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Roney CH, Whitaker J, Sim I, O'Neill L, Mukherjee RK, Razeghi O, Vigmond EJ, Wright M, O'Neill MD, Williams SE, Niederer SA. A technique for measuring anisotropy in atrial conduction to estimate conduction velocity and atrial fibre direction. Comput Biol Med 2019; 104:278-290. [PMID: 30415767 PMCID: PMC6506689 DOI: 10.1016/j.compbiomed.2018.10.019] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 10/17/2018] [Accepted: 10/17/2018] [Indexed: 01/04/2023]
Abstract
BACKGROUND Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. METHODS We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). RESULTS Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20∘. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. CONCLUSIONS We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.
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Affiliation(s)
- Caroline H Roney
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.
| | - John Whitaker
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Iain Sim
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Louisa O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Rahul K Mukherjee
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Orod Razeghi
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Edward J Vigmond
- LIRYC Electrophysiology and Heart Modeling Institute, Campus Xavier Arnozan, Avenue du Haut Lévêque, 33600, Pessac, France; Univ. Bordeaux, IMB, UMR 5251, F-33400, Talence, France
| | - Matthew Wright
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Mark D O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven E Williams
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven A Niederer
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
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Park HS, Jeong DS, Yu HT, Pak HN, Shim J, Kim JY, Kim J, Lee JM, Kim KH, Roh SY, Cho YJ, Kim YH, Yoon NS. 2018 Korean Guidelines for Catheter Ablation of Atrial Fibrillation: Part I. INTERNATIONAL JOURNAL OF ARRHYTHMIA 2018. [DOI: 10.18501/arrhythmia.2018.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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103
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Advanced Imaging of the Left Atrium with Cardiac Magnetic Resonance: A Review of Current and Emerging Methods and Clinical Applications. CURRENT RADIOLOGY REPORTS 2018. [DOI: 10.1007/s40134-018-0303-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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104
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Rossi S, Gaeta S, Griffith BE, Henriquez CS. Muscle Thickness and Curvature Influence Atrial Conduction Velocities. Front Physiol 2018; 9:1344. [PMID: 30420809 PMCID: PMC6215968 DOI: 10.3389/fphys.2018.01344] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 09/06/2018] [Indexed: 12/04/2022] Open
Abstract
Electroanatomical mapping is currently used to provide clinicians with information about the electrophysiological state of the heart and to guide interventions like ablation. These maps can be used to identify ectopic triggers of an arrhythmia such as atrial fibrillation (AF) or changes in the conduction velocity (CV) that have been associated with poor cell to cell coupling or fibrosis. Unfortunately, many factors are known to affect CV, including membrane excitability, pacing rate, wavefront curvature, and bath loading, making interpretation challenging. In this work, we show how endocardial conduction velocities are also affected by the geometrical factors of muscle thickness and wall curvature. Using an idealized three-dimensional strand, we show that transverse conductivities and boundary conditions can slow down or speed up signal propagation, depending on the curvature of the muscle tissue. In fact, a planar wavefront that is parallel to a straight line normal to the mid-surface does not remain normal to the mid-surface in a curved domain. We further demonstrate that the conclusions drawn from the idealized test case can be used to explain spatial changes in conduction velocities in a patient-specific reconstruction of the left atrial posterior wall. The simulations suggest that the widespread assumption of treating atrial muscle as a two-dimensional manifold for electrophysiological simulations will not accurately represent the endocardial conduction velocities in regions of the heart thicker than 0.5 mm with significant wall curvature.
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Affiliation(s)
- Simone Rossi
- Cardiovascular Modeling and Simulation Laboratory, Carolina Center for Interdisciplinary Applied Mathematics, University of North Carolina, Chapel Hill, NC, United States
| | - Stephen Gaeta
- Clinical Cardiac Electrophysiology/Cardiology Division, Duke University Medical Center, Durham, NC, United States
| | - Boyce E. Griffith
- Cardiovascular Modeling and Simulation Laboratory, Carolina Center for Interdisciplinary Applied Mathematics, University of North Carolina, Chapel Hill, NC, United States
- Departments of Mathematics, Applied Physical Sciences, and Biomedical Engineering, University of North Carolina, Chapel Hill, NC, United States
- McAllister Heart Institute, University of North Carolina, Chapel Hill, NC, United States
| | - Craig S. Henriquez
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, United States
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105
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Left atrial scarring and conduction velocity dynamics: Rate dependent conduction slowing predicts sites of localized reentrant atrial tachycardias. Int J Cardiol 2018; 278:114-119. [PMID: 30391065 DOI: 10.1016/j.ijcard.2018.10.072] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 10/16/2018] [Accepted: 10/22/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND Low voltage zones (LVZs) are associated with conduction velocity (CV) slowing. Rate-dependent CV slowing may play a role in reentry mechanisms. METHODS Patients undergoing catheter ablation for AT were enrolled. Aim was to assess the relationship between rate-dependent CV slowing and sites of localized reentrant atrial tachycardias (AT). On a bipolar voltage map regions were defined as non-LVZs [≥0.5 mV], LVZs [0.2-0.5 mV] and very-LVZs [<0.2 mV]. Unipolar electrograms were recorded with a 64-pole basket catheter during uninterrupted atrial pacing at four pacing intervals (PIs) during sinus rhythm. CVs were measured between pole pairs along the wavefront path. Sites of rate-dependent CV slowing were defined as exhibiting a reduction in CV between PI = 600 ms and 250 ms of ≥20% more than the mean CV reduction seen between these PIs for that voltage zone. Rate-dependent CV slowing sites were correlated to sites of localized reentrant ATs as confirmed with conventional mapping, entrainment and response to ablation. RESULTS Eighteen patients were included (63 ± 10 years). Mean CV at 600 ms was 1.53 ± 0.19 m/s in non-LVZs, 1.14 ± 0.15 m/s in LVZs, and 0.73 ± 0.13 m/s in very-LVZs respectively (p < 0.001). Rate-dependent CV slowing sites were predominantly in LVZs [0.2-0.5 mV] (74.4 ± 10.3%; p < 0.001). Localized reentrant ATs were mapped to these sites in 81.8% of cases (sensitivity 81.8%, 95% CI 48.2-97.9% and specificity 83.9%, 95% CI 81.8-86.0%). Macro-reentrant or focal ATs were not mapped to sites of rate-dependent CV slowing. CONCLUSIONS Rate-dependent CV slowing sites are predominantly confined to LVZs [0.2-0.5 mV] and the resultant CV heterogeneity may promote reentry mechanisms. These may represent a novel adjunctive target for AT ablation.
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106
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Vagos M, van Herck IGM, Sundnes J, Arevalo HJ, Edwards AG, Koivumäki JT. Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges. Front Physiol 2018; 9:1221. [PMID: 30233399 PMCID: PMC6131668 DOI: 10.3389/fphys.2018.01221] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 08/13/2018] [Indexed: 12/19/2022] Open
Abstract
The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.
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Affiliation(s)
- Márcia Vagos
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Ilsbeth G. M. van Herck
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Joakim Sundnes
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Hermenegild J. Arevalo
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Andrew G. Edwards
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Jussi T. Koivumäki
- BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
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107
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Fastl TE, Tobon-Gomez C, Crozier A, Whitaker J, Rajani R, McCarthy KP, Sanchez-Quintana D, Ho SY, O'Neill MD, Plank G, Bishop MJ, Niederer SA. Personalized computational modeling of left atrial geometry and transmural myofiber architecture. Med Image Anal 2018; 47:180-190. [PMID: 29753182 PMCID: PMC6277816 DOI: 10.1016/j.media.2018.04.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 03/27/2018] [Accepted: 04/03/2018] [Indexed: 01/15/2023]
Abstract
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by complete absence of coordinated atrial contraction and is associated with an increased morbidity and mortality. Personalized computational modeling provides a novel framework for integrating and interpreting the role of atrial electrophysiology (EP) including the underlying anatomy and microstructure in the development and sustenance of AF. Coronary computed tomography angiography data were segmented using a statistics-based approach and the smoothed voxel representations were discretized into high-resolution tetrahedral finite element (FE) meshes. To estimate the complex left atrial myofiber architecture, individual fiber fields were generated according to morphological data on the endo- and epicardial surfaces based on local solutions of Laplace’s equation and transmurally interpolated to tetrahedral elements. The influence of variable transmural microstructures was quantified through EP simulations on 3 patients using 5 different fiber interpolation functions. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity tetrahedral FE meshes. The novel algorithm for automated incorporation of the left atrial fiber architecture provided a realistic estimate of the atrial microstructure and was able to qualitatively capture all important fiber bundles. Consistent maximum local activation times were predicted in EP simulations using individual transmural fiber interpolation functions for each patient suggesting a negligible effect of the transmural myofiber architecture on EP. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts accounting for detailed anatomy and microstructure and facilitates simulations of atrial EP.
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Affiliation(s)
- Thomas E Fastl
- Department of Biomedical Engineering, King's College London, London, United Kingdom.
| | - Catalina Tobon-Gomez
- Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Andrew Crozier
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - John Whitaker
- Department of Biomedical Engineering, King's College London, London, United Kingdom; Department of Cardiology, Guy's and St Thomas' Hospitals, London, United Kingdom
| | - Ronak Rajani
- Department of Biomedical Engineering, King's College London, London, United Kingdom; Department of Cardiology, Guy's and St Thomas' Hospitals, London, United Kingdom
| | - Karen P McCarthy
- Cardiac Morphology Unit, Royal Brompton Hospital, London, United Kingdom
| | | | - Siew Y Ho
- Cardiac Morphology Unit, Royal Brompton Hospital, London, United Kingdom
| | - Mark D O'Neill
- Department of Biomedical Engineering, King's College London, London, United Kingdom; Department of Cardiology, Guy's and St Thomas' Hospitals, London, United Kingdom
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Martin J Bishop
- Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven A Niederer
- Department of Biomedical Engineering, King's College London, London, United Kingdom
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108
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Trayanova NA, Boyle PM, Nikolov PP. Personalized Imaging and Modeling Strategies for Arrhythmia Prevention and Therapy. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2018; 5:21-28. [PMID: 29546250 PMCID: PMC5847279 DOI: 10.1016/j.cobme.2017.11.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The goal of this article is to review advances in computational modeling of the heart, with a focus on recent non-invasive clinical imaging- and simulation-based strategies aimed at improving the diagnosis and treatment of patients with arrhythmias and structural heart disease. Following a brief overview of the field of computational cardiology, we present recent applications of the personalized virtual-heart approach in predicting the optimal targets for infarct-related ventricular tachycardia and atrial fibrillation ablation, and in determining risk of sudden cardiac death in myocardial infarction patients. The hope is that with such models at the patient bedside, therapies could be improved, invasiveness of diagnostic procedures minimized, and health-care costs reduced.
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Affiliation(s)
- Natalia A Trayanova
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
| | - Patrick M Boyle
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
| | - Plamen P Nikolov
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
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109
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Schmidt EJ, Halperin HR. MRI use for atrial tissue characterization in arrhythmias and for EP procedure guidance. Int J Cardiovasc Imaging 2018; 34:81-95. [PMID: 28593399 PMCID: PMC5889521 DOI: 10.1007/s10554-017-1179-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 05/24/2017] [Indexed: 12/19/2022]
Abstract
We review the utilization of magnetic resonance imaging methods for classifying atrial tissue properties that act as a substrate for common cardiac arrhythmias, such as atrial fibrillation. We then review state-of-the-art methods for mapping this substrate as a predicate for treatment, as well as methods used to ablate the electrical pathways that cause arrhythmia and restore patients to sinus rhythm.
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Affiliation(s)
- Ehud J Schmidt
- Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
| | - Henry R Halperin
- Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
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110
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Calkins H, Hindricks G, Cappato R, Kim YH, Saad EB, Aguinaga L, Akar JG, Badhwar V, Brugada J, Camm J, Chen PS, Chen SA, Chung MK, Cosedis Nielsen J, Curtis AB, Davies DW, Day JD, d’Avila A, (Natasja) de Groot NMS, Di Biase L, Duytschaever M, Edgerton JR, Ellenbogen KA, Ellinor PT, Ernst S, Fenelon G, Gerstenfeld EP, Haines DE, Haissaguerre M, Helm RH, Hylek E, Jackman WM, Jalife J, Kalman JM, Kautzner J, Kottkamp H, Kuck KH, Kumagai K, Lee R, Lewalter T, Lindsay BD, Macle L, Mansour M, Marchlinski FE, Michaud GF, Nakagawa H, Natale A, Nattel S, Okumura K, Packer D, Pokushalov E, Reynolds MR, Sanders P, Scanavacca M, Schilling R, Tondo C, Tsao HM, Verma A, Wilber DJ, Yamane T. 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation. Europace 2018; 20:e1-e160. [PMID: 29016840 PMCID: PMC5834122 DOI: 10.1093/europace/eux274] [Citation(s) in RCA: 733] [Impact Index Per Article: 122.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Affiliation(s)
- Hugh Calkins
- From the Johns Hopkins Medical Institutions, Baltimore, MD
| | | | - Riccardo Cappato
- Humanitas Research Hospital, Arrhythmias and Electrophysiology Research Center, Milan, Italy (Dr. Cappato is now with the Department of Biomedical Sciences, Humanitas University, Milan, Italy, and IRCCS, Humanitas Clinical and Research Center, Milan, Italy)
| | | | - Eduardo B Saad
- Hospital Pro-Cardiaco and Hospital Samaritano, Botafogo, Rio de Janeiro, Brazil
| | | | | | - Vinay Badhwar
- West Virginia University School of Medicine, Morgantown, WV
| | - Josep Brugada
- Cardiovascular Institute, Hospital Clínic, University of Barcelona, Catalonia, Spain
| | - John Camm
- St. George's University of London, London, United Kingdom
| | | | | | | | | | | | - D Wyn Davies
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - John D Day
- Intermountain Medical Center Heart Institute, Salt Lake City, UT
| | | | | | - Luigi Di Biase
- Albert Einstein College of Medicine, Montefiore-Einstein Center for Heart & Vascular Care, Bronx, NY
| | | | | | | | | | - Sabine Ernst
- Royal Brompton and Harefield NHS Foundation Trust, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Guilherme Fenelon
- Albert Einstein Jewish Hospital, Federal University of São Paulo, São Paulo, Brazil
| | | | | | | | | | - Elaine Hylek
- Boston University School of Medicine, Boston, MA
| | - Warren M Jackman
- Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Jose Jalife
- University of Michigan, Ann Arbor, MI, the National Center for Cardiovascular Research Carlos III (CNIC) and CIBERCV, Madrid, Spain
| | - Jonathan M Kalman
- Royal Melbourne Hospital and University of Melbourne, Melbourne, Australia
| | - Josef Kautzner
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Hans Kottkamp
- Hirslanden Hospital, Department of Electrophysiology, Zurich, Switzerland
| | | | | | - Richard Lee
- Saint Louis University Medical School, St. Louis, MO
| | - Thorsten Lewalter
- Department of Cardiology and Intensive Care, Hospital Munich-Thalkirchen, Munich, Germany
| | | | - Laurent Macle
- Montreal Heart Institute, Department of Medicine, Université de Montréal, Montréal, Canada
| | | | - Francis E Marchlinski
- Hospital of the University of Pennsylvania, University of Pennsylvania School of Medicine, Philadelphia, PA
| | | | - Hiroshi Nakagawa
- Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Andrea Natale
- Texas Cardiac Arrhythmia Institute, St. David's Medical Center, Austin, TX
| | - Stanley Nattel
- Montreal Heart Institute and Université de Montréal, Montreal, Canada, McGill University, Montreal, Canada, and University Duisburg-Essen, Essen, Germany
| | - Ken Okumura
- Division of Cardiology, Saiseikai Kumamoto Hospital, Kumamoto, Japan
| | | | - Evgeny Pokushalov
- State Research Institute of Circulation Pathology, Novosibirsk, Russia
| | | | - Prashanthan Sanders
- Centre for Heart Rhythm Disorders, South Australian Health and Medical Research Institute, University of Adelaide and Royal Adelaide Hospital, Adelaide, Australia
| | | | | | - Claudio Tondo
- Cardiac Arrhythmia Research Center, Centro Cardiologico Monzino, IRCCS, Department of Cardiovascular Sciences, University of Milan, Milan, Italy
| | | | - Atul Verma
- Southlake Regional Health Centre, University of Toronto, Toronto, Canada
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112
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Shinbane JS, Saxon LA. Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation. J Cardiovasc Comput Tomogr 2017; 12:16-27. [PMID: 29198733 DOI: 10.1016/j.jcct.2017.11.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 11/08/2017] [Accepted: 11/12/2017] [Indexed: 01/17/2023]
Abstract
Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality, cost effectiveness, and overall value to medical care.
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Affiliation(s)
- Jerold S Shinbane
- Division of Cardiovascular Medicine/USC Center for Body Computing, Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States.
| | - Leslie A Saxon
- Division of Cardiovascular Medicine/USC Center for Body Computing, Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
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113
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Calkins H, Hindricks G, Cappato R, Kim YH, Saad EB, Aguinaga L, Akar JG, Badhwar V, Brugada J, Camm J, Chen PS, Chen SA, Chung MK, Nielsen JC, Curtis AB, Davies DW, Day JD, d’Avila A, de Groot N(N, Di Biase L, Duytschaever M, Edgerton JR, Ellenbogen KA, Ellinor PT, Ernst S, Fenelon G, Gerstenfeld EP, Haines DE, Haissaguerre M, Helm RH, Hylek E, Jackman WM, Jalife J, Kalman JM, Kautzner J, Kottkamp H, Kuck KH, Kumagai K, Lee R, Lewalter T, Lindsay BD, Macle L, Mansour M, Marchlinski FE, Michaud GF, Nakagawa H, Natale A, Nattel S, Okumura K, Packer D, Pokushalov E, Reynolds MR, Sanders P, Scanavacca M, Schilling R, Tondo C, Tsao HM, Verma A, Wilber DJ, Yamane T. 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation. Heart Rhythm 2017; 14:e275-e444. [PMID: 28506916 PMCID: PMC6019327 DOI: 10.1016/j.hrthm.2017.05.012] [Citation(s) in RCA: 1415] [Impact Index Per Article: 202.1] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Indexed: 02/07/2023]
Affiliation(s)
- Hugh Calkins
- Johns Hopkins Medical Institutions, Baltimore, MD
| | | | - Riccardo Cappato
- Humanitas Research Hospital, Arrhythmias and Electrophysiology Research Center, Milan, Italy (Dr. Cappato is now with the Department of Biomedical Sciences, Humanitas University, Milan, Italy, and IRCCS, Humanitas Clinical and Research Center, Milan, Italy)
| | | | - Eduardo B. Saad
- Hospital Pro-Cardiaco and Hospital Samaritano, Botafogo, Rio de Janeiro, Brazil
| | | | | | - Vinay Badhwar
- West Virginia University School of Medicine, Morgantown, WV
| | - Josep Brugada
- Cardiovascular Institute, Hospital Clínic, University of Barcelona, Catalonia, Spain
| | - John Camm
- St. George’s University of London, London, United Kingdom
| | | | | | | | | | | | - D. Wyn Davies
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - John D. Day
- Intermountain Medical Center Heart Institute, Salt Lake City, UT
| | | | | | - Luigi Di Biase
- Albert Einstein College of Medicine, Montefiore-Einstein Center for Heart & Vascular Care, Bronx, NY
| | | | | | | | | | - Sabine Ernst
- Royal Brompton and Harefield NHS Foundation Trust, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Guilherme Fenelon
- Albert Einstein Jewish Hospital, Federal University of São Paulo, São Paulo, Brazil
| | | | | | | | | | - Elaine Hylek
- Boston University School of Medicine, Boston, MA
| | - Warren M. Jackman
- Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Jose Jalife
- University of Michigan, Ann Arbor, MI, the National Center for Cardiovascular Research Carlos III (CNIC) and CIBERCV, Madrid, Spain
| | - Jonathan M. Kalman
- Royal Melbourne Hospital and University of Melbourne, Melbourne, Australia
| | - Josef Kautzner
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Hans Kottkamp
- Hirslanden Hospital, Department of Electrophysiology, Zurich, Switzerland
| | | | | | - Richard Lee
- Saint Louis University Medical School, St. Louis, MO
| | - Thorsten Lewalter
- Department of Cardiology and Intensive Care, Hospital Munich-Thalkirchen, Munich, Germany
| | | | - Laurent Macle
- Montreal Heart Institute, Department of Medicine, Université de Montréal, Montréal, Canada
| | | | - Francis E. Marchlinski
- Hospital of the University of Pennsylvania, University of Pennsylvania School of Medicine, Philadelphia, PA
| | | | - Hiroshi Nakagawa
- Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Andrea Natale
- Texas Cardiac Arrhythmia Institute, St. David’s Medical Center, Austin, TX
| | - Stanley Nattel
- Montreal Heart Institute and Université de Montréal, Montreal, Canada, McGill University, Montreal, Canada, and University Duisburg-Essen, Essen, Germany
| | - Ken Okumura
- Division of Cardiology, Saiseikai Kumamoto Hospital, Kumamoto, Japan
| | | | - Evgeny Pokushalov
- State Research Institute of Circulation Pathology, Novosibirsk, Russia
| | | | - Prashanthan Sanders
- Centre for Heart Rhythm Disorders, South Australian Health and Medical Research Institute, University of Adelaide and Royal Adelaide Hospital, Adelaide, Australia
| | | | | | - Claudio Tondo
- Cardiac Arrhythmia Research Center, Centro Cardiologico Monzino, IRCCS, Department of Cardiovascular Sciences, University of Milan, Milan, Italy
| | | | - Atul Verma
- Southlake Regional Health Centre, University of Toronto, Toronto, Canada
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114
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Calvo D, Filgueiras-Rama D, Jalife J. Propagation of Sinus Waves in the Atrial Architecture: When Laminar Electrical Fluxes Turn Turbulent. Circ Arrhythm Electrophysiol 2017; 10:CIRCEP.117.005699. [PMID: 28912207 DOI: 10.1161/circep.117.005699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Accepted: 08/21/2017] [Indexed: 11/16/2022]
Affiliation(s)
- David Calvo
- From the Arrhythmia Unit, Instituto de Investigación Sanitaria del Principado de Asturias, Hospital Universitario Central de Asturias, Oviedo, Spain (D.C.); Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC) Carlos III, Madrid, Spain (D.F., J.J.); Hospital Clínico Universitario San Carlos, Madrid, Spain (D.F.-R.); Center for Arrhythmia Research, University of Michigan, Ann Arbor (D.F., J.J.); and CIBERCV, Madrid, Spain (D.F., J.J.)
| | - David Filgueiras-Rama
- From the Arrhythmia Unit, Instituto de Investigación Sanitaria del Principado de Asturias, Hospital Universitario Central de Asturias, Oviedo, Spain (D.C.); Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC) Carlos III, Madrid, Spain (D.F., J.J.); Hospital Clínico Universitario San Carlos, Madrid, Spain (D.F.-R.); Center for Arrhythmia Research, University of Michigan, Ann Arbor (D.F., J.J.); and CIBERCV, Madrid, Spain (D.F., J.J.)
| | - José Jalife
- From the Arrhythmia Unit, Instituto de Investigación Sanitaria del Principado de Asturias, Hospital Universitario Central de Asturias, Oviedo, Spain (D.C.); Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC) Carlos III, Madrid, Spain (D.F., J.J.); Hospital Clínico Universitario San Carlos, Madrid, Spain (D.F.-R.); Center for Arrhythmia Research, University of Michigan, Ann Arbor (D.F., J.J.); and CIBERCV, Madrid, Spain (D.F., J.J.).
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115
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Deng D, Murphy MJ, Hakim JB, Franceschi WH, Zahid S, Pashakhanloo F, Trayanova NA, Boyle PM. Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate. CHAOS (WOODBURY, N.Y.) 2017; 27:093932. [PMID: 28964164 PMCID: PMC5605332 DOI: 10.1063/1.5003340] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 09/04/2017] [Indexed: 05/30/2023]
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.
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Affiliation(s)
- Dongdong Deng
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Michael J Murphy
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Joe B Hakim
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - William H Franceschi
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Sohail Zahid
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Farhad Pashakhanloo
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Natalia A Trayanova
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Patrick M Boyle
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
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116
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Rossi S, Griffith BE. Incorporating inductances in tissue-scale models of cardiac electrophysiology. CHAOS (WOODBURY, N.Y.) 2017; 27:093926. [PMID: 28964127 PMCID: PMC5585078 DOI: 10.1063/1.5000706] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 07/17/2017] [Indexed: 06/07/2023]
Abstract
In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and we examine the effect of intracellular and extracellular inductances on the virtual electrode phenomenon.
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Affiliation(s)
- Simone Rossi
- Department of Mathematics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Boyce E Griffith
- Departments of Mathematics and Biomedical Engineering and McAllister Heart Institute, University of North Carolina, Chapel Hill, North Carolina 27599, USA
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117
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WITHDRAWN: 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation. J Arrhythm 2017. [DOI: 10.1016/j.joa.2017.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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118
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Zhao J, Hansen BJ, Wang Y, Csepe TA, Sul LV, Tang A, Yuan Y, Li N, Bratasz A, Powell KA, Kilic A, Mohler PJ, Janssen PML, Weiss R, Simonetti OP, Hummel JD, Fedorov VV. Three-dimensional Integrated Functional, Structural, and Computational Mapping to Define the Structural "Fingerprints" of Heart-Specific Atrial Fibrillation Drivers in Human Heart Ex Vivo. J Am Heart Assoc 2017; 6:JAHA.117.005922. [PMID: 28862969 PMCID: PMC5586436 DOI: 10.1161/jaha.117.005922] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Structural remodeling of human atria plays a key role in sustaining atrial fibrillation (AF), but insufficient quantitative analysis of human atrial structure impedes the treatment of AF. We aimed to develop a novel 3-dimensional (3D) structural and computational simulation analysis tool that could reveal the structural contributors to human reentrant AF drivers. METHODS AND RESULTS High-resolution panoramic epicardial optical mapping of the coronary-perfused explanted intact human atria (63-year-old woman, chronic hypertension, heart weight 608 g) was conducted during sinus rhythm and sustained AF maintained by spatially stable reentrant AF drivers in the left and right atrium. The whole atria (107×61×85 mm3) were then imaged with contrast-enhancement MRI (9.4 T, 180×180×360-μm3 resolution). The entire 3D human atria were analyzed for wall thickness (0.4-11.7 mm), myofiber orientations, and transmural fibrosis (36.9% subendocardium; 14.2% midwall; 3.4% subepicardium). The 3D computational analysis revealed that a specific combination of wall thickness and fibrosis ranges were primarily present in the optically defined AF driver regions versus nondriver tissue. Finally, a 3D human heart-specific atrial computer model was developed by integrating 3D structural and functional mapping data to test AF induction, maintenance, and ablation strategies. This 3D model reproduced the optically defined reentrant AF drivers, which were uninducible when fibrosis and myofiber anisotropy were removed from the model. CONCLUSIONS Our novel 3D computational high-resolution framework may be used to quantitatively analyze structural substrates, such as wall thickness, myofiber orientation, and fibrosis, underlying localized AF drivers, and aid the development of new patient-specific treatments.
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Affiliation(s)
- Jichao Zhao
- Auckland Bioengineering Institute, The University of Auckland, New Zealand
| | - Brian J Hansen
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Yufeng Wang
- Auckland Bioengineering Institute, The University of Auckland, New Zealand
| | - Thomas A Csepe
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Lidiya V Sul
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Alan Tang
- Auckland Bioengineering Institute, The University of Auckland, New Zealand
| | - Yiming Yuan
- Auckland Bioengineering Institute, The University of Auckland, New Zealand
| | - Ning Li
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Anna Bratasz
- Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Kimerly A Powell
- Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Ahmet Kilic
- Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Peter J Mohler
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Paul M L Janssen
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Raul Weiss
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Orlando P Simonetti
- Department of Biomedical Informatics, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - John D Hummel
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH.,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Vadim V Fedorov
- Department of Physiology & Cell Biology, The Ohio State University Wexner Medical Center, Columbus, OH .,Davis Heart & Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH
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119
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Boyle PM, Zahid S, Trayanova NA. Using personalized computer models to custom-tailor ablation procedures for atrial fibrillation patients: are we there yet? Expert Rev Cardiovasc Ther 2017; 15:339-341. [PMID: 28395557 DOI: 10.1080/14779072.2017.1317593] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Patrick M Boyle
- a Institute for Computational Medicine and Department of Biomedical Engineering , Johns Hopkins University , Baltimore , USA
| | - Sohail Zahid
- a Institute for Computational Medicine and Department of Biomedical Engineering , Johns Hopkins University , Baltimore , USA
| | - Natalia A Trayanova
- a Institute for Computational Medicine and Department of Biomedical Engineering , Johns Hopkins University , Baltimore , USA
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120
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Jacquemet V. Equivalent dipole sources to estimate the influence of extracellular myocardial anisotropy in thin-walled cardiac forward models. Math Biosci 2017; 286:31-38. [PMID: 28159543 DOI: 10.1016/j.mbs.2017.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Revised: 01/26/2017] [Accepted: 01/27/2017] [Indexed: 10/20/2022]
Abstract
The extracellular domain of the heart is anisotropic, which affects volume conduction and therefore body surface potentials. This paper tests the hypothesis that when wall thickness is sufficiently small (such as in the atria), the effect of extracellular anisotropy can be estimated by modifying local dipole current sources. A formula based on the Gabor-Nelson equivalent dipole and on the reciprocity theorem is derived to compute a linear transformation of the dipole sources that approximates in an isotropic volume conductor the far-field of the actual sources in an anisotropic volume conductor. It involves solving three Poisson equation (once for all). The results obtained in an atrial model embedded in a boundary-element torso model suggest that when wall thickness is < 3 mm, simulated P waves are weakly altered by extracellular anisotropy during sinus rhythm: an anisotropy ratio of 4:1 typically reduced the longitudinal component of the dipole sources by < 3%, increased the transverse component by < 5%, and increased the transmural component by ≈ 25% (which may be relevant in case of epicardial-endocardial dissociation). Due to uncertainty on experimental conductivity values, it is proposed that atrial extracellular anisotropy may be neglected when computing P waves.
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Affiliation(s)
- Vincent Jacquemet
- Université de Montréal, Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Montréal, Canada; Hôpital du Sacré-Coeur de Montréal, Centre de Recherche, 5400 boul. Gouin Ouest, Montréal, H4J 1C5, Canada.
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121
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Pashakhanloo F, Herzka DA, Mori S, Zviman M, Halperin H, Gai N, Bluemke DA, Trayanova NA, McVeigh ER. Submillimeter diffusion tensor imaging and late gadolinium enhancement cardiovascular magnetic resonance of chronic myocardial infarction. J Cardiovasc Magn Reson 2017; 19:9. [PMID: 28122618 PMCID: PMC5264305 DOI: 10.1186/s12968-016-0317-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 12/20/2016] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Knowledge of the three-dimensional (3D) infarct structure and fiber orientation remodeling is essential for complete understanding of infarct pathophysiology and post-infarction electromechanical functioning of the heart. Accurate imaging of infarct microstructure necessitates imaging techniques that produce high image spatial resolution and high signal-to-noise ratio (SNR). The aim of this study is to provide detailed reconstruction of 3D chronic infarcts in order to characterize the infarct microstructural remodeling in porcine and human hearts. METHODS We employed a customized diffusion tensor imaging (DTI) technique in conjunction with late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) on a 3T clinical scanner to image, at submillimeter resolution, myofiber orientation and scar structure in eight chronically infarcted porcine hearts ex vivo. Systematic quantification of local microstructure was performed and the chronic infarct remodeling was characterized at different levels of wall thickness and scar transmurality. Further, a human heart with myocardial infarction was imaged using the same DTI sequence. RESULTS The SNR of non-diffusion-weighted images was >100 in the infarcted and control hearts. Mean diffusivity and fractional anisotropy (FA) demonstrated a 43% increase, and a 35% decrease respectively, inside the scar tissue. Despite this, the majority of the scar showed anisotropic structure with FA higher than an isotropic liquid. The analysis revealed that the primary eigenvector orientation at the infarcted wall on average followed the pattern of original fiber orientation (imbrication angle mean: 1.96 ± 11.03° vs. 0.84 ± 1.47°, p = 0.61, and inclination angle range: 111.0 ± 10.7° vs. 112.5 ± 6.8°, p = 0.61, infarcted/control wall), but at a higher transmural gradient of inclination angle that increased with scar transmurality (r = 0.36) and the inverse of wall thickness (r = 0.59). Further, the infarcted wall exhibited a significant increase in both the proportion of left-handed epicardial eigenvectors, and in the angle incoherency. The infarcted human heart demonstrated preservation of primary eigenvector orientation at the thinned region of infarct, consistent with the findings in the porcine hearts. CONCLUSIONS The application of high-resolution DTI and LGE-CMR revealed the detailed organization of anisotropic infarct structure at a chronic state. This information enhances our understanding of chronic post-infarction remodeling in large animal and human hearts.
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Affiliation(s)
- Farhad Pashakhanloo
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Daniel A. Herzka
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins University, Baltimore, MD USA
| | - Muz Zviman
- Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Henry Halperin
- Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Neville Gai
- Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD USA
| | - David A. Bluemke
- Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD USA
| | - Natalia A. Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Elliot R. McVeigh
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
- Department of Medicine, Johns Hopkins University, Baltimore, MD USA
- Departments of Bioengineering, Medicine, Radiology, University of California, 9500 Gilman Drive-MC0412,La Jolla, San Diego, 92093-0412 CA USA
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122
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Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation. Sci Rep 2016; 6:36395. [PMID: 27812021 PMCID: PMC5095679 DOI: 10.1038/srep36395] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 10/11/2016] [Indexed: 11/08/2022] Open
Abstract
The occurrence of atrial fibrillation (AF) is associated with progressive changes in the calcium handling system of atrial myocytes. Calcium cycling instability has been implicated as an underlying mechanism of electrical alternans observed in patients who experience AF. However, the extent to which calcium-induced alternation of electrical activity in the atria contributes to arrhythmogenesis is unknown. In this study, we investigated the effects of calcium-driven alternans (CDA) on arrhythmia susceptibility in a biophysically detailed, 3D computer model of the human atria representing electrical and structural remodeling secondary to chronic AF. We found that elevated propensity to CDA rendered the atria vulnerable to ectopy-induced arrhythmia. It also increased the complexity and persistence of arrhythmias induced by fast pacing, with unstable scroll waves meandering and frequently breaking up to produce multiple wavelets. Our results suggest that calcium-induced electrical instability may increase arrhythmia vulnerability and promote increasing disorganization of arrhythmias in the chronic AF-remodeled atria, thus playing an important role in the progression of the disease.
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123
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Teh I, McClymont D, Burton RAB, Maguire ML, Whittington HJ, Lygate CA, Kohl P, Schneider JE. Resolving Fine Cardiac Structures in Rats with High-Resolution Diffusion Tensor Imaging. Sci Rep 2016; 6:30573. [PMID: 27466029 PMCID: PMC4964346 DOI: 10.1038/srep30573] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Accepted: 07/04/2016] [Indexed: 02/03/2023] Open
Abstract
Cardiac architecture is fundamental to cardiac function and can be assessed non-invasively with diffusion tensor imaging (DTI). Here, we aimed to overcome technical challenges in ex vivo DTI in order to extract fine anatomical details and to provide novel insights in the 3D structure of the heart. An integrated set of methods was implemented in ex vivo rat hearts, including dynamic receiver gain adjustment, gradient system scaling calibration, prospective adjustment of diffusion gradients, and interleaving of diffusion-weighted and non-diffusion-weighted scans. Together, these methods enhanced SNR and spatial resolution, minimised orientation bias in diffusion-weighting, and reduced temperature variation, enabling detection of tissue structures such as cell alignment in atria, valves and vessels at an unprecedented level of detail. Improved confidence in eigenvector reproducibility enabled tracking of myolaminar structures as a basis for segmentation of functional groups of cardiomyocytes. Ex vivo DTI facilitates acquisition of high quality structural data that complements readily available in vivo cardiac functional and anatomical MRI. The improvements presented here will facilitate next generation virtual models integrating micro-structural and electro-mechanical properties of the heart.
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Rebecca A. B. Burton
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, United Kingdom
| | - Mahon L. Maguire
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Hannah J. Whittington
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Craig A. Lygate
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Peter Kohl
- National Heart and Lung Institute, Imperial College London, London, SW3 6NP, United Kingdom
- Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg · Bad Krozingen, Medical School of the University of Freiburg, Freiburg, 79110, Germany
| | - Jürgen E. Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
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