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Roney CH, Solis Lemus JA, Lopez Barrera C, Zolotarev A, Ulgen O, Kerfoot E, Bevis L, Misghina S, Vidal Horrach C, Jaffery OA, Ehnesh M, Rodero C, Dharmaprani D, Ríos-Muñoz GR, Ganesan A, Good WW, Neic A, Plank G, Hopman LHGA, Götte MJW, Honarbakhsh S, Narayan SM, Vigmond E, Niederer S. Constructing bilayer and volumetric atrial models at scale. Interface Focus 2023; 13:20230038. [PMID: 38106921 PMCID: PMC10722212 DOI: 10.1098/rsfs.2023.0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/15/2023] [Indexed: 12/19/2023] Open
Abstract
To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk).
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Affiliation(s)
- Caroline H. Roney
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Jose Alonso Solis Lemus
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Carlos Lopez Barrera
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
- Center for Research in Advanced Materials S.C (CIMAV), Chihuahua, Mexico
| | - Alexander Zolotarev
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Onur Ulgen
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Eric Kerfoot
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Laura Bevis
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Semhar Misghina
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Caterina Vidal Horrach
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Ovais A. Jaffery
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Mahmoud Ehnesh
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Cristobal Rodero
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Dhani Dharmaprani
- College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Gonzalo R. Ríos-Muñoz
- Bioengineering Department, Universidad Carlos III de Madrid, Madrid 28911, Spain
- Department of Cardiology, Gregorio Marañón Health Research Institute (IiSGM), Hospital General Universitario Gregorio Marañón, Madrid 28007, Spain
- Center for Biomedical Research in Cardiovascular Disease Network (CIBERCV), Madrid 28029, Spain
| | - Anand Ganesan
- College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | | | | | - Gernot Plank
- Gottfried Schatz Research Center-Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | | | | | - Shohreh Honarbakhsh
- Electrophysiology Department, Barts Heart Centre, Barts Health NHS Trust, London, UK
| | - Sanjiv M. Narayan
- Department of Medicine and Cardiovascular Institute, Stanford University, Palo Alto, CA, USA
| | - Edward Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
- IMB, UMR 5251, University Bordeaux, Talence 33400, France
| | - Steven Niederer
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
- Turing Research and Innovation Cluster in Digital Twins (TRIC: DT), The Alan Turing Institute, London, UK
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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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