of Engineering and Materials Science, Queen Mary University of London London, UK
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Bahlke F, Englert F, Popa M, Bourier F, Reents T, Lennerz C, Kraft H, Martinez AT, Kottmaier M, Syväri J, Tydecks M, Telishevska M, Lengauer S, Hessling G, Deisenhofer I, Erhard N. First clinical data on artificial intelligence-guided catheter ablation in long-standing persistent atrial fibrillation. J Cardiovasc Electrophysiol 2024; 35:406-414. [PMID: 38197476 DOI: 10.1111/jce.16184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/20/2023] [Accepted: 12/29/2023] [Indexed: 01/11/2024]
Abstract
INTRODUCTION Despite advanced ablation strategies and major technological improvements, treatment of persistent atrial fibrillation (AF) remains challenging and the underlying pathophysiology is not fully understood. This study analyzed the multiple procedure outcome and safety of catheter ablation of spatiotemporal dispersions (DISPERS) detected by artificial intelligence (AI)-guided software in patients with long-standing persistent AF. METHODS AND RESULTS The Volta VX1 software was used for 50 consecutive patients undergoing catheter ablation for persistent AF. First, high-density mapping (78% biatrial) with a multipolar mapping catheter was performed. In addition to pulmonary vein isolation (PVI), ablation of DISPERS was performed aiming at homogenizing, dissecting, isolating, or connecting DISPERS areas to nonconducting anatomical structures. Follow-up contained regular visits at our outpatient clinic at 1, 3, 6, and 12 months including 7-day Holter electrocardiograms. Patients were mainly suffering from long-standing persistent AF (mean AF duration 50.30 ± 54.28 months). Following PVI, ablation of left atrial and right atrial DISPERS areas led to AF cycle length prolongation (mean of 162.0 ± 16.6 to 202.2 ± 21.6 ms after) and AF termination to atrial tachycardia (AT) or sinus rhythm (SR) in 12 patients (24%). No stroke or pericardial effusion occurred; major groin complications (pseudoaneurysm n = 1, atrioventricular fistula n = 1) were detected in two patients. After a blanking period of 6 weeks, recurrence of any atrial arrhythmia was documented in 26 patients (52%). The majority of patients presented with organized AT (n = 15) while AF was present in n = 9 patients and AT/AF was observed in n = 2 patients. Twenty-two patients underwent reablation. During a mean follow-up of 363.14 ± 187.42 days and after an average of 1.46 ± 0.68 procedures, 82% of patients remained in stable SR. CONCLUSION DISPERS-guided ablation using machine learning software (the Volta VX1 software) in addition to PVI in long-standing persistent AF ablation resulted in high long-term success rates regarding AF and AT elimination. Most arrhythmia recurrences were reentrant AT. After a total of 1.46 ± 0.68 procedures, freedom from AF/AT was 82%. Despite prolonged procedure times complication rates were low. Randomized studies are necessary to evaluate long-term efficacy of dispersion-guided ablation using AI.
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Affiliation(s)
- Fabian Bahlke
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Florian Englert
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Miruna Popa
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Felix Bourier
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Tilko Reents
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Carsten Lennerz
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Hannah Kraft
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Alex Tunsch Martinez
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Marc Kottmaier
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Jan Syväri
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Madeleine Tydecks
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Marta Telishevska
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Sarah Lengauer
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Gabriele Hessling
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Isabel Deisenhofer
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Nico Erhard
- Department of Electrophysiology, German Heart Center Munich, Technical University of Munich, Munich, Germany
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Wang T, Karel J, Invers-Rubio E, Hernández-Romero I, Peeters R, Bonizzi P, Guillem MS. Standardized 2D atrial mapping and its clinical applications. Comput Biol Med 2024; 168:107755. [PMID: 38039895 DOI: 10.1016/j.compbiomed.2023.107755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/10/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023]
Abstract
The visualization and comparison of electrophysiological information in the atrium among different patients could be facilitated by a standardized 2D atrial mapping. However, due to the complexity of the atrial anatomy, unfolding the 3D geometry into a 2D atrial mapping is challenging. In this study, we aim to develop a standardized approach to achieve a 2D atrial mapping that connects the left and right atria, while maintaining fixed positions and sizes of atrial segments across individuals. Atrial segmentation is a prerequisite for the process. Segmentation includes 19 different segments with 12 segments from the left atrium, 5 segments from the right atrium, and two segments for the atrial septum. To ensure consistent and physiologically meaningful segment connections, an automated procedure is applied to open up the atrial surfaces and project the 3D information into 2D. The corresponding 2D atrial mapping can then be utilized to visualize different electrophysiological information of a patient, such as activation time patterns or phase maps. This can in turn provide useful information for guiding catheter ablation. The proposed standardized 2D maps can also be used to compare more easily structural information like fibrosis distribution with rotor presence and location. We show several examples of visualization of different electrophysiological properties for both healthy subjects and patients affected by atrial fibrillation. These examples show that the proposed maps provide an easy way to visualize and interpret intra-subject information and perform inter-subject comparison, which may provide a reference framework for the analysis of the atrial fibrillation substrate before treatment, and during a catheter ablation procedure.
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Affiliation(s)
- Tiantian Wang
- Department of Advanced Computing Sciences, Maastricht University, The Netherlands
| | - Joël Karel
- Department of Advanced Computing Sciences, Maastricht University, The Netherlands.
| | - Eric Invers-Rubio
- Arrhythmia Unit, Hospital Clínic de Barcelona Cardiovascular Institute (ICCV), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | | | - Ralf Peeters
- Department of Advanced Computing Sciences, Maastricht University, The Netherlands
| | - Pietro Bonizzi
- Department of Advanced Computing Sciences, Maastricht University, The Netherlands
| | - Maria S Guillem
- ITACA Institute, Universitat Politècnica de València, Valencia, Spain
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Song E. Impact of noise on the instability of spiral waves in stochastic 2D mathematical models of human atrial fibrillation. J Biol Phys 2023; 49:521-533. [PMID: 37792115 PMCID: PMC10651617 DOI: 10.1007/s10867-023-09644-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 09/08/2023] [Indexed: 10/05/2023] Open
Abstract
Sustained spiral waves, also known as rotors, are pivotal mechanisms in persistent atrial fibrillation (AF). Stochasticity is inevitable in nonlinear biological systems such as the heart; however, it is unclear how noise affects the instability of spiral waves in human AF. This study presents a stochastic two-dimensional mathematical model of human AF and explores how Gaussian white noise affects the instability of spiral waves. In homogeneous tissue models, Gaussian white noise may lead to spiral-wave meandering and wavefront break-up. As the noise intensity increases, the spatial dispersion of phase singularity (PS) points increases. This finding indicates the potential AF-protective effects of cardiac system stochasticity by destabilizing the rotors. By contrast, Gaussian white noise is unlikely to affect the spiral-wave instability in the presence of localized scar or fibrosis regions. The PS points are located at the boundary or inside the scar/fibrosis regions. Localized scar or fibrosis may play a pivotal role in stabilizing spiral waves regardless of the presence of noise. This study suggests that fibrosis and scars are essential for stabilizing the rotors in stochastic mathematical models of AF. Further patient-derived realistic modeling studies are required to confirm the role of scar/fibrosis in AF pathophysiology.
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Affiliation(s)
- Euijun Song
- Yonsei University College of Medicine, Seoul, Republic of Korea.
- , Gyeonggi, Republic of Korea.
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9
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Africa PC, Piersanti R, Regazzoni F, Bucelli M, Salvador M, Fedele M, Pagani S, Dede' L, Quarteroni A. lifex-ep: a robust and efficient software for cardiac electrophysiology simulations. BMC Bioinformatics 2023; 24:389. [PMID: 37828428 PMCID: PMC10571323 DOI: 10.1186/s12859-023-05513-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors of various research teams, comprehensive and user-friendly software programs for cardiac simulations, capable of accurately replicating both normal and pathological conditions, are still in the process of achieving full maturity within the scientific community. RESULTS This work introduces [Formula: see text]-ep, a publicly available software for numerical simulations of the electrophysiology activity of the cardiac muscle, under both normal and pathological conditions. [Formula: see text]-ep employs the monodomain equation to model the heart's electrical activity. It incorporates both phenomenological and second-generation ionic models. These models are discretized using the Finite Element method on tetrahedral or hexahedral meshes. Additionally, [Formula: see text]-ep integrates the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, previously released in Africa et al., 2023, within [Formula: see text]-fiber. As an alternative, users can also choose to import myofibers from a file. This paper provides a concise overview of the mathematical models and numerical methods underlying [Formula: see text]-ep, along with comprehensive implementation details and instructions for users. [Formula: see text]-ep features exceptional parallel speedup, scaling efficiently when using up to thousands of cores, and its implementation has been verified against an established benchmark problem for computational electrophysiology. We showcase the key features of [Formula: see text]-ep through various idealized and realistic simulations conducted in both normal and pathological scenarios. Furthermore, the software offers a user-friendly and flexible interface, simplifying the setup of simulations using self-documenting parameter files. CONCLUSIONS [Formula: see text]-ep provides easy access to cardiac electrophysiology simulations for a wide user community. It offers a computational tool that integrates models and accurate methods for simulating cardiac electrophysiology within a high-performance framework, while maintaining a user-friendly interface. [Formula: see text]-ep represents a valuable tool for conducting in silico patient-specific simulations.
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Affiliation(s)
- Pasquale Claudio Africa
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- mathLab, Mathematics Area, SISSA International School for Advanced Studies, Trieste, Italy
| | - Roberto Piersanti
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
| | | | - Michele Bucelli
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Matteo Salvador
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California, USA
| | - Marco Fedele
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Stefano Pagani
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Luca Dede'
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Alfio Quarteroni
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne, Professor emeritus, Switzerland
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Song E. Effects of hydroxychloroquine on atrial electrophysiology in in silico wild-type and PITX2 +/- atrial cardiomyocytes. Herz 2023; 48:384-392. [PMID: 36732468 PMCID: PMC9894744 DOI: 10.1007/s00059-023-05162-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/07/2022] [Accepted: 12/30/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND Hydroxychloroquine (HCQ) is commonly used in the treatment of autoimmune diseases and increases the risk of QT interval prolongation. However, it is unclear how HCQ affects atrial electrophysiology and the risk of atrial fibrillation (AF). METHODS We quantitatively examined the potential atrial arrhythmogenic effects of HCQ on AF using a computational model of human atrial cardiomyocytes. We measured atrial electrophysiological markers after systematically varying HCQ concentrations. RESULTS The HCQ concentrations were positively correlated with the action potential duration (APD), resting membrane potential, refractory period, APD alternans threshold, and calcium transient alternans threshold (p < 0.05). By contrast, HCQ concentrations were inversely correlated with the maximum upstroke velocity and calcium transient amplitude (p < 0.05). When the therapeutic concentration (Cmax) of HCQ was applied, HCQ increased APD90 by 1.4% in normal sinus rhythm, 1.8% in wild-type AF, and 2.6% in paired-like homeodomain transcription factor 2 (PITX2)+/- AF, but did not affect the alternans thresholds. The overall in silico results suggest no significant atrial arrhythmogenic effects of HCQ at Cmax, instead implying a potential antiarrhythmic role of low-dose HCQ in AF. However, at an HCQ concentration of fourfold Cmax, a rapid pacing rate of 4 Hz induced prominent APD alternans, particularly in the PITX2+/- AF model. CONCLUSION Our in silico analysis suggests a potential antiarrhythmic role of low-dose HCQ in AF. Concomitant PITX2 mutations and high-dose HCQ treatments may increase the risk of AF, and this potential genotype/dose-dependent arrhythmogenic effect of HCQ should be investigated further.
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Affiliation(s)
- Euijun Song
- Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
- Yonsei University College of Medicine, Seoul, Republic of Korea.
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11
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Dasí A, Pope MT, Wijesurendra RS, Betts TR, Sachetto R, Bueno‐Orovio A, Rodriguez B. What determines the optimal pharmacological treatment of atrial fibrillation? Insights from in silico trials in 800 virtual atria. J Physiol 2023; 601:4013-4032. [PMID: 37475475 PMCID: PMC10952228 DOI: 10.1113/jp284730] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023] Open
Abstract
The best pharmacological treatment for each atrial fibrillation (AF) patient is unclear. We aim to exploit AF simulations in 800 virtual atria to identify key patient characteristics that guide the optimal selection of anti-arrhythmic drugs. The virtual cohort considered variability in electrophysiology and low voltage areas (LVA) and was developed and validated against experimental and clinical data from ionic currents to ECG. AF sustained in 494 (62%) atria, with large inward rectifier K+ current (IK1 ) and Na+ /K+ pump (INaK ) densities (IK1 0.11 ± 0.03 vs. 0.07 ± 0.03 S mF-1 ; INaK 0.68 ± 0.15 vs. 0.38 ± 26 S mF-1 ; sustained vs. un-sustained AF). In severely remodelled left atrium, with LVA extensions of more than 40% in the posterior wall, higher IK1 (median density 0.12 ± 0.02 S mF-1 ) was required for AF maintenance, and rotors localized in healthy right atrium. For lower LVA extensions, rotors could also anchor to LVA, in atria presenting short refractoriness (median L-type Ca2+ current, ICaL , density 0.08 ± 0.03 S mF-1 ). This atrial refractoriness, modulated by ICaL and fast Na+ current (INa ), determined pharmacological treatment success for both small and large LVA. Vernakalant was effective in atria presenting long refractoriness (median ICaL density 0.13 ± 0.05 S mF-1 ). For short refractoriness, atria with high INa (median density 8.92 ± 2.59 S mF-1 ) responded more favourably to amiodarone than flecainide, and the opposite was found in atria with low INa (median density 5.33 ± 1.41 S mF-1 ). In silico drug trials in 800 human atria identify inward currents as critical for optimal stratification of AF patient to pharmacological treatment and, together with the left atrial LVA extension, for accurately phenotyping AF dynamics. KEY POINTS: Atrial fibrillation (AF) maintenance is facilitated by small L-type Ca2+ current (ICaL ) and large inward rectifier K+ current (IK1 ) and Na+ /K+ pump. In severely remodelled left atrium, with low voltage areas (LVA) covering more than 40% of the posterior wall, sustained AF requires higher IK1 and rotors localize in healthy right atrium. For lower LVA extensions, rotors can also anchor to LVA, if the atria present short refractoriness (low ICaL ) Vernakalant is effective in atria presenting long refractoriness (high ICaL ). For short refractoriness, atria with fast Na+ current (INa ) up-regulation respond more favourably to amiodarone than flecainide, and the opposite is found in atria with low INa . The inward currents (ICaL and INa ) are critical for optimal stratification of AF patient to pharmacological treatment and, together with the left atrial LVA extension, for accurately phenotyping AF dynamics.
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Affiliation(s)
- Albert Dasí
- Department of Computer ScienceUniversity of OxfordOxfordUK
| | - Michael T.B. Pope
- Department of CardiologyOxford University Hospitals NHS Foundation TrustOxfordUK
- Department for Human Development and HealthUniversity of SouthamptonSouthamptonUK
| | - Rohan S. Wijesurendra
- Department of CardiologyOxford University Hospitals NHS Foundation TrustOxfordUK
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
| | - Tim R. Betts
- Department of CardiologyOxford University Hospitals NHS Foundation TrustOxfordUK
| | - Rafael Sachetto
- Departamento de Ciência da ComputaçãoUniversidade Federal de São João del‐ReiSão João del‐ReiBrazil
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12
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Boersma L, Andrade JG, Betts T, Duytschaever M, Pürerfellner H, Santoro F, Tzeis S, Verma A. Progress in atrial fibrillation ablation during 25 years of Europace journal. Europace 2023; 25:euad244. [PMID: 37622592 PMCID: PMC10451004 DOI: 10.1093/europace/euad244] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
The first edition of Europace journal in 1999 came right around the time of the landmark publication of the electrophysiologists from Bordeaux, establishing how elimination of ectopic activity from the pulmonary veins (PVs) resulted in a marked reduction of atrial fibrillation (AF). The past 25 years have seen an incredible surge in scientific interest to develop new catheters and energy sources to optimize durability and safety of ablation, as well as study the mechanisms for AF and devise ablation strategies. While ablation in the beginning was performed with classic 4 mm tip catheters that emitted radiofrequency (RF) energy to create tissue lesions, this evolved to using irrigation and contact force (CF) measurement while increasing power. Also, so-called single-shot devices were developed with balloons and arrays to create larger contiguous lesions, and energy sources changed from RF current to cryogenic ablation and more recently pulsed field ablation with electrical current. Although PV ablation has remained the basis for every AF ablation, it was soon recognized that this was not enough to cure all patients, especially those with non-paroxysmal AF. Standardized approaches for additional ablation targets have been used but have not been satisfactory in all patients so far. This led to highly technical mapping systems that are meant to unravel the drivers for the maintenance of AF. In the following sections, the development of energies, strategies, and tools is described with a focus on the contribution of Europace to publish the outcomes of studies that were done during the past 25 years.
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Affiliation(s)
- Lucas Boersma
- Cardiology Department, St. Antonius Hospital Nieuwegein/Amsterdam University Medical Center, PO 2500, 3430 EM Nieuwegein, The Netherlands
| | - Jason G Andrade
- Department of Medicine, University of British Columbia, Vancouver, Canada
- Cardiology Department, Center for Cardiovascular Innovation, Vancouver, Canada
- Montreal Heart Institute, Department of Medicine, Université de Montréal, Montreal, Canada
| | - Tim Betts
- Department of Cardiology, Oxford University, Oxford, UK
| | | | | | - Francesco Santoro
- Department of Medical and Surgery Sciences, University of Foggia, Foggia, Italy
| | - Stylianos Tzeis
- Cardiology Department, Mitera Hospital, Hygeia Group, Athens, Greece
| | - Atul Verma
- Cardiology Department, McGill University Health Center, Montreal, Quebec, Canada
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13
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Nairn D, Eichenlaub M, Müller-Edenborn B, Huang T, Lehrmann H, Nagel C, Azzolin L, Luongo G, Figueras Ventura RM, Rubio Forcada B, Vallès Colomer A, Westermann D, Arentz T, Dössel O, Loewe A, Jadidi A. Differences in atrial substrate localization using late gadolinium enhancement-magnetic resonance imaging, electrogram voltage, and conduction velocity: a cohort study using a consistent anatomical reference frame in patients with persistent atrial fibrillation. Europace 2023; 25:euad278. [PMID: 37713626 PMCID: PMC10533207 DOI: 10.1093/europace/euad278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 09/10/2023] [Indexed: 09/17/2023] Open
Abstract
AIMS Electro-anatomical voltage, conduction velocity (CV) mapping, and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) have been correlated with atrial cardiomyopathy (ACM). However, the comparability between these modalities remains unclear. This study aims to (i) compare pathological substrate extent and location between current modalities, (ii) establish spatial histograms in a cohort, (iii) develop a new estimated optimized image intensity threshold (EOIIT) for LGE-MRI identifying patients with ACM, (iv) predict rhythm outcome after pulmonary vein isolation (PVI) for persistent atrial fibrillation (AF). METHODS AND RESULTS Thirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Late gadolinium enhancement areas were classified using the UTAH, image intensity ratio (IIR >1.20), and new EOIIT method for comparison to low-voltage substrate (LVS) and slow conduction areas <0.2 m/s. Receiver operating characteristic analysis was used to determine LGE thresholds optimally matching LVS. Atrial cardiomyopathy was defined as LVS extent ≥5% of the left atrium (LA) surface at <0.5 mV. The degree and distribution of detected pathological substrate (percentage of individual LA surface are) varied significantly (P < 0.001) across the mapping modalities: 10% (interquartile range 0-14%) of the LA displayed LVS <0.5 mV vs. 7% (0-12%) slow conduction areas <0.2 m/s vs. 15% (8-23%) LGE with the UTAH method vs. 13% (2-23%) using IIR >1.20, with most discrepancies on the posterior LA. Optimized image intensity thresholds and each patient's mean blood pool intensity correlated linearly (R2 = 0.89, P < 0.001). Concordance between LGE-MRI-based and LVS-based ACM diagnosis improved with the novel EOIIT applied at the anterior LA [83% sensitivity, 79% specificity, area under the curve (AUC): 0.89] in comparison to the UTAH method (67% sensitivity, 75% specificity, AUC: 0.81) and IIR >1.20 (75% sensitivity, 62% specificity, AUC: 0.67). CONCLUSION Discordances in detected pathological substrate exist between LVS, CV, and LGE-MRI in the LA, irrespective of the LGE detection method. The new EOIIT method improves concordance of LGE-MRI-based ACM diagnosis with LVS in ablation-naive AF patients but discrepancy remains particularly on the posterior wall. All methods may enable the prediction of rhythm outcomes after PVI in patients with persistent AF.
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Affiliation(s)
- Deborah Nairn
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Martin Eichenlaub
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Björn Müller-Edenborn
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Taiyuan Huang
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Heiko Lehrmann
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Claudia Nagel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Luca Azzolin
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Giorgio Luongo
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | | | | | | | - Dirk Westermann
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Arentz
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | - Amir Jadidi
- Department of Cardiology and Angiology, Medical Center, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Arrhythmia Division, Department of Cardiology, Heart Center Lucerne, Lucerne Cantonal Hospital, Lucerne, Switzerland
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14
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Telle Å, Bargellini C, Chahine Y, Del Álamo JC, Akoum N, Boyle PM. Personalized biomechanical insights in atrial fibrillation: opportunities & challenges. Expert Rev Cardiovasc Ther 2023; 21:817-837. [PMID: 37878350 PMCID: PMC10841537 DOI: 10.1080/14779072.2023.2273896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 10/18/2023] [Indexed: 10/26/2023]
Abstract
INTRODUCTION Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke. AREAS COVERED In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care. EXPERT OPINION Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.
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Affiliation(s)
- Åshild Telle
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Clarissa Bargellini
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Yaacoub Chahine
- Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Juan C Del Álamo
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
- Center for Cardiovascular Biology, University of Washington, Seattle, WA, USA
| | - Nazem Akoum
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Patrick M Boyle
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Center for Cardiovascular Biology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
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15
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Betts TR, Good WW, Melki L, Metzner A, Grace A, Verma A, Murray S, James S, Wong T, Boersma LVA, Steven D, Sultan A, Busch S, Neužil P, de Asmundis C, Lee J, Szili-Török T. Treatment of pathophysiologic propagation outside of the pulmonary veins in retreatment of atrial fibrillation patients: RECOVER AF study. Europace 2023; 25:euad097. [PMID: 37072340 PMCID: PMC10228624 DOI: 10.1093/europace/euad097] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/23/2023] [Indexed: 04/20/2023] Open
Abstract
AIMS RECOVER AF evaluated the performance of whole-chamber non-contact charge-density mapping to guide the ablation of non-pulmonary vein (PV) targets in persistent atrial fibrillation (AF) patients following either a first or second failed procedure. METHODS AND RESULTS RECOVER AF was a prospective, non-randomized trial that enrolled patients scheduled for a first or second ablation retreatment for recurrent AF. The PVs were assessed and re-isolated if necessary. The AF maps were used to guide the ablation of non-PV targets through elimination of pathologic conduction patterns (PCPs). Primary endpoint was freedom from AF on or off antiarrhythmic drugs (AADs) at 12 months. Patients undergoing retreatment with the AcQMap System (n = 103) were 76% AF-free at 12 months [67% after single procedure (SP)] on or off AADs (80% free from AF on AADs). Patients who had only received a pulmonary vein isolation (PVI) prior to study treatment of non-PV targets with the AcQMap System were 91% AF-free at 12 months (83% SP). No major adverse events were reported. CONCLUSION Non-contact mapping can be used to target and guide the ablation of PCPs beyond the PVs in persistent AF patients returning for a first or second retreatment with 76% freedom from AF at 12 months. The AF freedom was particularly high, 91% (43/47), for patients enrolled having only a prior de novo PVI, and freedom from all atrial arrhythmias for this cohort was 74% (35/47). These early results are encouraging and suggest that guiding individualized targeted ablation of PCPs may therefore be advantageous to target at the earliest opportunity in patients with persistent AF.
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Affiliation(s)
- Timothy R Betts
- Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Headley Way, Oxford, OX3 9DU, UK
| | | | - Lea Melki
- R&D Algorithms, Acutus Medical, Carlsbad, CA, USA
| | - Andreas Metzner
- Cardiac Electrophysiology Department, Asklepios Klinik St. Georg, Hamburg, Germany
| | - Andrew Grace
- Department of Cardiology, Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK
| | - Atul Verma
- Division of Cardiology, McGill University Health Centre, McGill University, Montreal, QC, Canada
| | - Stephen Murray
- Cardiology Department, Freeman Hospital, Newcastle Upon Tyne, UK
| | - Simon James
- Cardiology Department, The James Cook University Hospital, Middlesbrough, UK
| | - Tom Wong
- Department of Cardiology, Royal Brompton Hospital, London, UK
| | - Lucas V A Boersma
- Cardiology Department, Sint Antonius Hospital, Nieuwegein, The Netherlands
| | - Daniel Steven
- Department of Electrophysiology, Heart Center, University of Cologne, Cologne, Germany
| | - Arian Sultan
- Department of Electrophysiology, Heart Center, University of Cologne, Cologne, Germany
| | - Sonia Busch
- Department Cardiology and Angiology, Klinikum Coburg, Coburg, Germany
| | - Petr Neužil
- Department of Cardiology, Homolka Hospital (Na Homolce Hospital), Prague, Czech Republic
| | - Carlo de Asmundis
- Heart Rhythm Management Centre, Cardiovascular Division, UZ Brussel—Vrije Universiteit Brussel, Brussels, Belgium
| | - Justin Lee
- Cardiology and Cardiothoracic Surgery, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Tamás Szili-Török
- Department of Cardiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
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16
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Together we are strong! Collaboration between clinicians and engineers as an enabler for better diagnosis and therapy of atrial arrhythmias. Med Biol Eng Comput 2023; 61:875-877. [PMID: 36746836 PMCID: PMC9988996 DOI: 10.1007/s11517-023-02788-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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17
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Yamamoto C, Trayanova NA. Atrial fibrillation: Insights from animal models, computational modeling, and clinical studies. EBioMedicine 2022; 85:104310. [PMID: 36309006 PMCID: PMC9619190 DOI: 10.1016/j.ebiom.2022.104310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/25/2022] [Accepted: 10/04/2022] [Indexed: 11/11/2022] Open
Abstract
Atrial fibrillation (AF) is the most common human arrhythmia, affecting millions of patients worldwide. A combination of risk factors and comorbidities results in complex atrial remodeling, which increases AF vulnerability and persistence. Insights from animal models, clinical studies, and computational modeling have advanced the understanding of the mechanisms and pathophysiology of AF. Areas of heterogeneous pathological remodeling, as well as altered electrophysiological properties, serve as a substrate for AF drivers and spontaneous activations. The complex and individualized presentation of this arrhythmia suggests that mechanisms-based personalized approaches will likely be needed to overcome current challenges in AF management. In this paper, we review the insights on the mechanisms of AF obtained from animal models and clinical studies and how computational models integrate this knowledge to advance AF clinical management. We also assess the challenges that need to be overcome to implement these mechanistic models in clinical practice.
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Affiliation(s)
- Carolyna Yamamoto
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Natalia A. Trayanova
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA,Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE), Johns Hopkins University, Baltimore, MD, USA,Corresponding author. Johns Hopkins, Johns Hopkins University, United States.
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18
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Bai J, Lu Y, Wang H, Zhao J. How synergy between mechanistic and statistical models is impacting research in atrial fibrillation. Front Physiol 2022; 13:957604. [PMID: 36111152 PMCID: PMC9468674 DOI: 10.3389/fphys.2022.957604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Atrial fibrillation (AF) with multiple complications, high morbidity and mortality, and low cure rates, has become a global public health problem. Although significant progress has been made in the treatment methods represented by anti-AF drugs and radiofrequency ablation, the therapeutic effect is not as good as expected. The reason is mainly because of our lack of understanding of AF mechanisms. This field has benefited from mechanistic and (or) statistical methodologies. Recent renewed interest in digital twin techniques by synergizing between mechanistic and statistical models has opened new frontiers in AF analysis. In the review, we briefly present findings that gave rise to the AF pathophysiology and current therapeutic modalities. We then summarize the achievements of digital twin technologies in three aspects: understanding AF mechanisms, screening anti-AF drugs and optimizing ablation strategies. Finally, we discuss the challenges that hinder the clinical application of the digital twin heart. With the rapid progress in data reuse and sharing, we expect their application to realize the transition from AF description to response prediction.
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Affiliation(s)
- Jieyun Bai
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Yaosheng Lu
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Huijin Wang
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Jichao Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
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