1
|
Serinagaoglu Dogrusoz Y, Bear LR, Bergquist JA, Rababah AS, Good W, Stoks J, Svehlikova J, van Dam E, Brooks DH, MacLeod RS. Evaluation of five methods for the interpolation of bad leads in the solution of the inverse electrocardiography problem. Physiol Meas 2024; 45:095012. [PMID: 39197474 DOI: 10.1088/1361-6579/ad74d6] [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: 03/06/2024] [Accepted: 08/28/2024] [Indexed: 09/01/2024]
Abstract
Objective.This study aims to assess the sensitivity of epicardial potential-based electrocardiographic imaging (ECGI) to the removal or interpolation of bad leads.Approach.We utilized experimental data from two distinct centers. Langendorff-perfused pig (n= 2) and dog (n= 2) hearts were suspended in a human torso-shaped tank and paced from the ventricles. Six different bad lead configurations were designed based on clinical experience. Five interpolation methods were applied to estimate the missing data. Zero-order Tikhonov regularization was used to solve the inverse problem for complete data, data with removed bad leads, and interpolated data. We assessed the quality of interpolated ECG signals and ECGI reconstructions using several metrics, comparing the performance of interpolation methods and the impact of bad lead removal versus interpolation on ECGI.Main results.The performance of ECG interpolation strongly correlated with ECGI reconstruction. The hybrid method exhibited the best performance among interpolation techniques, followed closely by the inverse-forward and Kriging methods. Bad leads located over high amplitude/high gradient areas on the torso significantly impacted ECGI reconstructions, even with minor interpolation errors. The choice between removing or interpolating bad leads depends on the location of missing leads and confidence in interpolation performance. If uncertainty exists, removing bad leads is the safer option, particularly when they are positioned in high amplitude/high gradient regions. In instances where interpolation is necessary, the inverse-forward and Kriging methods, which do not require training, are recommended.Significance.This study represents the first comprehensive evaluation of the advantages and drawbacks of interpolating versus removing bad leads in the context of ECGI, providing valuable insights into ECGI performance.
Collapse
Affiliation(s)
- Y Serinagaoglu Dogrusoz
- Middle East Technical University, Department of Electrical and Electronics Engineering, Ankara, Turkey
| | - L R Bear
- IHU-LIRYC, Fondation Bordeaux Université, Pessac, France
- Univ. Bordeaux, CRCTB, U1045 Bordeaux, France
- INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045 Bordeaux, France
| | - J A Bergquist
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - A S Rababah
- Jordanian Royal Medical Services, Amman, Jordan
| | - W Good
- Acutus Medical, Carlsbad, CA, United States of America
| | - J Stoks
- Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | - J Svehlikova
- Slovak Academy of Sciences, Institute of Measurement Science, Bratislava, Slovakia
| | | | - D H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, United States of America
| | - R S MacLeod
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
- School of Medicine, University of Utah, Salt Lake City, UT, United States of America
| |
Collapse
|
2
|
Jiang X, Missel R, Toloubidokhti M, Gillette K, Prassl AJ, Plank G, Horacek BM, Sapp JL, Wang L. Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2733-2744. [PMID: 38478452 PMCID: PMC11330696 DOI: 10.1109/tmi.2024.3377094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
State-space modeling (SSM) provides a general framework for many image reconstruction tasks. Error in a priori physiological knowledge of the imaging physics, can bring incorrectness to solutions. Modern deep-learning approaches show great promise but lack interpretability and rely on large amounts of labeled data. In this paper, we present a novel hybrid SSM framework for electrocardiographic imaging (ECGI) to leverage the advantage of state-space formulations in data-driven learning. We first leverage the physics-based forward operator to supervise the learning. We then introduce neural modeling of the transition function and the associated Bayesian filtering strategy. We applied the hybrid SSM framework to reconstruct electrical activity on the heart surface from body-surface potentials. In unsupervised settings of both in-silico and in-vivo data without cardiac electrical activity as the ground truth to supervise the learning, we demonstrated improved ECGI performances of the hybrid SSM framework trained from a small number of ECG observations in comparison to the fixed SSM. We further demonstrated that, when in-silico simulation data becomes available, mixed supervised and unsupervised training of the hybrid SSM achieved a further 40.6% and 45.6% improvements, respectively, in comparison to traditional ECGI baselines and supervised data-driven ECGI baselines for localizing the origin of ventricular activations in real data.
Collapse
|
3
|
Noheria A, Shahab A, Andrews C, Cuculich PS, Rudy Y. Pilot study to evaluate left-to-right ventricular offset in biventricular pacing-comparison of electrocardiographic imaging and ECG. J Cardiovasc Electrophysiol 2024; 35:1185-1195. [PMID: 38591763 DOI: 10.1111/jce.16272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/14/2024] [Accepted: 03/23/2024] [Indexed: 04/10/2024]
Abstract
INTRODUCTION Biventricular pacing (BiVp) improves outcomes in systolic heart failure patients with electrical dyssynchrony. BiVp is delivered from epicardial left ventricular (LV) and endocardial right ventricular (RV) electrodes. Acute electrical activation changes with different LV-RV stimulation offsets can help guide individually optimized BiVp programming. We sought to study the BiVp ventricular activation with different LV-RV offsets and compare with 12-lead ECG. METHODS In five patients with BiVp (63 ± 17-year-old, 80% male, LV ejection fraction 27 ± 6%), we evaluated acute ventricular epicardial activation, varying LV-RV offsets in 20 ms increments from -40 to 80 ms, using electrocardiographic imaging (ECGI) to obtain absolute ventricular electrical uncoupling (VEUabs, absolute difference in average LV and average RV activation time) and total activation time (TAT). For each patient, we calculated the correlation between ECGI and corresponding ECG (3D-QRS-area and QRS duration) with different LV-RV offsets. RESULTS The LV-RV offset to attain minimum VEUabs in individual patients ranged 20-60 ms. In all patients, a larger LV-RV offset was required to achieve minimum VEUabs (36 ± 17 ms) or 3D-QRS-area (40 ± 14 ms) than that for minimum TAT (-4 ± 9 ms) or QRS duration (-8 ± 11 ms). In individual patients, 3D-QRS-area correlated with VEUabs (r 0.65 ± 0.24) and QRS duration correlated with TAT (r 0.95 ± 0.02). Minimum VEUabs and minimum 3D-QRS-area were obtained by LV-RV offset within 20 ms of each other in all five patients. CONCLUSIONS LV-RV electrical uncoupling, as assessed by ECGI, can be minimized by optimizing LV-RV stimulation offset. 3D-QRS-area is a surrogate to identify LV-RV offset that minimizes LV-RV uncoupling.
Collapse
Affiliation(s)
- Amit Noheria
- Department of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Ahmed Shahab
- Department of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Christopher Andrews
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Phillip S Cuculich
- Cardiovascular Division, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Yoram Rudy
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| |
Collapse
|
4
|
Verheul LM, Groeneveld SA, Stoks J, Hoeksema WF, Cluitmans MJM, Postema PG, Wilde AAM, Volders PGA, Hassink RJ. The Dutch Idiopathic Ventricular Fibrillation Registry: progress report on the quest to identify the unidentifiable. Neth Heart J 2024; 32:238-244. [PMID: 38653923 PMCID: PMC11143118 DOI: 10.1007/s12471-024-01870-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/26/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Idiopathic ventricular fibrillation (iVF) is a rare cause of sudden cardiac arrest and, by definition, a diagnosis of exclusion. Due to the rarity of the disease, previous and current studies are limited by their retrospective design and small patient numbers. Even though the incidence of iVF has declined owing to the identification of new disease entities, an important subgroup of patients remains. AIM To expand the existing Dutch iVF Registry into a large nationwide cohort of patients initially diagnosed with iVF, to reveal the underlying cause of iVF in these patients, and to improve arrhythmia management. METHODS The Dutch iVF Registry includes sudden cardiac arrest survivors with an initial diagnosis of iVF. Clinical data and outcomes are collected. Outcomes include subsequent detection of a diagnosis other than 'idiopathic', arrhythmia recurrence and death. Non-invasive electrocardiographic imaging is used to investigate electropathological substrates and triggers of VF. RESULTS To date, 432 patients have been included in the registry (median age at event 40 years (interquartile range 28-52)), 61% male. During a median follow-up of 6 (2-12) years, 38 patients (9%) received a diagnosis other than 'idiopathic'. Eleven iVF patients were characterised with electrocardiographic imaging. CONCLUSION The Dutch iVF Registry is currently the largest of its kind worldwide. In this heterogeneous population of index patients, we aim to identify common functional denominators associated with iVF. With the implementation of non-invasive electrocardiographic imaging and other diagnostic modalities (e.g. echocardiographic deformation, cardiac magnetic resonance), we advance the possibilities to reveal pro-fibrillatory substrates.
Collapse
Affiliation(s)
- Lisa M Verheul
- Department of Cardiology, University Medical Centre Utrecht, Utrecht, The Netherlands.
| | - Sanne A Groeneveld
- Department of Cardiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Job Stoks
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Wiert F Hoeksema
- Department of Cardiology, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, The Netherlands
| | - Matthijs J M Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Pieter G Postema
- Department of Cardiology, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, The Netherlands
| | - Arthur A M Wilde
- Department of Cardiology, Amsterdam UMC, location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, The Netherlands
| | - Paul G A Volders
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Rutger J Hassink
- Department of Cardiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| |
Collapse
|
5
|
Hu W, Bian G, Huang L, Pi Y, Zhang X, Zhang X, de Albuquerque VHC, Wu W. Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing. IEEE J Biomed Health Inform 2024; 28:2500-2511. [PMID: 38051611 DOI: 10.1109/jbhi.2023.3339382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Emotion is a complex physiological and psychological activity, accompanied by subjective physiological sensations and objective physiological changes. The body sensation map describes the changes in body sensation associated with emotion in a topographic manner, but it relies on subjective evaluations from participants. Physiological signals are a more reliable measure of emotion, but most research focuses on the central nervous system, neglecting the importance of the peripheral nervous system. In this study, a body surface potential mapping (BSPM) system was constructed, and an experiment was designed to induce emotions and obtain high-density body surface potential information under negative and non-negative emotions. Then, by constructing and analyzing the functional connectivity network of BSPs, the high-density electrophysiological characteristics are obtained and visualized as bodily emotion maps. The results showed that the functional connectivity network of BSPs under negative emotions had denser connections, and emotion maps based on local clustering coefficient (LCC) are consistent with BSMs under negative emotions. in addition, our features can classify negative and non-negative emotions with the highest classification accuracy of 80.77%. In conclusion, this study constructs an emotion map based on high-density BSPs, which offers a novel approach to psychophysiological computing.
Collapse
|
6
|
Ran A, Cheng L, Xie S, Liu M, Pu C, Hu H, Liu H. Nonlocal based FISTA network for noninvasive cardiac transmembrane potential imaging. Phys Med Biol 2024; 69:075018. [PMID: 38417179 DOI: 10.1088/1361-6560/ad2e6d] [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: 04/23/2023] [Accepted: 02/28/2024] [Indexed: 03/01/2024]
Abstract
Objective. The primary aim of our study is to advance our understanding and diagnosis of cardiac diseases. We focus on the reconstruction of myocardial transmembrane potential (TMP) from body surface potential mapping.Approach. We introduce a novel methodology for the reconstruction of the dynamic distribution of TMP. This is achieved through the integration of convolutional neural networks with conventional optimization algorithms. Specifically, we utilize the subject-specific transfer matrix to describe the dynamic changes in TMP distribution and ECG observations at the body surface. To estimate the TMP distribution, we employ LNFISTA-Net, a learnable non-local regularized iterative shrinkage-thresholding network. The coupled estimation processes are iteratively repeated until convergence.Main results. Our experiments demonstrate the capabilities and benefits of this strategy. The results highlight the effectiveness of our approach in accurately estimating the TMP distribution, thereby providing a reliable method for the diagnosis of cardiac diseases.Significance. Our approach demonstrates promising results, highlighting its potential utility for a range of applications in the medical field. By providing a more accurate and dynamic reconstruction of TMP, our methodology could significantly improve the diagnosis and treatment of cardiac diseases, thereby contributing to advancements in healthcare.
Collapse
Affiliation(s)
- Ao Ran
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, People's Republic of China
| | - Linsheng Cheng
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, People's Republic of China
| | - Shuting Xie
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, People's Republic of China
| | - Muqing Liu
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, People's Republic of China
| | - Cailing Pu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, People's Republic of China
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, People's Republic of China
| | - Huafeng Liu
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, People's Republic of China
| |
Collapse
|
7
|
Goldie FC, Lee MMY, Coats CJ, Nordin S. Advances in Multi-Modality Imaging in Hypertrophic Cardiomyopathy. J Clin Med 2024; 13:842. [PMID: 38337535 PMCID: PMC10856479 DOI: 10.3390/jcm13030842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/27/2024] [Accepted: 01/28/2024] [Indexed: 02/12/2024] Open
Abstract
Hypertrophic cardiomyopathy (HCM) is characterized by abnormal growth of the myocardium with myofilament disarray and myocardial hyper-contractility, leading to left ventricular hypertrophy and fibrosis. Where culprit genes are identified, they typically relate to cardiomyocyte sarcomere structure and function. Multi-modality imaging plays a crucial role in the diagnosis, monitoring, and risk stratification of HCM, as well as in screening those at risk. Following the recent publication of the first European Society of Cardiology (ESC) cardiomyopathy guidelines, we build on previous reviews and explore the roles of electrocardiography, echocardiography, cardiac magnetic resonance (CMR), cardiac computed tomography (CT), and nuclear imaging. We examine each modality's strengths along with their limitations in turn, and discuss how they can be used in isolation, or in combination, to facilitate a personalized approach to patient care, as well as providing key information and robust safety and efficacy evidence within new areas of research.
Collapse
Affiliation(s)
- Fraser C. Goldie
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow G12 8TA, UK; (F.C.G.); (M.M.Y.L.); (C.J.C.)
| | - Matthew M. Y. Lee
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow G12 8TA, UK; (F.C.G.); (M.M.Y.L.); (C.J.C.)
| | - Caroline J. Coats
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow G12 8TA, UK; (F.C.G.); (M.M.Y.L.); (C.J.C.)
- Department of Cardiology, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| | - Sabrina Nordin
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow G12 8TA, UK; (F.C.G.); (M.M.Y.L.); (C.J.C.)
- Department of Cardiology, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| |
Collapse
|
8
|
van der Waal J, Meijborg V, Coronel R, Dubois R, Oostendorp T. Basis and applicability of noninvasive inverse electrocardiography: a comparison between cardiac source models. Front Physiol 2023; 14:1295103. [PMID: 38152249 PMCID: PMC10752226 DOI: 10.3389/fphys.2023.1295103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 11/30/2023] [Indexed: 12/29/2023] Open
Abstract
The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the inverse problem of electrocardiography. The method to solve the inverse problem depends on the chosen cardiac source model to describe cardiac electrical activity. In this paper, we describe the theoretical basis of two inverse methods based on the most commonly used cardiac source models: the epicardial potential model and the equivalent dipole layer model. We discuss similarities and differences in applicability, strengths and weaknesses and sketch a road towards improved inverse solutions by targeted use, sequential application or a combination of the two methods.
Collapse
Affiliation(s)
- Jeanne van der Waal
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Veronique Meijborg
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Ruben Coronel
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Rémi Dubois
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac, France
| | - Thom Oostendorp
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| |
Collapse
|
9
|
Bergquist JA, Zenger B, Rupp LC, Busatto A, Tate J, Brooks DH, Narayan A, MacLeod RS. Uncertainty quantification of the effect of cardiac position variability in the inverse problem of electrocardiographic imaging. Physiol Meas 2023; 44:105003. [PMID: 37734339 DOI: 10.1088/1361-6579/acfc32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 09/21/2023] [Indexed: 09/23/2023]
Abstract
Objective.Electrocardiographic imaging (ECGI) is a functional imaging modality that consists of two related problems, the forward problem of reconstructing body surface electrical signals given cardiac bioelectric activity, and the inverse problem of reconstructing cardiac bioelectric activity given measured body surface signals. ECGI relies on a model for how the heart generates bioelectric signals which is subject to variability in inputs. The study of how uncertainty in model inputs affects the model output is known as uncertainty quantification (UQ). This study establishes develops, and characterizes the application of UQ to ECGI.Approach.We establish two formulations for applying UQ to ECGI: a polynomial chaos expansion (PCE) based parametric UQ formulation (PCE-UQ formulation), and a novel UQ-aware inverse formulation which leverages our previously established 'joint-inverse' formulation (UQ joint-inverse formulation). We apply these to evaluate the effect of uncertainty in the heart position on the ECGI solutions across a range of ECGI datasets.Main results.We demonstrated the ability of our UQ-ECGI formulations to characterize the effect of parameter uncertainty on the ECGI inverse problem. We found that while the PCE-UQ inverse solution provided more complex outputs such as sensitivities and standard deviation, the UQ joint-inverse solution provided a more interpretable output in the form of a single ECGI solution. We find that between these two methods we are able to assess a wide range of effects that heart position variability has on the ECGI solution.Significance.This study, for the first time, characterizes in detail the application of UQ to the ECGI inverse problem. We demonstrated how UQ can provide insight into the behavior of ECGI using variability in cardiac position as a test case. This study lays the groundwork for future development of UQ-ECGI studies, as well as future development of ECGI formulations which are robust to input parameter variability.
Collapse
Affiliation(s)
- Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, United States of America
- Department of Biomedical Engineering, University of Utah, SLC, UT, United States of America
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, United States of America
- Department of Biomedical Engineering, University of Utah, SLC, UT, United States of America
- School of Medicine, University of Utah, SLC, UT, United States of America
| | - Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, United States of America
- Department of Biomedical Engineering, University of Utah, SLC, UT, United States of America
| | - Anna Busatto
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, United States of America
- Department of Biomedical Engineering, University of Utah, SLC, UT, United States of America
| | - Jess Tate
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
| | - Dana H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, United States of America
| | - Akil Narayan
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Department of Mathematics, University of Utah, SLC, UT, United States of America
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, United States of America
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, SLC, UT, United States of America
- Department of Biomedical Engineering, University of Utah, SLC, UT, United States of America
| |
Collapse
|
10
|
Yadan Z, Jian L, Jian W, Yifu L, Haiying L, Hairui L. An expert review of the inverse problem in electrocardiographic imaging for the non-invasive identification of atrial fibrillation drivers. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 240:107676. [PMID: 37343376 DOI: 10.1016/j.cmpb.2023.107676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/06/2023] [Accepted: 06/09/2023] [Indexed: 06/23/2023]
Abstract
BACKGROUND AND OBJECTIVE Electrocardiographic imaging (ECGI) has emerged as a non-invasive approach to identify atrial fibrillation (AF) driver sources. This paper aims to collect and review the current research literature on the ECGI inverse problem, summarize the research progress, and propose potential research directions for the future. METHODS AND RESULTS The effectiveness and feasibility of using ECGI to map AF driver sources may be influenced by several factors, such as inaccuracies in the atrial model due to heart movement or deformation, noise interference in high-density body surface potential (BSP), inconvenient and time-consuming BSP acquisition, errors in solving the inverse problem, and incomplete interpretation of the AF driving source information derived from the reconstructed epicardial potential. We review the current research progress on these factors and discuss possible improvement directions. Additionally, we highlight the limitations of ECGI itself, including the lack of a gold standard to validate the accuracy of ECGI technology in locating AF drivers and the challenges associated with guiding AF ablation based on post-processed epicardial potentials due to the intrinsic difference between epicardial and endocardial potentials. CONCLUSIONS Before performing ablation, ECGI can provide operators with predictive information about the underlying locations of AF driver by non-invasively and globally mapping the biatrial electrical activity. In the future, endocardial catheter mapping technology may benefit from the use of ECGI to enhance the diagnosis and ablation of AF.
Collapse
Affiliation(s)
- Zhang Yadan
- Institute of Biomedical Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
| | - Liang Jian
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, China
| | - Wu Jian
- Institute of Biomedical Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China.
| | - Li Yifu
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, China
| | - Li Haiying
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Li Hairui
- The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| |
Collapse
|
11
|
Marashly Q, Najjar SN, Hahn J, Rector GJ, Khawaja M, Chelu MG. Innovations in ventricular tachycardia ablation. J Interv Card Electrophysiol 2023; 66:1499-1518. [PMID: 35879516 DOI: 10.1007/s10840-022-01311-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 07/18/2022] [Indexed: 11/30/2022]
Abstract
Catheter ablation of ventricular arrhythmias (VAs) has evolved significantly over the past decade and is currently a well-established therapeutic option. Technological advances and improved understanding of VA mechanisms have led to tremendous innovations in VA ablation. The purpose of this review article is to provide an overview of current innovations in VA ablation. Mapping techniques, such as ultra-high density mapping, isochronal late activation mapping, and ripple mapping, have provided improved arrhythmogenic substrate delineation and potential procedural success while limiting duration of ablation procedure and potential hemodynamic compromise. Besides, more advanced mapping and ablation techniques such as epicardial and intramyocardial ablation approaches have allowed operators to more precisely target arrhythmogenic substrate. Moreover, advances in alternate energy sources, such as electroporation, as well as stereotactic radiation therapy have been proposed to be effective and safe. New catheters, such as the lattice and the saline-enhanced radiofrequency catheters, have been designed to provide deeper and more durable tissue ablation lesions compared to conventional catheters. Contact force optimization and baseline impedance modulation are important tools to optimize VT radiofrequency ablation and improve procedural success. Furthermore, advances in cardiac imaging, specifically cardiac MRI, have great potential in identifying arrhythmogenic substrate and evaluating ablation success. Overall, VA ablation has undergone significant advances over the past years. Innovations in VA mapping techniques, alternate energy source, new catheters, and utilization of cardiac imaging have great potential to improve overall procedural safety, hemodynamic stability, and procedural success.
Collapse
Affiliation(s)
- Qussay Marashly
- Division of Cardiology, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Salim N Najjar
- Division of Cardiology, Baylor College of Medicine, 7200 Cambridge Suite A6.137, MS: BCM621, Houston, TX, 77030, USA
| | - Joshua Hahn
- Division of Cardiology, Baylor College of Medicine, 7200 Cambridge Suite A6.137, MS: BCM621, Houston, TX, 77030, USA
| | - Graham J Rector
- Division of Cardiology, Baylor College of Medicine, 7200 Cambridge Suite A6.137, MS: BCM621, Houston, TX, 77030, USA
| | - Muzamil Khawaja
- Division of Cardiology, Baylor College of Medicine, 7200 Cambridge Suite A6.137, MS: BCM621, Houston, TX, 77030, USA
| | - Mihail G Chelu
- Division of Cardiology, Baylor College of Medicine, 7200 Cambridge Suite A6.137, MS: BCM621, Houston, TX, 77030, USA.
- Baylor St. Luke's Medical Center, Houston, USA.
- Texas Heart Institute, Houston, USA.
| |
Collapse
|
12
|
Parreira L, Carmo P, Nunes S, Marinheiro R, Mesquita D, Zubarev S, Chmelevsky M, Hitchen R, Ferreira A, Pinho J, Marques L, Chambel D, Amador P, Caria R, Adragão P. Electrocardiographic imaging to guide ablation of ventricular arrhythmias and agreement between two different systems. J Electrocardiol 2023; 80:143-150. [PMID: 37390586 DOI: 10.1016/j.jelectrocard.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 04/22/2023] [Accepted: 06/08/2023] [Indexed: 07/02/2023]
Abstract
BACKGROUND AND AIM A recent study using an epicardial-only electrocardiographic imaging (ECGI), suggests that the agreement of ECGI activation mapping and that of the contact mapping for ventricular arrhythmias (VA) is poor. The aim of this study was to assess the diagnostic value of two endo-epicardial ECGI systems using different cardiac sources and the agreement between them. METHODS We performed 69 ECGI procedures in 52 patients referred for ablation of VA at our center. One system based on the extracellular potentials was used in 26 patients, the other based on the equivalent double layer model in 9, and both in 17 patients. The first uses up to 224 leads and the second just the 12‑lead ECG. The localization of the VA was done using a segmental model of the ventricles. A perfect match (PM) was defined as a predicted location within the same anatomic segment, whereas a near match (NM) as a predicted location within the same segment or a contiguous one. RESULTS 44 patients underwent ablation, corresponding to 58 ECGI procedures (37 with the first and 21 with the second system). The percentage of PMs and NMs was not significantly different between the two systems, respectively 76% and 95%, p = 0.077, and 97% and 100%, p = 1.000. In 14 patients that underwent ablation and had the ECGI performed with both systems, raw agreement for PMs was 79%, p = 0.250 for disagreement. CONCLUSIONS ECGI systems were useful to identify the origin of the VAs, and the results were reproducible regardless the cardiac source.
Collapse
Affiliation(s)
- Leonor Parreira
- Hospital Luz Lisbon, Portugal; Setubal Hospital Center, Portugal.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
13
|
Dogrusoz YS, Rasoolzadeh N, Ondrusova B, Hlivak P, Zelinka J, Tysler M, Svehlikova J. Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data. Front Physiol 2023; 14:1197778. [PMID: 37362428 PMCID: PMC10288213 DOI: 10.3389/fphys.2023.1197778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).
Collapse
Affiliation(s)
- Yesim Serinagaoglu Dogrusoz
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Nika Rasoolzadeh
- Department of Electrical-Electronics Engineering, Middle East Technical University, Ankara, Türkiye
- Department of Scientific Computing, Middle East Technical University, Institute of Applied Mathematics, Ankara, Türkiye
| | - Beata Ondrusova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
- Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Bratislava, Slovakia
| | - Peter Hlivak
- National Institute for Cardiovascular Diseases, Bratislava, Slovakia
| | - Jan Zelinka
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Milan Tysler
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Jana Svehlikova
- Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
| |
Collapse
|
14
|
Hernández-Romero I, Molero R, Fambuena-Santos C, Herrero-Martín C, Climent AM, Guillem MS. Electrocardiographic imaging in the atria. Med Biol Eng Comput 2023; 61:879-896. [PMID: 36370321 PMCID: PMC9988819 DOI: 10.1007/s11517-022-02709-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022]
Abstract
The inverse problem of electrocardiography or electrocardiographic imaging (ECGI) is a technique for reconstructing electrical information about cardiac surfaces from noninvasive or non-contact recordings. ECGI has been used to characterize atrial and ventricular arrhythmias. Although it is a technology with years of progress, its development to characterize atrial arrhythmias is challenging. Complications can arise when trying to describe the atrial mechanisms that lead to abnormal propagation patterns, premature or tachycardic beats, and reentrant arrhythmias. This review addresses the various ECGI methodologies, regularization methods, and post-processing techniques used in the atria, as well as the context in which they are used. The current advantages and limitations of ECGI in the fields of research and clinical diagnosis of atrial arrhythmias are outlined. In addition, areas where ECGI efforts should be concentrated to address the associated unsatisfied needs from the atrial perspective are discussed.
Collapse
Affiliation(s)
| | - Rubén Molero
- ITACA, Universitat Politècnica de València, Valencia, Spain
| | | | | | | | | |
Collapse
|
15
|
Robustness of imageless electrocardiographic imaging against uncertainty in atrial morphology and location. J Electrocardiol 2023; 77:58-61. [PMID: 36634462 DOI: 10.1016/j.jelectrocard.2022.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/13/2022] [Accepted: 12/23/2022] [Indexed: 01/04/2023]
Abstract
INTRODUCTION Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry. METHODS Multiple‑lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes. RESULTS CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%. CONCLUSION Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice.
Collapse
|
16
|
Fruelund PZ, Van Dam PM, Melgaard J, Sommer A, Lundbye-Christensen S, Søgaard P, Zaremba T, Graff C, Riahi S. Novel non-invasive ECG imaging method based on the 12-lead ECG for reconstruction of ventricular activation: A proof-of-concept study. Front Cardiovasc Med 2023; 10:1087568. [PMID: 36818351 PMCID: PMC9932809 DOI: 10.3389/fcvm.2023.1087568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/18/2023] [Indexed: 02/05/2023] Open
Abstract
Aim Current non-invasive electrocardiographic imaging (ECGi) methods are often based on complex body surface potential mapping, limiting the clinical applicability. The aim of this pilot study was to evaluate the ability of a novel non-invasive ECGi method, based on the standard 12-lead ECG, to localize initial site of ventricular activation in right ventricular (RV) paced patients. Validation of the method was performed by comparing the ECGi reconstructed earliest site of activation against the true RV pacing site determined from cardiac computed tomography (CT). Methods This was a retrospective study using data from 34 patients, previously implanted with a dual chamber pacemaker due to advanced atrioventricular block. True RV lead position was determined from analysis of a post-implant cardiac CT scan. The ECGi method was based on an inverse-ECG algorithm applying electrophysiological rules. The algorithm integrated information from an RV paced 12-lead ECG together with a CT-derived patient-specific heart-thorax geometric model to reconstruct a 3D electrical ventricular activation map. Results The mean geodesic localization error (LE) between the ECGi reconstructed initial site of activation and the RV lead insertion site determined from CT was 13.9 ± 5.6 mm. The mean RV endocardial surface area was 146.0 ± 30.0 cm2 and the mean circular LE area was 7.0 ± 5.2 cm2 resulting in a relative LE of 5.0 ± 4.0%. Conclusion We demonstrated a novel non-invasive ECGi method, based on the 12-lead ECG, that accurately localized the RV pacing site in relation to the ventricular anatomy.
Collapse
Affiliation(s)
- Patricia Zerlang Fruelund
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark,*Correspondence: Patricia Zerlang Fruelund,
| | - Peter M. Van Dam
- Department of Cardiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Jacob Melgaard
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Anders Sommer
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | | | - Peter Søgaard
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Tomas Zaremba
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Claus Graff
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Sam Riahi
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| |
Collapse
|
17
|
Fambuena-Santos C, Hernández-Romero I, Molero R, Atienza F, Climent AM, Guillem MS. AF driver detection in pulmonary vein area by electropcardiographic imaging: Relation with a favorable outcome of pulmonary vein isolation. Front Physiol 2023; 14:1057700. [PMID: 36793415 PMCID: PMC9922892 DOI: 10.3389/fphys.2023.1057700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 01/10/2023] [Indexed: 01/31/2023] Open
Abstract
Pulmonary vein isolation (PVI) is the most successful treatment for atrial fibrillation (AF) nowadays. However, not all AF patients benefit from PVI. In this study, we evaluate the use of ECGI to identify reentries and relate rotor density in the pulmonary vein (PV) area as an indicator of PVI outcome. Rotor maps were computed in a set of 29 AF patients using a new rotor detection algorithm. The relationship between the distribution of reentrant activity and the clinical outcome after PVI was studied. The number of rotors and proportion of PSs in different atrial regions were computed and compared retrospectively in two groups of patients: patients that remained in sinus rhythm 6 months after PVI and patients with arrhythmia recurrence. The total number of rotors obtained was higher in patients returning to arrhythmia after the ablation (4.31 ± 2.77 vs. 3.58 ± 2.67%, p = 0.018). However, a significantly higher concentration of PSs in the pulmonary veins was found in patients that remained in sinus rhythm (10.20 ± 12.40% vs. 5.19 ± 9.13%, p = 0.011) 6 months after PVI. The results obtained show a direct relationship between the expected AF mechanism and the electrophysiological parameters provided by ECGI, suggesting that this technology offers relevant information to predict the clinical outcome after PVI in AF patients.
Collapse
Affiliation(s)
- Carlos Fambuena-Santos
- COR Laboratory, ITACA Institute, Universitat Politècnica de València, Valencia, Spain,*Correspondence: Carlos Fambuena-Santos,
| | | | - Rubén Molero
- COR Laboratory, ITACA Institute, Universitat Politècnica de València, Valencia, Spain
| | - Felipe Atienza
- Department of Cardiology, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Andreu M. Climent
- COR Laboratory, ITACA Institute, Universitat Politècnica de València, Valencia, Spain
| | - M S. Guillem
- COR Laboratory, ITACA Institute, Universitat Politècnica de València, Valencia, Spain
| |
Collapse
|
18
|
Zenger B, Bergquist JA, Busatto A, Good WW, Rupp LC, Sharma V, MacLeod RS. Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models. Front Physiol 2023; 14:1100471. [PMID: 36744034 PMCID: PMC9893785 DOI: 10.3389/fphys.2023.1100471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 01/02/2023] [Indexed: 01/21/2023] Open
Abstract
The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.
Collapse
Affiliation(s)
- Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
- Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States
- Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Jake A. Bergquist
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
- Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Anna Busatto
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
- Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | | | - Lindsay C. Rupp
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
- Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Vikas Sharma
- Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Rob S. MacLeod
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
- Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States
- Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| |
Collapse
|
19
|
Talevi G, Pannone L, Monaco C, Bori E, Cappello IA, Candelari M, Wyns M, Ramak R, La Meir M, Gharaviri A, Chierchia GB, Innocenti B, de Asmundis C. Evaluation of photogrammetry for medical application in cardiology. Front Bioeng Biotechnol 2023; 11:1044647. [PMID: 36714012 PMCID: PMC9879954 DOI: 10.3389/fbioe.2023.1044647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/05/2023] [Indexed: 01/14/2023] Open
Abstract
Background: In the field of medicine, photogrammetry has played for long time a marginal role due to the significant amount of work required that made it impractical for an extended medical use. Developments in digital photogrammetry occurred in the recent years, that have steadily increased the interest and application of this technique. The present study aims to compare photogrammetry reconstruction of heart with computed tomography (CT) as a reference. Methods: The photogrammetric reconstructions of digital images from ECG imaging derived images were performed. In particular, the ventricles of 15 patients with Brugada syndrome were reconstructed by using the free Zephyr Lite software. In order to evaluate the accuracy of the technique, measurements on the reconstructions were compared to patient-specific CT scan imported in ECG imaging software UZBCIT. Result: The results showed that digital photogrammetry in the context of ventricle reconstruction is feasible. The photogrammetric derived measurements of ventricles were not statistically different from CT scan measurements. Furthermore, the analysis showed high correlation of photogrammetry reconstructions with CT scan and a correlation coefficient close to 1. Conclusion: It is possible to reproduce digital objects by photogrammetry if the process described in this study is performed. The reconstruction of the ventricles from CT scan was very close to the values of the respective photogrammetric reconstruction.
Collapse
Affiliation(s)
- Giacomo Talevi
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Luigi Pannone
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Cinzia Monaco
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Edoardo Bori
- BEAMS Department (Bio Electro and Mechanical Systems), Université Libre de Bruxelles, Brussels, Belgium
| | - Ida Anna Cappello
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Mara Candelari
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Manon Wyns
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Robbert Ramak
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Mark La Meir
- Cardiac Surgery Department, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, Brussels, Belgium
| | - Ali Gharaviri
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Gian Battista Chierchia
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - Bernardo Innocenti
- BEAMS Department (Bio Electro and Mechanical Systems), Université Libre de Bruxelles, Brussels, Belgium
| | - Carlo de Asmundis
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium,*Correspondence: Carlo de Asmundis,
| |
Collapse
|
20
|
Talevi G, Pannone L, Monaco C, Bori E, Cappello IA, Candelari M, Ramak R, La Meir M, Gharaviri A, Chierchia GB, Innocenti B, de Asmundis C. Development of a 3D printed surgical guide for Brugada syndrome substrate ablation. Front Cardiovasc Med 2022; 9:1029685. [DOI: 10.3389/fcvm.2022.1029685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 11/01/2022] [Indexed: 11/16/2022] Open
Abstract
BackgroundBrugada syndrome (BrS) is a disease associated with ventricular arrhythmias and sudden cardiac death. Epicardial ablation has demonstrated high therapeutic efficacy in preventing ventricular arrhythmias. The purpose of this research is to define a workflow to create a patient-specific 3D-printed tool to be used as a surgical guide for epicardial ablation in BrS.MethodsDue to their mechanical properties and biocompatibility, the MED625FLX and TPU95A were used for cardiac 3D surgical guide printing. ECG imaging was used to define the target region on the right ventricular outflow tract (RVOT). CT scan imaging was used to design the model based on patient anatomy. A 3D patient-specific heart phantom was also printed for fitting test. Sterilization test was finally performed.Results3D printed surgical models with both TPU95A and MED625FLX models were in agreement with pre-specified imputed measurements. The phantom test showed retention of shape and correct fitting of the surgical tool to the reproduced phantom anatomy, as expected, for both materials. The surgical guide adapted to both the RVOT and the left anterior descending artery. Two of the 3D models produced in MED265FLX showed damage due to the sterilization process.ConclusionsA 3D printed patient-specific surgical guide for epicardial substrate ablation in BrS is feasible if a specific workflow is followed. The design of the 3D surgical guide ensures proper fitting on the heart phantom with good stability. Further investigations for clinical use are eagerly awaited.
Collapse
|
21
|
Yadan Z, Xin L, Jian W. Solving the inverse problem in electrocardiography imaging for atrial fibrillation using various time-frequency decomposition techniques based on empirical mode decomposition: A comparative study. Front Physiol 2022; 13:999900. [PMID: 36406997 PMCID: PMC9666773 DOI: 10.3389/fphys.2022.999900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/18/2022] [Indexed: 11/25/2022] Open
Abstract
Electrocardiographic imaging (ECGI) can aid in identifying the driving sources that cause and sustain atrial fibrillation (AF). Traditional regularization strategies for addressing the ECGI inverse problem are not currently concerned about the multi-scale analysis of the inverse problem, and these techniques are not clinically reliable. We have previously investigated the solution based on uniform phase mode decomposition (UPEMD-based) to the ECGI inverse problem. Numerous other methods for the time-frequency analysis derived from empirical mode decomposition (EMD-based) have not been applied to the inverse problem in ECGI. By applying many EMD-based solutions to the ECGI inverse problem and evaluating the performance of these solutions, we hope to find a more efficient EMD-based solution to the ECGI inverse problem. In this study, five AF simulation datasets and two real datasets from AF patients derived from a clinical ablation procedure are employed to evaluate the operating efficiency of several EMD-based solutions. The Pearson's correlation coefficient (CC), the relative difference measurement star (RDMS) of the computed epicardial dominant frequency (DF) map and driver probability (DP) map, and the distance (Dis) between the estimated and referenced most probable driving sources are used to evaluate the application of various EMD-based solutions in ECGI. The results show that for DF maps on all simulation datasets, the CC of UPEMD-based and improved UPEMD (IUPEMD)-based techniques are both greater than 0.95 and the CC of the empirical wavelet transform (EWT)-based solution is greater than 0.889, and the RDMS of UPEMD-based and IUPEMD-based approaches is less than 0.3 overall and the RDMS of EWT-based method is less than 0.48, performing better than other EMD-based solutions; for DP maps, the CC of UPEMD-based and IUPEMD-based techniques are close to 0.5, the CC of EWT-based is 0.449, and the CC of the remaining EMD-based techniques on the SAF and CAF is all below 0.1; the RDMS of UPEMD-based and IUPEMD-based are 0.06∼0.9 less than that of other EMD-based methods for all the simulation datasets overall. On two authentic AF datasets, the Dis between the first 10 real and estimated maximum DF positions of UPEMD-based and EWT-based methods are 212∼1440 less than that of others, demonstrating these two EMD-based solutions are superior and are suggested for clinical application in solving the ECGI inverse problem. On all datasets, EWT-based algorithms deconstruct the signal in the shortest time (no more than 0.12s), followed by UPEMD-based solutions (less than 0.81s), showing that these two schemes are more efficient than others.
Collapse
|
22
|
Gillette K, Gsell MAF, Strocchi M, Grandits T, Neic A, Manninger M, Scherr D, Roney CH, Prassl AJ, Augustin CM, Vigmond EJ, Plank G. A personalized real-time virtual model of whole heart electrophysiology. Front Physiol 2022; 13:907190. [PMID: 36213235 PMCID: PMC9539798 DOI: 10.3389/fphys.2022.907190] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/15/2022] [Indexed: 01/12/2023] Open
Abstract
Computer models capable of representing the intrinsic personal electrophysiology (EP) of the heart in silico are termed virtual heart technologies. When anatomy and EP are tailored to individual patients within the model, such technologies are promising clinical and industrial tools. Regardless of their vast potential, few virtual technologies simulating the entire organ-scale EP of all four-chambers of the heart have been reported and widespread clinical use is limited due to high computational costs and difficulty in validation. We thus report on the development of a novel virtual technology representing the electrophysiology of all four-chambers of the heart aiming to overcome these limitations. In our previous work, a model of ventricular EP embedded in a torso was constructed from clinical magnetic resonance image (MRI) data and personalized according to the measured 12 lead electrocardiogram (ECG) of a single subject under normal sinus rhythm. This model is then expanded upon to include whole heart EP and a detailed representation of the His-Purkinje system (HPS). To test the capacities of the personalized virtual heart technology to replicate standard clinical morphological ECG features under such conditions, bundle branch blocks within both the right and the left ventricles under two different conduction velocity settings are modeled alongside sinus rhythm. To ensure clinical viability, model generation was completely automated and simulations were performed using an efficient real-time cardiac EP simulator. Close correspondence between the measured and simulated 12 lead ECG was observed under normal sinus conditions and all simulated bundle branch blocks manifested relevant clinical morphological features.
Collapse
Affiliation(s)
- Karli Gillette
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Thomas Grandits
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- NAWI Graz, Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | | | - Martin Manninger
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Daniel Scherr
- Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | | | - Anton J. Prassl
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | | | - Gernot Plank
- Gottfried Schatz Research Center—Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- *Correspondence: Gernot Plank,
| |
Collapse
|
23
|
Njeru DK, Athawale TM, France JJ, Johnson CR. Quantifying and Visualizing Uncertainty for Source Localization in Electrocardiographic Imaging. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING. IMAGING & VISUALIZATION 2022; 11:812-822. [PMID: 37284179 PMCID: PMC10241371 DOI: 10.1080/21681163.2022.2113824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 08/12/2022] [Indexed: 06/08/2023]
Abstract
Electrocardiographic imaging (ECGI) presents a clinical opportunity to noninvasively understand the sources of arrhythmias for individual patients. To help increase the effectiveness of ECGI, we provide new ways to visualize associated measurement and modeling errors. In this paper, we study source localization uncertainty in two steps: First, we perform Monte Carlo simulations of a simple inverse ECGI source localization model with error sampling to understand the variations in ECGI solutions. Second, we present multiple visualization techniques, including confidence maps, level-sets, and topology-based visualizations, to better understand uncertainty in source localization. Our approach offers a new way to study uncertainty in the ECGI pipeline.
Collapse
Affiliation(s)
- Dennis K Njeru
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, USA
| | - Tushar M Athawale
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, USA
| | - Jessie J France
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, USA
| | - Chris R Johnson
- Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, USA
| |
Collapse
|
24
|
Monaco C, Galli A, Pannone L, Bisignani A, Miraglia V, Gauthey A, Al Housari M, Mojica J, Del Monte A, Lipartiti F, Rizzi S, Mouram S, Calburean PA, Ramark R, Pappaert G, Eltsov I, Bala G, Sorgente A, Overeinder I, Almorad A, Stroker E, Sieira J, Brugada P, Chierchia GB, La Meir M, de Asmundis C. Hybrid-Approach Ablation in Drug-Refractory Arrhythmogenic Right Ventricular Cardiomyopathy. Am J Cardiol 2022; 181:45-54. [PMID: 35973836 DOI: 10.1016/j.amjcard.2022.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 11/30/2022]
Abstract
Management of ventricular arrhythmias (VAs) beyond implantable cardioverter-defibrillator positioning in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) is challenging. Catheter ablation of the ventricular substrate often requires a combination of endocardial and epicardial approaches, with disappointing outcomes due to the progressive nature of the disease. We report the Universitair Ziekenhuis Brussel experience through a case series of 16 patients with drug-refractory ARVC, who have undergone endocardial and/or epicardial catheter ablation of VAs with a thoracoscopic hybrid-approach. After a mean follow-up time of 5.16 years (SD 2.9 years) from the first hybrid-approach ablation, VA recurrence was observed in 5 patients (31.25%): among these, patients 4 patients (80%) received a previous ablation and 1 of 11 patients (9.09%) who had a hybrid ablation as first approach had a VA recurrence (80% vs 9.09%; log-rank p = 0.04). Despite the recurrence rate of arrhythmic events, all patients had a significant reduction in the arrhythmic burden after ablation, with a mean of 4.65 years (SD 2.9 years) of freedom from clinically significant arrhythmias, defined as symptomatic VAs or implantable cardioverter-defibrillator-delivered therapies. In conclusion, our case series confirms that management of VAs in patients with ARVC is difficult because patients do not always respond to antiarrhythmic medications and can require multiple invasive procedures. A multidisciplinary approach involving cardiologists, cardiac surgeons, and cardiac electrophysiologists, together with recent cardiac mapping techniques and ablation tools, might mitigate these difficulties and improve outcomes.
Collapse
Affiliation(s)
- Cinzia Monaco
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Alessio Galli
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Luigi Pannone
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Antonio Bisignani
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Vincenzo Miraglia
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Anaïs Gauthey
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Maysam Al Housari
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Joerelle Mojica
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Alvise Del Monte
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Felicia Lipartiti
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Sergio Rizzi
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Sahar Mouram
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Paul-Adrian Calburean
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Robbert Ramark
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Gudrun Pappaert
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Ivan Eltsov
- Department of Cardiac Surgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Gezim Bala
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Antonio Sorgente
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Ingrid Overeinder
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Alexandre Almorad
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Erwin Stroker
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Juan Sieira
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Pedro Brugada
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Gian Battista Chierchia
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Mark La Meir
- Department of Cardiac Surgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium
| | - Carlo de Asmundis
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussel, Belgium.
| |
Collapse
|
25
|
Verheul LM, Groeneveld SA, Kirkels FP, Volders PGA, Teske AJ, Cramer MJ, Guglielmo M, Hassink RJ. State-of-the-Art Multimodality Imaging in Sudden Cardiac Arrest with Focus on Idiopathic Ventricular Fibrillation: A Review. J Clin Med 2022; 11:4680. [PMID: 36012918 PMCID: PMC9410297 DOI: 10.3390/jcm11164680] [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: 07/15/2022] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 11/16/2022] Open
Abstract
Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sudden cardiac arrest survivors undergo extensive clinical testing, with a growing role for multimodality imaging, before diagnosing "idiopathic" ventricular fibrillation. Multimodality imaging, considered as using multiple imaging modalities as diagnostics, is important for revealing structural myocardial abnormalities in patients with cardiac arrest. This review focuses on combining imaging modalities (echocardiography, cardiac magnetic resonance and computed tomography) and the electrocardiographic characterization of sudden cardiac arrest survivors and discusses the surplus value of multimodality imaging in the diagnostic routing of these patients. We focus on novel insights obtained through electrostructural and/or electromechanical imaging in apparently idiopathic ventricular fibrillation patients, with special attention to non-invasive electrocardiographic imaging.
Collapse
Affiliation(s)
- Lisa M. Verheul
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Sanne A. Groeneveld
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Feddo P. Kirkels
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Paul G. A. Volders
- Department of Cardiology, Maastricht University Medical Center, P. Debyelaan 25, 6229 HX Maastricht, The Netherlands
| | - Arco J. Teske
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Maarten J. Cramer
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Marco Guglielmo
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Rutger J. Hassink
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| |
Collapse
|
26
|
Chen KW, Bear L, Lin CW. Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks. SENSORS (BASEL, SWITZERLAND) 2022; 22:2331. [PMID: 35336502 PMCID: PMC8951148 DOI: 10.3390/s22062331] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 06/14/2023]
Abstract
Electrocardiographic imaging (ECGi) reconstructs electrograms at the heart's surface using the potentials recorded at the body's surface. This is called the inverse problem of electrocardiography. This study aimed to improve on the current solution methods using machine learning and deep learning frameworks. Electrocardiograms were simultaneously recorded from pigs' ventricles and their body surfaces. The Fully Connected Neural network (FCN), Long Short-term Memory (LSTM), Convolutional Neural Network (CNN) methods were used for constructing the model. A method is developed to align the data across different pigs. We evaluated the method using leave-one-out cross-validation. For the best result, the overall median of the correlation coefficient of the predicted ECG wave was 0.74. This study demonstrated that a neural network can be used to solve the inverse problem of ECGi with relatively small datasets, with an accuracy compatible with current standard methods.
Collapse
Affiliation(s)
- Ke-Wei Chen
- Department of BioMedical Engineering, National Cheng Kung University, Tainan City 70101, Taiwan;
| | - Laura Bear
- Electrophysiology and Heart Modelling Institute (IHU-LIRYC), Fondation Bordeaux Université, 33000 Bordeaux, France;
- Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM U1045, Université de Bordeaux, 33600 Pessac, France
| | - Che-Wei Lin
- Department of BioMedical Engineering, National Cheng Kung University, Tainan City 70101, Taiwan;
| |
Collapse
|
27
|
Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Reconstruction of cardiac position using body surface potentials. Comput Biol Med 2022; 142:105174. [PMID: 35065409 PMCID: PMC8844250 DOI: 10.1016/j.compbiomed.2021.105174] [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: 11/04/2021] [Revised: 12/22/2021] [Accepted: 12/23/2021] [Indexed: 11/03/2022]
Abstract
Electrocardiographic imaging (ECGI) is a noninvasive technique to assess the bioelectric activity of the heart which has been applied to aid in clinical diagnosis and management of cardiac dysfunction. ECGI is built on mathematical models that take into account several patient specific factors including the position of the heart within the torso. Errors in the localization of the heart within the torso, as might arise due to natural changes in heart position from respiration or changes in body position, contribute to errors in ECGI reconstructions of the cardiac activity, thereby reducing the clinical utility of ECGI. In this study we present a novel method for the reconstruction of cardiac geometry utilizing noninvasively acquired body surface potential measurements. Our geometric correction method simultaneously estimates the cardiac position over a series of heartbeats by leveraging an iterative approach which alternates between estimating the cardiac bioelectric source across all heartbeats and then estimating cardiac positions for each heartbeat. We demonstrate that our geometric correction method is able to reduce geometric error and improve ECGI accuracy in a wide range of testing scenarios. We examine the performance of our geometric correction method using different activation sequences, ranges of cardiac motion, and body surface electrode configurations. We find that after geometric correction resulting ECGI solution accuracy is improved and variability of the ECGI solutions between heartbeats is substantially reduced.
Collapse
Affiliation(s)
- Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Department of Biomedical Engineering, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States.
| | - Jaume Coll-Font
- Cardiovascular Bioengineering Imaging (CBM) Lab at the Massachusetts General Hospital, Boston, MA, United States
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Department of Biomedical Engineering, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; School of Medicine, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States
| | - Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Department of Biomedical Engineering, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States
| | | | - Dana H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, United States
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States; Department of Biomedical Engineering, University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, United States
| |
Collapse
|
28
|
Cluitmans M, Coll-Font J, Erem B, Bear L, Nguyên UC, Ter Bekke R, Volders PGA, Brooks D. Spatiotemporal approximation of cardiac activation and recovery isochrones. J Electrocardiol 2021; 71:1-9. [PMID: 34979408 DOI: 10.1016/j.jelectrocard.2021.12.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/15/2021] [Accepted: 12/21/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a unipolar EGM by the moment of maximum downslope of the QRS complex or maximum upslope of the T wave, respectively. However, both invasive and noninvasive recordings of intracardiac EGMs may suffer from noise and fractionation, making reliable detection of these deflections nontrivial. METHODS Here, we introduce a novel method that benefits from the spatial coupling of these processes, and incorporate not only the temporal EGM deflection, but also the spatial gradients. We validated this approach in computer simulations, in animal data with ECGI and invasive electrode recordings, and illustrated its use in a clinical case. RESULTS In the simulated data, the spatiotemporal approach was able to incorporate spatial information to better select the correct deflection in artificially fractionated EGMs and outperformed the traditional temporal-only method. In experimental data, the accuracy of time estimation from ECGI compared to invasive recordings significantly increased from R = 0.73 (activation) and R = 0.58 (recovery) with the temporal-only method to R = 0.79 (activation) and R = 0.72 (recovery) with the novel approach. Localization of the pacing origin of paced beats improved significantly from 36 mm mean error with the temporal-only approach to 23 mm with the spatiotemporal approach. CONCLUSION The spatiotemporal method to compute activation and recovery times from EGMs outperformed the traditional temporal-only approach in which spatial information was not taken into account.
Collapse
Affiliation(s)
- Matthijs Cluitmans
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands.
| | - Jaume Coll-Font
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | | | | | - Uyên Châu Nguyên
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Rachel Ter Bekke
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Paul G A Volders
- Cardiovascular Research Institute Maastricht, Maastricht University, the Netherlands
| | - Dana Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| |
Collapse
|
29
|
Stevenson WG, Sapp JL. Newer Methods for VT Ablation and When to Use Them. Can J Cardiol 2021; 38:502-514. [PMID: 34942300 DOI: 10.1016/j.cjca.2021.12.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/03/2021] [Accepted: 12/11/2021] [Indexed: 02/07/2023] Open
Abstract
Radiofrequency (RF) catheter ablation has long been an important therapy for ventricular tachycardia and frequent symptomatic premature ventricular beats and nonsustained arrhythmias when antiarrhythmic drugs fail to suppress the arrhythmias. It is increasingly used in preference to antiarrhythmic drugs, sparing the patient drug adverse effects. Ablation success varies with the underlying heart disease and type of arrhythmia, being very effective for patients without structural heart disease, less in structural heart disease. Failure occurs when a target for ablation cannot be identified, or ablation lesions fail to reach and abolish the arrhythmia substrate that may be extensive, intramural or subepicardial in location. Approaches to improving ablation lesion creation are modifications to RF ablation and emerging investigational techniques. Easily implemented modifications to RF methods include manipulating the size and location of the cutaneous dispersive electrode, increasing RF delivery duration, and use of lower tonicity catheter irrigation (usually 0.45% saline). When catheters can be placed on either side of culprit substrate RF can be delivered in a bipolar or simultaneous unipolar configuration that can be successful. Catheters with extendable/retractable irrigated needles for RF delivery are under investigation in clinical trials. Cryoablation is potentially useful in specific situations when maintaining contact is difficult. Transvascular ethanol ablation and stereotactic radioablation have both shown promise for arrhythmias that fail other ablation strategies. Although substantial clinical progress has been achieved, further improvement is clearly needed. With ability to increase ablation lesion size, continued careful evaluation of safety, which has been excellent for standard RF ablation, remains important.
Collapse
Affiliation(s)
- William G Stevenson
- The Cardiovascular Division, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee; The Heart Rhythm Service, Department of Medicine, Division of Cardiology, QEII Health Sciences Centre, Halifax, Nova Scotia, Canada.
| | - John L Sapp
- The Cardiovascular Division, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee; The Heart Rhythm Service, Department of Medicine, Division of Cardiology, QEII Health Sciences Centre, Halifax, Nova Scotia, Canada
| |
Collapse
|
30
|
Schuler S, Schaufelberger M, Bear LR, Bergquist JA, Cluitmans MJM, Coll-Font J, Onak ON, Zenger B, Loewe A, MacLeod RS, Brooks DH, Dossel O. Reducing Line-of-block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods. IEEE Trans Biomed Eng 2021; 69:2041-2052. [PMID: 34905487 DOI: 10.1109/tbme.2021.3135154] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs. METHODS Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals. RESULTS AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had a negligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays. CONCLUSION LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs. SIGNIFICANCE Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts and methods to reduce them.
Collapse
|
31
|
Bergquist J, Rupp L, Zenger B, Brundage J, Busatto A, MacLeod RS. Body Surface Potential Mapping: Contemporary Applications and Future Perspectives. HEARTS 2021; 2:514-542. [PMID: 35665072 PMCID: PMC9164986 DOI: 10.3390/hearts2040040] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Abstract
Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.
Collapse
Affiliation(s)
- Jake Bergquist
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Lindsay Rupp
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Brian Zenger
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
- School of Medicine, University of Utah, Salt Lake City, UT 84112, USA
| | - James Brundage
- School of Medicine, University of Utah, Salt Lake City, UT 84112, USA
| | - Anna Busatto
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Rob S. MacLeod
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
| |
Collapse
|
32
|
Roudijk RW, Boonstra MJ, Brummel R, Kassenberg W, Blom LJ, Oostendorp TF, Te Riele ASJM, van der Heijden JF, Asselbergs FW, van Dam PM, Loh P. Comparing Non-invasive Inverse Electrocardiography With Invasive Endocardial and Epicardial Electroanatomical Mapping During Sinus Rhythm. Front Physiol 2021; 12:730736. [PMID: 34671274 PMCID: PMC8521153 DOI: 10.3389/fphys.2021.730736] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 09/01/2021] [Indexed: 01/04/2023] Open
Abstract
This study presents a novel non-invasive equivalent dipole layer (EDL) based inverse electrocardiography (iECG) technique which estimates both endocardial and epicardial ventricular activation sequences. We aimed to quantitatively compare our iECG approach with invasive electro-anatomical mapping (EAM) during sinus rhythm with the objective of enabling functional substrate imaging and sudden cardiac death risk stratification in patients with cardiomyopathy. Thirteen patients (77% males, 48 ± 20 years old) referred for endocardial and epicardial EAM underwent 67-electrode body surface potential mapping and CT imaging. The EDL-based iECG approach was improved by mimicking the effects of the His-Purkinje system on ventricular activation. EAM local activation timing (LAT) maps were compared with iECG-LAT maps using absolute differences and Pearson’s correlation coefficient, reported as mean ± standard deviation [95% confidence interval]. The correlation coefficient between iECG-LAT maps and EAM was 0.54 ± 0.19 [0.49–0.59] for epicardial activation, 0.50 ± 0.27 [0.41–0.58] for right ventricular endocardial activation and 0.44 ± 0.29 [0.32–0.56] for left ventricular endocardial activation. The absolute difference in timing between iECG maps and EAM was 17.4 ± 7.2 ms for epicardial maps, 19.5 ± 7.7 ms for right ventricular endocardial maps, 27.9 ± 8.7 ms for left ventricular endocardial maps. The absolute distance between right ventricular endocardial breakthrough sites was 30 ± 16 mm and 31 ± 17 mm for the left ventricle. The absolute distance for latest epicardial activation was median 12.8 [IQR: 2.9–29.3] mm. This first in-human quantitative comparison of iECG and invasive LAT-maps on both the endocardial and epicardial surface during sinus rhythm showed improved agreement, although with considerable absolute difference and moderate correlation coefficient. Non-invasive iECG requires further refinements to facilitate clinical implementation and risk stratification.
Collapse
Affiliation(s)
- Robert W Roudijk
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Machteld J Boonstra
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Rolf Brummel
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Wil Kassenberg
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Lennart J Blom
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Thom F Oostendorp
- Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Anneline S J M Te Riele
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Jeroen F van der Heijden
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Folkert W Asselbergs
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London, United Kingdom.,Health Data Research UK, Institute of Health Informatics, University College London, London, United Kingdom
| | - Peter M van Dam
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,ECG Excellence BV, Nieuwerbrug, Netherlands
| | - Peter Loh
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| |
Collapse
|
33
|
Gander L, Krause R, Multerer M, Pezzuto S. Space-time shape uncertainties in the forward and inverse problem of electrocardiography. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2021; 37:e3522. [PMID: 34410040 PMCID: PMC9285968 DOI: 10.1002/cnm.3522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 06/27/2021] [Accepted: 08/13/2021] [Indexed: 06/08/2023]
Abstract
In electrocardiography, the "classic" inverse problem is the reconstruction of electric potentials at a surface enclosing the heart from remote recordings at the body surface and an accurate description of the anatomy. The latter being affected by noise and obtained with limited resolution due to clinical constraints, a possibly large uncertainty may be perpetuated in the inverse reconstruction. The purpose of this work is to study the effect of shape uncertainty on the forward and the inverse problem of electrocardiography. To this aim, the problem is first recast into a boundary integral formulation and then discretised with a collocation method to achieve high convergence rates and a fast time to solution. The shape uncertainty of the domain is represented by a random deformation field defined on a reference configuration. We propose a periodic-in-time covariance kernel for the random field and approximate the Karhunen-Loève expansion using low-rank techniques for fast sampling. The space-time uncertainty in the expected potential and its variance is evaluated with an anisotropic sparse quadrature approach and validated by a quasi-Monte Carlo method. We present several numerical experiments on a simplified but physiologically grounded two-dimensional geometry to illustrate the validity of the approach. The tested parametric dimension ranged from 100 up to 600. For the forward problem, the sparse quadrature is very effective. In the inverse problem, the sparse quadrature and the quasi-Monte Carlo method perform as expected, except for the total variation regularisation, where convergence is limited by lack of regularity. We finally investigate an H1/2 regularisation, which naturally stems from the boundary integral formulation, and compare it to more classical approaches.
Collapse
Affiliation(s)
- Lia Gander
- Center for Computational Medicine in CardiologyEuler Institute, Università della Svizzera italianaLuganoSwitzerland
| | - Rolf Krause
- Center for Computational Medicine in CardiologyEuler Institute, Università della Svizzera italianaLuganoSwitzerland
| | - Michael Multerer
- Center for Computational Medicine in CardiologyEuler Institute, Università della Svizzera italianaLuganoSwitzerland
| | - Simone Pezzuto
- Center for Computational Medicine in CardiologyEuler Institute, Università della Svizzera italianaLuganoSwitzerland
| |
Collapse
|
34
|
Schuler S, Pilia N, Potyagaylo D, Loewe A. Cobiveco: Consistent biventricular coordinates for precise and intuitive description of position in the heart - with MATLAB implementation. Med Image Anal 2021; 74:102247. [PMID: 34592711 DOI: 10.1016/j.media.2021.102247] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/18/2022]
Abstract
Ventricular coordinates are widely used as a versatile tool for various applications that benefit from a description of local position within the heart. However, the practical usefulness of ventricular coordinates is determined by their ability to meet application-specific requirements. For regression-based estimation of biventricular position, for example, a symmetric definition of coordinate directions in both ventricles is important. For the transfer of data between different hearts as another use case, the consistency of coordinate values across different geometries is particularly relevant. To meet these requirements, we compare different approaches to compute coordinates and present Cobiveco, a symmetric, consistent and intuitive biventricular coordinate system that builds upon existing coordinate systems, but overcomes some of their limitations. A novel one-way transfer error is introduced to assess the consistency of the coordinates. Normalized distances along bijective trajectories between two boundaries were found to be superior to solutions of Laplace's equation for defining coordinate values, as they show better linearity in space. Evaluation of transfer and linearity errors on 36 patient geometries revealed a more than 4-fold improvement compared to a state-of-the-art method. Finally, we show two application examples underlining the relevance for cardiac data processing. Cobiveco MATLAB code is available under a permissive open-source license.
Collapse
Affiliation(s)
- Steffen Schuler
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany.
| | - Nicolas Pilia
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| | | | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, Karlsruhe 76131, Germany
| |
Collapse
|
35
|
Peirlinck M, Sahli Costabal F, Kuhl E. Sex Differences in Drug-Induced Arrhythmogenesis. Front Physiol 2021; 12:708435. [PMID: 34489728 PMCID: PMC8417068 DOI: 10.3389/fphys.2021.708435] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 07/14/2021] [Indexed: 12/25/2022] Open
Abstract
The electrical activity in the heart varies significantly between men and women and results in a sex-specific response to drugs. Recent evidence suggests that women are more than twice as likely as men to develop drug-induced arrhythmia with potentially fatal consequences. Yet, the sex-specific differences in drug-induced arrhythmogenesis remain poorly understood. Here we integrate multiscale modeling and machine learning to gain mechanistic insight into the sex-specific origin of drug-induced cardiac arrhythmia at differing drug concentrations. To quantify critical drug concentrations in male and female hearts, we identify the most important ion channels that trigger male and female arrhythmogenesis, and create and train a sex-specific multi-fidelity arrhythmogenic risk classifier. Our study reveals that sex differences in ion channel activity, tissue conductivity, and heart dimensions trigger longer QT-intervals in women than in men. We quantify the critical drug concentration for dofetilide, a high risk drug, to be seven times lower for women than for men. Our results emphasize the importance of including sex as an independent biological variable in risk assessment during drug development. Acknowledging and understanding sex differences in drug safety evaluation is critical when developing novel therapeutic treatments on a personalized basis. The general trends of this study have significant implications on the development of safe and efficacious new drugs and the prescription of existing drugs in combination with other drugs.
Collapse
Affiliation(s)
- Mathias Peirlinck
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Francisco Sahli Costabal
- Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| |
Collapse
|
36
|
Bacoyannis T, Ly B, Cedilnik N, Cochet H, Sermesant M. Deep learning formulation of electrocardiographic imaging integrating image and signal information with data-driven regularization. Europace 2021; 23:i55-i62. [PMID: 33751073 DOI: 10.1093/europace/euaa391] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 12/07/2020] [Indexed: 12/22/2022] Open
Abstract
AIMS Electrocardiographic imaging (ECGI) is a promising tool to map the electrical activity of the heart non-invasively using body surface potentials (BSP). However, it is still challenging due to the mathematically ill-posed nature of the inverse problem to solve. Novel approaches leveraging progress in artificial intelligence could alleviate these difficulties. METHODS AND RESULTS We propose a deep learning (DL) formulation of ECGI in order to learn the statistical relation between BSP and cardiac activation. The presented method is based on Conditional Variational AutoEncoders using deep generative neural networks. To quantify the accuracy of this method, we simulated activation maps and BSP data on six cardiac anatomies.We evaluated our model by training it on five different cardiac anatomies (5000 activation maps) and by testing it on a new patient anatomy over 200 activation maps. Due to the probabilistic property of our method, we predicted 10 distinct activation maps for each BSP data. The proposed method is able to generate volumetric activation maps with a good accuracy on the simulated data: the mean absolute error is 9.40 ms with 2.16 ms standard deviation on this testing set. CONCLUSION The proposed formulation of ECGI enables to naturally include imaging information in the estimation of cardiac electrical activity from BSP. It naturally takes into account all the spatio-temporal correlations present in the data. We believe these features can help improve ECGI results.
Collapse
Affiliation(s)
- Tania Bacoyannis
- Inria, Université Côte d'Azur, Epione team, Sophia Antipolis, France
| | - Buntheng Ly
- Inria, Université Côte d'Azur, Epione team, Sophia Antipolis, France
| | - Nicolas Cedilnik
- Inria, Université Côte d'Azur, Epione team, Sophia Antipolis, France.,IHU Liryc, University of Bordeaux, Bordeaux, France
| | | | - Maxime Sermesant
- Inria, Université Côte d'Azur, Epione team, Sophia Antipolis, France.,IHU Liryc, University of Bordeaux, Bordeaux, France
| |
Collapse
|
37
|
Sermesant M, Delingette H, Cochet H, Jaïs P, Ayache N. Applications of artificial intelligence in cardiovascular imaging. Nat Rev Cardiol 2021; 18:600-609. [PMID: 33712806 DOI: 10.1038/s41569-021-00527-2] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2021] [Indexed: 01/31/2023]
Abstract
Research into artificial intelligence (AI) has made tremendous progress over the past decade. In particular, the AI-powered analysis of images and signals has reached human-level performance in many applications owing to the efficiency of modern machine learning methods, in particular deep learning using convolutional neural networks. Research into the application of AI to medical imaging is now very active, especially in the field of cardiovascular imaging because of the challenges associated with acquiring and analysing images of this dynamic organ. In this Review, we discuss the clinical questions in cardiovascular imaging that AI can be used to address and the principal methodological AI approaches that have been developed to solve the related image analysis problems. Some approaches are purely data-driven and rely mainly on statistical associations, whereas others integrate anatomical and physiological information through additional statistical, geometric and biophysical models of the human heart. In a structured manner, we provide representative examples of each of these approaches, with particular attention to the underlying computational imaging challenges. Finally, we discuss the remaining limitations of AI approaches in cardiovascular imaging (such as generalizability and explainability) and how they can be overcome.
Collapse
Affiliation(s)
| | | | - Hubert Cochet
- IHU Liryc, CHU Bordeaux, Université Bordeaux, Inserm 1045, Pessac, France
| | - Pierre Jaïs
- IHU Liryc, CHU Bordeaux, Université Bordeaux, Inserm 1045, Pessac, France
| | | |
Collapse
|
38
|
Aronis KN, Prakosa A, Bergamaschi T, Berger RD, Boyle PM, Chrispin J, Ju S, Marine JE, Sinha S, Tandri H, Ashikaga H, Trayanova NA. Characterization of the Electrophysiologic Remodeling of Patients With Ischemic Cardiomyopathy by Clinical Measurements and Computer Simulations Coupled With Machine Learning. Front Physiol 2021; 12:684149. [PMID: 34335294 PMCID: PMC8317643 DOI: 10.3389/fphys.2021.684149] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 06/22/2021] [Indexed: 11/13/2022] Open
Abstract
Rationale Patients with ischemic cardiomyopathy (ICMP) are at high risk for malignant arrhythmias, largely due to electrophysiological remodeling of the non-infarcted myocardium. The electrophysiological properties of the non-infarcted myocardium of patients with ICMP remain largely unknown. Objectives To assess the pro-arrhythmic behavior of non-infarcted myocardium in ICMP patients and couple computational simulations with machine learning to establish a methodology for the development of disease-specific action potential models based on clinically measured action potential duration restitution (APDR) data. Methods and Results We enrolled 22 patients undergoing left-sided ablation (10 ICMP) and compared APDRs between ICMP and structurally normal left ventricles (SNLVs). APDRs were clinically assessed with a decremental pacing protocol. Using genetic algorithms (GAs), we constructed populations of action potential models that incorporate the cohort-specific APDRs. The variability in the populations of ICMP and SNLV models was captured by clustering models based on their similarity using unsupervised machine learning. The pro-arrhythmic potential of ICMP and SNLV models was assessed in cell- and tissue-level simulations. Clinical measurements established that ICMP patients have a steeper APDR slope compared to SNLV (by 38%, p < 0.01). In cell-level simulations, APD alternans were induced in ICMP models at a longer cycle length compared to SNLV models (385–400 vs 355 ms). In tissue-level simulations, ICMP models were more susceptible for sustained functional re-entry compared to SNLV models. Conclusion Myocardial remodeling in ICMP patients is manifested as a steeper APDR compared to SNLV, which underlies the greater arrhythmogenic propensity in these patients, as demonstrated by cell- and tissue-level simulations using action potential models developed by GAs from clinical measurements. The methodology presented here captures the uncertainty inherent to GAs model development and provides a blueprint for use in future studies aimed at evaluating electrophysiological remodeling resulting from other cardiac diseases.
Collapse
Affiliation(s)
- Konstantinos N Aronis
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States.,Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Adityo Prakosa
- Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Teya Bergamaschi
- Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Ronald D Berger
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Patrick M Boyle
- Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Jonathan Chrispin
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Suyeon Ju
- Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Joseph E Marine
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Sunil Sinha
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Harikrishna Tandri
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Hiroshi Ashikaga
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Natalia A Trayanova
- Section of Electrophysiology, Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, United States.,Department of Biomedical Engineering, The Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| |
Collapse
|
39
|
Chaumont C, Suffee N, Gandjbakhch E, Balse E, Anselme F, Hatem SN. Epicardial origin of cardiac arrhythmias: clinical evidences and pathophysiology. Cardiovasc Res 2021; 118:1693-1702. [PMID: 34152392 PMCID: PMC9215195 DOI: 10.1093/cvr/cvab213] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/18/2021] [Indexed: 11/16/2022] Open
Abstract
Recent developments in imaging, mapping, and ablation techniques have shown that the epicardial region of the heart is a key player in the occurrence of ventricular arrhythmic events in several cardiac diseases, such as Brugada syndrome, arrhythmogenic cardiomyopathy, or dilated cardiomyopathy. At the atrial level as well, the epicardial region has emerged as an important determinant of the substrate of atrial fibrillation, pointing to common underlying pathophysiological mechanisms. Alteration in the gradient of repolarization between myocardial layers favouring the occurrence of re-entry circuits has largely been described. The fibro-fatty infiltration of the subepicardium is another shared substrate between ventricular and atrial arrhythmias. Recent data have emphasized the role of the epicardial reactivation in the formation of this arrhythmogenic substrate. There are new evidences supporting this structural remodelling process to be regulated by the recruitment of epicardial progenitor cells that can differentiate into adipocytes or fibroblasts under various stimuli. In addition, immune-inflammatory processes can also contribute to fibrosis of the subepicardial layer. A better understanding of such ‘electrical fragility’ of the epicardial area will open perspectives for novel biomarkers and therapeutic strategies. In this review article, a pathophysiological scheme of epicardial-driven arrhythmias will be proposed.
Collapse
Affiliation(s)
- Corentin Chaumont
- Cardiology Department, Rouen University Hospital, Rouen, France.,FHU REMOD-VHF, UNIROUEN, INSERM U1096, F76000, France
| | - Nadine Suffee
- INSERM UMRS1166, ICAN-Institute of CardioMetabolism and Nutrition, Sorbonne University, Institute of Cardiology, Pitié-Salpêtrière Hospital, Paris, France
| | - Estelle Gandjbakhch
- INSERM UMRS1166, ICAN-Institute of CardioMetabolism and Nutrition, Sorbonne University, Institute of Cardiology, Pitié-Salpêtrière Hospital, Paris, France
| | - Elise Balse
- INSERM UMRS1166, ICAN-Institute of CardioMetabolism and Nutrition, Sorbonne University, Institute of Cardiology, Pitié-Salpêtrière Hospital, Paris, France
| | - Frédéric Anselme
- Cardiology Department, Rouen University Hospital, Rouen, France.,FHU REMOD-VHF, UNIROUEN, INSERM U1096, F76000, France
| | - Stéphane N Hatem
- INSERM UMRS1166, ICAN-Institute of CardioMetabolism and Nutrition, Sorbonne University, Institute of Cardiology, Pitié-Salpêtrière Hospital, Paris, France
| |
Collapse
|
40
|
Bergquist JA, Coll-Font J, Zenger B, Rupp LC, Good WW, Brooks DH, MacLeod RS. Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation. FUNCTIONAL IMAGING AND MODELING OF THE HEART : ... INTERNATIONAL WORKSHOP, FIMH ..., PROCEEDINGS. FIMH 2021; 12738:493-502. [PMID: 34447971 PMCID: PMC8385662 DOI: 10.1007/978-3-030-78710-3_47] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Electrocardiographic imaging (ECGI) is an effective tool for noninvasive diagnosis of a range of cardiac dysfunctions. ECGI leverages a model of how cardiac bioelectric sources appear on the torso surface (the forward problem) and uses recorded body surface potential signals to reconstruct the bioelectric source (the inverse problem). Solutions to the inverse problem are sensitive to noise and variations in the body surface potential (BSP) recordings such as those caused by changes or errors in cardiac position. Techniques such as signal averaging seek to improve ECGI solutions by incorporating BSP signals from multiple heartbeats into an averaged BSP with a higher SNR to use when estimating the cardiac bioelectric source. However, signal averaging is limited when it comes to addressing sources of BSP variability such as beat to beat differences in the forward solution. We present a novel joint inverse formulation to solve for the cardiac source given multiple BSP recordings and known changes in the forward solution, here changes in the heart position. We report improved ECGI accuracy over signal averaging and averaged individual inverse solutions using this joint inverse formulation across multiple activation sequence types and regularization techniques with measured canine data and simulated heart motion. Our joint inverse formulation builds upon established techniques and consequently can easily be applied with many existing regularization techniques, source models, and forward problem formulations.
Collapse
Affiliation(s)
- Jake A Bergquist
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Jaume Coll-Font
- Cardiovascular Bioengineering & Imaging Lab, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, USA
| | - Brian Zenger
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Lindsay C Rupp
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Wilson W Good
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| | - Dana H Brooks
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
| | - Rob S MacLeod
- Biomedical Engineering Department, University of Utah, SLC, UT, 84112, USA
| |
Collapse
|
41
|
Jurak P, Bear LR, Nguyên UC, Viscor I, Andrla P, Plesinger F, Halamek J, Vondra V, Abell E, Cluitmans MJM, Dubois R, Curila K, Leinveber P, Prinzen FW. 3-Dimensional ventricular electrical activation pattern assessed from a novel high-frequency electrocardiographic imaging technique: principles and clinical importance. Sci Rep 2021; 11:11469. [PMID: 34075135 PMCID: PMC8169848 DOI: 10.1038/s41598-021-90963-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 05/19/2021] [Indexed: 11/29/2022] Open
Abstract
The study introduces and validates a novel high-frequency (100–400 Hz bandwidth, 2 kHz sampling frequency) electrocardiographic imaging (HFECGI) technique that measures intramural ventricular electrical activation. Ex-vivo experiments and clinical measurements were employed. Ex-vivo, two pig hearts were suspended in a human-torso shaped tank using surface tank electrodes, epicardial electrode sock, and plunge electrodes. We compared conventional epicardial electrocardiographic imaging (ECGI) with intramural activation by HFECGI and verified with sock and plunge electrodes. Clinical importance of HFECGI measurements was performed on 14 patients with variable conduction abnormalities. From 3 × 4 needle and 108 sock electrodes, 256 torso or 184 body surface electrodes records, transmural activation times, sock epicardial activation times, ECGI-derived activation times, and high-frequency activation times were computed. The ex-vivo transmural measurements showed that HFECGI measures intramural electrical activation, and ECGI-HFECGI activation times differences indicate endo-to-epi or epi-to-endo conduction direction. HFECGI-derived volumetric dyssynchrony was significantly lower than epicardial ECGI dyssynchrony. HFECGI dyssynchrony was able to distinguish between intraventricular conduction disturbance and bundle branch block patients.
Collapse
Affiliation(s)
- Pavel Jurak
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic.
| | - Laura R Bear
- IHU Liryc, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, CRCTB, U1045, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Uyên Châu Nguyên
- Department of Physiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Ivo Viscor
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic
| | - Petr Andrla
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic
| | - Filip Plesinger
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic
| | - Josef Halamek
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic
| | - Vlastimil Vondra
- Institute of Scientific Instruments, The Czech Academy of Sciences, Kralovopolska 147, Brno, 635 00, Czech Republic
| | - Emma Abell
- IHU Liryc, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, CRCTB, U1045, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Matthijs J M Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Rémi Dubois
- IHU Liryc, Fondation Bordeaux Université, Pessac-Bordeaux, France.,Univ. Bordeaux, CRCTB, U1045, Bordeaux, France.,INSERM, CRCTB, U1045, Bordeaux, France
| | - Karol Curila
- Cardiocenter, Department of Cardiology, 3rd Faculty of Medicine, Charles University and University Hospital Kralovske Vinohrady, Prague, Czech Republic
| | - Pavel Leinveber
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Frits W Prinzen
- Department of Physiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands
| |
Collapse
|
42
|
Bergquist JA, Good WW, Zenger B, Tate JD, Rupp LC, MacLeod RS. The electrocardiographic forward problem: A benchmark study. Comput Biol Med 2021; 134:104476. [PMID: 34051453 DOI: 10.1016/j.compbiomed.2021.104476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 05/02/2021] [Accepted: 05/03/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Electrocardiographic forward problems are crucial components for noninvasive electrocardiographic imaging (ECGI) that compute torso potentials from cardiac source measurements. Forward problems have few sources of error as they are physically well posed and supported by mature numerical and computational techniques. However, the residual errors reported from experimental validation studies between forward computed and measured torso signals remain surprisingly high. OBJECTIVE To test the hypothesis that incomplete cardiac source sampling, especially above the atrioventricular (AV) plane is a major contributor to forward solution errors. METHODS We used a modified Langendorff preparation suspended in a human-shaped electrolytic torso-tank and a novel pericardiac-cage recording array to thoroughly sample the cardiac potentials. With this carefully controlled experimental preparation, we minimized possible sources of error, including geometric error and torso inhomogeneities. We progressively removed recorded signals from above the atrioventricular plane to determine how the forward-computed torso-tank potentials were affected by incomplete source sampling. RESULTS We studied 240 beats total recorded from three different activation sequence types (sinus, and posterior and anterior left-ventricular free-wall pacing) in each of two experiments. With complete sampling by the cage electrodes, all correlation metrics between computed and measured torso-tank potentials were above 0.93 (maximum 0.99). The mean root-mean-squared error across all beat types was also low, less than or equal to 0.10 mV. A precipitous drop in forward solution accuracy was observed when we included only cage measurements below the AV plane. CONCLUSION First, our forward computed potentials using complete cardiac source measurements set a benchmark for similar studies. Second, this study validates the importance of complete cardiac source sampling above the AV plane to produce accurate forward computed torso potentials. Testing ECGI systems and techniques with these more complete and highly accurate datasets will improve inverse techniques and noninvasive detection of cardiac electrical abnormalities.
Collapse
Affiliation(s)
- Jake A Bergquist
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Wilson W Good
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA; School of Medicine, University of Utah, SLC, UT, USA.
| | - Jess D Tate
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA
| | - Lindsay C Rupp
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA
| | - Rob S MacLeod
- Scientific Computing and Imaging Institute, University of Utah, SLC, UT, USA; Nora Eccles Cardiovascular Research and Training Institute, University of Utah, SLC, UT, USA; Department of Biomedical Engineering, University of Utah, SLC, UT, USA; School of Medicine, University of Utah, SLC, UT, USA
| |
Collapse
|
43
|
Salinet J, Molero R, Schlindwein FS, Karel J, Rodrigo M, Rojo-Álvarez JL, Berenfeld O, Climent AM, Zenger B, Vanheusden F, Paredes JGS, MacLeod R, Atienza F, Guillem MS, Cluitmans M, Bonizzi P. Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value. Front Physiol 2021; 12:653013. [PMID: 33995122 PMCID: PMC8120164 DOI: 10.3389/fphys.2021.653013] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 03/22/2021] [Indexed: 01/16/2023] Open
Abstract
Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.
Collapse
Affiliation(s)
- João Salinet
- Biomedical Engineering, Centre for Engineering, Modelling and Applied Social Sciences (CECS), Federal University of ABC, São Bernardo do Campo, Brazil
| | - Rubén Molero
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Fernando S. Schlindwein
- School of Engineering, University of Leicester, United Kingdom and National Institute for Health Research, Leicester Cardiovascular Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Joël Karel
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands
| | - Miguel Rodrigo
- Electronic Engineering Department, Universitat de València, València, Spain
| | - José Luis Rojo-Álvarez
- Department of Signal Theory and Communications and Telematic Systems and Computation, University Rey Juan Carlos, Madrid, Spain
| | - Omer Berenfeld
- Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI, United States
| | - Andreu M. Climent
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Brian Zenger
- Biomedical Engineering Department, Scientific Computing and Imaging Institute (SCI), and Cardiovascular Research and Training Institute (CVRTI), The University of Utah, Salt Lake City, UT, United States
| | - Frederique Vanheusden
- Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
| | - Jimena Gabriela Siles Paredes
- Biomedical Engineering, Centre for Engineering, Modelling and Applied Social Sciences (CECS), Federal University of ABC, São Bernardo do Campo, Brazil
| | - Rob MacLeod
- Biomedical Engineering Department, Scientific Computing and Imaging Institute (SCI), and Cardiovascular Research and Training Institute (CVRTI), The University of Utah, Salt Lake City, UT, United States
| | - Felipe Atienza
- Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, and Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - María S. Guillem
- ITACA Institute, Universitat Politècnica de València, València, Spain
| | - Matthijs Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands
| | - Pietro Bonizzi
- Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands
| |
Collapse
|
44
|
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs. Med Image Anal 2021; 71:102080. [PMID: 33975097 DOI: 10.1016/j.media.2021.102080] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/15/2021] [Accepted: 04/06/2021] [Indexed: 12/21/2022]
Abstract
Cardiac digital twins (Cardiac Digital Twin (CDT)s) of human electrophysiology (Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that match like-for-like all available clinical observations. Due to their inherent predictive potential, CDTs show high promise as a complementary modality aiding in clinical decision making and also in the cost-effective, safe and ethical testing of novel EP device therapies. However, current workflows for both the anatomical and functional twinning phases within CDT generation, referring to the inference of model anatomy and parameters from clinical data, are not sufficiently efficient, robust and accurate for advanced clinical and industrial applications. Our study addresses three primary limitations impeding the routine generation of high-fidelity CDTs by introducing; a comprehensive parameter vector encapsulating all factors relating to the ventricular EP; an abstract reference frame within the model allowing the unattended manipulation of model parameter fields; a novel fast-forward electrocardiogram (Electrocardiogram (ECG)) model for efficient and bio-physically-detailed simulation required for parameter inference. A novel workflow for the generation of CDTs is then introduced as an initial proof of concept. Anatomical twinning was performed within a reasonable time compatible with clinical workflows (<4h) for 12 subjects from clinically-attained magnetic resonance images. After assessment of the underlying fast forward ECG model against a gold standard bidomain ECG model, functional twinning of optimal parameters according to a clinically-attained 12 lead ECG was then performed using a forward Saltelli sampling approach for a single subject. The achieved results in terms of efficiency and fidelity demonstrate that our workflow is well-suited and viable for generating biophysically-detailed CDTs at scale.
Collapse
|
45
|
Bear LR, Cluitmans M, Abell E, Rogier J, Labrousse L, Cheng LK, LeGrice I, Lever N, Sands GB, Smaill B, Haïssaguerre M, Bernus O, Coronel R, Dubois R. Electrocardiographic Imaging of Repolarization Abnormalities. J Am Heart Assoc 2021; 10:e020153. [PMID: 33880931 PMCID: PMC8200734 DOI: 10.1161/jaha.120.020153] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Background Dispersion and gradients in repolarization have been associated with life‐threatening arrhythmias, but are difficult to quantify precisely from surface electrocardiography. The objective of this study was to evaluate electrocardiographic imaging (ECGI) to noninvasively detect repolarization‐based abnormalities. Methods and Results Ex vivo data were obtained from Langendorff‐perfused pig hearts (n=8) and a human donor heart. Unipolar electrograms were recorded simultaneously during sinus rhythm from an epicardial sock and the torso‐shaped tank within which the heart was suspended. Regional repolarization heterogeneities were introduced through perfusion of dofetilide and pinacidil into separate perfusion beds. In vivo data included torso and epicardial potentials recorded simultaneously in anesthetized, closed‐chest pigs (n=5), during sinus rhythm, and ventricular pacing. For both data sets, ECGI accurately reconstructed T‐wave electrogram morphologies when compared with those recorded by the sock (ex vivo: correlation coefficient, 0.85 [0.52–0.96], in vivo: correlation coefficient, 0.86 [0.52–0.96]) and repolarization time maps (ex‐vivo: correlation coefficient, 0.73 [0.63–0.83], in vivo: correlation coefficient, 0.76 [0.67–0.82]). ECGI‐reconstructed repolarization time distributions were strongly correlated to those measured by the sock (both data sets, R2 ≥0.92). Although the position of the gradient was slightly shifted by 8.3 (0–13.9) mm, the mean, max, and SD between ECGI and recorded gradient values were highly correlated (R2=0.87, 0.75, and 0.86 respectively). There was no significant difference in ECGI accuracy between ex vivo and in vivo data. Conclusions ECGI reliably and accurately maps potentially critical repolarization abnormalities. This noninvasive approach allows imaging and quantifying individual parameters of abnormal repolarization‐based substrates in patients with arrhythmogenesis, to improve diagnosis and risk stratification.
Collapse
Affiliation(s)
- Laura R Bear
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | - Matthijs Cluitmans
- CARIM School for Cardiovascular Diseases Maastricht UMC Maastricht Netherlands
| | - Emma Abell
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | | | - Louis Labrousse
- IHU-LIRYCFondation Bordeaux Université Pessac France.,Department of Cardiac Surgery CHU Pessac France
| | - Leo K Cheng
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Ian LeGrice
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Nigel Lever
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Gregory B Sands
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Bruce Smaill
- Auckland Bioengineering Institute University of Auckland Auckland New Zealand
| | - Michel Haïssaguerre
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France.,Department of Cardiac Electrophysiology and Stimulation Bordeaux University Hospital (CHU) Pessac France
| | - Olivier Bernus
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| | - Ruben Coronel
- IHU-LIRYCFondation Bordeaux Université Pessac France.,Department of Experimental Cardiology Academic Medical Center Amsterdam the Netherlands
| | - Rémi Dubois
- IHU-LIRYCFondation Bordeaux Université Pessac France.,CRCTB U1045 Université de Bordeaux Bordeaux France.,Inserm U1045 CRCTB Pessac France
| |
Collapse
|
46
|
Pagani S, Dede’ L, Manzoni A, Quarteroni A. Data integration for the numerical simulation of cardiac electrophysiology. Pacing Clin Electrophysiol 2021; 44:726-736. [PMID: 33594761 PMCID: PMC8252775 DOI: 10.1111/pace.14198] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 01/26/2021] [Accepted: 02/07/2021] [Indexed: 12/20/2022]
Abstract
The increasing availability of extensive and accurate clinical data is rapidly shaping cardiovascular care by improving the understanding of physiological and pathological mechanisms of the cardiovascular system and opening new frontiers in designing therapies and interventions. In this direction, mathematical and numerical models provide a complementary relevant tool, able not only to reproduce patient-specific clinical indicators but also to predict and explore unseen scenarios. With this goal, clinical data are processed and provided as inputs to the mathematical model, which quantitatively describes the physical processes that occur in the cardiac tissue. In this paper, the process of integration of clinical data and mathematical models is discussed. Some challenges and contributions in the field of cardiac electrophysiology are reported.
Collapse
Affiliation(s)
- Stefano Pagani
- MOX‐Department of MathematicsPolitecnico di MilanoMilanItaly
| | - Luca Dede’
- MOX‐Department of MathematicsPolitecnico di MilanoMilanItaly
| | - Andrea Manzoni
- MOX‐Department of MathematicsPolitecnico di MilanoMilanItaly
| | - Alfio Quarteroni
- MOX‐Department of MathematicsPolitecnico di MilanoMilanItaly
- Institute of MathematicsEPFLLausanneSwitzerland
| |
Collapse
|
47
|
Borràs M, Chamorro-Servent J. Electrocardiographic Imaging: A Comparison of Iterative Solvers. Front Physiol 2021; 12:620250. [PMID: 33613311 PMCID: PMC7886787 DOI: 10.3389/fphys.2021.620250] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
Cardiac disease is a leading cause of morbidity and mortality in developed countries. Currently, non-invasive techniques that can identify patients at risk and provide accurate diagnosis and ablation guidance therapy are under development. One of these is electrocardiographic imaging (ECGI). In ECGI, the first step is to formulate a forward problem that relates the unknown potential sources on the cardiac surface to the measured body surface potentials. Then, the unknown potential sources on the cardiac surface are reconstructed through the solution of an inverse problem. Unfortunately, ECGI still lacks accuracy due to the underlying inverse problem being ill-posed, and this consequently imposes limitations on the understanding and treatment of many cardiac diseases. Therefore, it is necessary to improve the solution of the inverse problem. In this work, we transfer and adapt four inverse problem methods to the ECGI setting: algebraic reconstruction technique (ART), random ART, ART Split Bregman (ART-SB) and range restricted generalized minimal residual (RRGMRES) method. We test all these methods with data from the Experimental Data and Geometric Analysis Repository (EDGAR) and compare their solution with the recorded epicardial potentials provided by EDGAR and a generalized minimal residual (GMRES) iterative method computed solution. Activation maps are also computed and compared. The results show that ART achieved the most stable solutions and, for some datasets, returned the best reconstruction. Differences between the solutions derived from ART and random ART are almost negligible, and the accuracy of their solutions is followed by RRGMRES, ART-SB and finally the GMRES (which returned the worst reconstructions). The RRGMRES method provided the best reconstruction for some datasets but appeared to be less stable than ART when comparing different datasets. In conclusion, we show that the proposed methods (ART, random ART, and RRGMRES) improve the GMRES solution, which has been suggested as inverse problem solution for ECGI.
Collapse
Affiliation(s)
- Marta Borràs
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Judit Chamorro-Servent
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| |
Collapse
|
48
|
Roudijk RW, Taha K, Bourfiss M, Loh P, van den Heuvel L, Boonstra MJ, van Lint F, van der Voorn SM, Te Riele ASJM, Bosman LP, Christiaans I, van Veen TAB, Remme CA, van den Berg MP, van Tintelen JP, Asselbergs FW. Risk stratification and subclinical phenotyping of dilated and/or arrhythmogenic cardiomyopathy mutation-positive relatives: CVON eDETECT consortium. Neth Heart J 2021; 29:301-308. [PMID: 33528799 PMCID: PMC8160055 DOI: 10.1007/s12471-021-01542-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/14/2021] [Indexed: 11/17/2022] Open
Abstract
In relatives of index patients with dilated cardiomyopathy and arrhythmogenic cardiomyopathy, early detection of disease onset is essential to prevent sudden cardiac death and facilitate early treatment of heart failure. However, the optimal screening interval and combination of diagnostic techniques are unknown. The clinical course of disease in index patients and their relatives is variable due to incomplete and age-dependent penetrance. Several biomarkers, electrocardiographic and imaging (echocardiographic deformation imaging and cardiac magnetic resonance imaging) techniques are promising non-invasive methods for detection of subclinical cardiomyopathy. However, these techniques need optimisation and integration into clinical practice. Furthermore, determining the optimal interval and intensity of cascade screening may require a personalised approach. To address this, the CVON-eDETECT (early detection of disease in cardiomyopathy mutation carriers) consortium aims to integrate electronic health record data from long-term follow-up, diagnostic data sets, tissue and plasma samples in a multidisciplinary biobank environment to provide personalised risk stratification for heart failure and sudden cardiac death. Adequate risk stratification may lead to personalised screening, treatment and optimal timing of implantable cardioverter defibrillator implantation. In this article, we describe non-invasive diagnostic techniques used for detection of subclinical disease in relatives of index patients with dilated cardiomyopathy and arrhythmogenic cardiomyopathy.
Collapse
Affiliation(s)
- R W Roudijk
- Netherlands Heart Institute, Utrecht, The Netherlands.,Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - K Taha
- Netherlands Heart Institute, Utrecht, The Netherlands.,Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - M Bourfiss
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - P Loh
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - L van den Heuvel
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - M J Boonstra
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - F van Lint
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - S M van der Voorn
- Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - A S J M Te Riele
- Netherlands Heart Institute, Utrecht, The Netherlands.,Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - L P Bosman
- Netherlands Heart Institute, Utrecht, The Netherlands.,Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands
| | - I Christiaans
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Genetics, University Medical Centre Groningen, Groningen, The Netherlands
| | - T A B van Veen
- Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - C A Remme
- Department of Clinical and Experimental Cardiology, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - M P van den Berg
- Department of Cardiology, University Medical Centre Groningen, Groningen, The Netherlands
| | - J P van Tintelen
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.,Durrer Centre, Amsterdam, The Netherlands
| | - F W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands. .,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK. .,Health Data Research UK and Institute of Health Informatics, University College London, London, UK.
| |
Collapse
|
49
|
Grandits T, Gillette K, Neic A, Bayer J, Vigmond E, Pock T, Plank G. An Inverse Eikonal Method for Identifying Ventricular Activation Sequences from Epicardial Activation Maps. JOURNAL OF COMPUTATIONAL PHYSICS 2020; 419:109700. [PMID: 32952215 PMCID: PMC7116090 DOI: 10.1016/j.jcp.2020.109700] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
A key mechanism controlling cardiac function is the electrical activation sequence of the heart's main pumping chambers termed the ventricles. As such, personalization of the ventricular activation sequences is of pivotal importance for the clinical utility of computational models of cardiac electrophysiology. However, a direct observation of the activation sequence throughout the ventricular volume is virtually impossible. In this study, we report on a novel method for identification of activation sequences from activation maps measured at the outer surface of the heart termed the epicardium. Conceptually, the method attempts to identify the key factors governing the ventricular activation sequence - the timing of earliest activation sites (EAS) and the velocity tensor field within the ventricular walls - from sparse and noisy activation maps sampled from the epicardial surface and fits an Eikonal model to the observations. Regularization methods are first investigated to overcome the severe ill-posedness of the inverse problem in a simplified 2D example. These methods are then employed in an anatomically accurate biventricular model with two realistic activation models of varying complexity - a simplified trifascicular model (3F) and a topologically realistic model of the His-Purkinje system (HPS). Using epicardial activation maps at full resolution, we first demonstrate that reconstructing the volumetric activation sequence is, in principle, feasible under the assumption of known location of EAS and later evaluate robustness of the method against noise and reduced spatial resolution of observations. Our results suggest that the FIMIN algorithm is able to robustly recover the full 3D activation sequence using epicardial activation maps at a spatial resolution achievable with current mapping systems and in the presence of noise. Comparing the accuracy achieved in the reconstructed activation maps with clinical data uncertainties suggests that the FIMIN method may be suitable for the patient- specific parameterization of activation models.
Collapse
Affiliation(s)
- Thomas Grandits
- Institute of Computer Graphics and Vision, Graz University of Technology
- BioTechMed-Graz, Austria
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz
- BioTechMed-Graz, Austria
| | - Aurel Neic
- Institute of Biophysics, Medical University of Graz
| | - Jason Bayer
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux
| | - Edward Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux
| | - Thomas Pock
- Institute of Computer Graphics and Vision, Graz University of Technology
- BioTechMed-Graz, Austria
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz
- BioTechMed-Graz, Austria
| |
Collapse
|
50
|
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]
|