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Gerach T, Loewe A. Differential effects of mechano-electric feedback mechanisms on whole-heart activation, repolarization, and tension. J Physiol 2024; 602:4605-4624. [PMID: 38185911 DOI: 10.1113/jp285022] [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: 05/14/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024] Open
Abstract
The human heart is subject to highly variable amounts of strain during day-to-day activities and needs to adapt to a wide range of physiological demands. This adaptation is driven by an autoregulatory loop that includes both electrical and the mechanical components. In particular, mechanical forces are known to feed back into the cardiac electrophysiology system, which can result in pro- and anti-arrhythmic effects. Despite the widespread use of computational modelling and simulation for cardiac electrophysiology research, the majority of in silico experiments ignore this mechano-electric feedback entirely due to the high computational cost associated with solving cardiac mechanics. In this study, we therefore use an electromechanically coupled whole-heart model to investigate the differential and combined effects of electromechanical feedback mechanisms with a focus on their physiological relevance during sinus rhythm. In particular, we consider troponin-bound calcium, the effect of deformation on the tissue diffusion tensor, and stretch-activated channels. We found that activation of the myocardium was only significantly affected when including deformation into the diffusion term of the monodomain equation. Repolarization, on the other hand, was influenced by both troponin-bound calcium and stretch-activated channels and resulted in steeper repolarization gradients in the atria. The latter also caused afterdepolarizations in the atria. Due to its central role for tension development, calcium bound to troponin affected stroke volume and pressure. In conclusion, we found that mechano-electric feedback changes activation and repolarization patterns throughout the heart during sinus rhythm and lead to a markedly more heterogeneous electrophysiological substrate. KEY POINTS: The electrophysiological and mechanical function of the heart are tightly interrelated by excitation-contraction coupling (ECC) in the forward direction and mechano-electric feedback (MEF) in the reverse direction. While ECC is considered in many state-of-the-art computational models of cardiac electromechanics, less is known about the effect of different MEF mechanisms. Accounting for calcium bound to troponin increases stroke volume and delays repolarization. Geometry-mediated MEF leads to more heterogeneous activation and repolarization with steeper gradients. Both effects combine in an additive way. Non-selective stretch-activated channels as an additional MEF mechanism lead to heterogeneous diastolic transmembrane voltage, higher developed tension and delayed repolarization or afterdepolarizations in highly stretched parts of the atria. The differential and combined effects of these three MEF mechanisms during sinus rhythm activation in a human four-chamber heart model may have implications for arrhythmogenesis, both in terms of substrate (repolarization gradients) and triggers (ectopy).
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Affiliation(s)
- Tobias Gerach
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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2
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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 PMCID: PMC11381036 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.
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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
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3
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Hussain S, Falanga M, Chiaravalloti A, Tomasi C, Corsi C. Patient-specific left atrium contraction quantification associated with atrial fibrillation: A region-based approach. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 249:108138. [PMID: 38522329 DOI: 10.1016/j.cmpb.2024.108138] [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: 12/15/2023] [Revised: 03/17/2024] [Accepted: 03/18/2024] [Indexed: 03/26/2024]
Abstract
BACKGROUND AND OBJECTIVES Atrial fibrillation (AF) is a widespread cardiac arrhythmia that significantly impacts heart function. AF disrupts atrial mechanical contraction, leading to irregular, uncoordinated, and slow blood flow inside the atria which favors the formation of clots, primarily within the left atrium (LA). A standardized region-based analysis of the LA is missing, and there is not even any consensus about how to define the LA regions. In this study we propose an automatic approach for regionalizing the LA into segments to provide a comprehensive 3D region-based LA contraction assessment. LA global and regional contraction were quantified in control subjects and in AF patients to describe mechanical abnormalities associated with AF. METHODS The proposed automatic approach for LA regionalization was tested in thirteen control subjects and seventeen AF patients. After dividing LA into standard regions, we evaluated the global and regional mechanical function by measuring LA contraction parameters, such as regional volume, global and regional strains, regional wall motion and regional shortening fraction. RESULTS LA regionalization was successful in all study subjects. In the AF group compared with control subjects, results showed: a global impairment of LA contraction which appeared more pronounced along radial and circumferential direction; a regional impairment of radial strain which was more pronounced in septal, inferior, and lateral regions suggesting a greater reduction in mechanical efficiency in these regions in comparison to the posterior and anterior ones. CONCLUSION An automatic approach for LA regionalization was proposed. The regionalization method was proved to be robust with several LA anatomical variations and able to characterize contraction changes associated with AF.
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Affiliation(s)
| | | | | | - Corrado Tomasi
- Santa Maria delle Croci Hospital, AUSL della Romagna, Ravenna, Italy
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4
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Wülfers EM, Moss R, Lehrmann H, Arentz T, Westermann D, Seemann G, Odening KE, Steinfurt J. Whole-heart computational modelling provides further mechanistic insights into ST-elevation in Brugada syndrome. INTERNATIONAL JOURNAL OF CARDIOLOGY. HEART & VASCULATURE 2024; 51:101373. [PMID: 38464963 PMCID: PMC10924145 DOI: 10.1016/j.ijcha.2024.101373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/08/2024] [Accepted: 02/21/2024] [Indexed: 03/12/2024]
Abstract
Background Brugada syndrome (BrS) is characterized by dynamic ST-elevations in right precordial leads and increased risk of ventricular fibrillation and sudden cardiac death. As the mechanism underlying ST-elevation and malignant arrhythmias is controversial computational modeling can aid in exploring the disease mechanism. Thus we aim to test the main competing hypotheses ('delayed depolarization' vs. 'early repolarization') of BrS in a whole-heart computational model. Methods In a 3D whole-heart computational model, delayed epicardial RVOT activation with local conduction delay was simulated by reducing conductivity in the epicardial RVOT. Early repolarization was simulated by instead increasing the transient outward potassium current (Ito) in the same region. Additionally, a reduction in the fast sodium current (INa) was incorporated in both models. Results Delayed depolarization with local conduction delay in the computational model resulted in coved-type ST-elevation with negative T-waves in the precordial surface ECG leads. 'Saddleback'-shaped ST-elevation was obtained with reduced substrate extent or thickness. Increased Ito simulations showed early repolarization in the RVOT with a descending but not coved-type ST-elevation. Reduced INa did not show a significant effect on ECG morphology. Conclusions In this whole-heart BrS computational model of both major hypotheses, realistic coved-type ECG resulted only from delayed epicardial RVOT depolarization with local conduction delay but not early repolarizing ion channel modifications. These simulations provide further support for the depolarization hypothesis as electrophysiological mechanism underlying BrS.
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Affiliation(s)
- Eike M Wülfers
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Physics and Astronomy, Faculty of Sciences, Ghent University, Ghent, Belgium
| | - Robin Moss
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Heiko Lehrmann
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Arentz
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dirk Westermann
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katja E Odening
- Translational Cardiology, Department of Cardiology and Institute of Physiology, University Hospital Bern, University of Bern, Switzerland
| | - Johannes Steinfurt
- Department of Cardiology and Angiology, University Heart Center Freiburg - Bad Krozingen, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Rodero C, Baptiste TMG, Barrows RK, Lewalle A, Niederer SA, Strocchi M. Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways. FRONTIERS IN PHYSICS 2023; 11:1306210. [PMID: 38500690 PMCID: PMC7615748 DOI: 10.3389/fphy.2023.1306210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.
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Affiliation(s)
- Cristobal Rodero
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Tiffany M. G. Baptiste
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Rosie K. Barrows
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Alexandre Lewalle
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Steven A. Niederer
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
- Turing Research and Innovation Cluster in Digital Twins (TRIC: DT), The Alan Turing Institute, London, United Kingdom
| | - Marina Strocchi
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom
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Azzolin L, Eichenlaub M, Nagel C, Nairn D, Sánchez J, Unger L, Arentz T, Westermann D, Dössel O, Jadidi A, Loewe A. AugmentA: Patient-specific augmented atrial model generation tool. Comput Med Imaging Graph 2023; 108:102265. [PMID: 37392493 DOI: 10.1016/j.compmedimag.2023.102265] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 01/07/2023] [Accepted: 06/03/2023] [Indexed: 07/03/2023]
Abstract
Digital twins of patients' hearts are a promising tool to assess arrhythmia vulnerability and to personalize therapy. However, the process of building personalized computational models can be challenging and requires a high level of human interaction. We propose a patient-specific Augmented Atria generation pipeline (AugmentA) as a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models. AugmentA identifies and labels atrial orifices using only one reference point per atrium. If the user chooses to fit a statistical shape model to the input geometry, it is first rigidly aligned with the given mean shape before a non-rigid fitting procedure is applied. AugmentA automatically generates the fiber orientation and finds local conduction velocities by minimizing the error between the simulated and clinical local activation time (LAT) map. The pipeline was tested on a cohort of 29 patients on both segmented magnetic resonance images (MRI) and electroanatomical maps of the left atrium. Moreover, the pipeline was applied to a bi-atrial volumetric mesh derived from MRI. The pipeline robustly integrated fiber orientation and anatomical region annotations in 38.4 ± 5.7 s. In conclusion, AugmentA offers an automated and comprehensive pipeline delivering atrial digital twins from clinical data in procedural time.
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Affiliation(s)
- Luca Azzolin
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany.
| | - Martin Eichenlaub
- University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Claudia Nagel
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Deborah Nairn
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Jorge Sánchez
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Laura Unger
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Thomas Arentz
- University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Dirk Westermann
- University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Amir Jadidi
- University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering at Karlsruhe Institute of Technology, Karlsruhe, Germany
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7
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He J, Pertsov AM, Cherry EM, Fenton FH, Roney CH, Niederer SA, Zang Z, Mangharam R. Fiber Organization Has Little Effect on Electrical Activation Patterns During Focal Arrhythmias in the Left Atrium. IEEE Trans Biomed Eng 2023; 70:1611-1621. [PMID: 36399589 PMCID: PMC10183233 DOI: 10.1109/tbme.2022.3223063] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Over the past two decades there has been a steady trend towards the development of realistic models of cardiac conduction with increasing levels of detail. However, making models more realistic complicates their personalization and use in clinical practice due to limited availability of tissue and cellular scale data. One such limitation is obtaining information about myocardial fiber organization in the clinical setting. In this study, we investigated a chimeric model of the left atrium utilizing clinically derived patient-specific atrial geometry and a realistic, yet foreign for a given patient fiber organization. We discovered that even significant variability of fiber organization had a relatively small effect on the spatio-temporal activation pattern during regular pacing. For a given pacing site, the activation maps were very similar across all fiber organizations tested.
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Vila M, Rivolta MW, Barrios Espinosa CA, Unger LA, Luik A, Loewe A, Sassi R. Recommender system for ablation lines to treat complex atrial tachycardia. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 231:107406. [PMID: 36787660 DOI: 10.1016/j.cmpb.2023.107406] [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: 05/30/2022] [Revised: 01/30/2023] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND AND OBJECTIVE Planning the optimal ablation strategy for the treatment of complex atrial tachycardia (CAT) is a time consuming task and is error-prone. Recently, directed network mapping, a technology based on graph theory, proved to efficiently identify CAT based solely on data of clinical interventions. Briefly, a directed network was used to model the atrial electrical propagation and reentrant activities were identified by looking for closed-loop paths in the network. In this study, we propose a recommender system, built as an optimization problem, able to suggest the optimal ablation strategy for the treatment of CAT. METHODS The optimization problem modeled the optimal ablation strategy as that one interrupting all reentrant mechanisms while minimizing the ablated atrial surface. The problem was designed on top of directed network mapping. Considering the exponential complexity of finding the optimal solution of the problem, we introduced a heuristic algorithm with polynomial complexity. The proposed algorithm was applied to the data of i) 6 simulated scenarios including both left and right atrial flutter; and ii) 10 subjects that underwent a clinical routine. RESULTS The recommender system suggested the optimal strategy in 4 out of 6 simulated scenarios. On clinical data, the recommended ablation lines were found satisfactory on 67% of the cases according to the clinician's opinion, while they were correctly located in 89%. The algorithm made use of only data collected during mapping and was able to process them nearly real-time. CONCLUSIONS The first recommender system for the identification of the optimal ablation lines for CAT, based solely on the data collected during the intervention, is presented. The study may open up interesting scenarios for the application of graph theory for the treatment of CAT.
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Affiliation(s)
- Muhamed Vila
- Università degli Studi di Milano, Via Celoria 18, Milan, 20133, Italy
| | - Massimo W Rivolta
- Università degli Studi di Milano, Via Celoria 18, Milan, 20133, Italy.
| | - Cristian A Barrios Espinosa
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany
| | - Laura A Unger
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany
| | - Armin Luik
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Moltkestraße 90, Karlsruhe, 76133, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, 76131, Germany
| | - Roberto Sassi
- Università degli Studi di Milano, Via Celoria 18, Milan, 20133, Italy
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9
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Gerach T, Schuler S, Wachter A, Loewe A. The Impact of Standard Ablation Strategies for Atrial Fibrillation on Cardiovascular Performance in a Four-Chamber Heart Model. Cardiovasc Eng Technol 2023; 14:296-314. [PMID: 36652165 PMCID: PMC10102113 DOI: 10.1007/s13239-022-00651-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 11/29/2022] [Indexed: 01/19/2023]
Abstract
PURPOSE Atrial fibrillation is one of the most frequent cardiac arrhythmias in the industrialized world and ablation therapy is the method of choice for many patients. However, ablation scars alter the electrophysiological activation and the mechanical behavior of the affected atria. Different ablation strategies with the aim to terminate atrial fibrillation and prevent its recurrence exist but their impact on the performance of the heart is often neglected. METHODS In this work, we present a simulation study analyzing five commonly used ablation scar patterns and their combinations in the left atrium regarding their impact on the pumping function of the heart using an electromechanical whole-heart model. We analyzed how the altered atrial activation and increased stiffness due to the ablation scars affect atrial as well as ventricular contraction and relaxation. RESULTS We found that systolic and diastolic function of the left atrium is impaired by ablation scars and that the reduction of atrial stroke volume of up to 11.43% depends linearly on the amount of inactivated tissue. Consequently, the end-diastolic volume of the left ventricle, and thus stroke volume, was reduced by up to 1.4 and 1.8%, respectively. During ventricular systole, left atrial pressure was increased by up to 20% due to changes in the atrial activation sequence and the stiffening of scar tissue. CONCLUSION This study provides biomechanical evidence that atrial ablation has acute effects not only on atrial contraction but also on ventricular performance. Therefore, the position and extent of ablation scars is not only important for the termination of arrhythmias but is also determining long-term pumping efficiency. If confirmed in larger cohorts, these results have the potential to help tailoring ablation strategies towards minimal global cardiovascular impairment.
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Affiliation(s)
- Tobias Gerach
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Andreas Wachter
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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10
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Rossi S, Abdala L, Woodward A, Vavalle JP, Henriquez CS, Griffith BE. Rule-based definition of muscle bundles in patient-specific models of the left atrium. Front Physiol 2022; 13:912947. [PMID: 36311246 PMCID: PMC9597256 DOI: 10.3389/fphys.2022.912947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 06/29/2022] [Indexed: 11/13/2022] Open
Abstract
Atrial fibrillation (AF) is the most common arrhythmia encountered clinically, and as the population ages, its prevalence is increasing. Although the CHA2DS2- VASc score is the most used risk-stratification system for stroke risk in AF, it lacks personalization. Patient-specific computer models of the atria can facilitate personalized risk assessment and treatment planning. However, a challenge faced in creating such models is the complexity of the atrial muscle arrangement and its influence on the atrial fiber architecture. This work proposes a semi-automated rule-based algorithm to generate the local fiber orientation in the left atrium (LA). We use the solutions of several harmonic equations to decompose the LA anatomy into subregions. Solution gradients define a two-layer fiber field in each subregion. The robustness of our approach is demonstrated by recreating the fiber orientation on nine models of the LA obtained from AF patients who underwent WATCHMAN device implantation. This cohort of patients encompasses a variety of morphology variants of the left atrium, both in terms of the left atrial appendages (LAAs) and the number of pulmonary veins (PVs). We test the fiber construction algorithm by performing electrophysiology (EP) simulations. Furthermore, this study is the first to compare its results with other rule-based algorithms for the LA fiber architecture definition available in the literature. This analysis suggests that a multi-layer fiber architecture is important to capture complex electrical activation patterns. A notable advantage of our approach is the ability to reconstruct the main LA fiber bundles in a variety of morphologies while solving for a small number of harmonic fields, leading to a comparatively straightforward and reproducible approach.
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Affiliation(s)
- Simone Rossi
- Department of Mathematics, UNC Chapel Hill, Chapel Hill, NC, United States
| | - Laryssa Abdala
- Department of Mathematics, UNC Chapel Hill, Chapel Hill, NC, United States
| | - Andrew Woodward
- Advanced Medical Imaging Lab, UNC Chapel Hill, Chapel Hill, NC, United States
| | - John P. Vavalle
- Department of Medicine, UNC Chapel Hill, Chapel Hill, NC, United States
| | - Craig S. Henriquez
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Boyce E. Griffith
- Department of Mathematics, UNC Chapel Hill, Chapel Hill, NC, United States
- Department of Biomedical Engineering, UNC Chapel Hill, Chapel Hill, NC, United States
- McAllister Heart Institute, UNC Chapel Hill, Chapel Hill, NC, United States
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11
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Zang L, Gu K, Ji X, Zhang H, Yan S, Wu X. Effect of Anisotropic Electrical Conductivity Induced by Fiber Orientation on Ablation Characteristics of Pulsed Field Ablation in Atrial Fibrillation Treatment: A Computational Study. J Cardiovasc Dev Dis 2022; 9:319. [PMID: 36286271 PMCID: PMC9604654 DOI: 10.3390/jcdd9100319] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/15/2022] [Accepted: 09/19/2022] [Indexed: 09/07/2024] Open
Abstract
Pulsed field ablation (PFA) is a promising new ablation modality for the treatment of atrial fibrillation (AF); however, the effect of fiber orientation on the ablation characteristics of PFA in AF treatment is still unclear, which is likely an essential factor in influencing the ablation characteristics. This study constructed an anatomy-based left atrium (LA) model incorporating fiber orientation and selected various electrical conductivity and ablation targets to investigate the effect of anisotropic electrical conductivity (AC), compared with isotropic electrical conductivity (IC), on the ablation characteristics of PFA in AF treatment. The results show that the percentage differences in the size of the surface ablation area between AC and IC are greater than 73.71%; the maximum difference in the size of the ablation isosurface between AC and IC at different locations in the atrial wall is 3.65 mm (X-axis), 3.65 mm (Z-axis), and 4.03 mm (X-axis), respectively; and the percentage differences in the size of the ablation volume are greater than 6.9%. Under the condition of the pulse, the amplitude is 1000 V, the total PFA duration is 1 s, and the pulse train interval is 198.4 ms; the differences in the temperature increase between AC and IC in LA are less than 2.46 °C. Hence, this study suggests that in further exploration of the computational study of PFA in AF treatment using the same or similar conditions as those used here (myocardial electrical conductivity, pulse parameters, and electric field intensity damage threshold), to obtain more accurate computational results, it is necessary to adopt AC rather than IC to investigate the size of the surface ablation area, the size of the ablation isosurface, or the size of the ablation volume generated by PFA in LA. Moreover, if only investigating the temperature increase generated by PFA in LA, adopting IC instead of AC for simplifying the model construction process is reasonable.
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Affiliation(s)
- Lianru Zang
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Kaihao Gu
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Xingkai Ji
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Hao Zhang
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Shengjie Yan
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
| | - Xiaomei Wu
- Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, China
- Academy for Engineering and Technology, Fudan University, Shanghai 200433, China
- Key Laboratory of Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) of Shanghai, Fudan University, Shanghai 200032, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, China
- Yiwu Research Institute, Fudan University, Yiwu 322000, China
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12
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Moss R, Wülfers EM, Lewetag R, Hornyik T, Perez-Feliz S, Strohbach T, Menza M, Krafft A, Odening KE, Seemann G. A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution. PLoS One 2022; 17:e0270559. [PMID: 35771854 PMCID: PMC9246225 DOI: 10.1371/journal.pone.0270559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 06/13/2022] [Indexed: 11/19/2022] Open
Abstract
Computational modeling of electrophysiological properties of the rabbit heart is a commonly used way to enhance and/or complement findings from classic lab work on single cell or tissue levels. Yet, thus far, there was no possibility to extend the scope to include the resulting body surface potentials as a way of validation or to investigate the effect of certain pathologies. Based on CT imaging, we developed the first openly available computational geometrical model not only of the whole heart but also the complete torso of the rabbit. Additionally, we fabricated a 32-lead ECG-vest to record body surface potential signals of the aforementioned rabbit. Based on the developed geometrical model and the measured signals, we then optimized the activation sequence of the ventricles, recreating the functionality of the Purkinje network, and we investigated different apico-basal and transmural gradients in action potential duration. Optimization of the activation sequence resulted in an average root mean square error between measured and simulated signal of 0.074 mV/ms for all leads. The best-fit T-Wave, compared to measured data (0.038 mV/ms), resulted from incorporating an action potential duration gradient from base to apex with a respective shortening of 20 ms and a transmural gradient with a shortening of 15 ms from endocardium to epicardium. By making our model and measured data openly available, we hope to give other researchers the opportunity to verify their research, as well as to create the possibility to investigate the impact of electrophysiological alterations on body surface signals for translational research.
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Affiliation(s)
- Robin Moss
- 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
- * E-mail:
| | - Eike M. Wülfers
- 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
| | - Raphaela Lewetag
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
| | - Tibor Hornyik
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg ⋅ Bad Krozingen, Medical Center—University of Freiburg, Freiburg, Germany
- Translational Cardiology, Department of Cardiology and Department of Physiology, University Hospital Bern, Bern, Switzerland
| | - Stefanie Perez-Feliz
- 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
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
| | - Tim Strohbach
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Marius Menza
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Axel Krafft
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
| | - Katja E. Odening
- Department of Cardiology and Angiology I, Heart Center University of Freiburg, Medical Faculty, Freiburg, Germany
- Translational Cardiology, Department of Cardiology and Department of Physiology, University Hospital Bern, Bern, Switzerland
| | - 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
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13
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Moss R, Wülfers EM, Schuler S, Loewe A, Seemann G. A Fully-Coupled Electro-Mechanical Whole-Heart Computational Model: Influence of Cardiac Contraction on the ECG. Front Physiol 2022; 12:778872. [PMID: 34975532 PMCID: PMC8716847 DOI: 10.3389/fphys.2021.778872] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/17/2021] [Indexed: 01/12/2023] Open
Abstract
The ECG is one of the most commonly used non-invasive tools to gain insights into the electrical functioning of the heart. It has been crucial as a foundation in the creation and validation of in silico models describing the underlying electrophysiological processes. However, so far, the contraction of the heart and its influences on the ECG have mainly been overlooked in in silico models. As the heart contracts and moves, so do the electrical sources within the heart responsible for the signal on the body surface, thus potentially altering the ECG. To illuminate these aspects, we developed a human 4-chamber electro-mechanically coupled whole heart in silico model and embedded it within a torso model. Our model faithfully reproduces measured 12-lead ECG traces, circulatory characteristics, as well as physiological ventricular rotation and atrioventricular valve plane displacement. We compare our dynamic model to three non-deforming ones in terms of standard clinically used ECG leads (Einthoven and Wilson) and body surface potential maps (BSPM). The non-deforming models consider the heart at its ventricular end-diastatic, end-diastolic and end-systolic states. The standard leads show negligible differences during P-Wave and QRS-Complex, yet during T-Wave the leads closest to the heart show prominent differences in amplitude. When looking at the BSPM, there are no notable differences during the P-Wave, but effects of cardiac motion can be observed already during the QRS-Complex, increasing further during the T-Wave. We conclude that for the modeling of activation (P-Wave/QRS-Complex), the associated effort of simulating a complete electro-mechanical approach is not worth the computational cost. But when looking at ventricular repolarization (T-Wave) in standard leads as well as BSPM, there are areas where the signal can be influenced by cardiac motion of the heart to an extent that should not be ignored.
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Affiliation(s)
- Robin Moss
- 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
| | - Eike Moritz Wülfers
- 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
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- 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
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14
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Vila M, Rivolta MW, Luongo G, Unger LA, Luik A, Gigli L, Lombardi F, Loewe A, Sassi R. Atrial Flutter Mechanism Detection Using Directed Network Mapping. Front Physiol 2021; 12:749635. [PMID: 34764882 PMCID: PMC8577834 DOI: 10.3389/fphys.2021.749635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/28/2021] [Indexed: 11/13/2022] Open
Abstract
Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios.
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Affiliation(s)
- Muhamed Vila
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
| | | | - Giorgio Luongo
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Laura Anna Unger
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Armin Luik
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Lorenzo Gigli
- UOC Malattie Cardiovascolari, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Federico Lombardi
- UOC Malattie Cardiovascolari, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Roberto Sassi
- Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy
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15
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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: 70] [Impact Index Per Article: 23.3] [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.
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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
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16
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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.
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17
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Kovacheva E, Gerach T, Schuler S, Ochs M, Dössel O, Loewe A. Causes of altered ventricular mechanics in hypertrophic cardiomyopathy: an in-silico study. Biomed Eng Online 2021; 20:69. [PMID: 34294108 PMCID: PMC8296558 DOI: 10.1186/s12938-021-00900-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/08/2021] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Hypertrophic cardiomyopathy (HCM) is typically caused by mutations in sarcomeric genes leading to cardiomyocyte disarray, replacement fibrosis, impaired contractility, and elevated filling pressures. These varying tissue properties are associated with certain strain patterns that may allow to establish a diagnosis by means of non-invasive imaging without the necessity of harmful myocardial biopsies or contrast agent application. With a numerical study, we aim to answer: how the variability in each of these mechanisms contributes to altered mechanics of the left ventricle (LV) and if the deformation obtained in in-silico experiments is comparable to values reported from clinical measurements. METHODS We conducted an in-silico sensitivity study on physiological and pathological mechanisms potentially underlying the clinical HCM phenotype. The deformation of the four-chamber heart models was simulated using a finite-element mechanical solver with a sliding boundary condition to mimic the tissue surrounding the heart. Furthermore, a closed-loop circulatory model delivered the pressure values acting on the endocardium. Deformation measures and mechanical behavior of the heart models were evaluated globally and regionally. RESULTS Hypertrophy of the LV affected the course of strain, strain rate, and wall thickening-the root-mean-squared difference of the wall thickening between control (mean thickness 10 mm) and hypertrophic geometries (17 mm) was >10%. A reduction of active force development by 40% led to less overall deformation: maximal radial strain reduced from 26 to 21%. A fivefold increase in tissue stiffness caused a more homogeneous distribution of the strain values among 17 heart segments. Fiber disarray led to minor changes in the circumferential and radial strain. A combination of pathological mechanisms led to reduced and slower deformation of the LV and halved the longitudinal shortening of the LA. CONCLUSIONS This study uses a computer model to determine the changes in LV deformation caused by pathological mechanisms that are presumed to underlay HCM. This knowledge can complement imaging-derived information to obtain a more accurate diagnosis of HCM.
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Affiliation(s)
- Ekaterina Kovacheva
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany
| | - Tobias Gerach
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany
| | - Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany
| | - Marco Ochs
- Department of Cardiology, Theresienkrankenhaus, Academic Teaching Hospital of Heidelberg University, Bassermannstr.1, 68165, Mannheim, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany.
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18
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Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach. MATHEMATICS 2021. [DOI: 10.3390/math9111247] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [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.
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19
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Nagel C, Luongo G, Azzolin L, Schuler S, Dössel O, Loewe A. Non-Invasive and Quantitative Estimation of Left Atrial Fibrosis Based on P Waves of the 12-Lead ECG-A Large-Scale Computational Study Covering Anatomical Variability. J Clin Med 2021; 10:1797. [PMID: 33924210 PMCID: PMC8074591 DOI: 10.3390/jcm10081797] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 04/09/2021] [Accepted: 04/13/2021] [Indexed: 11/21/2022] Open
Abstract
The arrhythmogenesis of atrial fibrillation is associated with the presence of fibrotic atrial tissue. Not only fibrosis but also physiological anatomical variability of the atria and the thorax reflect in altered morphology of the P wave in the 12-lead electrocardiogram (ECG). Distinguishing between the effects on the P wave induced by local atrial substrate changes and those caused by healthy anatomical variations is important to gauge the potential of the 12-lead ECG as a non-invasive and cost-effective tool for the early detection of fibrotic atrial cardiomyopathy to stratify atrial fibrillation propensity. In this work, we realized 54,000 combinations of different atria and thorax geometries from statistical shape models capturing anatomical variability in the general population. For each atrial model, 10 different volume fractions (0-45%) were defined as fibrotic. Electrophysiological simulations in sinus rhythm were conducted for each model combination and the respective 12-lead ECGs were computed. P wave features (duration, amplitude, dispersion, terminal force in V1) were extracted and compared between the healthy and the diseased model cohorts. All investigated feature values systematically in- or decreased with the left atrial volume fraction covered by fibrotic tissue, however value ranges overlapped between the healthy and the diseased cohort. Using all extracted P wave features as input values, the amount of the fibrotic left atrial volume fraction was estimated by a neural network with an absolute root mean square error of 8.78%. Our simulation results suggest that although all investigated P wave features highly vary for different anatomical properties, the combination of these features can contribute to non-invasively estimate the volume fraction of atrial fibrosis using ECG-based machine learning approaches.
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Affiliation(s)
- Claudia Nagel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany; (G.L.); (L.A.); (S.S.); (O.D.); (A.L.)
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20
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Azzolin L, Schuler S, Dössel O, Loewe A. A Reproducible Protocol to Assess Arrhythmia Vulnerability in silico: Pacing at the End of the Effective Refractory Period. Front Physiol 2021; 12:656411. [PMID: 33868025 PMCID: PMC8047415 DOI: 10.3389/fphys.2021.656411] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 03/10/2021] [Indexed: 01/31/2023] Open
Abstract
In both clinical and computational studies, different pacing protocols are used to induce arrhythmia and non-inducibility is often considered as the endpoint of treatment. The need for a standardized methodology is urgent since the choice of the protocol used to induce arrhythmia could lead to contrasting results, e.g., in assessing atrial fibrillation (AF) vulnerabilty. Therefore, we propose a novel method-pacing at the end of the effective refractory period (PEERP)-and compare it to state-of-the-art protocols, such as phase singularity distribution (PSD) and rapid pacing (RP) in a computational study. All methods were tested by pacing from evenly distributed endocardial points at 1 cm inter-point distance in two bi-atrial geometries. Seven different atrial models were implemented: five cases without specific AF-induced remodeling but with decreasing global conduction velocity and two persistent AF cases with an increasing amount of fibrosis resembling different substrate remodeling stages. Compared with PSD and RP, PEERP induced a larger variety of arrhythmia complexity requiring, on average, only 2.7 extra-stimuli and 3 s of simulation time to initiate reentry. Moreover, PEERP and PSD were the protocols which unveiled a larger number of areas vulnerable to sustain stable long living reentries compared to RP. Finally, PEERP can foster standardization and reproducibility, since, in contrast to the other protocols, it is a parameter-free method. Furthermore, we discuss its clinical applicability. We conclude that the choice of the inducing protocol has an influence on both initiation and maintenance of AF and we propose and provide PEERP as a reproducible method to assess arrhythmia vulnerability.
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Affiliation(s)
- Luca Azzolin
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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21
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Luongo G, Schuler S, Luik A, Almeida TP, Soriano DC, Dossel O, Loewe A. Non-Invasive Characterization of Atrial Flutter Mechanisms Using Recurrence Quantification Analysis on the ECG: A Computational Study. IEEE Trans Biomed Eng 2021; 68:914-925. [PMID: 32746003 DOI: 10.1109/tbme.2020.2990655] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Atrial flutter (AFl) is a common arrhythmia that can be categorized according to different self-sustained electrophysiological mechanisms. The non-invasive discrimination of such mechanisms would greatly benefit ablative methods for AFl therapy as the driving mechanisms would be described prior to the invasive procedure, helping to guide ablation. In the present work, we sought to implement recurrence quantification analysis (RQA) on 12-lead ECG signals from a computational framework to discriminate different electrophysiological mechanisms sustaining AFl. METHODS 20 different AFl mechanisms were generated in 8 atrial models and were propagated into 8 torso models via forward solution, resulting in 1,256 sets of 12-lead ECG signals. Principal component analysis was applied on the 12-lead ECGs, and six RQA-based features were extracted from the most significant principal component scores in two different approaches: individual component RQA and spatial reduced RQA. RESULTS In both approaches, RQA-based features were significantly sensitive to the dynamic structures underlying different AFl mechanisms. Hit rate as high as 67.7% was achieved when discriminating the 20 AFl mechanisms. RQA-based features estimated for a clinical sample suggested high agreement with the results found in the computational framework. CONCLUSION RQA has been shown an effective method to distinguish different AFl electrophysiological mechanisms in a non-invasive computational framework. A clinical 12-lead ECG used as proof of concept showed the value of both the simulations and the methods. SIGNIFICANCE The non-invasive discrimination of AFl mechanisms helps to delineate the ablation strategy, reducing time and resources required to conduct invasive cardiac mapping and ablation procedures.
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22
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Luongo G, Azzolin L, Rivolta MW, Sassi R, Martinez JP, Laguna P, Dossel O, Loewe A. Non-Invasive Identification of Atrial Fibrillation Driver Location Using the 12-lead ECG: Pulmonary Vein Rotors vs. other Locations. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:410-413. [PMID: 33018015 DOI: 10.1109/embc44109.2020.9176135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Atrial fibrillation (AF) is an irregular heart rhythm due to disorganized atrial electrical activity, often sustained by rotational drivers called rotors. In the present work, we sought to characterize and discriminate whether simulated single stable rotors are located in the pulmonary veins (PVs) or not, only by using non-invasive signals (i.e., the 12-lead ECG). Several features have been extracted from the signals, such as Hjort descriptors, recurrence quantification analysis (RQA), and principal component analysis. All the extracted features have shown significant discriminatory power, with particular emphasis to the RQA parameters. A decision tree classifier achieved 98.48% accuracy, 83.33% sensitivity, and 100% specificity on simulated data.Clinical Relevance-This study might guide ablation procedures, suggesting doctors to proceed directly in some patients with a pulmonary veins isolation, and avoiding the prior use of an invasive atrial mapping system.
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Frisch D, Oesterlein TG, Unger LA, Lenis G, Wakili R, Schmitt C, Luik A, Dossel O, Loewe A. Mapping and Removing the Ventricular Far Field Component in Unipolar Atrial Electrograms. IEEE Trans Biomed Eng 2020; 67:2905-2915. [DOI: 10.1109/tbme.2020.2973471] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Abstract
Atrial anisotropy affects electrical propagation patterns, anchor locations of atrial reentrant drivers, and atrial mechanics. However, patient-specific atrial fibre fields and anisotropy measurements are not currently available, and consequently assigning fibre fields to atrial models is challenging. We aimed to construct an atrial fibre atlas from a high-resolution DTMRI dataset that optimally reproduces electrophysiology simulation predictions corresponding to patient-specific fibre fields, and to develop a methodology for automatically assigning fibres to patient-specific anatomies. We extended an atrial coordinate system to map the pulmonary veins, vena cava and appendages to standardised positions in the coordinate system corresponding to the average location across the anatomies. We then expressed each fibre field in this atrial coordinate system and calculated an average fibre field. To assess the effects of fibre field on patient-specific modelling predictions, we calculated paced activation time maps and electrical driver locations during AF. In total, 756 activation time maps were calculated (7 anatomies with 9 fibre maps and 2 pacing locations, for the endocardial, epicardial and bilayer surface models of the LA and RA). Patient-specific fibre fields had a relatively small effect on average paced activation maps (range of mean local activation time difference for LA fields: 2.67-3.60 ms, and for RA fields: 2.29-3.44 ms), but had a larger effect on maximum LAT differences (range for LA 12.7-16.6%; range for RA 11.9-15.0%). A total of 126 phase singularity density maps were calculated (7 anatomies with 9 fibre maps for the LA and RA bilayer models). The fibre field corresponding to anatomy 1 had the highest median PS density map correlation coefficient for LA bilayer simulations (0.44 compared to the other correlations, ranging from 0.14 to 0.39), while the average fibre field had the highest correlation for the RA bilayer simulations (0.61 compared to the other correlations, ranging from 0.37 to 0.56). For sinus rhythm simulations, average activation time is robust to fibre field direction; however, maximum differences can still be significant. Patient specific fibres are more important for arrhythmia simulations, particularly in the left atrium. We propose using the fibre field corresponding to DTMRI dataset 1 for LA simulations, and the average fibre field for RA simulations as these optimally predicted arrhythmia properties.
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Roney CH, Pashaei A, Meo M, Dubois R, Boyle PM, Trayanova NA, Cochet H, Niederer SA, Vigmond EJ. Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes. Med Image Anal 2019; 55:65-75. [PMID: 31026761 PMCID: PMC6543067 DOI: 10.1016/j.media.2019.04.004] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 03/07/2019] [Accepted: 04/15/2019] [Indexed: 11/26/2022]
Abstract
We introduce a coordinate system for the atria based on anatomical landmarks. We construct the coordinates from solutions to Laplace’s equation. We demonstrate the mapping of both scalar and vector data between different atria. The coordinate system was used for registration and 2D visualisation of multimodal data. Patient specific meshes with atrial structures and fibre direction were constructed using just five landmark points.
Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system. In the atria, this is challenging due to the complexity and variability of the anatomy. We aimed to develop and validate a Universal Atrial Coordinate (UAC) system for the following applications: combination and assessment of multimodal data; comparison of spatial data across patients; 2D visualization; and construction of patient specific geometries to test mechanistic hypotheses. Left and right atrial LGE-MRI data were segmented and meshed. Two coordinates were calculated for each atrium by solving Laplace’s equation, with boundary conditions assigned using five landmark points. The coordinate system was used to map spatial information between atrial meshes, including scalar fields measured using different mapping modalities, and atrial anatomic structures and fibre directions from a reference geometry. Average error in point transfer from a source mesh to a destination mesh and back again was less than 0.1 mm for the left atrium and 0.02 mm for the right atrium. Patient specific meshes were constructed using the coordinate system and phase singularity density maps from arrhythmia simulations were visualised in 2D. In conclusion, we have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation.
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Affiliation(s)
- Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom.
| | - Ali Pashaei
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France; IMB Bordeaux Institute of Mathematics, University of Bordeaux, 351 cours de la Libération, Talence 33405, France
| | - Marianna Meo
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France; University of Bordeaux, CRCTB, U1045, Bordeaux, France; INSERM, CRCTB, U1045, Bordeaux, France
| | - Rémi Dubois
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France; University of Bordeaux, CRCTB, U1045, Bordeaux, France; INSERM, CRCTB, U1045, Bordeaux, France
| | | | | | - Hubert Cochet
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France
| | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom
| | - Edward J Vigmond
- Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Pessac-Bordeaux, France; IMB Bordeaux Institute of Mathematics, University of Bordeaux, 351 cours de la Libération, Talence 33405, France
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Loewe A, Poremba E, Oesterlein T, Luik A, Schmitt C, Seemann G, Dössel O. Patient-Specific Identification of Atrial Flutter Vulnerability-A Computational Approach to Reveal Latent Reentry Pathways. Front Physiol 2019; 9:1910. [PMID: 30692934 PMCID: PMC6339942 DOI: 10.3389/fphys.2018.01910] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 12/18/2018] [Indexed: 11/23/2022] Open
Abstract
Atypical atrial flutter (AFlut) is a reentrant arrhythmia which patients frequently develop after ablation for atrial fibrillation (AF). Indeed, substrate modifications during AF ablation can increase the likelihood to develop AFlut and it is clinically not feasible to reliably and sensitively test if a patient is vulnerable to AFlut. Here, we present a novel method based on personalized computational models to identify pathways along which AFlut can be sustained in an individual patient. We build a personalized model of atrial excitation propagation considering the anatomy as well as the spatial distribution of anisotropic conduction velocity and repolarization characteristics based on a combination of a priori knowledge on the population level and information derived from measurements performed in the individual patient. The fast marching scheme is employed to compute activation times for stimuli from all parts of the atria. Potential flutter pathways are then identified by tracing loops from wave front collision sites and constricting them using a geometric snake approach under consideration of the heterogeneous wavelength condition. In this way, all pathways along which AFlut can be sustained are identified. Flutter pathways can be instantiated by using an eikonal-diffusion phase extrapolation approach and a dynamic multifront fast marching simulation. In these dynamic simulations, the initial pattern eventually turns into the one driven by the dominant pathway, which is the only pathway that can be observed clinically. We assessed the sensitivity of the flutter pathway maps with respect to conduction velocity and its anisotropy. Moreover, we demonstrate the application of tailored models considering disease-specific repolarization properties (healthy, AF-remodeled, potassium channel mutations) as well as applicabiltiy on a clinical dataset. Finally, we tested how AFlut vulnerability of these substrates is modulated by exemplary antiarrhythmic drugs (amiodarone, dronedarone). Our novel method allows to assess the vulnerability of an individual patient to develop AFlut based on the personal anatomical, electrophysiological, and pharmacological characteristics. In contrast to clinical electrophysiological studies, our computational approach provides the means to identify all possible AFlut pathways and not just the currently dominant one. This allows to consider all relevant AFlut pathways when tailoring clinical ablation therapy in order to reduce the development and recurrence of AFlut.
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Affiliation(s)
- Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Emanuel Poremba
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Tobias Oesterlein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Armin Luik
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Claus Schmitt
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Gunnar Seemann
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg Bad Krozingen, Freiburg, Germany
- Faculty of Medicine, Albert-Ludwigs University, Freiburg, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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27
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Andlauer R, Seemann G, Baron L, Dössel O, Kohl P, Platonov P, Loewe A. Influence of left atrial size on P-wave morphology: differential effects of dilation and hypertrophy. Europace 2018; 20:iii36-iii44. [DOI: 10.1093/europace/euy231] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 09/19/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- Robin Andlauer
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 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
| | - Lukas Baron
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, Germany
| | - Peter Kohl
- 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
| | - Pyotr Platonov
- Department of Cardiology and The Center for Integrative Electrocardiology at Lund University (CIEL), Lund, Sweden
- Arrhythmia Clinic, Skåne University Hospital, Lund, Sweden
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe, Germany
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28
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Dossel O, Oesterlein T, Unger L, Loewe A, Schmitt C, Luik A. Spatio-temporal Analysis of Multichannel Atrial Electrograms Based on a Concept of Active Areas. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:490-493. [PMID: 30440441 DOI: 10.1109/embc.2018.8512410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Atrial tachycardia and atrial flutter are frequent arrhythmia that occur spontaneously and after ablation of atrial fibrillation. Depolarization waves that differ significantly from sinus rhythm propagate across the atria with high frequency (typically 140 to 220 beats per minute). A detailed and personalized analysis of the spread of depolarization is imperative for a successful ablation therapy. Thus, catheters with several electrodes are employed to measure multichannel electrograms inside the atria. Here we propose a new concept for spatio-temporal analysis of multichannel electrograms during atrial tachycardia and atrial flutter. It is based on the calculation of simultaneously active areas. The method allows to identify atrial tachycardia and to automatically distinguish between subtypes of focal activity, micro-reentry and macro-reentry.
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29
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Oesterlein TG, Loewe A, Lenis G, Luik A, Schmitt C, Dossel O. Automatic Identification of Reentry Mechanisms and Critical Sites During Atrial Tachycardia by Analyzing Areas of Activity. IEEE Trans Biomed Eng 2018; 65:2334-2344. [DOI: 10.1109/tbme.2018.2794321] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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30
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Alessandrini M, Valinoti M, Unger L, Oesterlein T, Dössel O, Corsi C, Loewe A, Severi S. A Computational Framework to Benchmark Basket Catheter Guided Ablation in Atrial Fibrillation. Front Physiol 2018; 9:1251. [PMID: 30298012 PMCID: PMC6161611 DOI: 10.3389/fphys.2018.01251] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 08/20/2018] [Indexed: 11/13/2022] Open
Abstract
Catheter ablation is a curative therapeutic approach for atrial fibrillation (AF). Ablation of rotational sources based on basket catheter measurements has been proposed as a promising approach in patients with persistent AF to complement pulmonary vein isolation. However, clinically reported success rates are equivocal calling for a mechanistic investigation under controlled conditions. We present a computational framework to benchmark ablation strategies considering the whole cycle from excitation propagation to electrogram acquisition and processing to virtual therapy. Fibrillation was induced in a patient-specific 3D volumetric model of the left atrium, which was homogeneously remodeled to sustain reentry. The resulting extracellular potential field was sampled using models of grid catheters as well as realistically deformed basket catheters considering the specific atrial anatomy. The virtual electrograms were processed to compute phase singularity density maps to target rotor tips with up to three circular ablations. Stable rotors were successfully induced in different regions of the homogeneously remodeled atrium showing that rotors are not constrained to unique anatomical structures or locations. Density maps of rotor tip trajectories correctly identified and located the rotors (deviation < 10 mm) based on catheter recordings only for sufficient resolution (inter-electrode distance ≤3 mm) and proximity to the wall (≤10 mm). Targeting rotor sites with ablation did not stop reentries in the homogeneously remodeled atria independent from lesion size (1-7 mm radius), from linearly connecting lesions with anatomical obstacles, and from the number of rotors targeted sequentially (≤3). Our results show that phase maps derived from intracardiac electrograms can be a powerful tool to map atrial activation patterns, yet they can also be misleading due to inaccurate localization of the rotor tip depending on electrode resolution and distance to the wall. This should be considered to avoid ablating regions that are in fact free of rotor sources of AF. In our experience, ablation of rotor sites was not successful to stop fibrillation. Our comprehensive simulation framework provides the means to holistically benchmark ablation strategies in silico under consideration of all steps involved in electrogram-based therapy and, in future, could be used to study more heterogeneously remodeled disease states as well.
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Affiliation(s)
- Martino Alessandrini
- Department of Electronic Engineering and Information Technology, University of Bologna, Cesena, Italy
| | - Maddalena Valinoti
- Department of Electronic Engineering and Information Technology, University of Bologna, Cesena, Italy
| | - Laura Unger
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Tobias Oesterlein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Cristiana Corsi
- Department of Electronic Engineering and Information Technology, University of Bologna, Cesena, Italy
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Stefano Severi
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
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31
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Novel Electrocardiographic Criteria for Real-Time Assessment of Anterior Mitral Line Block. JACC Clin Electrophysiol 2018; 4:920-932. [DOI: 10.1016/j.jacep.2018.03.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 03/01/2018] [Accepted: 03/06/2018] [Indexed: 11/18/2022]
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32
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Loewe A, Dössel O. Commentary: Virtual In-Silico Modeling Guided Catheter Ablation Predicts Effective Linear Ablation Lesion Set for Longstanding Persistent Atrial Fibrillation: Multicenter Prospective Randomized Study. Front Physiol 2018; 8:1113. [PMID: 29313849 PMCID: PMC5744431 DOI: 10.3389/fphys.2017.01113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Accepted: 12/15/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Olaf Dössel
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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33
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Andlauer R, Loewe A, Dössel O, Seemann G. Effect of left atrial hypertrophy on P-wave morphology in a computational model. CURRENT DIRECTIONS IN BIOMEDICAL ENGINEERING 2016. [DOI: 10.1515/cdbme-2016-0133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
AbstractP-wave assessment is frequently used in clinical practice to recognize atrial abnormalities. However, the use of P-wave criteria to diagnose specific atrial abnormalities such as left atrial enlargement has shown to be of limited use since these abnormalities can be difficult to distinguish using P-wave criteria to date. Hence, a mechanistic understanding how specific atrial abnormalities affect the P-wave is desirable. In this study, we investigated the effect of left atrial hypertrophy on P-wave morphology using an in silico approach. In a cohort of four realistic patient models, we homogeneously increased left atrial wall thickness in up to seven degrees of left atrial hypertrophy. Excitation conduction was simulated using a monodomain finite element approach. Then, the resulting transmembrane voltage distribution was used to calculate the corresponding extracellular potential distribution on the torso by solving the forward problem of electrocardiography. In our simulation setup, left atrial wall thickening strongly correlated with an increased absolute value of the P-wave terminal force (PTF) in Wilson lead V1 due to an increased negative amplitude while P-wave duration was unaffected. Remarkably, an increased PTF-V1 has often been associated with left atrial enlargement which is defined as a rather increased left atrial volume than a solely thickened left atrium. Hence, the observed contribution of left atrial wall thickness changes to PTF-V1 might explain the poor empirical correlation of left atrial enlargement with PTF-V1.
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Affiliation(s)
- Robin Andlauer
- 1Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Germany
| | - Axel Loewe
- 2Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76128 Karlsruhe
| | - Olaf Dössel
- 1Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Germany
| | - Gunnar Seemann
- 1Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Germany
- 3Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg, Bad Krozingen, Freiburg, Germany; and Medical Department, Albert-Ludwigs University, Freiburg, Germany
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