1
|
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
|
2
|
Djemai M, Cupelli M, Boutjdir M, Chahine M. Optical Mapping of Cardiomyocytes in Monolayer Derived from Induced Pluripotent Stem Cells. Cells 2023; 12:2168. [PMID: 37681899 PMCID: PMC10487143 DOI: 10.3390/cells12172168] [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: 07/18/2023] [Revised: 08/21/2023] [Accepted: 08/25/2023] [Indexed: 09/09/2023] Open
Abstract
Optical mapping is a powerful imaging technique widely adopted to measure membrane potential changes and intracellular Ca2+ variations in excitable tissues using voltage-sensitive dyes and Ca2+ indicators, respectively. This powerful tool has rapidly become indispensable in the field of cardiac electrophysiology for studying depolarization wave propagation, estimating the conduction velocity of electrical impulses, and measuring Ca2+ dynamics in cardiac cells and tissues. In addition, mapping these electrophysiological parameters is important for understanding cardiac arrhythmia mechanisms. In this review, we delve into the fundamentals of cardiac optical mapping technology and its applications when applied to hiPSC-derived cardiomyocytes and discuss related advantages and challenges. We also provide a detailed description of the processing and analysis of optical mapping data, which is a crucial step in the study of cardiac diseases and arrhythmia mechanisms for extracting and comparing relevant electrophysiological parameters.
Collapse
Affiliation(s)
- Mohammed Djemai
- CERVO Brain Research Center, Institut Universitaire en Santé Mentale de Québec, Quebec City, QC G1J 2G3, Canada
| | - Michael Cupelli
- Cardiovascular Research Program, VA New York Harbor Healthcare System, New York, NY 11209, USA
- Department of Medicine, Cell Biology and Pharmacology, State University of New York Downstate Health Sciences University, New York, NY 11203, USA
| | - Mohamed Boutjdir
- Cardiovascular Research Program, VA New York Harbor Healthcare System, New York, NY 11209, USA
- Department of Medicine, Cell Biology and Pharmacology, State University of New York Downstate Health Sciences University, New York, NY 11203, USA
- Department of Medicine, NYU School of Medicine, New York, NY 10016, USA
| | - Mohamed Chahine
- CERVO Brain Research Center, Institut Universitaire en Santé Mentale de Québec, Quebec City, QC G1J 2G3, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| |
Collapse
|
3
|
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
|
4
|
Correlation between conduction velocity and frequency analysis in patients with atrial fibrillation using high-density charge mapping. Med Biol Eng Comput 2022; 60:3081-3090. [DOI: 10.1007/s11517-022-02659-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 08/22/2022] [Indexed: 10/14/2022]
|
5
|
Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate. Med Biol Eng Comput 2022; 60:2463-2478. [PMID: 35867323 PMCID: PMC9365755 DOI: 10.1007/s11517-022-02621-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/07/2022] [Indexed: 11/02/2022]
Abstract
Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.
Collapse
|
6
|
Pagani S, Dede' L, Frontera A, Salvador M, Limite LR, Manzoni A, Lipartiti F, Tsitsinakis G, Hadjis A, Della Bella P, Quarteroni A. A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation. Front Physiol 2021; 12:673612. [PMID: 34305637 PMCID: PMC8297688 DOI: 10.3389/fphys.2021.673612] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/28/2021] [Indexed: 12/19/2022] Open
Abstract
In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model. Our new model parametrization is then adopted to predict the formation and self-sustainment of localized reentries characterizing atrial fibrillation, by numerically simulating the onset of ectopic beats from the pulmonary veins. We investigate the paroxysmal and the persistent form of AF starting from electro-anatomical maps of two patients. The model's response to stimulation shows how substrate characteristics play a key role in inducing and sustaining these arrhythmias. Localized reentries are less frequent and less stable in case of paroxysmal AF, while they tend to anchor themselves in areas affected by severe slow conduction in case of persistent AF.
Collapse
Affiliation(s)
- S Pagani
- MOX-Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - L Dede'
- MOX-Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - A Frontera
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - M Salvador
- MOX-Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - L R Limite
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - A Manzoni
- MOX-Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - F Lipartiti
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - G Tsitsinakis
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - A Hadjis
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - P Della Bella
- Department of Arrhythmology, San Raffaele Hospital, Milan, Italy
| | - A Quarteroni
- MOX-Department of Mathematics, Politecnico di Milano, Milan, Italy.,Institute of Mathematics, EPFL, Lausanne, Switzerland
| |
Collapse
|
7
|
Good WW, Zenger B, Bergquist JA, Rupp LC, Gillette K, Plank G, MacLeod RS. Quantifying the Spatiotemporal Influence of Acute Myocardial Ischemia on Volumetric Conduction Speeds. COMPUTING IN CARDIOLOGY 2021; 47. [PMID: 33937430 DOI: 10.22489/cinc.2020.279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Acute myocardial ischemia compromises the ordered electrical activation of the heart, however, because of sampling limitations, volumetric changes in activation have not been measured. We used a large-animal experimental model and high-resolution volumetric mapping to study the effects of ischemia on conduction speeds (CS) throughout the myocardium. We estimated CS and electrocardiographic changes (ST segments) and evaluated the spatial and temporal correlations between them across 11 controlled episodes. We found that ischemia induces significant conduction slowing, reducing the global median speed by 25 cm/s. Furthermore, there was a high temporal correlation between the development of ischemic severity and CS (corr. = 0.93) through each episode. The spatial correlations between ST-segment changes and CS slowing were more spatially complex than expected with substantial slowing at the periphery of the zones that showed ST-segment changes. This is the first study that has documented in an experimental model volumetric changes of CS during acute myocardial ischemia and explored the relationships between ischemia development in space and time. We showed that conduction speed changes are spatiotemporally correlated to ischemic severity and illustrated the biphasic response long proposed from cellular studies.
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
| | - 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.,School of Medicine, 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
|
8
|
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
|