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Koopsen T, Gerrits W, van Osta N, van Loon T, Wouters P, Prinzen FW, Vernooy K, Delhaas T, Teske AJ, Meine M, Cramer MJ, Lumens J. Virtual pacing of a patient's digital twin to predict left ventricular reverse remodelling after cardiac resynchronization therapy. Europace 2023; 26:euae009. [PMID: 38288616 PMCID: PMC10825733 DOI: 10.1093/europace/euae009] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 01/09/2024] [Indexed: 02/01/2024] Open
Abstract
AIMS Identifying heart failure (HF) patients who will benefit from cardiac resynchronization therapy (CRT) remains challenging. We evaluated whether virtual pacing in a digital twin (DT) of the patient's heart could be used to predict the degree of left ventricular (LV) reverse remodelling post-CRT. METHODS AND RESULTS Forty-five HF patients with wide QRS complex (≥130 ms) and reduced LV ejection fraction (≤35%) receiving CRT were retrospectively enrolled. Echocardiography was performed before (baseline) and 6 months after CRT implantation to obtain LV volumes and 18-segment longitudinal strain. A previously developed algorithm was used to generate 45 DTs by personalizing the CircAdapt model to each patient's baseline measurements. From each DT, baseline septal-to-lateral myocardial work difference (MWLW-S,DT) and maximum rate of LV systolic pressure rise (dP/dtmax,DT) were derived. Biventricular pacing was then simulated using patient-specific atrioventricular delay and lead location. Virtual pacing-induced changes ΔMWLW-S,DT and ΔdP/dtmax,DT were correlated with real-world LV end-systolic volume change at 6-month follow-up (ΔLVESV). The DT's baseline MWLW-S,DT and virtual pacing-induced ΔMWLW-S,DT were both significantly associated with the real patient's reverse remodelling ΔLVESV (r = -0.60, P < 0.001 and r = 0.62, P < 0.001, respectively), while correlation between ΔdP/dtmax,DT and ΔLVESV was considerably weaker (r = -0.34, P = 0.02). CONCLUSION Our results suggest that the reduction of septal-to-lateral work imbalance by virtual pacing in the DT can predict real-world post-CRT LV reverse remodelling. This DT approach could prove to be an additional tool in selecting HF patients for CRT and has the potential to provide valuable insights in optimization of CRT delivery.
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Affiliation(s)
- Tijmen Koopsen
- Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Universiteitssingel 40, 6200 MD, The Netherlands
| | - Willem Gerrits
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Nick van Osta
- Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Universiteitssingel 40, 6200 MD, The Netherlands
| | - Tim van Loon
- Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Universiteitssingel 40, 6200 MD, The Netherlands
| | - Philippe Wouters
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Frits W Prinzen
- Department of Physiology, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | - Kevin Vernooy
- Department of Cardiology, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Cardiology, Maastricht University Medical Center (MUMC), Maastricht, The Netherlands
- Department of Cardiology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tammo Delhaas
- Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Universiteitssingel 40, 6200 MD, The Netherlands
| | - Arco J Teske
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Mathias Meine
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Maarten J Cramer
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Universiteitssingel 40, 6200 MD, The Netherlands
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Rodero C, Baptiste TMG, Barrows RK, Lewalle A, Niederer SA, Strocchi M. Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways. FRONTIERS IN PHYSICS 2023; 11:1306210. [PMID: 38500690 PMCID: PMC7615748 DOI: 10.3389/fphy.2023.1306210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.
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Affiliation(s)
- Cristobal Rodero
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Tiffany M. G. Baptiste
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Rosie K. Barrows
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Alexandre Lewalle
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Steven A. Niederer
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Turing Research and Innovation Cluster in Digital Twins (TRIC: DT), The Alan Turing Institute, London, United Kingdom
| | - Marina Strocchi
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
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Remme CA, Heijman J, Gomez AM, Zaza A, Odening KE. 25 years of basic and translational science in EP Europace: novel insights into arrhythmia mechanisms and therapeutic strategies. Europace 2023; 25:euad210. [PMID: 37622575 PMCID: PMC10450791 DOI: 10.1093/europace/euad210] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 06/19/2023] [Indexed: 08/26/2023] Open
Abstract
In the last 25 years, EP Europace has published more than 300 basic and translational science articles covering different arrhythmia types (ranging from atrial fibrillation to ventricular tachyarrhythmias), different diseases predisposing to arrhythmia formation (such as genetic arrhythmia disorders and heart failure), and different interventional and pharmacological anti-arrhythmic treatment strategies (ranging from pacing and defibrillation to different ablation approaches and novel drug-therapies). These studies have been conducted in cellular models, small and large animal models, and in the last couple of years increasingly in silico using computational approaches. In sum, these articles have contributed substantially to our pathophysiological understanding of arrhythmia mechanisms and treatment options; many of which have made their way into clinical applications. This review discusses a representative selection of EP Europace manuscripts covering the topics of pacing and ablation, atrial fibrillation, heart failure and pro-arrhythmic ventricular remodelling, ion channel (dys)function and pharmacology, inherited arrhythmia syndromes, and arrhythmogenic cardiomyopathies, highlighting some of the advances of the past 25 years. Given the increasingly recognized complexity and multidisciplinary nature of arrhythmogenesis and continued technological developments, basic and translational electrophysiological research is key advancing the field. EP Europace aims to further increase its contribution to the discovery of arrhythmia mechanisms and the implementation of mechanism-based precision therapy approaches in arrhythmia management.
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Affiliation(s)
- Carol Ann Remme
- Department of Experimental Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Academic Medical Center, Room K2-104.2, Meibergdreef 11, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, The Netherlands
| | - Jordi Heijman
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Ana M Gomez
- Signaling and Cardiovascular Pathophysiology, UMR-S 1180, Inserm, Université Paris-Saclay, 91400 Orsay, France
| | - Antonio Zaza
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milan, Italy
| | - Katja E Odening
- Translational Cardiology, Department of Cardiology and Department of Physiology, Inselspital University Hospital Bern, University of Bern, 3012 Bern, Switzerland
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Gray RA, Pathmanathan P. Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges. J Cardiovasc Transl Res 2018; 11:80-88. [PMID: 29512059 PMCID: PMC5908828 DOI: 10.1007/s12265-018-9792-2] [Citation(s) in RCA: 93] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 02/02/2018] [Indexed: 02/07/2023]
Abstract
Patient-specific computer models have been developed representing a variety of aspects of the cardiovascular system spanning the disciplines of electrophysiology, electromechanics, solid mechanics, and fluid dynamics. These physiological mechanistic models predict macroscopic phenomena such as electrical impulse propagation and contraction throughout the entire heart as well as flow and pressure dynamics occurring in the ventricular chambers, aorta, and coronary arteries during each heartbeat. Such models have been used to study a variety of clinical scenarios including aortic aneurysms, coronary stenosis, cardiac valvular disease, left ventricular assist devices, cardiac resynchronization therapy, ablation therapy, and risk stratification. After decades of research, these models are beginning to be incorporated into clinical practice directly via marketed devices and indirectly by improving our understanding of the underlying mechanisms of health and disease within a clinical context.
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Affiliation(s)
- Richard A Gray
- Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD, 20993, USA.
- , Silver Spring, USA.
| | - Pras Pathmanathan
- Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD, 20993, USA
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