1
|
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 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.
Collapse
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
| |
Collapse
|
2
|
Que W, Bian Y, Chen S, Zhao X, Ji Z, Hu P, Han C, Shi L. Efficient electrocardiogram generation based on cardiac electric vector simulation model. Comput Biol Med 2024; 177:108629. [PMID: 38820778 DOI: 10.1016/j.compbiomed.2024.108629] [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: 01/22/2024] [Revised: 04/27/2024] [Accepted: 05/18/2024] [Indexed: 06/02/2024]
Abstract
This study introduces a novel Cardiac Electric Vector Simulation Model (CEVSM) to address the computational inefficiencies and low fidelity of traditional electrophysiological models in generating electrocardiograms (ECGs). Our approach leverages CEVSM to efficiently produce reliable ECG samples, facilitating data augmentation essential for the computer-aided diagnosis of myocardial infarction (MI). Significantly, experimental results show that our model dramatically reduces computation time compared to conventional models, with the self-adapting regression transformation matrix method (SRTM) providing clear advantages. SRTM not only achieves high fidelity in ECG simulations but also ensures exceptional consistency with the gold standard method, greatly enhancing MI localization accuracy by data augmentation. These advancements highlight the potential of our model to generate dependable ECG training samples, making it highly suitable for data augmentation and significantly advancing the development and validation of intelligent MI diagnostic systems. Furthermore, this study demonstrates the feasibility of applying life system simulations in the training of medical big models.
Collapse
Affiliation(s)
- Wenge Que
- Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Yingnan Bian
- School of Logistics, Henan College of Transportation, Zhengzhou, 450000, China.
| | - Shengjie Chen
- Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Xiliang Zhao
- Center for Coronary Artery Disease, Division of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China.
| | - Zehua Ji
- Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Pingge Hu
- Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Chuang Han
- School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, 450000, China.
| | - Li Shi
- Department of Automation, Tsinghua University, Beijing, 100084, China; Beijing National Research Center for Information Science and Technology, Beijing, 100084, China.
| |
Collapse
|
3
|
Salvador M, Kong F, Peirlinck M, Parker DW, Chubb H, Dubin AM, Marsden AL. Digital twinning of cardiac electrophysiology for congenital heart disease. J R Soc Interface 2024; 21:20230729. [PMID: 38835246 DOI: 10.1098/rsif.2023.0729] [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: 12/08/2023] [Accepted: 03/15/2024] [Indexed: 06/06/2024] Open
Abstract
In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in paediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and using rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in paediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.
Collapse
Affiliation(s)
- Matteo Salvador
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Fanwei Kong
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Mathias Peirlinck
- Department of Biomechanical Engineering, Delft University of Technology , Delft, The Netherlands
| | - David W Parker
- Stanford Research Computing Center, Stanford University , Stanford, CA, USA
| | - Henry Chubb
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Anne M Dubin
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Alison L Marsden
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
- Department of Bioengineering, Stanford University , Stanford, CA, USA
| |
Collapse
|
4
|
Gsell MAF, Neic A, Bishop MJ, Gillette K, Prassl AJ, Augustin CM, Vigmond EJ, Plank G. ForCEPSS-A framework for cardiac electrophysiology simulations standardization. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 251:108189. [PMID: 38728827 DOI: 10.1016/j.cmpb.2024.108189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/04/2024] [Accepted: 04/17/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND AND OBJECTIVE Simulation of cardiac electrophysiology (CEP) is an important research tool that is increasingly being adopted in industrial and clinical applications. Typical workflows for CEP simulation consist of a sequence of processing stages starting with building an anatomical model and then calibrating its electrophysiological properties to match observable data. While the calibration stages are common and generalizable, most CEP studies re-implement these steps in complex and highly variable workflows. This lack of standardization renders the execution of computational CEP studies in an efficient, robust, and reproducible manner a significant challenge. Here, we propose ForCEPSS as an efficient and robust, yet flexible, software framework for standardizing CEP simulation studies. METHODS AND RESULTS Key processing stages of CEP simulation studies are identified and implemented in a standardized workflow that builds on openCARP1 Plank et al. (2021) and the Python-based carputils2 framework. Stages include (i) the definition and initialization of action potential phenotypes, (ii) the tissue scale calibration of conduction properties, (iii) the functional initialization to approximate a limit cycle corresponding to the dynamic reference state according to an experimental protocol, and, (iv) the execution of the CEP study where the electrophysiological response to a perturbation of the limit cycle is probed. As an exemplar application, we employ ForCEPSS to prepare a CEP study according to the Virtual Arrhythmia Risk Prediction protocol used for investigating the arrhythmogenic risk of developing infarct-related ventricular tachycardia (VT) in ischemic cardiomyopathy patients. We demonstrate that ForCEPSS enables a fully automated execution of all stages of this complex protocol. CONCLUSION ForCEPSS offers a novel comprehensive, standardized, and automated CEP simulation workflow. The high degree of automation accelerates the execution of CEP simulation studies, reduces errors, improves robustness, and makes CEP studies reproducible. Verification of simulation studies within the CEP modeling community is thus possible. As such, ForCEPSS makes an important contribution towards increasing transparency, standardization, and reproducibility of in silico CEP experiments.
Collapse
Affiliation(s)
- Matthias A F Gsell
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | | | | | - Karli Gillette
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - Anton J Prassl
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - Christoph M Augustin
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria
| | - Edward J Vigmond
- Liryc Cardiac Modeling Institute, Fondation Bordeaux University, Bordeaux, France; CNRS, Bordeaux INP, IMB, University of Bordeaux, Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria.
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Ernault AC, Al-Shama RFM, Li J, Devalla HD, de Groot JR, Coronel R, Vigmond E, Boukens BJ. Interpretation of field and LEAP potentials recorded from cardiomyocyte monolayers. Am J Physiol Heart Circ Physiol 2024; 326:H800-H811. [PMID: 38180452 DOI: 10.1152/ajpheart.00463.2023] [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: 07/27/2023] [Revised: 12/04/2023] [Accepted: 01/02/2024] [Indexed: 01/06/2024]
Abstract
Multielectrode arrays (MEAs) are the method of choice for electrophysiological characterization of cardiomyocyte monolayers. The field potentials recorded using an MEA are like extracellular electrograms recorded from the myocardium using conventional electrodes. Nevertheless, different criteria are used to interpret field potentials and extracellular electrograms, which hamper correct interpretation and translation to the patient. To validate the criteria for interpretation of field potentials, we used neonatal rat cardiomyocytes to generate monolayers. We recorded field potentials using an MEA and simultaneously recorded action potentials using sharp microelectrodes. In parallel, we recreated our experimental setting in silico and performed simulations. We show that the amplitude of the local RS complex of a field potential correlated with conduction velocity in silico but not in vitro. The peak time of the T wave in field potentials exhibited a strong correlation with APD90 while the steepest upslope correlated well with APD50. However, this relationship only holds when the T wave displayed a biphasic pattern. Next, we simulated local extracellular action potentials (LEAPs). The shape of the LEAP differed markedly from the shape of the local action potential, but the final duration of the LEAP coincided with APD90. Criteria for interpretation of extracellular electrograms should be applied to field potentials. This will provide a strong basis for the analysis of heterogeneity in conduction velocity and repolarization in cultured monolayers of cardiomyocytes. Finally, a LEAP is not a recording of the local action potential but is generated by intracellular current provided by neighboring cardiomyocytes and is superior to field potential duration in estimating APD90.NEW & NOTEWORTHY We present a physiological basis for the interpretation of multielectrode array-derived, extracellular, electrical signals.
Collapse
Affiliation(s)
- Auriane C Ernault
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Rushd F M Al-Shama
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Jiuru Li
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Harsha D Devalla
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Joris R de Groot
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Ruben Coronel
- Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Edward Vigmond
- IHU Liryc, Fondation Bordeaux Université, Bordeaux, France
- University of Bordeaux, Talence, France
| | - Bastiaan J Boukens
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Department of Physiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| |
Collapse
|
7
|
常 益, 董 明, 王 彬, 范 力. [Developments of ex vivo cardiac electrical mapping and intelligent labeling of atrial fibrillation substrates]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2024; 41:184-190. [PMID: 38403620 PMCID: PMC10894749 DOI: 10.7507/1001-5515.202211046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 10/13/2023] [Indexed: 02/27/2024]
Abstract
Cardiac three-dimensional electrophysiological labeling technology is the prerequisite and foundation of atrial fibrillation (AF) ablation surgery, and invasive labeling is the current clinical method, but there are many shortcomings such as large trauma, long procedure duration, and low success rate. In recent years, because of its non-invasive and convenient characteristics, ex vivo labeling has become a new direction for the development of electrophysiological labeling technology. With the rapid development of computer hardware and software as well as the accumulation of clinical database, the application of deep learning technology in electrocardiogram (ECG) data is becoming more extensive and has made great progress, which provides new ideas for the research of ex vivo cardiac mapping and intelligent labeling of AF substrates. This paper reviewed the research progress in the fields of ECG forward problem, ECG inverse problem, and the application of deep learning in AF labeling, discussed the problems of ex vivo intelligent labeling of AF substrates and the possible approaches to solve them, prospected the challenges and future directions for ex vivo cardiac electrophysiology labeling.
Collapse
Affiliation(s)
- 益 常
- 西安交通大学 电工材料电气绝缘国家重点实验室(西安 710049)State Key Library of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, P. R. China
| | - 明 董
- 西安交通大学 电工材料电气绝缘国家重点实验室(西安 710049)State Key Library of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, P. R. China
| | - 彬 王
- 西安交通大学 电工材料电气绝缘国家重点实验室(西安 710049)State Key Library of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, P. R. China
| | - 力宏 范
- 西安交通大学 电工材料电气绝缘国家重点实验室(西安 710049)State Key Library of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, P. R. China
| |
Collapse
|
8
|
Qian S, Ugurlu D, Fairweather E, Strocchi M, Toso LD, Deng Y, Plank G, Vigmond E, Razavi R, Young A, Lamata P, Bishop M, Niederer S. Developing Cardiac Digital Twins at Scale: Insights from Personalised Myocardial Conduction Velocity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.12.05.23299435. [PMID: 38106072 PMCID: PMC10723499 DOI: 10.1101/2023.12.05.23299435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology-constrained in-silico representations, enabling inference of multi-scale properties tied to these mechanisms. We constructed 3464 anatomically-accurate CDTs using cardiac magnetic resonance images from UK biobank and personalised their myocardial conduction velocities (CVs) from electrocardiograms (ECG), through an automated framework. We found well-known sex-specific differences in QRS duration were fully explained by myocardial anatomy, as CV remained consistent across sexes. Conversely, significant associations of CV with ageing and increased BMI suggest myocardial tissue remodelling. Novel associations were observed with left ventricular ejection fraction and mental-health phenotypes, through a phenome-wide association study, and CV was also linked with adverse clinical outcomes. Our study highlights the utility of population-based CDTs in assessing intersubject variability and uncovering strong links with mental health.
Collapse
|
9
|
Strocchi M, Wijesuriya N, Mehta V, de Vere F, Rinaldi CA, Niederer SA. Computational Modelling Enabling In Silico Trials for Cardiac Physiologic Pacing. J Cardiovasc Transl Res 2023:10.1007/s12265-023-10453-y. [PMID: 37870689 DOI: 10.1007/s12265-023-10453-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/10/2023] [Indexed: 10/24/2023]
Abstract
Conduction system pacing (CSP) has the potential to achieve physiological-paced activation by pacing the ventricular conduction system. Before CSP is adopted in standard clinical practice, large, randomised, and multi-centre trials are required to investigate CSP safety and efficacy compared to standard biventricular pacing (BVP). Furthermore, there are unanswered questions about pacing thresholds required to achieve optimal pacing delivery while preventing device battery draining, and about which patient groups are more likely to benefit from CSP rather than BVP. In silico studies have been increasingly used to investigate mechanisms underlying changes in cardiac function in response to pathologies and treatment. In the context of CSP, they have been used to improve our understanding of conduction system capture to optimise CSP delivery and battery life, and noninvasively compare different pacing methods on different patient groups. In this review, we discuss the in silico studies published to date investigating different aspects of CSP delivery.
Collapse
Affiliation(s)
- Marina Strocchi
- National Heart and Lung Institute, Imperial College London, 72 Du Cane Road, W12 0HS, London, UK.
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Nadeev Wijesuriya
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Vishal Mehta
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Felicity de Vere
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Christopher A Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Steven A Niederer
- National Heart and Lung Institute, Imperial College London, 72 Du Cane Road, W12 0HS, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- The Alan Turing Institute, London, UK
| |
Collapse
|
10
|
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: 0] [Impact Index Per Article: 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.
Collapse
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
| |
Collapse
|
11
|
Pilia N, Schuler S, Rees M, Moik G, Potyagaylo D, Dössel O, Loewe A. Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning. Artif Intell Med 2023; 143:102619. [PMID: 37673581 DOI: 10.1016/j.artmed.2023.102619] [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: 09/12/2022] [Revised: 06/18/2023] [Accepted: 06/24/2023] [Indexed: 09/08/2023]
Abstract
Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources outside the sinus node. Catheter ablation of these foci is a curative treatment in order to inactivate the abnormal triggering activity. However, the localization procedure is usually time-consuming and requires an invasive procedure in the catheter lab. To facilitate and expedite the treatment, we present two novel localization support techniques based on convolutional neural networks (CNNs) that address these clinical needs. In contrast to existing methods, our approaches were designed to be independent of the patient-specific geometry and directly applicable to surface ECG signals, while also delivering a binary transmural position. Moreover, one of the method's outputs can be interpreted as several ranked solutions. The CNNs were trained on a dataset containing only simulated data and evaluated both on simulated test data and clinical data. On a novel large and open simulated dataset, the median test error was below 3 mm. The median localization error on the unseen clinical data ranged from 32 mm to 41 mm without optimizing the pre-processing and CNN to the clinical data. Interpreting the output of one of the approaches as ranked solutions, the best median error of the top-3 solutions decreased to 20 mm on the clinical data. The transmural position was correctly detected in up to 82% of all clinical cases. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need for patient-specific geometrical information. Furthermore, providing multiple solutions can assist physicians in identifying the true activation source amongst more than one possible location. With further optimization to clinical data, these methods have high potential to accelerate clinical interventions, replace certain steps within these procedures and consequently reduce procedural risk and improve VT patient outcomes.
Collapse
Affiliation(s)
- Nicolas Pilia
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Maike Rees
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gerald Moik
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, 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
| |
Collapse
|
12
|
Gillette K, Gsell MAF, Nagel C, Bender J, Winkler B, Williams SE, Bär M, Schäffter T, Dössel O, Plank G, Loewe A. MedalCare-XL: 16,900 healthy and pathological synthetic 12 lead ECGs from electrophysiological simulations. Sci Data 2023; 10:531. [PMID: 37553349 PMCID: PMC10409805 DOI: 10.1038/s41597-023-02416-4] [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: 03/29/2023] [Accepted: 07/25/2023] [Indexed: 08/10/2023] Open
Abstract
Mechanistic cardiac electrophysiology models allow for personalized simulations of the electrical activity in the heart and the ensuing electrocardiogram (ECG) on the body surface. As such, synthetic signals possess known ground truth labels of the underlying disease and can be employed for validation of machine learning ECG analysis tools in addition to clinical signals. Recently, synthetic ECGs were used to enrich sparse clinical data or even replace them completely during training leading to improved performance on real-world clinical test data. We thus generated a novel synthetic database comprising a total of 16,900 12 lead ECGs based on electrophysiological simulations equally distributed into healthy control and 7 pathology classes. The pathological case of myocardial infraction had 6 sub-classes. A comparison of extracted features between the virtual cohort and a publicly available clinical ECG database demonstrated that the synthetic signals represent clinical ECGs for healthy and pathological subpopulations with high fidelity. The ECG database is split into training, validation, and test folds for development and objective assessment of novel machine learning algorithms.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - Claudia Nagel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Jule Bender
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Benjamin Winkler
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
| | - Steven E Williams
- King's College London, London, United Kingdom
- University of Edinburgh, Edinburgh, United Kingdom
| | - Markus Bär
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
| | - Tobias Schäffter
- Physikalisch-Technische Bundesanstalt, National Metrology Institute, Berlin, Germany
- King's College London, London, United Kingdom
- Biomedical Engineering, Technische Universität Berlin, Einstein Centre Digital Future, Berlin, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| |
Collapse
|
13
|
Buoso S, Joyce T, Schulthess N, Kozerke S. MRXCAT2.0: Synthesis of realistic numerical phantoms by combining left-ventricular shape learning, biophysical simulations and tissue texture generation. J Cardiovasc Magn Reson 2023; 25:25. [PMID: 37076840 PMCID: PMC10116689 DOI: 10.1186/s12968-023-00934-z] [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: 09/16/2022] [Accepted: 03/15/2023] [Indexed: 04/21/2023] Open
Abstract
BACKGROUND Standardised performance assessment of image acquisition, reconstruction and processing methods is limited by the absence of images paired with ground truth reference values. To this end, we propose MRXCAT2.0 to generate synthetic data, covering healthy and pathological function, using a biophysical model. We exemplify the approach by generating cardiovascular magnetic resonance (CMR) images of healthy, infarcted, dilated and hypertrophic left-ventricular (LV) function. METHOD In MRXCAT2.0, the XCAT torso phantom is coupled with a statistical shape model, describing population (patho)physiological variability, and a biophysical model, providing known and detailed functional ground truth of LV morphology and function. CMR balanced steady-state free precession images are generated using MRXCAT2.0 while realistic image appearance is ensured by assigning texturized tissue properties to the phantom labels. FINDING Paired CMR image and ground truth data of LV function were generated with a range of LV masses (85-140 g), ejection fractions (34-51%) and peak radial and circumferential strains (0.45 to 0.95 and - 0.18 to - 0.13, respectively). These ranges cover healthy and pathological cases, including infarction, dilated and hypertrophic cardiomyopathy. The generation of the anatomy takes a few seconds and it improves on current state-of-the-art models where the pathological representation is not explicitly addressed. For the full simulation framework, the biophysical models require approximately two hours, while image generation requires a few minutes per slice. CONCLUSION MRXCAT2.0 offers synthesis of realistic images embedding population-based anatomical and functional variability and associated ground truth parameters to facilitate a standardized assessment of CMR acquisition, reconstruction and processing methods.
Collapse
Affiliation(s)
- Stefano Buoso
- Institute for Biomedical Engineering, ETH Zurich and University Zurich, Zurich, Switzerland.
| | - Thomas Joyce
- Institute for Biomedical Engineering, ETH Zurich and University Zurich, Zurich, Switzerland
| | - Nico Schulthess
- Institute for Biomedical Engineering, ETH Zurich and University Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, ETH Zurich and University Zurich, Zurich, Switzerland
| |
Collapse
|
14
|
Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology. Comput Biol Med 2023; 156:106696. [PMID: 36870172 PMCID: PMC10040614 DOI: 10.1016/j.compbiomed.2023.106696] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/18/2023] [Accepted: 02/14/2023] [Indexed: 03/03/2023]
Abstract
Mechanoelectric feedback (MEF) in the heart operates through several mechanisms which serve to regulate cardiac function. Stretch activated channels (SACs) in the myocyte membrane open in response to cell lengthening, while tension generation depends on stretch, shortening velocity, and calcium concentration. How all of these mechanisms interact and their effect on cardiac output is still not fully understood. We sought to gauge the acute importance of the different MEF mechanisms on heart function. An electromechanical computer model of a dog heart was constructed, using a biventricular geometry of 500K tetrahedral elements. To describe cellular behavior, we used a detailed ionic model to which a SAC model and an active tension model, dependent on stretch and shortening velocity and with calcium sensitivity, were added. Ventricular inflow and outflow were connected to the CircAdapt model of cardiovascular circulation. Pressure-volume loops and activation times were used for model validation. Simulations showed that SACs did not affect acute mechanical response, although if their trigger level was decreased sufficiently, they could cause premature excitations. The stretch dependence of tension had a modest effect in reducing the maximum stretch, and stroke volume, while shortening velocity had a much bigger effect on both. MEF served to reduce the heterogeneity in stretch while increasing tension heterogeneity. In the context of left bundle branch block, a decreased SAC trigger level could restore cardiac output by reducing the maximal stretch when compared to cardiac resynchronization therapy. MEF is an important aspect of cardiac function and could potentially mitigate activation problems.
Collapse
|
15
|
Strocchi M, Gillette K, Neic A, Elliott MK, Wijesuriya N, Mehta V, Vigmond EJ, Plank G, Rinaldi CA, Niederer SA. Effect of scar and His-Purkinje and myocardium conduction on response to conduction system pacing. J Cardiovasc Electrophysiol 2023; 34:984-993. [PMID: 36738149 PMCID: PMC10089967 DOI: 10.1111/jce.15847] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/27/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Conduction system pacing (CSP), in the form of His bundle pacing (HBP) or left bundle branch pacing (LBBP), is emerging as a valuable cardiac resynchronization therapy (CRT) delivery method. However, patient selection and therapy personalization for CSP delivery remain poorly characterized. We aim to compare pacing-induced electrical synchrony during CRT, HBP, LBBP, HBP with left ventricular (LV) epicardial lead (His-optimized CRT [HOT-CRT]), and LBBP with LV epicardial lead (LBBP-optimized CRT [LOT-CRT]) in patients with different conduction disease presentations using computational modeling. METHODS We simulated ventricular activation on 24 four-chamber heart geometries, including His-Purkinje systems with proximal left bundle branch block (LBBB). We simulated septal scar, LV lateral wall scar, and mild and severe myocardium and LV His-Purkinje system conduction disease by decreasing the conduction velocity (CV) down to 70% and 35% of the healthy CV. Electrical synchrony was measured by the shortest interval to activate 90% of the ventricles (90% of biventricular activation time [BIVAT-90]). RESULTS Severe LV His-Purkinje conduction disease favored CRT (BIVAT-90: HBP 101.5 ± 7.8 ms vs. CRT 93.0 ± 8.9 ms, p < .05), with additional electrical synchrony induced by HOT-CRT (87.6 ± 6.7 ms, p < .05) and LOT-CRT (73.9 ± 7.6 ms, p < .05). Patients with slow myocardium CV benefit more from CSP compared to CRT (BIVAT-90: CRT 134.5 ± 24.1 ms; HBP 97.1 ± 9.9 ms, p < .01; LBBP: 101.5 ± 10.7 ms, p < .01). Septal but not lateral wall scar made CSP ineffective, while CRT was able to resynchronize the ventricles in the presence of septal scar (BIVAT-90: baseline 119.1 ± 10.8 ms vs. CRT 85.1 ± 14.9 ms, p < .01). CONCLUSION Severe LV His-Purkinje conduction disease attenuates the benefits of CSP, with additional improvements achieved with HOT-CRT and LOT-CRT. Septal but not lateral wall scars make CSP ineffective.
Collapse
Affiliation(s)
| | - Karli Gillette
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | | | - Mark K. Elliott
- King’s College London, London, UK
- Guy’s and St Thomas’ NHS Foundation trust, London, UK
| | - Nadeev Wijesuriya
- King’s College London, London, UK
- Guy’s and St Thomas’ NHS Foundation trust, London, UK
| | - Vishal Mehta
- King’s College London, London, UK
- Guy’s and St Thomas’ NHS Foundation trust, London, UK
| | - Edward J. Vigmond
- University of Bordeaux, CNRS, Bordeaux, Talence, France
- IHU Liryc, Bordeaux, Talence, France
| | - Gernot Plank
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | | | | |
Collapse
|
16
|
Ogiermann D, Perotti LE, Balzani D. A simple and efficient adaptive time stepping technique for low-order operator splitting schemes applied to cardiac electrophysiology. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2023; 39:e3670. [PMID: 36510350 DOI: 10.1002/cnm.3670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 10/25/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
We present a simple, yet efficient adaptive time stepping scheme for cardiac electrophysiology (EP) simulations based on standard operator splitting techniques. The general idea is to exploit the relation between the splitting error and the reaction's magnitude-found in a previous one-dimensional analytical study by Spiteri and Ziaratgahi-to construct the new time step controller for three-dimensional problems. Accordingly, we propose to control the time step length of the operator splitting scheme as a function of the reaction magnitude, in addition to the common approach of adapting the reaction time step. This conforms with observations in numerical experiments supporting the need for a significantly smaller time step length during depolarization than during repolarization. The proposed scheme is compared with classical proportional-integral-differential controllers using state-of-the-art error estimators, which are also presented in details as they have not been previously applied in the context of cardiac EP with operator splitting techniques. Benchmarks show that choosing the time step as a sigmoidal function of the reaction magnitude is highly efficient and full cardiac cycles can be computed with precision even in a realistic biventricular setup. The proposed scheme outperforms common adaptive time stepping techniques, while depending on fewer tuning parameters.
Collapse
Affiliation(s)
- Dennis Ogiermann
- Chair of Continuum Mechanics, Ruhr University Bochum, Bochum, Germany
| | - Luigi E Perotti
- Mechanical and Aerospace Engineering Department, University of Central Florida, Orlando, Florida, USA
| | - Daniel Balzani
- Chair of Continuum Mechanics, Ruhr University Bochum, Bochum, Germany
| |
Collapse
|
17
|
Campos FO, Shiferaw Y, Whitaker J, Plank G, Bishop MJ. Subthreshold delayed afterdepolarizations provide an important arrhythmogenic substrate in the border zone of infarcted hearts. Heart Rhythm 2023; 20:299-306. [PMID: 36343889 DOI: 10.1016/j.hrthm.2022.10.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 10/26/2022] [Accepted: 10/31/2022] [Indexed: 11/08/2022]
Affiliation(s)
- Fernando O Campos
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - Yohannes Shiferaw
- Department of Physics, University of California, Los Angeles, California
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gernot Plank
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Martin J Bishop
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| |
Collapse
|
18
|
Calibration of Cohorts of Virtual Patient Heart Models Using Bayesian History Matching. Ann Biomed Eng 2023; 51:241-252. [PMID: 36271218 PMCID: PMC9832095 DOI: 10.1007/s10439-022-03095-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 09/29/2022] [Indexed: 01/28/2023]
Abstract
Previous patient-specific model calibration techniques have treated each patient independently, making the methods expensive for large-scale clinical adoption. In this work, we show how we can reuse simulations to accelerate the patient-specific model calibration pipeline. To represent anatomy, we used a Statistical Shape Model and to represent function, we ran electrophysiological simulations. We study the use of 14 biomarkers to calibrate the model, training one Gaussian Process Emulator (GPE) per biomarker. To fit the models, we followed a Bayesian History Matching (BHM) strategy, wherein each iteration a region of the parameter space is ruled out if the emulation with that set of parameter values produces is "implausible". We found that without running any extra simulations we can find 87.41% of the non-implausible parameter combinations. Moreover, we showed how reducing the uncertainty of the measurements from 10 to 5% can reduce the final parameter space by 6 orders of magnitude. This innovation allows for a model fitting technique, therefore reducing the computational load of future biomedical studies.
Collapse
|
19
|
Strocchi M, Wijesuriya N, Elliott MK, Gillette K, Neic A, Mehta V, Vigmond EJ, Plank G, Rinaldi CA, Niederer SA. Leadless biventricular left bundle and endocardial lateral wall pacing versus left bundle only pacing in left bundle branch block patients. Front Physiol 2022; 13:1049214. [PMID: 36589454 PMCID: PMC9794756 DOI: 10.3389/fphys.2022.1049214] [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: 09/20/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
Biventricular endocardial (BIV-endo) pacing and left bundle pacing (LBP) are novel delivery methods for cardiac resynchronization therapy (CRT). Both pacing methods can be delivered through leadless pacing, to avoid risks associated with endocardial or transvenous leads. We used computational modelling to quantify synchrony induced by BIV-endo pacing and LBP through a leadless pacing system, and to investigate how the right-left ventricle (RV-LV) delay, RV lead location and type of left bundle capture affect response. We simulated ventricular activation on twenty-four four-chamber heart meshes inclusive of His-Purkinje networks with left bundle branch block (LBBB). Leadless biventricular (BIV) pacing was simulated by adding an RV apical stimulus and an LV lateral wall stimulus (BIV-endo lateral) or targeting the left bundle (BIV-LBP), with an RV-LV delay set to 5 ms. To test effect of prolonged RV-LV delays and RV pacing location, the RV-LV delay was increased to 35 ms and/or the RV stimulus was moved to the RV septum. BIV-endo lateral pacing was less sensitive to increased RV-LV delays, while RV septal pacing worsened response compared to RV apical pacing, especially for long RV-LV delays. To investigate how left bundle capture affects response, we computed 90% BIV activation times (BIVAT-90) during BIV-LBP with selective and non-selective capture, and left bundle branch area pacing (LBBAP), simulated by pacing 1 cm below the left bundle. Non-selective LBP was comparable to selective LBP. LBBAP was worse than selective LBP (BIVAT-90: 54.2 ± 5.7 ms vs. 62.7 ± 6.5, p < 0.01), but it still significantly reduced activation times from baseline. Finally, we compared leadless LBP with RV pacing against optimal LBP delivery through a standard lead system by simulating BIV-LBP and selective LBP alone with and without optimized atrioventricular delay (AVD). Although LBP alone with optimized AVD was better than BIV-LBP, when AVD optimization was not possible BIV-LBP outperformed LBP alone, because the RV pacing stimulus shortened RV activation (BIVAT-90: 54.2 ± 5.7 ms vs. 66.9 ± 5.1 ms, p < 0.01). BIV-endo lateral pacing or LBP delivered through a leadless system could potentially become an alternative to standard CRT. RV-LV delay, RV lead location and type of left bundle capture affect leadless pacing efficacy and should be considered in future trial designs.
Collapse
Affiliation(s)
- Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Nadeev Wijesuriya
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Mark K. Elliott
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Karli Gillette
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | | | - Vishal Mehta
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Edward J. Vigmond
- University of Bordeaux, CNRS, Bordeaux, France
- IHU Liryc, Bordeaux, France
| | - Gernot Plank
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Christopher A. Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Steven A. Niederer
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| |
Collapse
|
20
|
Galappaththige S, Gray RA, Costa CM, Niederer S, Pathmanathan P. Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar. PLoS Comput Biol 2022; 18:e1010541. [PMID: 36215228 PMCID: PMC9550052 DOI: 10.1371/journal.pcbi.1010541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 09/02/2022] [Indexed: 11/07/2022] Open
Abstract
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. However, such efforts have generally been motivated by models of medical devices or generic patient models; how best to evaluate the credibility of PSMs has largely been unexplored. The aim of this paper is to understand and demonstrate the credibility assessment process for PSMs using patient-specific cardiac electrophysiological (EP) modeling as an exemplar. We first review approaches used to generate cardiac PSMs and consider how verification, validation, and uncertainty quantification (VVUQ) apply to cardiac PSMs. Next, we execute two simulation studies using a publicly available virtual cohort of 24 patient-specific ventricular models, the first a multi-patient verification study, the second investigating the impact of uncertainty in personalized and non-personalized inputs in a virtual cohort. We then use the findings from our analyses to identify how important characteristics of PSMs can be considered when assessing credibility with the approach of the ASME V&V40 Standard, accounting for PSM concepts such as inter- and intra-user variability, multi-patient and “every-patient” error estimation, uncertainty quantification in personalized vs non-personalized inputs, clinical validation, and others. The results of this paper will be useful to developers of cardiac and other medical image based PSMs, when assessing PSM credibility. Patient-specific models are computational models that have been personalized using data from a patient. After decades of research, recent computational, data science and healthcare advances have opened the door to the fulfilment of the enormous potential of such models, from truly personalized medicine to efficient and cost-effective testing of new medical products. However, reliability (credibility) of patient-specific models is key to their success, and there are currently no general guidelines for evaluating credibility of patient-specific models. Here, we consider how frameworks and model evaluation activities that have been developed for generic (not patient-specific) computational models, can be extended to patient specific models. We achieve this through a detailed analysis of the activities required to evaluate cardiac electrophysiological models, chosen as an exemplar field due to its maturity and the complexity of such models. This is the first paper on the topic of reliability of patient-specific models and will help pave the way to reliable and trusted patient-specific modeling across healthcare applications.
Collapse
Affiliation(s)
- Suran Galappaththige
- Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland, United States of America
| | - Richard A. Gray
- Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland, United States of America
| | - Caroline Mendonca Costa
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Steven Niederer
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Pras Pathmanathan
- Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland, United States of America
- * E-mail:
| |
Collapse
|
21
|
Gillette K, Gsell MAF, Strocchi M, Grandits T, Neic A, Manninger M, Scherr D, Roney CH, Prassl AJ, Augustin CM, Vigmond EJ, Plank G. A personalized real-time virtual model of whole heart electrophysiology. Front Physiol 2022; 13:907190. [PMID: 36213235 PMCID: PMC9539798 DOI: 10.3389/fphys.2022.907190] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/15/2022] [Indexed: 01/12/2023] Open
Abstract
Computer models capable of representing the intrinsic personal electrophysiology (EP) of the heart in silico are termed virtual heart technologies. When anatomy and EP are tailored to individual patients within the model, such technologies are promising clinical and industrial tools. Regardless of their vast potential, few virtual technologies simulating the entire organ-scale EP of all four-chambers of the heart have been reported and widespread clinical use is limited due to high computational costs and difficulty in validation. We thus report on the development of a novel virtual technology representing the electrophysiology of all four-chambers of the heart aiming to overcome these limitations. In our previous work, a model of ventricular EP embedded in a torso was constructed from clinical magnetic resonance image (MRI) data and personalized according to the measured 12 lead electrocardiogram (ECG) of a single subject under normal sinus rhythm. This model is then expanded upon to include whole heart EP and a detailed representation of the His-Purkinje system (HPS). To test the capacities of the personalized virtual heart technology to replicate standard clinical morphological ECG features under such conditions, bundle branch blocks within both the right and the left ventricles under two different conduction velocity settings are modeled alongside sinus rhythm. To ensure clinical viability, model generation was completely automated and simulations were performed using an efficient real-time cardiac EP simulator. Close correspondence between the measured and simulated 12 lead ECG was observed under normal sinus conditions and all simulated bundle branch blocks manifested relevant clinical morphological features.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Thomas Grandits
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Martin Manninger
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Daniel Scherr
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | | | - Anton J. Prassl
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | | | - Gernot Plank
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- *Correspondence: Gernot Plank,
| |
Collapse
|
22
|
Strocchi M, Gillette K, Neic A, Elliott MK, Wijesuriya N, Mehta V, Vigmond EJ, Plank G, Rinaldi CA, Niederer SA. Comparison between conduction system pacing and cardiac resynchronization therapy in right bundle branch block patients. Front Physiol 2022; 13:1011566. [PMID: 36213223 PMCID: PMC9532840 DOI: 10.3389/fphys.2022.1011566] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 08/29/2022] [Indexed: 11/20/2022] Open
Abstract
A significant number of right bundle branch block (RBBB) patients receive cardiac resynchronization therapy (CRT), despite lack of evidence for benefit in this patient group. His bundle (HBP) and left bundle pacing (LBP) are novel CRT delivery methods, but their effect on RBBB remains understudied. We aim to compare pacing-induced electrical synchrony during conventional CRT, HBP, and LBP in RBBB patients with different conduction disturbances, and to investigate whether alternative ways of delivering LBP improve response to pacing. We simulated ventricular activation on twenty-four four-chamber heart geometries each including a His-Purkinje system with proximal right bundle branch block (RBBB). We simulated RBBB combined with left anterior and posterior fascicular blocks (LAFB and LPFB). Additionally, RBBB was simulated in the presence of slow conduction velocity (CV) in the myocardium, left ventricular (LV) or right ventricular (RV) His-Purkinje system, and whole His-Purkinje system. Electrical synchrony was measured by the shortest interval to activate 90% of the ventricles (BIVAT-90). Compared to baseline, HBP significantly improved activation times for RBBB alone (BIVAT-90: 66.9 ± 5.5 ms vs. 42.6 ± 3.8 ms, p < 0.01), with LAFB (69.5 ± 5.0 ms vs. 58.1 ± 6.2 ms, p < 0.01), with LPFB (81.8 ± 6.6 ms vs. 62.9 ± 6.2 ms, p < 0.01), with slow myocardial CV (119.4 ± 11.4 ms vs. 97.2 ± 10.0 ms, p < 0.01) or slow CV in the whole His-Purkinje system (102.3 ± 7.0 ms vs. 75.5 ± 5.2 ms, p < 0.01). LBP was only effective in RBBB cases if combined with anodal capture of the RV septum myocardium (BIVAT-90: 66.9 ± 5.5 ms vs. 48.2 ± 5.2 ms, p < 0.01). CRT significantly reduced activation times in RBBB in the presence of severely slow RV His-Purkinje CV (95.1 ± 7.9 ms vs. 84.3 ± 9.3 ms, p < 0.01) and LPFB (81.8 ± 6.6 ms vs. CRT: 72.9 ± 8.6 ms, p < 0.01). Both CRT and HBP were ineffective with severely slow CV in the LV His-Purkinje system. HBP is effective in RBBB patients with otherwise healthy myocardium and Purkinje system, while CRT and LBP are ineffective. Response to LBP improves when LBP is combined with RV septum anodal capture. CRT is better than HBP only in patients with severely slow CV in the RV His-Purkinje system, while CV slowing of the whole His-Purkinje system and the myocardium favor HBP over CRT.
Collapse
Affiliation(s)
- Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Karli Gillette
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | | | - Mark K. Elliott
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Nadeev Wijesuriya
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Vishal Mehta
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | | | - Gernot Plank
- BioTechMed-Graz, Graz, Austria
- Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Christopher A. Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Steven A. Niederer
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| |
Collapse
|
23
|
Vergara C, Stella S, Maines M, Africa PC, Catanzariti D, Demattè C, Centonze M, Nobile F, Quarteroni A, Del Greco M. Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region. Med Biol Eng Comput 2022; 60:2307-2319. [PMID: 35729476 PMCID: PMC9293833 DOI: 10.1007/s11517-022-02610-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 06/07/2022] [Indexed: 01/18/2023]
Abstract
This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. We considered the Eikonal-diffusion equation and to recover the electrical activation maps in the myocardium. The model was calibrated by using activation times acquired in the coronary sinus (CS) branches or in the CS solely with an electroanatomic mapping system (EAMS) during cardiac resynchronization therapy (CRT). We applied our computational tool to ten patients founding an excellent accordance with EAMS measures; in particular, the error for LEAS location was less than 4 mm. We also calibrated our model using only information in the CS, still obtaining an excellent agreement with the measured LEAS. The proposed tool was able to accurately reproduce the electrical activation maps and in particular LEAS location in the CS branches, with an almost real-time computational effort, regardless of the presence of myocardial fibrosis, even when information only at CS was used to calibrate the model. This could be useful in the clinical practice since LEAS is often used as a target site for the left lead placement during CRT.
Collapse
Affiliation(s)
- Christian Vergara
- LABS, Dipartimento Di Chimica, Materiali E Ingegneria Chimica “Giulio Natta”, Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20233 Milan, Italy
| | - Simone Stella
- Dipartimento Di Matematica, MOX, Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20233 Milan, Italy
| | - Massimiliano Maines
- Department of Cardiology, S. Maria del Carmine Hospital, corso Verona 4, 38068 Rovereto, TN Italy
| | - Pasquale Claudio Africa
- Dipartimento Di Matematica, MOX, Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20233 Milan, Italy
| | - Domenico Catanzariti
- Department of Cardiology, S. Maria del Carmine Hospital, corso Verona 4, 38068 Rovereto, TN Italy
| | - Cristina Demattè
- Department of Cardiology, S. Maria del Carmine Hospital, corso Verona 4, 38068 Rovereto, TN Italy
| | - Maurizio Centonze
- U.O. Di Radiologia Di Borgo-Pergine, Borgo Valsugana Hospital, viale Vicenza 9, 38051 Borgo Valsugana, (TN) Italy
| | - Fabio Nobile
- Institute of Mathematics, CSQI, École Polytechnique Fédérale de Lausanne, Route Cantonale, 1015 Lausanne, Switzerland
| | - Alfio Quarteroni
- Dipartimento Di Matematica, MOX, Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20233 Milan, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Maurizio Del Greco
- Department of Cardiology, S. Maria del Carmine Hospital, corso Verona 4, 38068 Rovereto, TN Italy
| |
Collapse
|
24
|
Caforio F, Augustin CM, Alastruey J, Gsell MAF, Plank G. A coupling strategy for a first 3D-1D model of the cardiovascular system to study the effects of pulse wave propagation on cardiac function. COMPUTATIONAL MECHANICS 2022; 70:703-722. [PMID: 36124206 PMCID: PMC9477941 DOI: 10.1007/s00466-022-02206-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
A key factor governing the mechanical performance of the heart is the bidirectional coupling with the vascular system, where alterations in vascular properties modulate the pulsatile load imposed on the heart. Current models of cardiac electromechanics (EM) use simplified 0D representations of the vascular system when coupling to anatomically accurate 3D EM models is considered. However, these ignore important effects related to pulse wave transmission. Accounting for these effects requires 1D models, but a 3D-1D coupling remains challenging. In this work, we propose a novel, stable strategy to couple a 3D cardiac EM model to a 1D model of blood flow in the largest systemic arteries. For the first time, a personalised coupled 3D-1D model of left ventricle and arterial system is built and used in numerical benchmarks to demonstrate robustness and accuracy of our scheme over a range of time steps. Validation of the coupled model is performed by investigating the coupled system's physiological response to variations in the arterial system affecting pulse wave propagation, comprising aortic stiffening, aortic stenosis or bifurcations causing wave reflections. Our first 3D-1D coupled model is shown to be efficient and robust, with negligible additional computational costs compared to 3D-0D models. We further demonstrate that the calibrated 3D-1D model produces simulated data that match with clinical data under baseline conditions, and that known physiological responses to alterations in vascular resistance and stiffness are correctly replicated. Thus, using our coupled 3D-1D model will be beneficial in modelling studies investigating wave propagation phenomena.
Collapse
Affiliation(s)
- Federica Caforio
- Institute of Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Jordi Alastruey
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, King’s Health Partners, St. Thomas’ Hospital, London, SE1 7EH UK
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| |
Collapse
|
25
|
Farquhar ME, Burrage K, Weber Dos Santos R, Bueno-Orovio A, Lawson BA. Graph-based homogenisation for modelling cardiac fibrosis. JOURNAL OF COMPUTATIONAL PHYSICS 2022; 459:None. [PMID: 35959500 PMCID: PMC9352598 DOI: 10.1016/j.jcp.2022.111126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 02/15/2022] [Accepted: 03/02/2022] [Indexed: 05/02/2023]
Abstract
Fibrosis, the excess of extracellular matrix, can affect, and even block, propagation of action potential in cardiac tissue. This can result in deleterious effects on heart function, but the nature and severity of these effects depend strongly on the localisation of fibrosis and its by-products in cardiac tissue, such as collagen scar formation. Computer simulation is an important means of understanding the complex effects of fibrosis on activation patterns in the heart, but concerns of computational cost place restrictions on the spatial resolution of these simulations. In this work, we present a novel numerical homogenisation technique that uses both Eikonal and graph approaches to allow fine-scale heterogeneities in conductivity to be incorporated into a coarser mesh. Homogenisation achieves this by deriving effective conductivity tensors so that a coarser mesh can then be used for numerical simulation. By taking a graph-based approach, our homogenisation technique functions naturally on irregular grids and does not rely upon any assumptions of periodicity, even implicitly. We present results of action potential propagation through fibrotic tissue in two dimensions that show the graph-based homogenisation technique is an accurate and effective way to capture fine-scale domain information on coarser meshes in the context of sharp-fronted travelling waves of activation. As test problems, we consider excitation propagation in tissue with diffuse fibrosis and through a tunnel-like structure designed to test homogenisation, interaction of an excitation wave with a scar region, and functional re-entry.
Collapse
Affiliation(s)
- Megan E. Farquhar
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Kevin Burrage
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
- Department of Computer Science, Oxford University, Oxford, United Kingdom
| | - Rodrigo Weber Dos Santos
- Department of Computer Science and Program on Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
| | | | - Brodie A.J. Lawson
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
- Centre for Data Science, Queensland University of Technology, Brisbane, Australia
| |
Collapse
|
26
|
Sánchez J, Loewe A. A Review of Healthy and Fibrotic Myocardium Microstructure Modeling and Corresponding Intracardiac Electrograms. Front Physiol 2022; 13:908069. [PMID: 35620600 PMCID: PMC9127661 DOI: 10.3389/fphys.2022.908069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 04/21/2022] [Indexed: 11/13/2022] Open
Abstract
Computational simulations of cardiac electrophysiology provide detailed information on the depolarization phenomena at different spatial and temporal scales. With the development of new hardware and software, in silico experiments have gained more importance in cardiac electrophysiology research. For plane waves in healthy tissue, in vivo and in silico electrograms at the surface of the tissue demonstrate symmetric morphology and high peak-to-peak amplitude. Simulations provided insight into the factors that alter the morphology and amplitude of the electrograms. The situation is more complex in remodeled tissue with fibrotic infiltrations. Clinically, different changes including fractionation of the signal, extended duration and reduced amplitude have been described. In silico, numerous approaches have been proposed to represent the pathological changes on different spatial and functional scales. Different modeling approaches can reproduce distinct subsets of the clinically observed electrogram phenomena. This review provides an overview of how different modeling approaches to incorporate fibrotic and structural remodeling affect the electrogram and highlights open challenges to be addressed in future research.
Collapse
|
27
|
Karabelas E, Gsell MA, Haase G, Plank G, Augustin CM. An accurate, robust, and efficient finite element framework with applications to anisotropic, nearly and fully incompressible elasticity. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2022; 394:114887. [PMID: 35432634 PMCID: PMC7612621 DOI: 10.1016/j.cma.2022.114887] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative split of the deformation gradient into a volumetric and an isochoric part is a very common approach. However, the finite element analysis of such problems often suffers from severe volumetric locking effects and numerical instabilities. In this paper, we present novel methods to overcome volumetric locking phenomena for using stabilized P1-P1 elements. We introduce different stabilization techniques and demonstrate the high robustness and computational efficiency of the chosen methods. In two benchmark problems from the literature as well as an advanced application to cardiac electromechanics, we compare the approach to standard linear elements and show the accuracy and versatility of the methods to simulate anisotropic, nearly and fully incompressible materials. We demonstrate the potential of this numerical framework to accelerate accurate simulations of biological tissues to the extent of enabling patient-specific parameterization studies, where numerous forward simulations are required.
Collapse
Affiliation(s)
- Elias Karabelas
- Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Gundolf Haase
- Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Correspondence to: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstrasse 6/IV, Graz 8010, Austria. (C.M. Augustin)
| |
Collapse
|
28
|
Anderson RD, Rodriguez Padilla J, Joens C, Masse S, Bhaskaran A, Magtibay K, Niri A, Asta J, Lai P, Azam MA, Vigmond E, Nanthakumar K. On the Electrophysiology and Mapping of Intramural Arrhythmic Focus. Circ Arrhythm Electrophysiol 2022; 15:e010384. [PMID: 35323037 DOI: 10.1161/circep.121.010384] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Conventional mapping of focal ventricular arrhythmias relies on unipolar electrogram characteristics and early local activation times. Deep intramural foci are common and associated with high recurrence rates following catheter-based radiofrequency ablation. We assessed the accuracy of unipolar morphological patterns and mapping surface indices to predict the site and depth of ventricular arrhythmogenic focal sources. METHODS An experimental beating-heart model used Langendorff-perfused, healthy swine hearts. A custom 56-pole electrode array catheter was positioned on the left ventricle. A plunge needle was placed perpendicular in the center of the grid to simulate arrhythmic foci at variable depths. Unipolar electrograms and local activation times were generated. Simulation models from 2 human hearts were also included with grids positioned simultaneously on the endocardium-epicardium from multiple left ventricular, septal, and outflow tract sites. RESULTS A unipolar Q or QS complex lacks specificity for superficial arrhythmic foci, as this morphology pattern occupies a large surface area and is the predominant pattern as intramural depth increases without developing a R component. There is progressive displacement from the arrhythmic focus to the surface exit as intramural focus depth increases. A shorter total activation time over the overlying electrode array, larger surface area within initial 20 ms activation, and a dual surface breakout pattern all indicate a deep focus. CONCLUSIONS Displacement from the focal intramural origin to the exit site on the mapping surface could lead to erroneous lesion delivery strategies. Traditional unipolar electrogram features lack specificity to predict the intramural arrhythmic source; however, novel endocardial-epicardial mapping surface indices can be used to determine the depth of arrhythmic foci.
Collapse
Affiliation(s)
- Robert D Anderson
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | | | - Christian Joens
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Stephane Masse
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Abhishek Bhaskaran
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Karl Magtibay
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Ahmed Niri
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - John Asta
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Patrick Lai
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Mohammed Ali Azam
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| | - Edward Vigmond
- IHU Liryc, Hôpital Xavier Arnozan, Pessac Cedex, France (J.R.P., E.V.)
| | - Kumaraswamy Nanthakumar
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, Ontario, Canada (R.D.A., C.J., S.M., A.B., K.M., A.N., J.A., P.L., M.A.A., K.N.)
| |
Collapse
|
29
|
An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility. MATHEMATICS 2022. [DOI: 10.3390/math10081293] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios.
Collapse
|
30
|
Rodriguez Padilla J, Petras A, Magat J, Bayer J, Bihan-Poudec Y, El-Hamrani D, Ramlugun G, Neic A, Augustin C, Vaillant F, Constantin M, Benoist D, Pourtau L, Dubes V, Rogier J, Labrousse L, Bernus O, Quesson B, Haissaguerre M, Gsell M, Plank G, Ozenne V, Vigmond E. Impact of Intraventricular Septal Fiber Orientation on Cardiac Electromechanical Function. Am J Physiol Heart Circ Physiol 2022; 322:H936-H952. [PMID: 35302879 PMCID: PMC9109800 DOI: 10.1152/ajpheart.00050.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Cardiac fiber direction is an important factor determining the propagation of electrical activity, as well as the development of mechanical force. In this article, we imaged the ventricles of several species with special attention to the intraventricular septum to determine the functional consequences of septal fiber organization. First, we identified a dual-layer organization of the fiber orientation in the intraventricular septum of ex vivo sheep hearts using diffusion tensor imaging at high field MRI. To expand the scope of the results, we investigated the presence of a similar fiber organization in five mammalian species (rat, canine, pig, sheep, and human) and highlighted the continuity of the layer with the moderator band in large mammalian species. We implemented the measured septal fiber fields in three-dimensional electromechanical computer models to assess the impact of the fiber orientation. The downward fibers produced a diamond activation pattern superficially in the right ventricle. Electromechanically, there was very little change in pressure volume loops although the stress distribution was altered. In conclusion, we clarified that the right ventricular septum has a downwardly directed superficial layer in larger mammalian species, which can have modest effects on stress distribution. NEW & NOTEWORTHY A dual-layer organization of the fiber orientation in the intraventricular septum was identified in ex vivo hearts of large mammals. The RV septum has a downwardly directed superficial layer that is continuous with the moderator band. Electrically, it produced a diamond activation pattern. Electromechanically, little change in pressure volume loops were noticed but stress distribution was altered. Fiber distribution derived from diffusion tensor imaging should be considered for an accurate strain and stress analysis.
Collapse
Affiliation(s)
| | - Argyrios Petras
- Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria
| | - Julie Magat
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Jason Bayer
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, IMB, UMR 5251, Talence, France
| | - Yann Bihan-Poudec
- Centre de Neuroscience Cognitive, CNRS UMR 5229, Université Claude Bernard Lyon I, France
| | - Dounia El-Hamrani
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Girish Ramlugun
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Aurel Neic
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Christoph Augustin
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Fanny Vaillant
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Marion Constantin
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - David Benoist
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Line Pourtau
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Virginie Dubes
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | | | | | - Olivier Bernus
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | - Bruno Quesson
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France.,INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, Bordeaux, France
| | | | - Matthias Gsell
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Valéry Ozenne
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Edward Vigmond
- Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, IMB, UMR 5251, Talence, France
| |
Collapse
|
31
|
Jung A, Gsell MAF, Augustin CM, Plank G. An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics—A Multi-Fidelity Approach for Personalising Active Mechanics. MATHEMATICS 2022; 10:823. [PMID: 35295404 PMCID: PMC7612499 DOI: 10.3390/math10050823] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
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 a novel, fully automated, and efficient approach for personalising biophysically detailed active mechanics models using a two-step multi-fidelity solution. In the first step, active mechanical behaviour in a given 3D EM model is represented by a purely phenomenological, low-fidelity model, which is personalised at the organ scale by calibration to clinical cavity pressure data. Then, in the second step, median traces of nodal cellular active stress, intracellular calcium concentration, and fibre stretch are generated and utilised to personalise the desired high-fidelity model at the cellular scale using a 0D model of cardiac EM. Our novel approach was tested on a cohort of seven human left ventricular (LV) EM models, created from patients treated for aortic coarctation (CoA). Goodness of fit, computational cost, and robustness of the algorithm against uncertainty in the clinical data and variations of initial guesses were evaluated. We demonstrate that our multi-fidelity approach facilitates the personalisation of a biophysically detailed active stress model within only a few (2 to 4) expensive 3D organ-scale simulations—a computational effort compatible with clinical model applications.
Collapse
Affiliation(s)
- Alexander Jung
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging—Division of Biophysics, Medical University Graz, 8010 Graz, Austria
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging—Division of Biophysics, Medical University Graz, 8010 Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, 8010 Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging—Division of Biophysics, Medical University Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
- Correspondence:
| | - Gernot Plank
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging—Division of Biophysics, Medical University Graz, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
| |
Collapse
|
32
|
Mendonca Costa C, Gemmell P, Elliott MK, Whitaker J, Campos FO, Strocchi M, Neic A, Gillette K, Vigmond E, Plank G, Razavi R, O'Neill M, Rinaldi CA, Bishop MJ. Determining anatomical and electrophysiological detail requirements for computational ventricular models of porcine myocardial infarction. Comput Biol Med 2022; 141:105061. [PMID: 34915331 PMCID: PMC8819160 DOI: 10.1016/j.compbiomed.2021.105061] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/04/2021] [Accepted: 11/20/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Computational models of the heart built from cardiac MRI and electrophysiology (EP) data have shown promise for predicting the risk of and ablation targets for myocardial infarction (MI) related ventricular tachycardia (VT), as well as to predict paced activation sequences in heart failure patients. However, most recent studies have relied on low resolution imaging data and little or no EP personalisation, which may affect the accuracy of model-based predictions. OBJECTIVE To investigate the impact of model anatomy, MI scar morphology, and EP personalisation strategies on paced activation sequences and VT inducibility to determine the level of detail required to make accurate model-based predictions. METHODS Imaging and EP data were acquired from a cohort of six pigs with experimentally induced MI. Computational models of ventricular anatomy, incorporating MI scar, were constructed including bi-ventricular or left ventricular (LV) only anatomy, and MI scar morphology with varying detail. Tissue conductivities and action potential duration (APD) were fitted to 12-lead ECG data using the QRS duration and the QT interval, respectively, in addition to corresponding literature parameters. Paced activation sequences and VT induction were simulated. Simulated paced activation and VT inducibility were compared between models and against experimental data. RESULTS Simulations predict that the level of model anatomical detail has little effect on simulated paced activation, with all model predictions comparing closely with invasive EP measurements. However, detailed scar morphology from high-resolution images, bi-ventricular anatomy, and personalized tissue conductivities are required to predict experimental VT outcome. CONCLUSION This study provides clear guidance for model generation based on clinical data. While a representing high level of anatomical and scar detail will require high-resolution image acquisition, EP personalisation based on 12-lead ECG can be readily incorporated into modelling pipelines, as such data is widely available.
Collapse
Affiliation(s)
- Caroline Mendonca Costa
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK.
| | - Philip Gemmell
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | - Mark K Elliott
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | - John Whitaker
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | - Fernando O Campos
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | - Marina Strocchi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | | | - Karli Gillette
- Gottfried Schatz Research Center, Biophysics, Medical University of Graz, Austria; Medical University of Graz, Austria and BioTechMed, Graz, Austria
| | - Edward Vigmond
- Institut de Rythmologie et de modélisation cardiaque (LIRYC), University of Bordeaux, France
| | - Gernot Plank
- Medical University of Graz, Austria and BioTechMed, Graz, Austria
| | - Reza Razavi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| | - Mark O'Neill
- Department of Cardiology, Guy's and St Thomas' Hospital, London, UK
| | - Christopher A Rinaldi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Department of Cardiology, Guy's and St Thomas' Hospital, London, UK
| | - Martin J Bishop
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, UK
| |
Collapse
|
33
|
Rodero C, Strocchi M, Lee AWC, Rinaldi CA, Vigmond EJ, Plank G, Lamata P, Niederer SA. Impact of anatomical reverse remodelling in the design of optimal quadripolar pacing leads: A computational study. Comput Biol Med 2022; 140:105073. [PMID: 34852973 PMCID: PMC8752960 DOI: 10.1016/j.compbiomed.2021.105073] [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: 10/06/2021] [Revised: 11/23/2021] [Accepted: 11/23/2021] [Indexed: 11/28/2022]
Abstract
Lead position is an important factor in determining response to Cardiac Resynchronization Therapy (CRT) in dyssynchronous heart failure (HF) patients. Multipoint pacing (MPP) enables pacing from multiple electrodes within the same lead, improving the potential outcome for patients. Virtual quadripolar lead designs were evaluated by simulating pacing from all combinations of 1 and 2 electrodes along the lead in each virtual patient from cohorts of HF (n = 24) and simulated reverse remodelled (RR, n = 20) patients. Electrical synchrony was assessed by the time 90% of the ventricular myocardium is activated (AT090). Optimal 1 and 2 electrode pacing configurations for AT090 were combined to identify the 4-electrode lead design that maximised benefits across all patients. LV pacing in the HF cohort in all possible single and double electrode locations reduced AT090 by 14.48 ± 5.01 ms (11.92 ± 3.51%). The major determinant of reduction in activation time was patient anatomy. Pacing with a single optimal lead design reduced AT090 more in the HF cohort than the RR cohort (12.68 ± 3.29% vs 10.81 ± 2.34%). Pacing with a single combined HF and RR population-optimised lead design achieves electrical resynchronization with near equivalence to personalised lead designs both in HF and RR anatomies. These findings suggest that although lead configurations have to be tailored to each patient, a single optimal lead design is sufficient to obtain near-optimal results across most patients. This study shows the potential of virtual clinical trials as tools to compare existing and explore new lead designs.
Collapse
Affiliation(s)
- Cristobal Rodero
- Cardiac Electro-Mechanics Research Group, Biomedical Engineering Department, King ́s College London, London, United Kingdom.
| | - Marina Strocchi
- Cardiac Electro-Mechanics Research Group, Biomedical Engineering Department, King ́s College London, London, United Kingdom
| | - Angela W C Lee
- Cardiac Electro-Mechanics Research Group, Biomedical Engineering Department, King ́s College London, London, United Kingdom
| | - Christopher A Rinaldi
- King's College London, Interdisciplinary Medical Imaging Group, London, United Kingdom
| | - Edward J Vigmond
- Institute of Electrophysiology and Heart Modeling, Foundation Bordeaux University, Bordeaux, France; Bordeaux Institute of Mathematics, UMR-5251, University of Bordeaux, Bordeaux, France
| | - Gernot Plank
- Medical University of Graz, Gottfried Schatz Research Center - Biophysics, Graz, Austria
| | - Pablo Lamata
- Cardiac Electro-Mechanics Research Group, Biomedical Engineering Department, King ́s College London, London, United Kingdom
| | - Steven A Niederer
- Cardiac Electro-Mechanics Research Group, Biomedical Engineering Department, King ́s College London, London, United Kingdom
| |
Collapse
|
34
|
Roney CH, Sillett C, Whitaker J, Lemus JAS, Sim I, Kotadia I, O'Neill M, Williams SE, Niederer SA. Applications of multimodality imaging for left atrial catheter ablation. Eur Heart J Cardiovasc Imaging 2021; 23:31-41. [PMID: 34747450 PMCID: PMC8685603 DOI: 10.1093/ehjci/jeab205] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 11/13/2022] Open
Abstract
Atrial arrhythmias, including atrial fibrillation and atrial flutter, may be treated through catheter ablation. The process of atrial arrhythmia catheter ablation, which includes patient selection, pre-procedural planning, intra-procedural guidance, and post-procedural assessment, is typically characterized by the use of several imaging modalities to sequentially inform key clinical decisions. Increasingly, advanced imaging modalities are processed via specialized image analysis techniques and combined with intra-procedural electrical measurements to inform treatment approaches. Here, we review the use of multimodality imaging for left atrial ablation procedures. The article first outlines how imaging modalities are routinely used in the peri-ablation period. We then describe how advanced imaging techniques may inform patient selection for ablation and ablation targets themselves. Ongoing research directions for improving catheter ablation outcomes by using imaging combined with advanced analyses for personalization of ablation targets are discussed, together with approaches for their integration in the standard clinical environment. Finally, we describe future research areas with the potential to improve catheter ablation outcomes.
Collapse
Affiliation(s)
- Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Charles Sillett
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | | | - Iain Sim
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Irum Kotadia
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Mark O'Neill
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | - Steven E Williams
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
- Centre for Cardiovascular Science, The University of Edinburgh, Scotland, UK
| | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| |
Collapse
|
35
|
Gillette K, Gsell MAF, Bouyssier J, Prassl AJ, Neic A, Vigmond EJ, Plank G. Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology. Ann Biomed Eng 2021; 49:3143-3153. [PMID: 34431016 PMCID: PMC8671274 DOI: 10.1007/s10439-021-02825-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/26/2021] [Indexed: 11/28/2022]
Abstract
Personalized 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 between model predictions and clinical data such as the 12 lead electrocardiogram (ECG). We thus develop an automated two stage approach for HPS personalization. A fascicular-based model is first introduced that modulates the endocardial Purkinje network. Only emergent features of sites of earliest activation within the ventricular myocardium and a fast-conducting sub-endocardial layer are accounted for. It is then replaced by a topologically realistic Purkinje-based representation of the HPS. Feasibility of the approach is demonstrated. Equivalence between both HPS model representations is investigated by comparing activation patterns and 12 lead ECGs under both sinus rhythm and right-ventricular apical pacing. Predominant ECG morphology is preserved by both HPS models under sinus conditions, but elucidates differences during pacing.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
| | - Julien Bouyssier
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Anton J Prassl
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria
| | | | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
| |
Collapse
|
36
|
Augustin CM, Gsell MA, Karabelas E, Willemen E, Prinzen FW, Lumens J, Vigmond EJ, Plank G. A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021; 386:114092. [PMID: 34630765 PMCID: PMC7611781 DOI: 10.1016/j.cma.2021.114092] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D-0D model to a limit cycle under baseline conditions, the model's ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.
Collapse
Affiliation(s)
- Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Erik Willemen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Frits W. Prinzen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Edward J. Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Correspondence to: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstrasse 6/IV, Graz 8010, Austria. (G. Plank)
| |
Collapse
|
37
|
Augustin CM, Gsell MAF, Karabelas E, Willemen E, Prinzen FW, Lumens J, Vigmond EJ, Plank G. A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021; 386:114092. [PMID: 34630765 DOI: 10.1016/jxma.2021.114092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D-0D model to a limit cycle under baseline conditions, the model's ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.
Collapse
Affiliation(s)
- Christoph M Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Erik Willemen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Frits W Prinzen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| |
Collapse
|
38
|
Zenger B, Good WW, Bergquist JA, Rupp LC, Perez M, Stoddard GJ, Sharma V, MacLeod RS. Transient recovery of epicardial and torso ST-segment ischemic signals during cardiac stress tests: A possible physiological mechanism. J Electrocardiol 2021; 69S:38-44. [PMID: 34384615 PMCID: PMC8664997 DOI: 10.1016/j.jelectrocard.2021.07.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/24/2021] [Accepted: 07/06/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Acute myocardial ischemia has several characteristic ECG findings, including clinically detectable ST-segment deviations. However, the sensitivity and specificity of diagnosis based on ST-segment changes are low. Furthermore, ST-segment deviations have been shown to be transient and spontaneously recover without any indication the ischemic event has subsided. OBJECTIVE Assess the transient recovery of ST-segment deviations on remote recording electrodes during a partial occlusion cardiac stress test and compare them to intramyocardial ST-segment deviations. METHODS We used a previously validated porcine experimental model of acute myocardial ischemia with controllable ischemic load and simultaneous electrical measurements within the heart wall, on the epicardial surface, and on the torso surface. Simulated cardiac stress tests were induced by occluding a coronary artery while simultaneously pacing rapidly or infusing dobutamine to stimulate cardiac function. Postexperimental imaging created anatomical models for data visualization and quantification. Markers of ischemia were identified as deviations in the potentials measured at 40% of the ST-segment. Intramural cardiac conduction speed was also determined using the inverse gradient method. We assessed changes in intramyocardial ischemic volume proportion, conduction speed, clinical presence of ischemia on remote recording arrays, and regional changes to intramyocardial ischemia. We defined the peak deviation response time as the time interval after onset of ischemia at which maximum ST-segment deviation was achieved, and ST-recovery time was the interval when ST deviation returned to below thresholded of ST elevation. RESULTS In both epicardial and torso recordings, the peak ST-segment deviation response time was 4.9±1.1 min and the ST-recovery time was approximately 7.9±2.5 min, both well before the termination of the ischemic stress. At peak response time, conduction speed was reduced by 50% and returned to near baseline at ST-recovery. The overall ischemic volume proportion initially increased, on average, to 37% at peak response time; however, it recovered to only 30% at the ST-recovery time. By contrast, the subepicardial region of the myocardial wall showed 40% ischemic volume at peak response time and recovered much more strongly to 25% as epicardial ST-segment deviations returned to baseline. CONCLUSION Our data show that remote ischemic signal recovery correlates with a recovery of the subepicardial myocardium, whereas subendocardial ischemic development persists.
Collapse
Affiliation(s)
- Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA; School of Medicine, University of Utah, SLC, UT, USA.
| | - Wilson W Good
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Maura Perez
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
| | | | - Vikas Sharma
- School of Medicine, University of Utah, SLC, UT, USA
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| |
Collapse
|
39
|
Good WW, Gillette KK, Zenger B, Bergquist JA, Rupp LC, Tate J, Anderson D, Gsell MAF, Plank G, MacLeod RS. Estimation and Validation of Cardiac Conduction Velocity and Wavefront Reconstruction Using Epicardial and Volumetric Data. IEEE Trans Biomed Eng 2021; 68:3290-3300. [PMID: 33784613 DOI: 10.1109/tbme.2021.3069792] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE In this study, we have used whole heart simulations parameterized with large animal experiments to validate three techniques (two from the literature and one novel) for estimating epicardial and volumetric conduction velocity (CV). METHODS We used an eikonal-based simulation model to generate ground truth activation sequences with prescribed CVs. Using the sampling density achieved experimentally we examined the accuracy with which we could reconstruct the wavefront, and then examined the robustness of three CV estimation techniques to reconstruction related error. We examined a triangulation-based, inverse-gradient-based, and streamline-based techniques for estimating CV cross the surface and within the volume of the heart. RESULTS The reconstructed activation times agreed closely with simulated values, with 50-70% of the volumetric nodes and 97-99% of the epicardial nodes were within 1 ms of the ground truth. We found close agreement between the CVs calculated using reconstructed versus ground truth activation times, with differences in the median estimated CV on the order of 3-5% volumetrically and 1-2% superficially, regardless of what technique was used. CONCLUSION Our results indicate that the wavefront reconstruction and CV estimation techniques are accurate, allowing us to examine changes in propagation induced by experimental interventions such as acute ischemia, ectopic pacing, or drugs. SIGNIFICANCE We implemented, validated, and compared the performance of a number of CV estimation techniques. The CV estimation techniques implemented in this study produce accurate, high-resolution CV fields that can be used to study propagation in the heart experimentally and clinically.
Collapse
|
40
|
Lee AWC, Razeghi O, Solis-Lemus JA, Strocchi M, Sidhu B, Gould J, Behar JM, Elliott M, Mehta V, Plank G, Rinaldi CA, Niederer SA. Non-invasive simulated electrical and measured mechanical indices predict response to cardiac resynchronization therapy. Comput Biol Med 2021; 138:104872. [PMID: 34598070 DOI: 10.1016/j.compbiomed.2021.104872] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/09/2021] [Accepted: 09/09/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Cardiac Resynchronization Therapy (CRT) in dyssynchronous heart failure patients is ineffective in 20-30% of cases. Sub-optimal left ventricular (LV) pacing location can lead to non-response, thus there is interest in LV lead location optimization. Invasive acute haemodynamic response (AHR) measurements have been used to optimize the LV pacing location during CRT implantation. In this manuscript, we aim to predict the optimal lead location (AHR>10%) with non-invasive computed tomography (CT) based measures of cardiac anatomical and mechanical properties, and simulated electrical activation times. METHODS Non-invasive measurements from CT images and ECG were acquired from 34 patients indicated for CRT upgrade. The LV lead was implanted and AHR was measured at different pacing sites. Computer models of the ventricles were used to simulate the electrical activation of the heart, track the mechanical motion throughout the cardiac cycle and measure the wall thickness of the LV on a patient specific basis. RESULTS We tested the ability of electrical, mechanical and anatomical indices to predict the optimal LV location. Electrical (RV-LV delay) and mechanical (time to peak contraction) indices were correlated with an improved AHR, while wall thickness was not predictive. A logistic regression model combining RV-LV delay and time to peak contraction was able to predict positive response with 70 ± 11% accuracy and AUROC curve of 0.73. CONCLUSION Non-invasive electrical and mechanical indices can predict optimal epicardial lead location. Prospective analysis of these indices could allow clinicians to test the AHR at fewer pacing sites and reduce time, costs and risks to patients.
Collapse
Affiliation(s)
- Angela W C Lee
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - Orod Razeghi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Jose Alonso Solis-Lemus
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Baldeep Sidhu
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Justin Gould
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Jonathan M Behar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Royal Brompton Hospital, London, United Kingdom
| | - Mark Elliott
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Vishal Mehta
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gernot Plank
- Department of Biophysics, Medical University of Graz, Graz, Austria
| | - Christopher A Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| |
Collapse
|
41
|
Irakoze É, Jacquemet V. Multiparameter optimization of nonuniform passive diffusion properties for creating coarse-grained equivalent models of cardiac propagation. Comput Biol Med 2021; 138:104863. [PMID: 34562679 DOI: 10.1016/j.compbiomed.2021.104863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/06/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022]
Abstract
The arrhythmogenic role of discrete cardiac propagation may be assessed by comparing discrete (fine-grained) and equivalent continuous (coarse-grained) models. We aim to develop an optimization algorithm for estimating the smooth conductivity field that best reproduces the diffusion properties of a given discrete model. Our algorithm iteratively adjusts local conductivity of the coarse-grained continuous model by simulating passive diffusion from white noise initial conditions during 3-10 ms and computing the root mean square error with respect to the discrete model. The coarse-grained conductivity field was interpolated from up to 300 evenly spaced control points. We derived an approximate formula for the gradient of the cost function that required (in two dimensions) only two additional simulations per iteration regardless of the number of estimated parameters. Conjugate gradient solver facilitated simultaneous optimization of multiple conductivity parameters. The method was tested in rectangular anisotropic tissues with uniform and nonuniform conductivity (slow regions with sinusoidal profile) and random diffuse fibrosis, as well as in a monolayer interconnected cable model of the left atrium with spatially-varying fibrosis density. Comparison of activation maps served as validation. The results showed that after convergence the errors in activation time were < 1 ms for rectangular geometries and 1-3 ms in the atrial model. Our approach based on the comparison of passive properties (<10 ms simulation) avoids performing active propagation simulations (>100 ms) at each iteration while reproducing activation maps, with possible applications to investigating the impact of microstructure on arrhythmias.
Collapse
Affiliation(s)
- Éric Irakoze
- Pharmacology and Physiology Department, Institute of Biomedical Engineering, Université de Montréal, Montreal, QC, H3T 1J4, Canada; Hôpital Du Sacré-Cœur de Montréal, Research Center, 5400 Boul. Gouin Ouest, Montreal, QC, H4J 1C5, Canada
| | - Vincent Jacquemet
- Pharmacology and Physiology Department, Institute of Biomedical Engineering, Université de Montréal, Montreal, QC, H3T 1J4, Canada; Hôpital Du Sacré-Cœur de Montréal, Research Center, 5400 Boul. Gouin Ouest, Montreal, QC, H4J 1C5, Canada.
| |
Collapse
|
42
|
Rupp LC, Bergquist JA, Zenger B, Gillette K, Narayan A, Tate JD, Plank G, MacLeod RS. The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification. COMPUTING IN CARDIOLOGY 2021; 48:10.23919/cinc53138.2021.9662950. [PMID: 35449765 PMCID: PMC9020927 DOI: 10.23919/cinc53138.2021.9662950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Fiber structure governs the spread of excitation in the heart; however, little is known about the effects of physiological variability in fiber orientation on epicardial activation. To investigate these effects, we implemented ventricular simulations of activation using rule-based fiber orientations, and robust uncertainty quantification algorithms to capture detailed maps of model sensitivity. Specifically, we implemented polynomial chaos expansion, which allows for robust exploration with reduced computational demand through an emulator function to approximate the underlying forward model. We applied these techniques to examine the activation sequence of the heart in response to both epicardial and endocardial stimuli within the left ventricular free wall and variations in fiber orientation. Our results showed that physiological variation in fiber orientation does not significantly impact the location of activation features, but it does impact the overall spread of activation. Future studies will investigate under which circumstances physiological changes in fiber orientation might alter electrical propagation such that the resulting simulations produce misleading outcomes.
Collapse
Affiliation(s)
- Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
- Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
- Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
- Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
- Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
- Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
- Department of Biomedical Engineering, University of Utah, SLC, UT, USA
- School of Medicine, University of Utah, SLC, UT, USA
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Akil Narayan
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
| | - Jess D Tate
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
- Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
- Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| |
Collapse
|
43
|
A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ECG simulations. Med Image Anal 2021; 74:102210. [PMID: 34450467 DOI: 10.1016/j.media.2021.102210] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 06/29/2021] [Accepted: 08/04/2021] [Indexed: 11/20/2022]
Abstract
Large-scale electrophysiological simulations to obtain electrocardiograms (ECG) carry the potential to produce extensive datasets for training of machine learning classifiers to, e.g., discriminate between different cardiac pathologies. The adoption of simulations for these purposes is limited due to a lack of ready-to-use models covering atrial anatomical variability. We built a bi-atrial statistical shape model (SSM) of the endocardial wall based on 47 segmented human CT and MRI datasets using Gaussian process morphable models. Generalization, specificity, and compactness metrics were evaluated. The SSM was applied to simulate atrial ECGs in 100 random volumetric instances. The first eigenmode of our SSM reflects a change of the total volume of both atria, the second the asymmetry between left vs. right atrial volume, the third a change in the prominence of the atrial appendages. The SSM is capable of generalizing well to unseen geometries and 95% of the total shape variance is covered by its first 24 eigenvectors. The P waves in the 12-lead ECG of 100 random instances showed a duration of 109.7±12.2 ms in accordance with large cohort studies. The novel bi-atrial SSM itself as well as 100 exemplary instances with rule-based augmentation of atrial wall thickness, fiber orientation, inter-atrial bridges and tags for anatomical structures have been made publicly available. This novel, openly available bi-atrial SSM can in future be employed to generate large sets of realistic atrial geometries as a basis for in silico big data approaches.
Collapse
|
44
|
Grandits T, Effland A, Pock T, Krause R, Plank G, Pezzuto S. GEASI: Geodesic-based earliest activation sites identification in cardiac models. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2021; 37:e3505. [PMID: 34170082 PMCID: PMC8459297 DOI: 10.1002/cnm.3505] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/19/2021] [Accepted: 06/22/2021] [Indexed: 05/18/2023]
Abstract
The identification of the initial ventricular activation sequence is a critical step for the correct personalization of patient-specific cardiac models. In healthy conditions, the Purkinje network is the main source of the electrical activation, but under pathological conditions the so-called earliest activation sites (EASs) are possibly sparser and more localized. Yet, their number, location and timing may not be easily inferred from remote recordings, such as the epicardial activation or the 12-lead electrocardiogram (ECG), due to the underlying complexity of the model. In this work, we introduce GEASI (Geodesic-based Earliest Activation Sites Identification) as a novel approach to simultaneously identify all EASs. To this end, we start from the anisotropic eikonal equation modeling cardiac electrical activation and exploit its Hamilton-Jacobi formulation to minimize a given objective function, for example, the quadratic mismatch to given activation measurements. This versatile approach can be extended to estimate the number of activation sites by means of the topological gradient, or fitting a given ECG. We conducted various experiments in 2D and 3D for in-silico models and an in-vivo intracardiac recording collected from a patient undergoing cardiac resynchronization therapy. The results demonstrate the clinical applicability of GEASI for potential future personalized models and clinical intervention.
Collapse
Affiliation(s)
- Thomas Grandits
- Institute of Computer Graphics and VisionTU GrazGrazAustria
- BioTechMed‐GrazGrazAustria
| | - Alexander Effland
- Institute of Computer Graphics and VisionTU GrazGrazAustria
- Silicon Austria Labs (TU Graz SAL DES Lab)GrazAustria
- Institute for Applied MathematicsUniversity of BonnBonnGermany
| | - Thomas Pock
- Institute of Computer Graphics and VisionTU GrazGrazAustria
- BioTechMed‐GrazGrazAustria
| | - Rolf Krause
- Center for Computational Medicine in Cardiology, Euler InstituteUniversità della Svizzera ItalianaLuganoSwitzerland
| | - Gernot Plank
- BioTechMed‐GrazGrazAustria
- Gottfried Schatz Research Center—Division of BiophysicsMedical University of GrazGrazAustria
| | - Simone Pezzuto
- Center for Computational Medicine in Cardiology, Euler InstituteUniversità della Svizzera ItalianaLuganoSwitzerland
| |
Collapse
|
45
|
Abstract
Computer modeling of the electrophysiology of the heart has undergone significant progress. A healthy heart can be modeled starting from the ion channels via the spread of a depolarization wave on a realistic geometry of the human heart up to the potentials on the body surface and the ECG. Research is advancing regarding modeling diseases of the heart. This article reviews progress in calculating and analyzing the corresponding electrocardiogram (ECG) from simulated depolarization and repolarization waves. First, we describe modeling of the P-wave, the QRS complex and the T-wave of a healthy heart. Then, both the modeling and the corresponding ECGs of several important diseases and arrhythmias are delineated: ischemia and infarction, ectopic beats and extrasystoles, ventricular tachycardia, bundle branch blocks, atrial tachycardia, flutter and fibrillation, genetic diseases and channelopathies, imbalance of electrolytes and drug-induced changes. Finally, we outline the potential impact of computer modeling on ECG interpretation. Computer modeling can contribute to a better comprehension of the relation between features in the ECG and the underlying cardiac condition and disease. It can pave the way for a quantitative analysis of the ECG and can support the cardiologist in identifying events or non-invasively localizing diseased areas. Finally, it can deliver very large databases of reliably labeled ECGs as training data for machine learning.
Collapse
|
46
|
Monaci S, Gillette K, Puyol-Antón E, Rajani R, Plank G, King A, Bishop M. Automated Localization of Focal Ventricular Tachycardia From Simulated Implanted Device Electrograms: A Combined Physics-AI Approach. Front Physiol 2021; 12:682446. [PMID: 34276403 PMCID: PMC8281305 DOI: 10.3389/fphys.2021.682446] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 05/31/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Focal ventricular tachycardia (VT) is a life-threating arrhythmia, responsible for high morbidity rates and sudden cardiac death (SCD). Radiofrequency ablation is the only curative therapy against incessant VT; however, its success is dependent on accurate localization of its source, which is highly invasive and time-consuming. Objective: The goal of our study is, as a proof of concept, to demonstrate the possibility of utilizing electrogram (EGM) recordings from cardiac implantable electronic devices (CIEDs). To achieve this, we utilize fast and accurate whole torso electrophysiological (EP) simulations in conjunction with convolutional neural networks (CNNs) to automate the localization of focal VTs using simulated EGMs. Materials and Methods: A highly detailed 3D torso model was used to simulate ∼4000 focal VTs, evenly distributed across the left ventricle (LV), utilizing a rapid reaction-eikonal environment. Solutions were subsequently combined with lead field computations on the torso to derive accurate electrocardiograms (ECGs) and EGM traces, which were used as inputs to CNNs to localize focal sources. We compared the localization performance of a previously developed CNN architecture (Cartesian probability-based) with our novel CNN algorithm utilizing universal ventricular coordinates (UVCs). Results: Implanted device EGMs successfully localized VT sources with localization error (8.74 mm) comparable to ECG-based localization (6.69 mm). Our novel UVC CNN architecture outperformed the existing Cartesian probability-based algorithm (errors = 4.06 mm and 8.07 mm for ECGs and EGMs, respectively). Overall, localization was relatively insensitive to noise and changes in body compositions; however, displacements in ECG electrodes and CIED leads caused performance to decrease (errors 16-25 mm). Conclusion: EGM recordings from implanted devices may be used to successfully, and robustly, localize focal VT sources, and aid ablation planning.
Collapse
Affiliation(s)
| | - Karli Gillette
- Division of Biophysics, Medical University of Graz, Graz, Austria
| | | | | | - Gernot Plank
- Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Andrew King
- King’s College London, London, United Kingdom
| | | |
Collapse
|
47
|
Kunisch K, Trautmann P. An Inverse Problem Involving a Viscous Eikonal Equation with Applications in Electrophysiology. VIETNAM JOURNAL OF MATHEMATICS 2021; 50:301-317. [PMID: 34901261 PMCID: PMC8632858 DOI: 10.1007/s10013-021-00509-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 02/24/2021] [Indexed: 06/14/2023]
Abstract
In this work we discuss the reconstruction of cardiac activation instants based on a viscous Eikonal equation from boundary observations. The problem is formulated as a least squares problem and solved by a projected version of the Levenberg-Marquardt method. Moreover, we analyze the well-posedness of the state equation and derive the gradient of the least squares functional with respect to the activation instants. In the numerical examples we also conduct an experiment in which the location of the activation sites and the activation instants are reconstructed jointly based on an adapted version of the shape gradient method from (J. Math. Biol. 79, 2033-2068, 2019). We are able to reconstruct the activation instants as well as the locations of the activations with high accuracy relative to the noise level.
Collapse
Affiliation(s)
- Karl Kunisch
- Institute for Mathematics and Scientific Computing, University of Graz, Heinrichstrasse 36, A-8010 Graz, Austria
- Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Science, Linz, Austria
| | - Philip Trautmann
- Institute for Mathematics and Scientific Computing, University of Graz, Heinrichstrasse 36, A-8010 Graz, Austria
| |
Collapse
|
48
|
Pagani S, Manzoni A. Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2021; 37:e3450. [PMID: 33599106 PMCID: PMC8244126 DOI: 10.1002/cnm.3450] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 02/05/2021] [Accepted: 02/07/2021] [Indexed: 06/12/2023]
Abstract
We present a new, computationally efficient framework to perform forward uncertainty quantification (UQ) in cardiac electrophysiology. We consider the monodomain model to describe the electrical activity in the cardiac tissue, coupled with the Aliev-Panfilov model to characterize the ionic activity through the cell membrane. We address a complete forward UQ pipeline, including both: (i) a variance-based global sensitivity analysis for the selection of the most relevant input parameters, and (ii) a way to perform uncertainty propagation to investigate the impact of intra-subject variability on outputs of interest depending on the cardiac potential. Both tasks exploit stochastic sampling techniques, thus implying overwhelming computational costs because of the huge amount of queries to the high-fidelity, full-order computational model obtained by approximating the coupled monodomain/Aliev-Panfilov system through the finite element method. To mitigate this computational burden, we replace the full-order model with computationally inexpensive projection-based reduced-order models (ROMs) aimed at reducing the state-space dimensionality. Resulting approximation errors on the outputs of interest are finally taken into account through artificial neural network (ANN)-based models, enhancing the accuracy of the whole UQ pipeline. Numerical results show that the proposed physics-based ROMs outperform regression-based emulators relying on ANNs built with the same amount of training data, in terms of both numerical accuracy and overall computational efficiency.
Collapse
Affiliation(s)
- Stefano Pagani
- MOX, Dipartimento di MatematicaPolitecnico di MilanoMilanItaly
| | - Andrea Manzoni
- MOX, Dipartimento di MatematicaPolitecnico di MilanoMilanItaly
| |
Collapse
|
49
|
Rupp LC, Good WW, Bergquist JA, Zenger B, Gillette K, Plank G, MacLeod RS. Effect of Myocardial Fiber Direction on Epicardial Activation Patterns. COMPUTING IN CARDIOLOGY 2021; 47. [PMID: 33937432 DOI: 10.22489/cinc.2020.399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Fiber structure governs the spread of excitation in the heart, however, little is known about the effects of physiological variability in the fiber orientation on epicardial activation. To investigate these effects, we used computer simulation to compare ventricular activation sequences initiated from stimulus sites at regularly spaced depths within the myocardium under varying rule-based fiber ranges. We compared the effects using four characteristics of epicardial breakthrough (BKT): location, area, shape (calculated via the axis ratio of a fitted ellipse), and orientation. Our results showed changes in the BKT characteristics as pacing depth increased, e.g., the area increased, the shape became more circular, and the orientation rotated counterclockwise, regardless of the fiber orientation. Furthermore, the maximal differences in epicardial activation from a single pacing site for location, area, axis ratio, and orientation were 1.2 mm, 74 mm 2 , 0.16, and 26°, respectively. Our results suggest that variability in fiber orientation has a negligible effect on the location, area, and shape of the BKT, while fluctuations were observed in the BKT orientation in response to the fiber fields, especially for epicardial stimulation sites. Our results suggest the fiber field orientation plays only a minor role in activation simulations of ectopic beats.
Collapse
Affiliation(s)
- Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.,Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Wilson W Good
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.,Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.,Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.,Department of Biomedical Engineering, University of Utah, SLC, UT, USA.,School of Medicine, University of Utah, SLC, UT, USA
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA.,Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| |
Collapse
|
50
|
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs. Med Image Anal 2021; 71:102080. [PMID: 33975097 DOI: 10.1016/j.media.2021.102080] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/15/2021] [Accepted: 04/06/2021] [Indexed: 12/21/2022]
Abstract
Cardiac digital twins (Cardiac Digital Twin (CDT)s) of human electrophysiology (Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that match like-for-like all available clinical observations. Due to their inherent predictive potential, CDTs show high promise as a complementary modality aiding in clinical decision making and also in the cost-effective, safe and ethical testing of novel EP device therapies. However, current workflows for both the anatomical and functional twinning phases within CDT generation, referring to the inference of model anatomy and parameters from clinical data, are not sufficiently efficient, robust and accurate for advanced clinical and industrial applications. Our study addresses three primary limitations impeding the routine generation of high-fidelity CDTs by introducing; a comprehensive parameter vector encapsulating all factors relating to the ventricular EP; an abstract reference frame within the model allowing the unattended manipulation of model parameter fields; a novel fast-forward electrocardiogram (Electrocardiogram (ECG)) model for efficient and bio-physically-detailed simulation required for parameter inference. A novel workflow for the generation of CDTs is then introduced as an initial proof of concept. Anatomical twinning was performed within a reasonable time compatible with clinical workflows (<4h) for 12 subjects from clinically-attained magnetic resonance images. After assessment of the underlying fast forward ECG model against a gold standard bidomain ECG model, functional twinning of optimal parameters according to a clinically-attained 12 lead ECG was then performed using a forward Saltelli sampling approach for a single subject. The achieved results in terms of efficiency and fidelity demonstrate that our workflow is well-suited and viable for generating biophysically-detailed CDTs at scale.
Collapse
|