1
|
Bayer JD, Sobota V, Bear LR, Haïssaguerre M, Vigmond EJ. A His bundle pacing protocol for suppressing ventricular arrhythmia maintenance and improving defibrillation efficacy. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 253:108239. [PMID: 38823116 DOI: 10.1016/j.cmpb.2024.108239] [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: 01/08/2024] [Revised: 05/18/2024] [Accepted: 05/21/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND The excitable gap (EG), defined as the excitable tissue between two subsequent wavefronts of depolarization, is critical for maintaining reentry that underlies deadly ventricular arrhythmias. EG in the His-Purkinje Network (HPN) plays an important role in the maintenance of electrical wave reentry that underlies these arrhythmias. OBJECTIVE To determine if rapid His bundle pacing (HBP) during reentry reduces the amount of EG in the HPN and ventricular myocardium to suppress reentry maintenance and/or improve defibrillation efficacy. METHODS In a virtual human biventricular model, reentry was initiated with rapid line pacing followed by HBP delivered for 3, 6, or 9 s at pacing cycle lengths (PCLs) ranging from 10 to 300 ms (n=30). EG was calculated independently for the HPN and myocardium over each PCL. Defibrillation efficacy was assessed for each PCL by stimulating myocardial surface EG with delays ranging from 0.25 to 9 s (increments of 0.25 s, n=36) after the start of HBP. Defibrillation was successful if reentry terminated within 1 s after EG stimulation. This defibrillation protocol was repeated without HBP. To test the approach under different pathological conditions, all protocols were repeated in the model with right (RBBB) or left (LBBB) bundle branch block. RESULTS Compared to without pacing, HBP for >3 seconds reduced average EG in the HPN and myocardium across a broad range of PCLs for the default, RBBB, and LBBB models. HBP >6 seconds terminated reentrant arrhythmia by converting HPN activation to a sinus rhythm behavior in the default (6/30 PCLs) and RBBB (7/30 PCLs) models. Myocardial EG stimulation during HBP increased the number of successful defibrillation attempts by 3%-19% for 30/30 PCLs in the default model, 3%-6% for 14/30 PCLs in the RBBB model, and 3%-11% for 27/30 PCLs in the LBBB model. CONCLUSION HBP can reduce the amount of excitable gap and suppress reentry maintenance in the HPN and myocardium. HBP can also improve the efficacy of low-energy defibrillation approaches targeting excitable myocardium. HBP during reentrant arrhythmias is a promising anti-arrhythmic and defibrillation strategy.
Collapse
Affiliation(s)
- Jason D Bayer
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, 33600, Pessac-Bordeaux, France; University of Bordeaux, Institut de Mathématiques de Bordeaux, UMR 5251, 33400, Talence, France.
| | - Vladimír Sobota
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, 33600, Pessac-Bordeaux, France; University of Bordeaux, Institut de Mathématiques de Bordeaux, UMR 5251, 33400, Talence, France
| | - Laura R Bear
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, 33600, Pessac-Bordeaux, France
| | - Michel Haïssaguerre
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, 33600, Pessac-Bordeaux, France; Haut-Lévêque Cardiology Hospital, University Hospital Center (CHU) of Bordeaux, Pessac, France
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, 33600, Pessac-Bordeaux, France; University of Bordeaux, Institut de Mathématiques de Bordeaux, UMR 5251, 33400, Talence, France
| |
Collapse
|
2
|
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
|
3
|
Arnold R, Prassl AJ, Neic A, Thaler F, Augustin CM, Gsell MAF, Gillette K, Manninger M, Scherr D, Plank G. pyCEPS: A cross-platform electroanatomic mapping data to computational model conversion platform for the calibration of digital twin models of cardiac electrophysiology. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 254:108299. [PMID: 38959599 DOI: 10.1016/j.cmpb.2024.108299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/10/2024] [Accepted: 06/19/2024] [Indexed: 07/05/2024]
Abstract
BACKGROUND AND OBJECTIVE Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific calibration of digital twin models. However, data exported from commercial EAM systems are challenging to access and parse. Converting to data formats that are easily amenable to be viewed and analyzed with commonly used cardiac simulation software tools such as openCARP remains challenging. We therefore developed an open-source platform, pyCEPS, for parsing and converting clinical EAM data conveniently to standard formats widely adopted within the cardiac modeling community. METHODS AND RESULTS pyCEPS is an open-source Python-based platform providing the following functions: (i) access and interrogate the EAM data exported from clinical mapping systems; (ii) efficient browsing of EAM data to preview mapping procedures, electrograms (EGMs), and electro-cardiograms (ECGs); (iii) conversion to modeling formats according to the openCARP standard, to be amenable to analysis with standard tools and advanced workflows as used for in silico EAM data. Documentation and training material to facilitate access to this complementary research tool for new users is provided. We describe the technological underpinnings and demonstrate the capabilities of pyCEPS first, and showcase its use in an exemplary modeling application where we use clinical imaging data to build a patient-specific anatomical model. CONCLUSION With pyCEPS we offer an open-source framework for accessing EAM data, and converting these to cardiac modeling standard formats. pyCEPS provides the core functionality needed to integrate EAM data in cardiac modeling research. We detail how pyCEPS could be integrated into model calibration workflows facilitating the calibration of a computational model based on EAM data.
Collapse
Affiliation(s)
- Robert Arnold
- 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
| | | | - Franz Thaler
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria
| | - Christoph M Augustin
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - 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; BioTechMed-Graz, Graz, Austria
| | - Martin Manninger
- Division of Cardiology, Department of Medicine, Medical University of Graz, Graz, Austria
| | - Daniel Scherr
- Division of Cardiology, Department of Medicine, Medical University of Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria; NumeriCor GmbH, Graz, Austria; BioTechMed-Graz, Graz, Austria.
| |
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
|
Jacquemet V. Improved algorithm for generating evenly-spaced streamlines from an orientation field on a triangulated surface. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 251:108202. [PMID: 38703718 DOI: 10.1016/j.cmpb.2024.108202] [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: 02/20/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Vector fields such as cardiac fiber orientation can be visualized on a surface using streamlines. The application of evenly-spaced streamline generation to the construction of interconnected cable structure for cardiac propagation models has more stringent requirements imperfectly fulfilled by current algorithms. METHOD We developed an open-source C++/python package for the placement of evenly-spaced streamlines on a triangulated surface. The new algorithm improves upon previous works by more accurately handling streamline extremities, U-turns and limit cycles, by providing stronger geometrical guarantees on inter-streamline minimal distance, particularly when a high density of streamlines (up to 10μm spacing) is desired, and by making a more efficient parallel implementation available. The approach requires finding intersections between geometrical capsules and triangles to update an occupancy mask defined on the triangles. This enables fast streamline integration from thousands of seed points to identify optimal streamline placement. RESULTS The algorithm was assessed qualitatively on different left atrial models of fiber orientation with varying mesh resolutions (up to 375k triangles) and quantitatively by measuring streamline lengths and distribution of inter-streamline minimal distance. The complexity and the computational performance of the algorithm were studied as a function of streamline spacing in relation to triangular mesh resolution. CONCLUSION More accurate geometrical computations, attention to details and fine-tuning led to an algorithm more amenable to applications that require precise positioning of streamlines.
Collapse
Affiliation(s)
- 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
|
6
|
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
|
7
|
Pankewitz LR, Hustad KG, Govil S, Perry JC, Hegde S, Tang R, Omens JH, Young AA, McCulloch AD, Arevalo HJ. A universal biventricular coordinate system incorporating valve annuli: Validation in congenital heart disease. Med Image Anal 2024; 93:103091. [PMID: 38301348 PMCID: PMC11227738 DOI: 10.1016/j.media.2024.103091] [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: 05/15/2023] [Revised: 11/29/2023] [Accepted: 01/12/2024] [Indexed: 02/03/2024]
Abstract
Universal coordinate systems have been proposed to facilitate anatomic registration between three-dimensional images, data and models of the ventricles of the heart. However, current universal ventricular coordinate systems do not account for the outflow tracts and valve annuli where the anatomy is complex. Here we propose an extension to the 'Cobiveco' biventricular coordinate system that also accounts for the intervalvular bridges of the base and provides a tool for anatomically consistent registration between widely varying biventricular shapes. CobivecoX uses a novel algorithm to separate intervalvular bridges and assign new coordinates, including an inflow-outflow coordinate, to describe local positions in these regions uniquely and consistently. Anatomic consistency of registration was validated using curated three-dimensional biventricular shape models derived from cardiac MRI measurements in normal hearts and hearts from patients with congenital heart diseases. This new method allows the advantages of universal cardiac coordinates to be used for three-dimensional ventricular imaging data and models that include the left and right ventricular outflow tracts and valve annuli.
Collapse
Affiliation(s)
- Lisa R Pankewitz
- Simula Research Laboratory, Kristian Augusts gate 23, 0164 Oslo, Norway; Department of Informatics, University of Oslo, Gaustadalléen 23B, 0373 Oslo, Norway
| | - Kristian G Hustad
- Simula Research Laboratory, Kristian Augusts gate 23, 0164 Oslo, Norway
| | - Sachin Govil
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA
| | - James C Perry
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA; Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Sanjeet Hegde
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Renxiang Tang
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA
| | - Jeffrey H Omens
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA; Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Alistair A Young
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Andrew D McCulloch
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0412, USA; Department of Medicine, University of California San Diego, La Jolla, CA, USA.
| | | |
Collapse
|
8
|
Strocchi M, Rodero C, Roney CH, Mendonca Costa C, Plank G, Lamata P, Niederer SA. A Semi-automatic Pipeline for Generation of Large Cohorts of Four-Chamber Heart Meshes. Methods Mol Biol 2024; 2735:117-127. [PMID: 38038846 DOI: 10.1007/978-1-0716-3527-8_7] [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] [Indexed: 12/02/2023]
Abstract
Computational models for cardiac electro-mechanics have been increasingly used to further understand heart function. Small cohort and single patient computational studies provide useful insight into cardiac pathophysiology and response to therapy. However, these smaller studies have limited capability to capture the high level of anatomical variability seen in cardiology patients. Larger cohort studies are, on the other hand, more representative of the study population, but building several patient-specific anatomical meshes can be time-consuming and requires access to larger datasets of imaging data, image processing software to label anatomical structures and tools to create high fidelity anatomical meshes. Limited access to these tools and data might limit advances in this area of research. In this chapter, we present our semi-automatic pipeline to build patient-specific four-chamber heart meshes from CT imaging datasets, including ventricular myofibers and a set of universal ventricular and atrial coordinates. This pipeline was applied to CT images from both heart failure patients and healthy controls to generate cohorts of tetrahedral meshes suitable for electro-mechanics simulations. Both cohorts were made publicly available in order to promote computational studies employing large virtual cohorts.
Collapse
Affiliation(s)
- Marina Strocchi
- Department of Biomedical Engineering, King's College London, London, UK
| | - Cristobal Rodero
- Department of Biomedical Engineering, King's College London, London, UK
| | - Caroline H Roney
- Department of Biomedical Engineering, King's College London, London, UK
| | | | | | - Pablo Lamata
- Department of Biomedical Engineering, King's College London, London, UK
| | - Steven A Niederer
- Department of Biomedical Engineering, King's College London, London, UK.
| |
Collapse
|
9
|
Rodero C, Baptiste TMG, Barrows RK, Lewalle A, Niederer SA, Strocchi M. Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways. FRONTIERS IN PHYSICS 2023; 11:1306210. [PMID: 38500690 PMCID: PMC7615748 DOI: 10.3389/fphy.2023.1306210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.
Collapse
Affiliation(s)
- Cristobal Rodero
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Tiffany M. G. Baptiste
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Rosie K. Barrows
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Alexandre Lewalle
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Steven A. Niederer
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Turing Research and Innovation Cluster in Digital Twins (TRIC: DT), The Alan Turing Institute, London, United Kingdom
| | - Marina Strocchi
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| |
Collapse
|
10
|
Meijer C, Uh HW, el Bouhaddani S. Digital Twins in Healthcare: Methodological Challenges and Opportunities. J Pers Med 2023; 13:1522. [PMID: 37888133 PMCID: PMC10608065 DOI: 10.3390/jpm13101522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/14/2023] [Accepted: 10/15/2023] [Indexed: 10/28/2023] Open
Abstract
One of the most promising advancements in healthcare is the application of digital twin technology, offering valuable applications in monitoring, diagnosis, and development of treatment strategies tailored to individual patients. Furthermore, digital twins could also be helpful in finding novel treatment targets and predicting the effects of drugs and other chemical substances in development. In this review article, we consider digital twins as virtual counterparts of real human patients. The primary aim of this narrative review is to give an in-depth look into the various data sources and methodologies that contribute to the construction of digital twins across several healthcare domains. Each data source, including blood glucose levels, heart MRI and CT scans, cardiac electrophysiology, written reports, and multi-omics data, comes with different challenges regarding standardization, integration, and interpretation. We showcase how various datasets and methods are used to overcome these obstacles and generate a digital twin. While digital twin technology has seen significant progress, there are still hurdles in the way to achieving a fully comprehensive patient digital twin. Developments in non-invasive and high-throughput data collection, as well as advancements in modeling and computational power will be crucial to improve digital twin systems. We discuss a few critical developments in light of the current state of digital twin technology. Despite challenges, digital twin research holds great promise for personalized patient care and has the potential to shape the future of healthcare innovation.
Collapse
Affiliation(s)
| | | | - Said el Bouhaddani
- Department Data Science & Biostatistics, Julius Center, UMC Utrecht, 3584 CX Utrecht, The Netherlands (H.-W.U.)
| |
Collapse
|
11
|
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
|
12
|
Li L, Ding W, Huang L, Zhuang X, Grau V. Multi-modality cardiac image computing: A survey. Med Image Anal 2023; 88:102869. [PMID: 37384950 DOI: 10.1016/j.media.2023.102869] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 05/01/2023] [Accepted: 06/12/2023] [Indexed: 07/01/2023]
Abstract
Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases. It allows a combination of complementary anatomical, morphological and functional information, increases diagnosis accuracy, and improves the efficacy of cardiovascular interventions and clinical outcomes. Fully-automated processing and quantitative analysis of multi-modality cardiac images could have a direct impact on clinical research and evidence-based patient management. However, these require overcoming significant challenges including inter-modality misalignment and finding optimal methods to integrate information from different modalities. This paper aims to provide a comprehensive review of multi-modality imaging in cardiology, the computing methods, the validation strategies, the related clinical workflows and future perspectives. For the computing methodologies, we have a favored focus on the three tasks, i.e., registration, fusion and segmentation, which generally involve multi-modality imaging data, either combining information from different modalities or transferring information across modalities. The review highlights that multi-modality cardiac imaging data has the potential of wide applicability in the clinic, such as trans-aortic valve implantation guidance, myocardial viability assessment, and catheter ablation therapy and its patient selection. Nevertheless, many challenges remain unsolved, such as missing modality, modality selection, combination of imaging and non-imaging data, and uniform analysis and representation of different modalities. There is also work to do in defining how the well-developed techniques fit in clinical workflows and how much additional and relevant information they introduce. These problems are likely to continue to be an active field of research and the questions to be answered in the future.
Collapse
Affiliation(s)
- Lei Li
- Department of Engineering Science, University of Oxford, Oxford, UK.
| | - Wangbin Ding
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
| | - Liqin Huang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
| | - Xiahai Zhuang
- School of Data Science, Fudan University, Shanghai, China
| | - Vicente Grau
- Department of Engineering Science, University of Oxford, Oxford, UK
| |
Collapse
|
13
|
Qian S, Monaci S, Mendonca-Costa C, Campos F, Gemmell P, Zaidi HA, Rajani R, Whitaker J, Rinaldi CA, Bishop MJ. Additional coils mitigate elevated defibrillation threshold in right-sided implantable cardioverter defibrillator generator placement: a simulation study. Europace 2023; 25:euad146. [PMID: 37314196 PMCID: PMC10265967 DOI: 10.1093/europace/euad146] [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: 01/20/2023] [Accepted: 05/13/2023] [Indexed: 06/15/2023] Open
Abstract
AIMS The standard implantable cardioverter defibrillator (ICD) generator (can) is placed in the left pectoral area; however, in certain circumstances, right-sided cans may be required which may increase defibrillation threshold (DFT) due to suboptimal shock vectors. We aim to quantitatively assess whether the potential increase in DFT of right-sided can configurations may be mitigated by alternate positioning of the right ventricular (RV) shocking coil or adding coils in the superior vena cava (SVC) and coronary sinus (CS). METHODS AND RESULTS A cohort of CT-derived torso models was used to assess DFT of ICD configurations with right-sided cans and alternate positioning of RV shock coils. Efficacy changes with additional coils in the SVC and CS were evaluated. A right-sided can with an apical RV shock coil significantly increased DFT compared to a left-sided can [19.5 (16.4, 27.1) J vs. 13.3 (11.7, 19.9) J, P < 0.001]. Septal positioning of the RV coil led to a further DFT increase when using a right-sided can [26.7 (18.1, 36.1) J vs. 19.5 (16.4, 27.1) J, P < 0.001], but not a left-sided can [12.1 (8.1, 17.6) J vs. 13.3 (11.7, 19.9) J, P = 0.099). Defibrillation threshold of a right-sided can with apical or septal coil was reduced the most by adding both SVC and CS coils [19.5 (16.4, 27.1) J vs. 6.6 (3.9, 9.9) J, P < 0.001, and 26.7 (18.1, 36.1) J vs. 12.1 (5.7, 13.5) J, P < 0.001]. CONCLUSION Right-sided, compared to left-sided, can positioning results in a 50% increase in DFT. For right-sided cans, apical shock coil positioning produces a lower DFT than septal positions. Elevated right-sided can DFTs may be mitigated by utilizing additional coils in SVC and CS.
Collapse
Affiliation(s)
- Shuang Qian
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Sofia Monaci
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Caroline Mendonca-Costa
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Fernando Campos
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Philip Gemmell
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Hassan A Zaidi
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| | - Ronak Rajani
- Department of Cardiology, Guy’s and St Thomas’ Hospital, Westminster Bridge Rd, London SE1 7EH, UK
| | - John Whitaker
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
- Department of Cardiology, Guy’s and St Thomas’ Hospital, Westminster Bridge Rd, London SE1 7EH, UK
| | - Christopher A Rinaldi
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
- Department of Cardiology, Guy’s and St Thomas’ Hospital, Westminster Bridge Rd, London SE1 7EH, UK
| | - Martin J Bishop
- Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, Kings College London, 4th North Wing, St Thomas’ Hospital, London SE1 7EH, UK
| |
Collapse
|
14
|
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
|
15
|
Monaci S, Qian S, Gillette K, Puyol-Antón E, Mukherjee R, Elliott MK, Whitaker J, Rajani R, O’Neill M, Rinaldi CA, Plank G, King AP, Bishop MJ. Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices. Europace 2023; 25:469-477. [PMID: 36369980 PMCID: PMC9935046 DOI: 10.1093/europace/euac178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
AIMS Existing strategies that identify post-infarct ventricular tachycardia (VT) ablation target either employ invasive electrophysiological (EP) mapping or non-invasive modalities utilizing the electrocardiogram (ECG). Their success relies on localizing sites critical to the maintenance of the clinical arrhythmia, not always recorded on the 12-lead ECG. Targeting the clinical VT by utilizing electrograms (EGM) recordings stored in implanted devices may aid ablation planning, enhancing safety and speed and potentially reducing the need of VT induction. In this context, we aim to develop a non-invasive computational-deep learning (DL) platform to localize VT exit sites from surface ECGs and implanted device intracardiac EGMs. METHODS AND RESULTS A library of ECGs and EGMs from simulated paced beats and representative post-infarct VTs was generated across five torso models. Traces were used to train DL algorithms to localize VT sites of earliest systolic activation; first tested on simulated data and then on a clinically induced VT to show applicability of our platform in clinical settings. Localization performance was estimated via localization errors (LEs) against known VT exit sites from simulations or clinical ablation targets. Surface ECGs successfully localized post-infarct VTs from simulated data with mean LE = 9.61 ± 2.61 mm across torsos. VT localization was successfully achieved from implanted device intracardiac EGMs with mean LE = 13.10 ± 2.36 mm. Finally, the clinically induced VT localization was in agreement with the clinical ablation volume. CONCLUSION The proposed framework may be utilized for direct localization of post-infarct VTs from surface ECGs and/or implanted device EGMs, or in conjunction with efficient, patient-specific modelling, enhancing safety and speed of ablation planning.
Collapse
Affiliation(s)
- Sofia Monaci
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Shuang Qian
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | | | - Esther Puyol-Antón
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Rahul Mukherjee
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
- Guy’s and St Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Mark K Elliott
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
- Guy’s and St Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - John Whitaker
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
- Guy’s and St Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Ronak Rajani
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
- Guy’s and St Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Mark O’Neill
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Christopher A Rinaldi
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
- Guy’s and St Thomas’ Hospital, London SE1 7EH, United Kingdom
| | | | - Andrew P King
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Martin J Bishop
- Biomedical Engineering & Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| |
Collapse
|
16
|
Sung E, Prakosa A, Kyranakis S, Berger RD, Chrispin J, Trayanova NA. Wavefront directionality and decremental stimuli synergistically improve identification of ventricular tachycardia substrate: insights from personalized computational heart models. Europace 2023; 25:223-235. [PMID: 36006658 PMCID: PMC10103576 DOI: 10.1093/europace/euac140] [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: 04/12/2022] [Accepted: 07/16/2022] [Indexed: 11/14/2022] Open
Abstract
AIMS Multiple wavefront pacing (MWP) and decremental pacing (DP) are two electroanatomic mapping (EAM) strategies that have emerged to better characterize the ventricular tachycardia (VT) substrate. The aim of this study was to assess how well MWP, DP, and their combination improve identification of electrophysiological abnormalities on EAM that reflect infarct remodelling and critical VT sites. METHODS AND RESULTS Forty-eight personalized computational heart models were reconstructed using images from post-infarct patients undergoing VT ablation. Paced rhythms were simulated by delivering an initial (S1) and an extra-stimulus (S2) from one of 100 locations throughout each heart model. For each pacing, unipolar signals were computed along the myocardial surface to simulate substrate EAM. Six EAM features were extracted and compared with the infarct remodelling and critical VT sites. Concordance of S1 EAM features between different maps was lower in hearts with smaller amounts of remodelling. Incorporating S1 EAM features from multiple maps greatly improved the detection of remodelling, especially in hearts with less remodelling. Adding S2 EAM features from multiple maps decreased the number of maps required to achieve the same detection accuracy. S1 EAM features from multiple maps poorly identified critical VT sites. However, combining S1 and S2 EAM features from multiple maps paced near VT circuits greatly improved identification of critical VT sites. CONCLUSION Electroanatomic mapping with MWP is more advantageous for characterization of substrate in hearts with less remodelling. During substrate EAM, MWP and DP should be combined and delivered from locations proximal to a suspected VT circuit to optimize identification of the critical VT site.
Collapse
Affiliation(s)
- Eric Sung
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Adityo Prakosa
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Stephen Kyranakis
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Ronald D Berger
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
- Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Baltimore, MD 21287, USA
| | - Jonathan Chrispin
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
- Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Baltimore, MD 21287, USA
| | - Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287, USA
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
| |
Collapse
|
17
|
Zenger B, Bergquist JA, Busatto A, Good WW, Rupp LC, Sharma V, MacLeod RS. Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models. Front Physiol 2023; 14:1100471. [PMID: 36744034 PMCID: PMC9893785 DOI: 10.3389/fphys.2023.1100471] [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: 11/16/2022] [Accepted: 01/02/2023] [Indexed: 01/21/2023] Open
Abstract
The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.
Collapse
Affiliation(s)
- Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States,*Correspondence: Brian Zenger,
| | - Jake A. Bergquist
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Anna Busatto
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | | | - Lindsay C. Rupp
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Vikas Sharma
- Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Rob S. MacLeod
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| |
Collapse
|
18
|
Padilla JR, Anderson RD, Joens C, Masse S, Bhaskaran A, Niri A, Lai P, Azam MA, Lee G, Vigmond E, Nanthakumar K. Orientation of conduction velocity vectors on cardiac mapping surfaces. Europace 2023; 25:1172-1182. [PMID: 36609707 PMCID: PMC10062359 DOI: 10.1093/europace/euac259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/06/2022] [Indexed: 01/09/2023] Open
Abstract
AIMS Electroanatomical maps using automated conduction velocity (CV) algorithms are now being calculated using two-dimensional (2D) mapping tools. We studied the accuracy of mapping surface 2D CV, compared to the three-dimensional (3D) vectors, and the influence of mapping resolution in non-scarred animal and human heart models. METHODS AND RESULTS Two models were used: a healthy porcine Langendorff model with transmural needle electrodes and a computer stimulation model of the ventricles built from an MRI-segmented, excised human heart. Local activation times (LATs) within the 3D volume of the mesh were used to calculate true 3D CVs (direction and velocity) for different pixel resolutions ranging between 500 μm and 4 mm (3D CVs). CV was also calculated for endocardial surface-only LATs (2D CV). In the experimental model, surface (2D) CV was faster on the epicardium (0.509 m/s) compared to the endocardium (0.262 m/s). In stimulation models, 2D CV significantly exceeded 3D CVs across all mapping resolutions and increased as resolution decreased. Three-dimensional and 2D left ventricle CV at 500 μm resolution increased from 429.2 ± 189.3 to 527.7 ± 253.8 mm/s (P < 0.01), respectively, with modest correlation (R = 0.64). Decreasing the resolution to 4 mm significantly increased 2D CV and weakened the correlation (R = 0.46). The majority of CV vectors were not parallel (<30°) to the mapping surface providing a potential mechanistic explanation for erroneous LAT-based CV over-estimation. CONCLUSION Ventricular CV is overestimated when using 2D LAT-based CV calculation of the mapping surface and significantly compounded by mapping resolution. Three-dimensional electric field-based approaches are needed in mapping true CV on mapping surfaces.
Collapse
Affiliation(s)
| | - Robert D Anderson
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Christian Joens
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Stephane Masse
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Abhishek Bhaskaran
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Ahmed Niri
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Patrick Lai
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Mohammed Ali Azam
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| | - Geoffrey Lee
- Department of Cardiology, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | | | - Kumaraswamy Nanthakumar
- Hull Family Cardiac Fibrillation Management Laboratory, Division of Cardiology, University Health Network, Toronto General Hospital, 150 Gerrard Street West, GW3-526, Toronto, Ontario M5G 2C4, Canada
| |
Collapse
|
19
|
Kamali R, Kwan E, Regouski M, Bunch TJ, Dosdall DJ, Hsu E, Macleod RS, Polejaeva I, Ranjan R. Contribution of atrial myofiber architecture to atrial fibrillation. PLoS One 2023; 18:e0279974. [PMID: 36719871 PMCID: PMC9888724 DOI: 10.1371/journal.pone.0279974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 12/19/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND The role of fiber orientation on a global chamber level in sustaining atrial fibrillation (AF) is unknown. The goal of this study was to correlate the fiber direction derived from Diffusion Tensor Imaging (DTI) with AF inducibility. METHODS Transgenic goats with cardiac-specific overexpression of constitutively active TGF-β1 (n = 14) underwent AF inducibility testing by rapid pacing in the left atrium. We chose a minimum of 10 minutes of sustained AF as a cut-off for AF inducibility. Explanted hearts underwent DTI to determine the fiber direction. Using tractography data, we clustered, visualized, and quantified the fiber helix angles in 8 different regions of the left atrial wall using two reference vectors defined based on anatomical landmarks. RESULTS Sustained AF was induced in 7 out of 14 goats. The mean helix fiber angles in 7 out of 8 selected regions were statistically different (P-Value < 0.05) in the AF inducible group. The average fractional anisotropy (FA) and the mean diffusivity (MD) were similar in the two groups with FA of 0.32±0.08 and MD of 8.54±1.72 mm2/s in the non-inducible group and FA of 0.31±0.05 (P-value = 0.90) and MD of 8.68±1.60 mm2/s (P-value = 0.88) in the inducible group. CONCLUSIONS DTI based fiber direction shows significant variability across subjects with a significant difference between animals that are AF inducible versus animals that are not inducible. Fiber direction might be contributing to the initiation and sustaining of AF, and its role needs to be investigated further.
Collapse
Affiliation(s)
- Roya Kamali
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
- Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, Utah, United States of America
| | - Eugene Kwan
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
- Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, Utah, United States of America
| | - Misha Regouski
- Department of Animal, Dairy and Veterinary Sciences, Utah State University, Logan, Utah, United States of America
| | - T. Jared Bunch
- Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, United States of America
| | - Derek J. Dosdall
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
- Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, Utah, United States of America
- Department of Surgery, University of Utah, Salt Lake City, Utah, United States of America
| | - Ed Hsu
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
| | - Rob S. Macleod
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
| | - Irina Polejaeva
- Department of Animal, Dairy and Veterinary Sciences, Utah State University, Logan, Utah, United States of America
| | - Ravi Ranjan
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
- Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, Utah, United States of America
- * E-mail:
| |
Collapse
|
20
|
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
|
21
|
Sung E, Prakosa A, Zhou S, Berger RD, Chrispin J, Nazarian S, Trayanova NA. Fat infiltration in the infarcted heart as a paradigm for ventricular arrhythmias. NATURE CARDIOVASCULAR RESEARCH 2022; 1:933-945. [PMID: 36589896 PMCID: PMC9802586 DOI: 10.1038/s44161-022-00133-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Infiltrating adipose tissue (inFAT) has been recently found to co-localize with scar in infarcted hearts and may contribute to ventricular arrhythmias (VAs), a life-threatening heart rhythm disorder. However, the contribution of inFAT to VA has not been well-established. We investigated the role of inFAT versus scar in VA through a combined prospective clinical and mechanistic computational study. Using personalized computational heart models and comparing the results from simulations of VA dynamics with measured electrophysiological abnormalities during the clinical procedure, we demonstrate that inFAT, rather than scar, is a primary driver of arrhythmogenic propensity and is frequently present in critical regions of the VA circuit. We determined that, within the VA circuitry, inFAT, as opposed to scar, is primarily responsible for conduction slowing in critical sites, mechanistically promoting VA. Our findings implicate inFAT as a dominant player in infarct-related VA, challenging existing paradigms and opening the door for unexplored anti-arrhythmic strategies.
Collapse
Affiliation(s)
- Eric Sung
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.,Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA
| | - Adityo Prakosa
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.,Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA
| | - Shijie Zhou
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.,Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA
| | - Ronald D. Berger
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA.,Department of Medicine, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, USA
| | - Jonathan Chrispin
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA.,Department of Medicine, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, USA.,These authors jointly supervised this work: Jonathan Chrispin, Saman Nazarian, Natalia A. Trayanova
| | - Saman Nazarian
- Division of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,These authors jointly supervised this work: Jonathan Chrispin, Saman Nazarian, Natalia A. Trayanova
| | - Natalia A. Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.,Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA.,These authors jointly supervised this work: Jonathan Chrispin, Saman Nazarian, Natalia A. Trayanova.,Correspondence and requests for materials should be addressed to Natalia A. Trayanova.
| |
Collapse
|
22
|
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
|
23
|
Stimm J, Guenthner C, Kozerke S, Stoeck CT. Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data. NMR IN BIOMEDICINE 2022; 35:e4667. [PMID: 34964179 PMCID: PMC9285076 DOI: 10.1002/nbm.4667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 06/14/2023]
Abstract
Cardiac electrophysiology and cardiac mechanics both depend on the average cardiomyocyte long-axis orientation. In the realm of personalized medicine, knowledge of the patient-specific changes in cardiac microstructure plays a crucial role. Patient-specific computational modelling has emerged as a tool to better understand disease progression. In vivo cardiac diffusion tensor imaging (cDTI) is a vital tool to non-destructively measure the average cardiomyocyte long-axis orientation in the heart. However, cDTI suffers from long scan times, rendering volumetric, high-resolution acquisitions challenging. Consequently, interpolation techniques are needed to populate bio-mechanical models with patient-specific average cardiomyocyte long-axis orientations. In this work, we compare five interpolation techniques applied to in vivo and ex vivo porcine input data. We compare two tensor interpolation approaches, one rule-based approximation, and two data-driven, low-rank models. We demonstrate the advantage of tensor interpolation techniques, resulting in lower interpolation errors than do low-rank models and rule-based methods adapted to cDTI data. In an ex vivo comparison, we study the influence of three imaging parameters that can be traded off against acquisition time: in-plane resolution, signal to noise ratio, and number of acquired short-axis imaging slices.
Collapse
Affiliation(s)
- Johanna Stimm
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian Guenthner
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Sebastian Kozerke
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian T. Stoeck
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
- Division of Surgical ResearchUniversity Hospital ZurichUniversity ZurichSwitzerland
| |
Collapse
|
24
|
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
|
25
|
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
|
26
|
Stimm J, Nordsletten DA, Jilberto J, Miller R, Berberoğlu E, Kozerke S, Stoeck CT. Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods. Front Physiol 2022; 13:1042537. [PMID: 36518106 PMCID: PMC9742433 DOI: 10.3389/fphys.2022.1042537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022] Open
Abstract
Simulations of cardiac electrophysiology and mechanics have been reported to be sensitive to the microstructural anisotropy of the myocardium. Consequently, a personalized representation of cardiac microstructure is a crucial component of accurate, personalized cardiac biomechanical models. In-vivo cardiac Diffusion Tensor Imaging (cDTI) is a non-invasive magnetic resonance imaging technique capable of probing the heart's microstructure. Being a rather novel technique, issues such as low resolution, signal-to noise ratio, and spatial coverage are currently limiting factors. We outline four interpolation techniques with varying degrees of data fidelity, different amounts of smoothing strength, and varying representation error to bridge the gap between the sparse in-vivo data and the model, requiring a 3D representation of microstructure across the myocardium. We provide a workflow to incorporate in-vivo myofiber orientation into a left ventricular model and demonstrate that personalized modelling based on fiber orientations from in-vivo cDTI data is feasible. The interpolation error is correlated with a trend in personalized parameters and simulated physiological parameters, strains, and ventricular twist. This trend in simulation results is consistent across material parameter settings and therefore corresponds to a bias introduced by the interpolation method. This study suggests that using a tensor interpolation approach to personalize microstructure with in-vivo cDTI data, reduces the fiber uncertainty and thereby the bias in the simulation results.
Collapse
Affiliation(s)
- Johanna Stimm
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - David A Nordsletten
- Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, Ann Arbor, MI, United States.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Javiera Jilberto
- Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, Ann Arbor, MI, United States
| | - Renee Miller
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ezgi Berberoğlu
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Division of Surgical Research, University Hospital Zurich, University Zurich, Zurich, Switzerland
| |
Collapse
|
27
|
The Purkinje network plays a major role in low-energy ventricular defibrillation. Comput Biol Med 2021; 141:105133. [PMID: 34954609 DOI: 10.1016/j.compbiomed.2021.105133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/10/2021] [Accepted: 12/10/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND During ventricular fibrillation (VF), targeting the excitable gap (EG) of reentry throughout the myocardium with low-energy surface stimulation shows promise for painless defibrillation. However, the Purkinje network may provide alternative pathways for reentry to evade termination. This study investigates the role of the Purkinje network in painless defibrillation. METHODS In a computational human biventricular model featuring a Purkinje network, VF was initiated with 4 Hz epicardial pacing. Defibrillation was attempted by stimulating myocardial surface EG with a low-energy 2 ms duration pulse at 2x stimulus capture, which was administered at coupling intervals incremented by 0.25 s between 0.25 and 5 s after VF initiation. Defibrillation was accomplished if reentry ceased ≤ 1 s after the defibrillation pulse. The protocol was repeated with the Purkinje network and myocardial surface EG stimulated simultaneously, and again after uncoupling the Purkinje network from the myocardium. RESULTS VF with the Purkinje network coupled and uncoupled had comparable dominant frequency in the left (3.81 ± 0.44 versus 3.77 ± 0.53 Hz) and right (3.80 ± 0.37 versus 3.76 ± 0.48 Hz) ventricles. When uncoupling the Purkinje network, myocardial surface EG stimulation terminated VF for all defibrillation pulses. When coupled, myocardial EG surface stimulation terminated VF for only 55% of the defibrillation pulses, but improved to 100% when stimulated simultaneously with Purkinje network EG. Defibrillation failures were attributed to EG evading stimulation in the Purkinje network. CONCLUSIONS Defibrillation that exclusively targets myocardium can fail due to accessory pathways in the Purkinje network that allow for reentrant activity to evade termination and maintain VF. Painless defibrillation strategies should be adapted to include the Purkinje network.
Collapse
|
28
|
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
|
29
|
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
|
30
|
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
|
31
|
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
|
32
|
Schuler S, Pilia N, Potyagaylo D, Loewe A. Cobiveco: Consistent biventricular coordinates for precise and intuitive description of position in the heart - with MATLAB implementation. Med Image Anal 2021; 74:102247. [PMID: 34592711 DOI: 10.1016/j.media.2021.102247] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/18/2022]
Abstract
Ventricular coordinates are widely used as a versatile tool for various applications that benefit from a description of local position within the heart. However, the practical usefulness of ventricular coordinates is determined by their ability to meet application-specific requirements. For regression-based estimation of biventricular position, for example, a symmetric definition of coordinate directions in both ventricles is important. For the transfer of data between different hearts as another use case, the consistency of coordinate values across different geometries is particularly relevant. To meet these requirements, we compare different approaches to compute coordinates and present Cobiveco, a symmetric, consistent and intuitive biventricular coordinate system that builds upon existing coordinate systems, but overcomes some of their limitations. A novel one-way transfer error is introduced to assess the consistency of the coordinates. Normalized distances along bijective trajectories between two boundaries were found to be superior to solutions of Laplace's equation for defining coordinate values, as they show better linearity in space. Evaluation of transfer and linearity errors on 36 patient geometries revealed a more than 4-fold improvement compared to a state-of-the-art method. Finally, we show two application examples underlining the relevance for cardiac data processing. Cobiveco MATLAB code is available under a permissive open-source license.
Collapse
Affiliation(s)
- Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany.
| | - Nicolas Pilia
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | | | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| |
Collapse
|
33
|
Hussain U, Baron CA, Khan AR. Tractography in Curvilinear Coordinates. Front Neurosci 2021; 15:716538. [PMID: 34512250 PMCID: PMC8428760 DOI: 10.3389/fnins.2021.716538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
Coordinate invariance of physical laws is central in physics, it grants us the freedom to express observations in coordinate systems that provide computational convenience. In the context of medical imaging there are numerous examples where departing from Cartesian to curvilinear coordinates leads to ease of visualization and simplicity, such as spherical coordinates in the brain's cortex, or universal ventricular coordinates in the heart. In this work we introduce tools that enhance the use of existing diffusion tractography approaches to utilize arbitrary coordinates. To test our method we perform simulations that gauge tractography performance by calculating the specificity and sensitivity of tracts generated from curvilinear coordinates in comparison with those generated from Cartesian coordinates, and we find that curvilinear coordinates generally show improved sensitivity and specificity compared to Cartesian. Also, as an application of our method, we show how harmonic coordinates can be used to enhance tractography for the hippocampus.
Collapse
Affiliation(s)
- Uzair Hussain
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada
| | - Corey A Baron
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,School of Biomedical Engineering, Western University, London, ON, Canada
| | - Ali R Khan
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,School of Biomedical Engineering, Western University, London, ON, Canada
| |
Collapse
|
34
|
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
|
35
|
Plank G, Loewe A, Neic A, Augustin C, Huang YL, Gsell MAF, Karabelas E, Nothstein M, Prassl AJ, Sánchez J, Seemann G, Vigmond EJ. The openCARP simulation environment for cardiac electrophysiology. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106223. [PMID: 34171774 DOI: 10.1016/j.cmpb.2021.106223] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/28/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE Cardiac electrophysiology is a medical specialty with a long and rich tradition of computational modeling. Nevertheless, no community standard for cardiac electrophysiology simulation software has evolved yet. Here, we present the openCARP simulation environment as one solution that could foster the needs of large parts of this community. METHODS AND RESULTS openCARP and the Python-based carputils framework allow developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity. The continuously expanding openCARP user community is supported by tailored infrastructure. Documentation and training material facilitate access to this complementary research tool for new users. After a brief historic review, this paper summarizes requirements for a high-usability electrophysiology simulator and describes how openCARP fulfills them. We introduce the openCARP modeling workflow in a multi-scale example of atrial fibrillation simulations on single cell, tissue, organ and body level and finally outline future development potential. CONCLUSION As an open simulator, openCARP can advance the computational cardiac electrophysiology field by making state-of-the-art simulations accessible. In combination with the carputils framework, it offers a tailored software solution for the scientific community and contributes towards increasing use, transparency, standardization and reproducibility of in silico experiments.
Collapse
Affiliation(s)
- Gernot Plank
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | | | - Christoph Augustin
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Yung-Lin Huang
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg. Bad Krozingen, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias A F Gsell
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Mark Nothstein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Anton J Prassl
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Jorge Sánchez
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg. Bad Krozingen, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; Université Bordeaux, IMB, UMR 5251, F-33400 Talence, France
| |
Collapse
|
36
|
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
|
37
|
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
|
38
|
Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach. MATHEMATICS 2021. [DOI: 10.3390/math9111247] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Mathematical models of the human heart are evolving to become a cornerstone of precision medicine and support clinical decision making by providing a powerful tool to understand the mechanisms underlying pathophysiological conditions. In this study, we present a detailed mathematical description of a fully coupled multi-scale model of the human heart, including electrophysiology, mechanics, and a closed-loop model of circulation. State-of-the-art models based on human physiology are used to describe membrane kinetics, excitation-contraction coupling and active tension generation in the atria and the ventricles. Furthermore, we highlight ways to adapt this framework to patient specific measurements to build digital twins. The validity of the model is demonstrated through simulations on a personalized whole heart geometry based on magnetic resonance imaging data of a healthy volunteer. Additionally, the fully coupled model was employed to evaluate the effects of a typical atrial ablation scar on the cardiovascular system. With this work, we provide an adaptable multi-scale model that allows a comprehensive personalization from ion channels to the organ level enabling digital twin modeling.
Collapse
|
39
|
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
|
40
|
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
|
41
|
Stimm J, Buoso S, Berberoğlu E, Kozerke S, Genet M, Stoeck CT. A 3D personalized cardiac myocyte aggregate orientation model using MRI data-driven low-rank basis functions. Med Image Anal 2021; 71:102064. [PMID: 33957560 DOI: 10.1016/j.media.2021.102064] [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: 11/17/2020] [Revised: 03/01/2021] [Accepted: 03/31/2021] [Indexed: 12/17/2022]
Abstract
Cardiac myocyte aggregate orientation has a strong impact on cardiac electrophysiology and mechanics. Studying the link between structural characteristics, strain, and stresses over the cardiac cycle and cardiac function requires a full volumetric representation of the microstructure. In this work, we exploit the structural similarity across hearts to extract a low-rank representation of predominant myocyte orientation in the left ventricle from high-resolution magnetic resonance ex-vivo cardiac diffusion tensor imaging (cDTI) in porcine hearts. We compared two reduction methods, Proper Generalized Decomposition combined with Singular Value Decomposition and Proper Orthogonal Decomposition. We demonstrate the existence of a general set of basis functions of aggregated myocyte orientation which defines a data-driven, personalizable, parametric model featuring higher flexibility than existing atlas and rule-based approaches. A more detailed representation of microstructure matching the available patient data can improve the accuracy of personalized computational models. Additionally, we approximate the myocyte orientation of one ex-vivo human heart and demonstrate the feasibility of transferring the basis functions to humans.
Collapse
Affiliation(s)
- Johanna Stimm
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Stefano Buoso
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Ezgi Berberoğlu
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Martin Genet
- Laboratoire de Mécanique des Solides, École Polytechnique, Palaiseau, France; M3DISIM team, Inria / Université Paris-Saclay, Palaiseau, France; C.N.R.S./Université Paris-Saclay, Palaiseau, France
| | - Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| |
Collapse
|
42
|
Bernardino G, Hodzic A, Langet H, Legallois D, De Craene M, González Ballester MÁ, Saloux É, Bijnens B. Volumetric parcellation of the cardiac right ventricle for regional geometric and functional assessment. Med Image Anal 2021; 71:102044. [PMID: 33872960 DOI: 10.1016/j.media.2021.102044] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 02/01/2021] [Accepted: 03/25/2021] [Indexed: 11/25/2022]
Abstract
3D echocardiography is an increasingly popular tool for assessing cardiac remodelling in the right ventricle (RV). It allows quantification of the cardiac chambers without any geometric assumptions, which is the main weakness of 2D echocardiography. However, regional quantification of geometry and function is limited by the lower spatial and temporal resolution and the scarcity of identifiable anatomical landmarks, especially within the ventricular cavity. We developed a technique for regionally assessing the volume of 3 relevant RV volumetric regions: apical, inlet and outflow. The proposed parcellation method is based on the geodesic distances to anatomical landmarks that are easily identifiable in the images: the apex and the tricuspid and pulmonary valves, each associated to a region. Based on these distances, we define a partition in the endocardium at end-diastole (ED). This partition is then interpolated to the blood cavity using the Laplace equation, which allows to compute regional volumes. For obtaining an end-systole (ES) partition, the endocardial partition is transported from ED to ES using a commercial image-based tracking software, and then the interpolation process is repeated. We assessed the intra- and inter-observer reproducibility using a 10-subjects dataset containing repeated quantifications of the same images, obtaining intra- and inter- observer errors (7-12% and 10-23% respectively). Finally, we propose a novel synthetic mesh generation algorithm that deforms a template mesh imposing a user-defined strain to a template mesh. We used this method to create a new dataset for involving distinct types of remodelling that were used to assess the sensitivity of the parcellation method to identify volume changes affecting different parts. We show that the parcellation method is adequate for capturing local circumferential and global circumferential and longitudinal RV remodelling, which are the most clinically relevant cases.
Collapse
Affiliation(s)
- Gabriel Bernardino
- BCN Medtech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
| | - Amir Hodzic
- Normandie Univ, UNICAEN, CHU de Caen Normandie, Department of Clinical Physiology, Inserm Comete, GIP Cyceron, Caen, France
| | | | - Damien Legallois
- Normandie Univ, UNICAEN, CHU de Caen Normandie, Department of Cardiology, EA4650 SEILIRM, Caen, France
| | | | - Miguel Ángel González Ballester
- BCN Medtech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; ICREA, Barcelona, Spain
| | - Éric Saloux
- Normandie Univ, UNICAEN, CHU de Caen Normandie, Department of Cardiology, EA4650 SEILIRM, Caen, France
| | - Bart Bijnens
- ICREA, Barcelona, Spain; IDIBAPS, Barcelona, Spain; KULeuven, Leuven, Belgium
| |
Collapse
|
43
|
Rodero C, Strocchi M, Marciniak M, Longobardi S, Whitaker J, O’Neill MD, Gillette K, Augustin C, Plank G, Vigmond EJ, Lamata P, Niederer SA. Linking statistical shape models and simulated function in the healthy adult human heart. PLoS Comput Biol 2021; 17:e1008851. [PMID: 33857152 PMCID: PMC8049237 DOI: 10.1371/journal.pcbi.1008851] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 03/03/2021] [Indexed: 01/09/2023] Open
Abstract
Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.
Collapse
Affiliation(s)
- Cristobal Rodero
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
- * E-mail:
| | - Marina Strocchi
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Maciej Marciniak
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Stefano Longobardi
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - John Whitaker
- Cardiovascular Imaging Department, King’s College London, London, United Kingdom
| | - Mark D. O’Neill
- Department of Cardiology, St Thomas’ Hospital, London, United Kingdom
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | | | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Edward J. Vigmond
- Institute of Electrophysiology and Heart Modeling, Foundation Bordeaux University, Bordeaux, France
- Bordeaux Institute of Mathematics, University of Bordeaux, Bordeaux, France
| | - Pablo Lamata
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Steven A. Niederer
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
| |
Collapse
|
44
|
Good WW, Zenger B, Bergquist JA, Rupp LC, Gillette KK, Gsell MAF, Plank G, MacLeod RS. Quantifying the spatiotemporal influence of acute myocardial ischemia on volumetric conduction velocity. J Electrocardiol 2021; 66:86-94. [PMID: 33836460 DOI: 10.1016/j.jelectrocard.2021.03.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 02/28/2021] [Accepted: 03/10/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Acute myocardial ischemia occurs when coronary perfusion to the heart is inadequate, which can perturb the highly organized electrical activation of the heart and can result in adverse cardiac events including sudden cardiac death. Ischemia is known to influence the ST and repolarization phases of the ECG, but it also has a marked effect on propagation (QRS); however, studies investigating propagation during ischemia have been limited. METHODS We estimated conduction velocity (CV) and ischemic stress prior to and throughout 20 episodes of experimentally induced ischemia in order to quantify the progression and correlation of volumetric conduction changes during ischemia. To estimate volumetric CV, we 1) reconstructed the activation wavefront; 2) calculated the elementwise gradient to approximate propagation direction; and 3) estimated conduction speed (CS) with an inverse-gradient technique. RESULTS We found that acute ischemia induces significant conduction slowing, reducing the global median speed by 20 cm/s. We observed a biphasic response in CS (acceleration then deceleration) early in some ischemic episodes. Furthermore, we noted a high temporal correlation between ST-segment changes and CS slowing; however, when comparing these changes over space, we found only moderate correlation (corr. = 0.60). DISCUSSION This study is the first to report volumetric CS changes (acceleration and slowing) during episodes of acute ischemia in the whole heart. We showed that while CS changes progress in a similar time course to ischemic stress (measured by ST-segment shifts), the spatial overlap is complex and variable, showing extreme conduction slowing both in and around regions experiencing severe ischemia.
Collapse
Affiliation(s)
- Wilson W Good
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT, USA.
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT, USA; School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT, USA
| | - Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | | | | | | | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT, USA
| |
Collapse
|
45
|
Building Models of Patient-Specific Anatomy and Scar Morphology from Clinical MRI Data. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11663-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
46
|
Good WW, Zenger B, Bergquist JA, Rupp LC, Gillette K, Angel N, Chou D, Plank G, MacLeod RS. Combining endocardial mapping and electrocardiographic imaging (ECGI) for improving PVC localization: A feasibility study. J Electrocardiol 2021; 69S:51-54. [PMID: 34649726 PMCID: PMC9014370 DOI: 10.1016/j.jelectrocard.2021.08.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/10/2021] [Accepted: 08/13/2021] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Accurate reconstruction of cardiac activation wavefronts is crucial for clinical diagnosis, management, and treatment of cardiac arrhythmias. Furthermore, reconstruction of activation profiles within the intramural myocardium has long been impossible because electrical mapping was only performed on the endocardial surface. Recent advancements in electrocardiographic imaging (ECGI) have made endocardial and epicardial activation mapping possible. We propose a novel approach to use both endocardial and epicardial mapping in a combined approach to reconstruct intramural activation times. OBJECTIVE To implement and validate a combined epicardial/endocardial intramural activation time reconstruction technique. METHODS We used 11 simulations of ventricular activation paced from sites throughout myocardial wall and extracted endocardial and epicardial activation maps at approximate clinical resolution. From these maps, we interpolated the activation times through the myocardium using thin-plate-spline radial basis functions. We evaluated activation time reconstruction accuracy using root-mean-squared error (RMSE) of activation times and the percent of nodes within 1 ms of the ground truth. RESULTS Reconstructed intramural activation times showed an RMSE and percentage of nodes within 1 ms of the ground truth simulations of 3 ms and 70%, respectively. In the worst case, the RMSE and percentage of nodes were 4 ms and 60%, respectively. CONCLUSION We showed that a simple, yet effective combination of clinical endocardial and epicardial activation maps can accurately reconstruct intramural wavefronts. Furthermore, we showed that this approach provided robust reconstructions across multiple intramural stimulation sites.
Collapse
Affiliation(s)
- Wilson W. Good
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA,Department of Biomedical Engineering, University of Utah, SLC, UT, USA,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA,Acutus Medical, Carlsbad, CA, USA
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA,Department of Biomedical Engineering, University of Utah, SLC, UT, USA,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
| | - Jake A. Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA,Department of Biomedical Engineering, University of Utah, SLC, UT, USA,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
| | - Lindsay C. Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA,Department of Biomedical Engineering, University of Utah, SLC, UT, USA,Nora Eccles Cardiovascular Research and Training Institute, 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,Department of Biomedical Engineering, University of Utah, SLC, UT, USA,Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA
| |
Collapse
|
47
|
Bifulco SF, Akoum N, Boyle PM. Translational applications of computational modelling for patients with cardiac arrhythmias. Heart 2020; 107:heartjnl-2020-316854. [PMID: 33303478 PMCID: PMC10896425 DOI: 10.1136/heartjnl-2020-316854] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 11/13/2020] [Accepted: 11/19/2020] [Indexed: 11/04/2022] Open
Abstract
Cardiac arrhythmia is associated with high morbidity, and its underlying mechanisms are poorly understood. Computational modelling and simulation approaches have the potential to improve standard-of-care therapy for these disorders, offering deeper understanding of complex disease processes and sophisticated translational tools for planning clinical procedures. This review provides a clinician-friendly summary of recent advancements in computational cardiology. Organ-scale models automatically generated from clinical-grade imaging data are used to custom tailor our understanding of arrhythmia drivers, estimate future arrhythmogenic risk and personalise treatment plans. Recent mechanistic insights derived from atrial and ventricular arrhythmia simulations are highlighted, and the potential avenues to patient care (eg, by revealing new antiarrhythmic drug targets) are covered. Computational approaches geared towards improving outcomes in resynchronisation therapy have used simulations to elucidate optimal patient selection and lead location. Technology to personalise catheter ablation procedures are also covered, specifically preliminary outcomes form early-stage or pilot clinical studies. To conclude, future developments in computational cardiology are discussed, including improving the representation of patient-specific fibre orientations and fibrotic remodelling characterisation and how these might improve understanding of arrhythmia mechanisms and provide transformative tools for patient-specific therapy.
Collapse
Affiliation(s)
- Savannah F Bifulco
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Nazem Akoum
- Department of Cardiology, University of Washington, Seattle, Washington, USA
| | - Patrick M Boyle
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
- Center for Cardiovascular Biology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell & Regenerative Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
48
|
Grandits T, Gillette K, Neic A, Bayer J, Vigmond E, Pock T, Plank G. An Inverse Eikonal Method for Identifying Ventricular Activation Sequences from Epicardial Activation Maps. JOURNAL OF COMPUTATIONAL PHYSICS 2020; 419:109700. [PMID: 32952215 PMCID: PMC7116090 DOI: 10.1016/j.jcp.2020.109700] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
A key mechanism controlling cardiac function is the electrical activation sequence of the heart's main pumping chambers termed the ventricles. As such, personalization of the ventricular activation sequences is of pivotal importance for the clinical utility of computational models of cardiac electrophysiology. However, a direct observation of the activation sequence throughout the ventricular volume is virtually impossible. In this study, we report on a novel method for identification of activation sequences from activation maps measured at the outer surface of the heart termed the epicardium. Conceptually, the method attempts to identify the key factors governing the ventricular activation sequence - the timing of earliest activation sites (EAS) and the velocity tensor field within the ventricular walls - from sparse and noisy activation maps sampled from the epicardial surface and fits an Eikonal model to the observations. Regularization methods are first investigated to overcome the severe ill-posedness of the inverse problem in a simplified 2D example. These methods are then employed in an anatomically accurate biventricular model with two realistic activation models of varying complexity - a simplified trifascicular model (3F) and a topologically realistic model of the His-Purkinje system (HPS). Using epicardial activation maps at full resolution, we first demonstrate that reconstructing the volumetric activation sequence is, in principle, feasible under the assumption of known location of EAS and later evaluate robustness of the method against noise and reduced spatial resolution of observations. Our results suggest that the FIMIN algorithm is able to robustly recover the full 3D activation sequence using epicardial activation maps at a spatial resolution achievable with current mapping systems and in the presence of noise. Comparing the accuracy achieved in the reconstructed activation maps with clinical data uncertainties suggests that the FIMIN method may be suitable for the patient- specific parameterization of activation models.
Collapse
Affiliation(s)
- Thomas Grandits
- Institute of Computer Graphics and Vision, Graz University of Technology
- BioTechMed-Graz, Austria
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz
- BioTechMed-Graz, Austria
| | - Aurel Neic
- Institute of Biophysics, Medical University of Graz
| | - Jason Bayer
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux
| | - Edward Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux
| | - Thomas Pock
- Institute of Computer Graphics and Vision, Graz University of Technology
- BioTechMed-Graz, Austria
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz
- BioTechMed-Graz, Austria
| |
Collapse
|
49
|
Monaci S, Strocchi M, Rodero C, Gillette K, Whitaker J, Rajani R, Rinaldi CA, O'Neill M, Plank G, King A, Bishop MJ. In-silico pace-mapping using a detailed whole torso model and implanted electronic device electrograms for more efficient ablation planning. Comput Biol Med 2020; 125:104005. [PMID: 32971325 DOI: 10.1016/j.compbiomed.2020.104005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 09/07/2020] [Accepted: 09/07/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Pace-mapping is a commonly used electrophysiological (EP) procedure which aims to identify exit sites of ventricular tachycardia (VT) by matching ventricular activation patterns (assessed by QRS morphology) at specific pacing locations with activation during VT. However, long procedure durations and the need for VT induction render this technique non-optimal. To demonstrate the potential of in-silico pace-mapping, using stored electrogram (EGM) recordings of clinical VT from implanted devices to guide pre-procedural ablation planning. METHOD Six scar-related VT episodes were simulated in a 3D torso model reconstructed from computed tomography (CT) imaging data, including three different infarct anatomies mapped from infarcted porcine imaging data. In-silico pace-mapping was performed to localise VT exit sites and isthmuses by using 12-lead electrocardiogram (ECG) signals and different combinations of EGM sensing vectors from implanted devices, through the creation of conventional correlation maps and reference-less maps. RESULTS Our in-silico platform was successful in identifying VT exit sites for a variety of different VT morphologies from both ECG correlation maps and corresponding EGM maps, with the latter dependent upon the number of sensing vectors used. We also showed the added utility of both ECG and EGM reference-less pace-mapping for the identification of slow-conducting isthmuses, uncovering the optimal algorithm parameters. Finally, EGM-based pace-mapping was shown to be more dependent upon the mapped surface (epicardial/endocardial), relative to the VT origin. CONCLUSIONS In-silico pace-mapping can be used along with EGMs from implanted devices to localise VT ablation targets in pre-procedural planning.
Collapse
Affiliation(s)
| | | | | | | | | | - Ronak Rajani
- King's College London, London, United Kingdom; Guy's and St Thomas' Hospital, London, United Kingdom
| | - Christopher A Rinaldi
- King's College London, London, United Kingdom; Guy's and St Thomas' Hospital, London, United Kingdom
| | | | | | - Andrew King
- King's College London, London, United Kingdom
| | | |
Collapse
|
50
|
Gemmell PM, Gillette K, Balaban G, Rajani R, Vigmond EJ, Plank G, Bishop MJ. A computational investigation into rate-dependant vectorcardiogram changes due to specific fibrosis patterns in non-ischæmic dilated cardiomyopathy. Comput Biol Med 2020; 123:103895. [PMID: 32741753 PMCID: PMC7429989 DOI: 10.1016/j.compbiomed.2020.103895] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 06/12/2020] [Accepted: 06/27/2020] [Indexed: 01/13/2023]
Abstract
Patients with scar-associated fibrotic tissue remodelling are at greater risk of ventricular arrhythmic events, but current methods to detect the presence of such remodelling require invasive procedures. We present here a potential method to detect the presence, location and dimensions of scar using pacing-dependent changes in the vectorcardiogram (VCG). Using a clinically-derived whole-torso computational model, simulations were conducted at both slow and rapid pacing for a variety of scar patterns within the myocardium, with various VCG-derived metrics being calculated, with changes in these metrics being assessed for their ability to discern the presence and size of scar. Our results indicate that differences in the dipole angle at the end of the QRS complex and differences in the QRS area and duration may be used to predict scar properties. Using machine learning techniques, we were also able to predict the location of the scar to high accuracy, using only these VCG-derived rate-dependent changes as input. Such a non-invasive predictive tool for the presence of scar represents a potentially useful clinical tool for identifying patients at arrhythmic risk.
Collapse
Affiliation(s)
- Philip M Gemmell
- King's College London, St. Thomas' Hospital North Wing, London, SE1 7EH, UK.
| | - Karli Gillette
- Medical University of Graz, Division of Biophysics, Neue Stiftingtalstraße 6(MC1.D.)/IV, 8010 Graz, Austria
| | - Gabriel Balaban
- University of Oslo, Research Group for Biomedical Infomatics, Gaustadalléen 23B 0373 Oslo, Norway
| | - Ronak Rajani
- King's College London, St. Thomas' Hospital North Wing, London, SE1 7EH, UK
| | - Edward J Vigmond
- University of Bordeaux, IHU Liryc, Site Hopital Xavier Arnozan, Avenue de Haut-Leveque, 33604 Pessac, France
| | - Gernot Plank
- Medical University of Graz, Division of Biophysics, Neue Stiftingtalstraße 6(MC1.D.)/IV, 8010 Graz, Austria
| | - Martin J Bishop
- King's College London, St. Thomas' Hospital North Wing, London, SE1 7EH, UK
| |
Collapse
|