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Rodero C, Strocchi M, Marciniak M, Longobardi S, Whitaker J, O’Neill MD, Gillette K, Augustin C, Plank G, Vigmond EJ, Lamata P, Niederer SA. Linking statistical shape models and simulated function in the healthy adult human heart. PLoS Comput Biol 2021; 17:e1008851. [PMID: 33857152 PMCID: PMC8049237 DOI: 10.1371/journal.pcbi.1008851] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 03/03/2021] [Indexed: 01/09/2023] Open
Abstract
Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.
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Affiliation(s)
- Cristobal Rodero
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
- * E-mail:
| | - Marina Strocchi
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Maciej Marciniak
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Stefano Longobardi
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - John Whitaker
- Cardiovascular Imaging Department, King’s College London, London, United Kingdom
| | - Mark D. O’Neill
- Department of Cardiology, St Thomas’ Hospital, London, United Kingdom
| | - Karli Gillette
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | | | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Austria
| | - Edward J. Vigmond
- Institute of Electrophysiology and Heart Modeling, Foundation Bordeaux University, Bordeaux, France
- Bordeaux Institute of Mathematics, University of Bordeaux, Bordeaux, France
| | - Pablo Lamata
- Cardiac Modelling and Imaging Biomarkers, Biomedical Engineering Department, King´s College London, London, United Kingdom
| | - Steven A. Niederer
- Cardiac Electromechanics Research Group, Biomedical Engineering Department, King´s College London, London, United Kingdom
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Nguyen TD, Kadri OE, Voronov RS. An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine. Front Bioeng Biotechnol 2020; 8:529365. [PMID: 33102452 PMCID: PMC7546862 DOI: 10.3389/fbioe.2020.529365] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 08/31/2020] [Indexed: 02/05/2023] Open
Abstract
Cardiovascular diseases account for the number one cause of deaths in the world. Part of the reason for such grim statistics is our limited understanding of the underlying mechanisms causing these devastating pathologies, which is made difficult by the invasiveness of the procedures associated with their diagnosis (e.g., inserting catheters into the coronal artery to measure blood flow to the heart). Likewise, it is also difficult to design and test assistive devices without implanting them in vivo. However, with the recent advancements made in biomedical scanning technologies and computer simulations, image-based modeling (IBM) has arisen as the next logical step in the evolution of non-invasive patient-specific cardiovascular medicine. Yet, due to its novelty, it is still relatively unknown outside of the niche field. Therefore, the goal of this manuscript is to review the current state-of-the-art and the limitations of the methods used in this area of research, as well as their applications to personalized cardiovascular investigations and treatments. Specifically, the modeling of three different physics – electrophysiology, biomechanics and hemodynamics – used in the cardiovascular IBM is discussed in the context of the physiology that each one of them describes and the mechanisms of the underlying cardiac diseases that they can provide insight into. Only the “bare-bones” of the modeling approaches are discussed in order to make this introductory material more accessible to an outside observer. Additionally, the imaging methods, the aspects of the unique cardiac anatomy derived from them, and their relation to the modeling algorithms are reviewed. Finally, conclusions are drawn about the future evolution of these methods and their potential toward revolutionizing the non-invasive diagnosis, virtual design of treatments/assistive devices, and increasing our understanding of these lethal cardiovascular diseases.
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Affiliation(s)
- Thanh Danh Nguyen
- Otto H. York Department of Chemical and Materials Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Olufemi E Kadri
- Otto H. York Department of Chemical and Materials Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ, United States.,UC-P&G Simulation Center, University of Cincinnati, Cincinnati, OH, United States
| | - Roman S Voronov
- Otto H. York Department of Chemical and Materials Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ, United States.,Department of Biomedical Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ, United States
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Isotani A, Yoneda K, Iwamura T, Watanabe M, Okada JI, Washio T, Sugiura S, Hisada T, Ando K. Patient-specific heart simulation can identify non-responders to cardiac resynchronization therapy. Heart Vessels 2020; 35:1135-1147. [PMID: 32166443 PMCID: PMC7332486 DOI: 10.1007/s00380-020-01577-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 02/28/2020] [Indexed: 11/30/2022]
Abstract
To identify non-responders to cardiac resynchronization therapy (CRT), various biomarkers have been proposed, but these attempts have not been successful to date. We tested the clinical applicability of computer simulation of CRT for the identification of non-responders. We used the multi-scale heart simulator “UT-Heart,” which can reproduce the electrophysiology and mechanics of the heart based on a molecular model of the excitation–contraction mechanism. Patient-specific heart models were created for eight heart failure patients who were treated with CRT, based on the clinical data recorded before treatment. Using these heart models, bi-ventricular pacing simulations were performed at multiple pacing sites adopted in clinical practice. Improvement in pumping function measured by the relative change of maximum positive derivative of left ventricular pressure (%ΔdP/dtmax) was compared with the clinical outcome. The operators of the simulation were blinded to the clinical outcome. In six patients, the relative reduction in end-systolic volume exceeded 15% in the follow-up echocardiogram at 3 months (responders) and the remaining two patients were judged as non-responders. The simulated %ΔdP/dtmax at the best lead position could identify responders and non-responders successfully. With further refinement of the model, patient-specific simulation could be a useful tool for identifying non-responders to CRT.
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Affiliation(s)
- Akihiro Isotani
- Department of Cardiovascular Medicine, Kokura Memorial Hospital, Asano 3-2-1, Kokurakita-ku, Kitakyushu, Fukuoka, 802-8555, Japan
| | - Kazunori Yoneda
- Healthcare System Unit, Fujitsu Ltd, Ota-ku, Kamata, 144-8588, Japan
| | - Takashi Iwamura
- Healthcare System Unit, Fujitsu Ltd, Ota-ku, Kamata, 144-8588, Japan
| | - Masahiro Watanabe
- Healthcare System Unit, Fujitsu Ltd, Ota-ku, Kamata, 144-8588, Japan
| | - Jun-Ichi Okada
- Future Center Initiative, The University of Tokyo, Wakashiba 178-4-4, Kashiwa, Chiba, 277-0871, Japan
- UT-Heart Inc. Nozawa, 3-25-8, Setagaya, Tokyo, 154-0003, Japan
| | - Takumi Washio
- Future Center Initiative, The University of Tokyo, Wakashiba 178-4-4, Kashiwa, Chiba, 277-0871, Japan
- UT-Heart Inc. Nozawa, 3-25-8, Setagaya, Tokyo, 154-0003, Japan
| | - Seiryo Sugiura
- UT-Heart Inc. Nozawa, 3-25-8, Setagaya, Tokyo, 154-0003, Japan.
- Future Center #304, Wakashiba 178-4-4, Kashiwa, Chiba, 277-0871, Japan.
| | - Toshiaki Hisada
- UT-Heart Inc. Nozawa, 3-25-8, Setagaya, Tokyo, 154-0003, Japan
| | - Kenji Ando
- Department of Cardiovascular Medicine, Kokura Memorial Hospital, Asano 3-2-1, Kokurakita-ku, Kitakyushu, Fukuoka, 802-8555, Japan
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Strocchi M, Augustin CM, Gsell MAF, Karabelas E, Neic A, Gillette K, Razeghi O, Prassl AJ, Vigmond EJ, Behar JM, Gould J, Sidhu B, Rinaldi CA, Bishop MJ, Plank G, Niederer SA. A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations. PLoS One 2020; 15:e0235145. [PMID: 32589679 PMCID: PMC7319311 DOI: 10.1371/journal.pone.0235145] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 06/09/2020] [Indexed: 12/12/2022] Open
Abstract
Computational models of the heart are increasingly being used in the development of devices, patient diagnosis and therapy guidance. While software techniques have been developed for simulating single hearts, there remain significant challenges in simulating cohorts of virtual hearts from multiple patients. To facilitate the development of new simulation and model analysis techniques by groups without direct access to medical data, image analysis techniques and meshing tools, we have created the first publicly available virtual cohort of twenty-four four-chamber hearts. Our cohort was built from heart failure patients, age 67±14 years. We segmented four-chamber heart geometries from end-diastolic (ED) CT images and generated linear tetrahedral meshes with an average edge length of 1.1±0.2mm. Ventricular fibres were added in the ventricles with a rule-based method with an orientation of -60° and 80° at the epicardium and endocardium, respectively. We additionally refined the meshes to an average edge length of 0.39±0.10mm to show that all given meshes can be resampled to achieve an arbitrary desired resolution. We ran simulations for ventricular electrical activation and free mechanical contraction on all 1.1mm-resolution meshes to ensure that our meshes are suitable for electro-mechanical simulations. Simulations for electrical activation resulted in a total activation time of 149±16ms. Free mechanical contractions gave an average left ventricular (LV) and right ventricular (RV) ejection fraction (EF) of 35±1% and 30±2%, respectively, and a LV and RV stroke volume (SV) of 95±28mL and 65±11mL, respectively. By making the cohort publicly available, we hope to facilitate large cohort computational studies and to promote the development of cardiac computational electro-mechanics for clinical applications.
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Affiliation(s)
- Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
| | | | | | - Elias Karabelas
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
| | | | - Karli Gillette
- Institute of Biophysics, Medical University of Graz, Graz, Steiermark, Austria
| | - Orod Razeghi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
| | - Anton J. Prassl
- Institute of Biophysics, Medical University of Graz, Graz, Steiermark, Austria
| | - Edward J. Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, F-33600 Pessac- Bordeaux, France
- University of Bordeaux, IMB, UMR 5251, F-33400 Talence, France
| | - Jonathan M. Behar
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, City of London, United Kingdom
| | - Justin Gould
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, City of London, United Kingdom
| | - Baldeep Sidhu
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, City of London, United Kingdom
| | - Christopher A. Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, City of London, United Kingdom
| | - Martin J. Bishop
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz, Graz, Steiermark, Austria
| | - Steven A. Niederer
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, City of London, United Kingdom
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Kariya T, Washio T, Okada JI, Nakagawa M, Watanabe M, Kadooka Y, Sano S, Nagai R, Sugiura S, Hisada T. Personalized Perioperative Multi-scale, Multi-physics Heart Simulation of Double Outlet Right Ventricle. Ann Biomed Eng 2020; 48:1740-1750. [PMID: 32152800 DOI: 10.1007/s10439-020-02488-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 03/02/2020] [Indexed: 10/24/2022]
Abstract
For treatment of complex congenital heart disease, computer simulation using a three-dimensional heart model may help to improve outcomes by enabling detailed preoperative evaluations. However, no highly integrated model that accurately reproduces a patient's pathophysiology, which is required for this simulation has been reported. We modelled a case of complex congenital heart disease, double outlet right ventricle with ventricular septal defect and atrial septal defect. From preoperative computed tomography images, finite element meshes of the heart and torso were created, and cell model of cardiac electrophysiology and sarcomere dynamics was implemented. The parameter values of the heart model were adjusted to reproduce the patient's electrocardiogram and haemodynamics recorded preoperatively. Two options of in silico surgery were performed using this heart model, and the resulting changes in performance were examined. Preoperative and postoperative simulations showed good agreement with clinical records including haemodynamics and measured oxyhaemoglobin saturations. The use of a detailed sarcomere model also enabled comparison of energetic efficiency between the two surgical options. A novel in silico model of congenital heart disease that integrates molecular models of cardiac function successfully reproduces the observed pathophysiology. The simulation of postoperative state by in silico surgeries can help guide clinical decision-making.
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Affiliation(s)
- Taro Kariya
- Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Takumi Washio
- UT-Heart Inc, The University of Tokyo, Tokyo, Kashiwa-no-ha Campus Station Satellite #304, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan
| | - Jun-Ichi Okada
- UT-Heart Inc, The University of Tokyo, Tokyo, Kashiwa-no-ha Campus Station Satellite #304, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan
| | - Machiko Nakagawa
- Next-Generation Healthcare Innovation Center, Fujitsu Ltd., Tokyo, Japan
| | - Masahiro Watanabe
- Next-Generation Healthcare Innovation Center, Fujitsu Ltd., Tokyo, Japan
| | - Yoshimasa Kadooka
- Next-Generation Healthcare Innovation Center, Fujitsu Ltd., Tokyo, Japan
| | - Shunji Sano
- Department of Cardiac Surgery, Okayama University, Okayama, Japan
- Division of Pediatric Cardiothoracic Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Ryozo Nagai
- Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
- Jichi Medical University, Tochigi, Japan
| | - Seiryo Sugiura
- UT-Heart Inc, The University of Tokyo, Tokyo, Kashiwa-no-ha Campus Station Satellite #304, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan.
| | - Toshiaki Hisada
- UT-Heart Inc, The University of Tokyo, Tokyo, Kashiwa-no-ha Campus Station Satellite #304, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan
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Strocchi M, Gsell MAF, Augustin CM, Razeghi O, Roney CH, Prassl AJ, Vigmond EJ, Behar JM, Gould JS, Rinaldi CA, Bishop MJ, Plank G, Niederer SA. Simulating ventricular systolic motion in a four-chamber heart model with spatially varying robin boundary conditions to model the effect of the pericardium. J Biomech 2020; 101:109645. [PMID: 32014305 PMCID: PMC7677892 DOI: 10.1016/j.jbiomech.2020.109645] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 01/15/2020] [Accepted: 01/15/2020] [Indexed: 12/11/2022]
Abstract
The pericardium affects cardiac motion by limiting epicardial displacement normal to the surface. In computational studies, it is important for the model to replicate realistic motion, as this affects the physiological fidelity of the model. Previous computational studies showed that accounting for the effect of the pericardium allows for a more realistic motion simulation. In this study, we describe the mechanism through which the pericardium causes improved cardiac motion. We simulated electrical activation and contraction of the ventricles on a four-chamber heart in the presence and absence of the effect of the pericardium. We simulated the mechanical constraints imposed by the pericardium by applying normal Robin boundary conditions on the ventricular epicardium. We defined a regional scaling of normal springs stiffness based on image-derived motion from CT images. The presence of the pericardium reduced the error between simulated and image-derived end-systolic configurations from 12.8±4.1 mm to 5.7±2.5 mm. First, the pericardium prevents the ventricles from spherising during isovolumic contraction, reducing the outward motion of the free walls normal to the surface and the upwards motion of the apex. Second, by restricting the inward motion of the free and apical walls of the ventricles the pericardium increases atrioventricular plane displacement by four folds during ejection. Our results provide a mechanistic explanation of the importance of the pericardium in physiological simulations of electromechanical cardiac function.
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Affiliation(s)
- Marina Strocchi
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | | | | | - Orod Razeghi
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Caroline H Roney
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Anton J Prassl
- Department of Biophysics, Medical University of Graz, Graz, Austria
| | - Edward J Vigmond
- University of Bordeaux, Talence, France; LIRYC Electrophysiology and Heart Modeling Institute, Campus Xavier Arnozan, Pessac, France
| | - Jonathan M Behar
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Cardiology Department, Guys and St Thomas' NHS Foundation Trust, London, UK
| | - Justin S Gould
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Cardiology Department, Guys and St Thomas' NHS Foundation Trust, London, UK
| | - Christopher A Rinaldi
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Cardiology Department, Guys and St Thomas' NHS Foundation Trust, London, UK
| | - Martin J Bishop
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gernot Plank
- Department of Biophysics, Medical University of Graz, Graz, Austria
| | - Steven A Niederer
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Lee AWC, Nguyen UC, Razeghi O, Gould J, Sidhu BS, Sieniewicz B, Behar J, Mafi-Rad M, Plank G, Prinzen FW, Rinaldi CA, Vernooy K, Niederer S. A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data. Med Image Anal 2019; 57:197-213. [PMID: 31326854 PMCID: PMC6746621 DOI: 10.1016/j.media.2019.06.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 06/20/2019] [Accepted: 06/27/2019] [Indexed: 12/13/2022]
Abstract
Background Cardiac Resynchronization Therapy (CRT) is one of the few effective treatments for heart failure patients with ventricular dyssynchrony. The pacing location of the left ventricle is indicated as a determinant of CRT outcome. Objective Patient specific computational models allow the activation pattern following CRT implant to be predicted and this may be used to optimize CRT lead placement. Methods In this study, the effects of heterogeneous cardiac substrate (scar, fast endocardial conduction, slow septal conduction, functional block) on accurately predicting the electrical activation of the LV epicardium were tested to determine the minimal detail required to create a rule based model of cardiac electrophysiology. Non-invasive clinical data (CT or CMR images and 12 lead ECG) from eighteen patients from two centers were used to investigate the models. Results Validation with invasive electro-anatomical mapping data identified that computer models with fast endocardial conduction were able to predict the electrical activation with a mean distance errors of 9.2 ± 0.5 mm (CMR data) or (CT data) 7.5 ± 0.7 mm. Conclusion This study identified a simple rule-based fast endocardial conduction model, built using non-invasive clinical data that can be used to rapidly and robustly predict the electrical activation of the heart. Pre-procedural prediction of the latest electrically activating region to identify the optimal LV pacing site could potentially be a useful clinical planning tool for CRT procedures.
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Affiliation(s)
- A W C Lee
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - U C Nguyen
- Department of Physiology, Maastricht University Medical Center (MUMC+), Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands; Department of Cardiology, Maastricht University Medical Center (MUMC+), Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands
| | - O Razeghi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - J Gould
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - B S Sidhu
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - B Sieniewicz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - J Behar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Bart's Heart Centre, St. Bartholomew's Hospital, London, United Kingdom
| | - M Mafi-Rad
- Department of Cardiology, Maastricht University Medical Center (MUMC+), Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands
| | - G Plank
- Department of Biophysics, Medical University of Graz, Graz, Austria
| | - F W Prinzen
- Department of Physiology, Maastricht University Medical Center (MUMC+), Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands
| | - C A Rinaldi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - K Vernooy
- Department of Cardiology, Maastricht University Medical Center (MUMC+), Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands; Department of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - S Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Lee AWC, Costa CM, Strocchi M, Rinaldi CA, Niederer SA. Computational Modeling for Cardiac Resynchronization Therapy. J Cardiovasc Transl Res 2018; 11:92-108. [PMID: 29327314 PMCID: PMC5908824 DOI: 10.1007/s12265-017-9779-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 12/18/2017] [Indexed: 11/21/2022]
Abstract
Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure (HF) patients with an electrical substrate pathology causing ventricular dyssynchrony. However 40-50% of patients do not respond to treatment. Cardiac modeling of the electrophysiology, electromechanics, and hemodynamics of the heart has been used to study mechanisms behind HF pathology and CRT response. Recently, multi-scale dyssynchronous HF models have been used to study optimal device settings and optimal lead locations, investigate the underlying cardiac pathophysiology, as well as investigate emerging technologies proposed to treat cardiac dyssynchrony. However the breadth of patient and experimental data required to create and parameterize these models and the computational resources required currently limits the use of these models to small patient numbers. In the future, once these technical challenges are overcome, biophysically based models of the heart have the potential to become a clinical tool to aid in the diagnosis and treatment of HF.
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Affiliation(s)
- Angela W C Lee
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | | | - Marina Strocchi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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9
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Okada JI, Washio T, Nakagawa M, Watanabe M, Kadooka Y, Kariya T, Yamashita H, Yamada Y, Momomura SI, Nagai R, Hisada T, Sugiura S. Multi-scale, tailor-made heart simulation can predict the effect of cardiac resynchronization therapy. J Mol Cell Cardiol 2017; 108:17-23. [PMID: 28502795 DOI: 10.1016/j.yjmcc.2017.05.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 05/09/2017] [Accepted: 05/10/2017] [Indexed: 01/09/2023]
Abstract
BACKGROUND The currently proposed criteria for identifying patients who would benefit from cardiac resynchronization therapy (CRT) still need to be optimized. A multi-scale heart simulation capable of reproducing the electrophysiology and mechanics of a beating heart may help resolve this problem. The objective of this retrospective study was to test the capability of patient-specific simulation models to reproduce the response to CRT by applying the latest multi-scale heart simulation technology. METHODS AND RESULTS We created patient-specific heart models with realistic three-dimensional morphology based on the clinical data recorded before treatment in nine patients with heart failure and conduction block treated by biventricular pacing. Each model was tailored to reproduce the surface electrocardiogram and hemodynamics of each patient in formats similar to those used in clinical practice, including electrocardiography (ECG), echocardiography, and hemodynamic measurements. We then performed CRT simulation on each heart model according to the actual pacing protocol and compared the results with the clinical data. CRT simulation improved the ECG index and diminished wall motion dyssynchrony in each patient. These results, however, did not correlate with the actual response. The best correlation was obtained between the maximum value of the time derivative of ventricular pressure (dP/dtmax) and the clinically observed improvement in the ejection fraction (EF) (r=0.94, p<0.01). CONCLUSIONS By integrating the complex pathophysiology of the heart, patient-specific, multi-scale heart simulation could successfully reproduce the response to CRT. With further verification, this technique could be a useful tool in clinical decision making.
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Affiliation(s)
- Jun-Ichi Okada
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba 277-0871, Japan.
| | - Takumi Washio
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba 277-0871, Japan
| | - Machiko Nakagawa
- Healthcare System Unit, Fujitsu Ltd., Ota-ku, Tokyo 144-8588, Japan
| | | | | | - Taro Kariya
- Department of Cardiovascular Medicine, School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hiroshi Yamashita
- Department of Cardiovascular Medicine, School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Yoko Yamada
- Department of Cardiovascular Medicine, Saitama Medical Center, Jichi Medical University, Saitama-shi, Saitama 330-8503, Japan
| | - Shin-Ichi Momomura
- Department of Cardiovascular Medicine, Saitama Medical Center, Jichi Medical University, Saitama-shi, Saitama 330-8503, Japan
| | - Ryozo Nagai
- Department of Cardiovascular Medicine, School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Toshiaki Hisada
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba 277-0871, Japan; Healthcare System Unit, Fujitsu Ltd., Ota-ku, Tokyo 144-8588, Japan
| | - Seiryo Sugiura
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba 277-0871, Japan
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10
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Galli E, Leclercq C, Donal E. Mechanical dyssynchrony in heart failure: Still a valid concept for optimizing treatment? Arch Cardiovasc Dis 2017; 110:60-68. [DOI: 10.1016/j.acvd.2016.12.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 11/30/2016] [Accepted: 12/01/2016] [Indexed: 12/15/2022]
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11
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Soto Iglesias D, Duchateau N, Kostantyn Butakov CB, Andreu D, Fernandez-Armenta J, Bijnens B, Berruezo A, Sitges M, Camara O. Quantitative Analysis of Electro-Anatomical Maps: Application to an Experimental Model of Left Bundle Branch Block/Cardiac Resynchronization Therapy. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM 2016; 5:1900215. [PMID: 29164019 PMCID: PMC5477765 DOI: 10.1109/jtehm.2016.2634006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Revised: 08/08/2016] [Accepted: 11/14/2016] [Indexed: 01/02/2023]
Abstract
Electro-anatomical maps (EAMs) are commonly acquired in clinical routine for guiding
ablation therapies. They provide voltage and activation time information on a 3-D
anatomical mesh representation, making them useful for analyzing the electrical
activation patterns in specific pathologies. However, the variability between the
different acquisitions and anatomies hampers the comparison between different maps.
This paper presents two contributions for the analysis of electrical patterns in EAM
data from biventricular surfaces of cardiac chambers. The first contribution is an
integrated automatic 2-D disk representation (2-D bull’s eye plot) of the left
ventricle (LV) and right ventricle (RV) obtained with a quasi-conformal mapping from
the 3-D EAM meshes, that allows an analysis of cardiac resynchronization therapy
(CRT) lead positioning, interpretation of global (total activation time), and local
indices (local activation time (LAT), surrogates of conduction velocity,
inter-ventricular, and transmural delays) that characterize changes in the electrical
activation pattern. The second contribution is a set of indices derived from the
electrical activation: speed maps, computed from LAT values, to study the electrical
wave propagation, and histograms of isochrones to analyze regional electrical
heterogeneities in the ventricles. We have applied the proposed methods to look for
the underlying physiological mechanisms of left bundle branch block (LBBB) and CRT,
with the goal of optimizing the therapy by improving CRT response. To better
illustrate the benefits of the proposed tools, we created a set of synthetically
generated and fully controlled activation patterns, where the proposed representation
and indices were validated. Then, the proposed analysis tools are used to analyze EAM
data from an experimental swine model of induced LBBB with an implanted CRT device.
We have analyzed and compared the electrical activation patterns at baseline, LBBB,
and CRT stages in four animals: two without any structural disease and two with an
induced infarction. By relating the CRT lead location with electrical dyssynchrony,
we evaluated current hypotheses about lead placement in CRT and showed that optimal
pacing sites should target the RV lead close to the apex and the LV one distant from
it.
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Affiliation(s)
- David Soto Iglesias
- PhySense, Information and Communication Technologies DepartmentUniversitat Pompeu Fabra.,Cardiology DepartmentThorax Institute, Hospital Clinic
| | | | | | - David Andreu
- Cardiology DepartmentThorax Institute, Hospital Clinic
| | | | - Bart Bijnens
- PhySense, Information and Communication Technologies DepartmentUniversitat Pompeu Fabra.,Catalan Institution for Research and Advanced Studies
| | | | - Marta Sitges
- Cardiology DepartmentThorax Institute, Hospital Clinic
| | - Oscar Camara
- PhySense, Information and Communication Technologies DepartmentUniversitat Pompeu Fabra
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12
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Amr A, Kayvanpour E, Sedaghat-Hamedani F, Passerini T, Mihalef V, Lai A, Neumann D, Georgescu B, Buss S, Mereles D, Zitron E, Posch AE, Würstle M, Mansi T, Katus HA, Meder B. Personalized Computer Simulation of Diastolic Function in Heart Failure. GENOMICS PROTEOMICS & BIOINFORMATICS 2016; 14:244-52. [PMID: 27477449 PMCID: PMC4996856 DOI: 10.1016/j.gpb.2016.04.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 04/21/2016] [Accepted: 04/26/2016] [Indexed: 01/14/2023]
Abstract
The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (τ). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.
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Affiliation(s)
- Ali Amr
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany
| | - Elham Kayvanpour
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany
| | - Farbod Sedaghat-Hamedani
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany
| | - Tiziano Passerini
- Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA
| | - Viorel Mihalef
- Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA
| | - Alan Lai
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany
| | - Dominik Neumann
- Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA
| | - Bogdan Georgescu
- Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA
| | - Sebastian Buss
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany
| | - Derliz Mereles
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany
| | - Edgar Zitron
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany
| | - Andreas E Posch
- Siemens Healthcare, Strategy and Innovation, 91052 Erlangen, Germany
| | | | - Tommaso Mansi
- Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA
| | - Hugo A Katus
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany
| | - Benjamin Meder
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
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13
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Panthee N, Okada JI, Washio T, Mochizuki Y, Suzuki R, Koyama H, Ono M, Hisada T, Sugiura S. Tailor-made heart simulation predicts the effect of cardiac resynchronization therapy in a canine model of heart failure. Med Image Anal 2016; 31:46-62. [PMID: 26973218 DOI: 10.1016/j.media.2016.02.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Revised: 02/12/2016] [Accepted: 02/15/2016] [Indexed: 11/25/2022]
Abstract
Despite extensive studies on clinical indices for the selection of patient candidates for cardiac resynchronization therapy (CRT), approximately 30% of selected patients do not respond to this therapy. Herein, we examined whether CRT simulations based on individualized realistic three-dimensional heart models can predict the therapeutic effect of CRT in a canine model of heart failure with left bundle branch block. In four canine models of failing heart with dyssynchrony, individualized three-dimensional heart models reproducing the electromechanical activity of each animal were created based on the computer tomographic images. CRT simulations were performed for 25 patterns of three ventricular pacing lead positions. Lead positions producing the best and the worst therapeutic effects were selected in each model. The validity of predictions was tested in acute experiments in which hearts were paced from the sites identified by simulations. We found significant correlations between the experimentally observed improvement in ejection fraction (EF) and the predicted improvements in ejection fraction (P<0.01) or the maximum value of the derivative of left ventricular pressure (P<0.01). The optimal lead positions produced better outcomes compared with the worst positioning in all dogs studied, although there were significant variations in responses. Variations in ventricular wall thickness among the dogs may have contributed to these responses. Thus CRT simulations using the individualized three-dimensional heart models can predict acute hemodynamic improvement, and help determine the optimal positions of the pacing lead.
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Affiliation(s)
- Nirmal Panthee
- Department of Cardiac Surgery, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 Japan
| | - Jun-ichi Okada
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871 Japan; UT-Heart Inc. 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003 Japan
| | - Takumi Washio
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871 Japan; UT-Heart Inc. 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003 Japan
| | - Youhei Mochizuki
- Laboratory of Veterinary Internal Medicine, Nippon Veterinary and Life Science University, 1-7-1 Kyonancho, Musashino-shi, Tokyo 180-8602 Japan
| | - Ryohei Suzuki
- Laboratory of Veterinary Internal Medicine, Nippon Veterinary and Life Science University, 1-7-1 Kyonancho, Musashino-shi, Tokyo 180-8602 Japan
| | - Hidekazu Koyama
- Laboratory of Veterinary Internal Medicine, Nippon Veterinary and Life Science University, 1-7-1 Kyonancho, Musashino-shi, Tokyo 180-8602 Japan
| | - Minoru Ono
- Department of Cardiac Surgery, School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 Japan
| | - Toshiaki Hisada
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871 Japan; UT-Heart Inc. 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003 Japan
| | - Seiryo Sugiura
- Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871 Japan; UT-Heart Inc. 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003 Japan.
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14
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Trayanova NA, Chang KC. How computer simulations of the human heart can improve anti-arrhythmia therapy. J Physiol 2016; 594:2483-502. [PMID: 26621489 DOI: 10.1113/jp270532] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2015] [Accepted: 11/25/2015] [Indexed: 01/26/2023] Open
Abstract
Over the last decade, the state-of-the-art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation-guided approaches to anti-arrhythmic drug development and patient-specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti-arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia.
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Affiliation(s)
- Natalia A Trayanova
- Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.,Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Kelly C Chang
- Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
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15
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Lekadir K, Lange M, Zimmer VA, Hoogendoorn C, Frangi AF. Statistically-driven 3D fiber reconstruction and denoising from multi-slice cardiac DTI using a Markov random field model. Med Image Anal 2016; 27:105-16. [DOI: 10.1016/j.media.2015.03.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Revised: 11/10/2014] [Accepted: 03/14/2015] [Indexed: 11/29/2022]
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16
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Kayvanpour E, Mansi T, Sedaghat-Hamedani F, Amr A, Neumann D, Georgescu B, Seegerer P, Kamen A, Haas J, Frese KS, Irawati M, Wirsz E, King V, Buss S, Mereles D, Zitron E, Keller A, Katus HA, Comaniciu D, Meder B. Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart. PLoS One 2015; 10:e0134869. [PMID: 26230546 PMCID: PMC4521877 DOI: 10.1371/journal.pone.0134869] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Accepted: 07/14/2015] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. METHODS AND RESULTS State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. CONCLUSION This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation.
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Affiliation(s)
- Elham Kayvanpour
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Tommaso Mansi
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Farbod Sedaghat-Hamedani
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Ali Amr
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Dominik Neumann
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Bogdan Georgescu
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Philipp Seegerer
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Ali Kamen
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Jan Haas
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Karen S. Frese
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Maria Irawati
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
| | - Emil Wirsz
- Siemens AG, Corporate Technology, Erlangen, Germany
| | - Vanessa King
- Siemens Corporation, Corporate Technology, Sensor Technologies, Princeton, New Jersey, United States of America
| | - Sebastian Buss
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
| | - Derliz Mereles
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
| | - Edgar Zitron
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
| | - Andreas Keller
- Biomarker Discovery Center Heidelberg, Heidelberg, Germany
- Department of Human Genetics, Saarland University, Homburg, Germany
| | - Hugo A. Katus
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
- Klaus Tschira Institute for Computational Cardiology, Heidelberg, Germany
| | - Dorin Comaniciu
- Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, New Jersey, United States of America
| | - Benjamin Meder
- Department of Medicine III, University of Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
- Klaus Tschira Institute for Computational Cardiology, Heidelberg, Germany
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17
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Walmsley J, Arts T, Derval N, Bordachar P, Cochet H, Ploux S, Prinzen FW, Delhaas T, Lumens J. Fast Simulation of Mechanical Heterogeneity in the Electrically Asynchronous Heart Using the MultiPatch Module. PLoS Comput Biol 2015. [PMID: 26204520 PMCID: PMC4512705 DOI: 10.1371/journal.pcbi.1004284] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Cardiac electrical asynchrony occurs as a result of cardiac pacing or conduction disorders such as left bundle-branch block (LBBB). Electrically asynchronous activation causes myocardial contraction heterogeneity that can be detrimental for cardiac function. Computational models provide a tool for understanding pathological consequences of dyssynchronous contraction. Simulations of mechanical dyssynchrony within the heart are typically performed using the finite element method, whose computational intensity may present an obstacle to clinical deployment of patient-specific models. We present an alternative based on the CircAdapt lumped-parameter model of the heart and circulatory system, called the MultiPatch module. Cardiac walls are subdivided into an arbitrary number of patches of homogeneous tissue. Tissue properties and activation time can differ between patches. All patches within a wall share a common wall tension and curvature. Consequently, spatial location within the wall is not required to calculate deformation in a patch. We test the hypothesis that activation time is more important than tissue location for determining mechanical deformation in asynchronous hearts. We perform simulations representing an experimental study of myocardial deformation induced by ventricular pacing, and a patient with LBBB and heart failure using endocardial recordings of electrical activation, wall volumes, and end-diastolic volumes. Direct comparison between simulated and experimental strain patterns shows both qualitative and quantitative agreement between model fibre strain and experimental circumferential strain in terms of shortening and rebound stretch during ejection. Local myofibre strain in the patient simulation shows qualitative agreement with circumferential strain patterns observed in the patient using tagged MRI. We conclude that the MultiPatch module produces realistic regional deformation patterns in the asynchronous heart and that activation time is more important than tissue location within a wall for determining myocardial deformation. The CircAdapt model is therefore capable of fast and realistic simulations of dyssynchronous myocardial deformation embedded within the closed-loop cardiovascular system. Under normal conditions, the electrical activation of the heart is almost synchronous, leading to uniform contraction. Due to either pathology or electrical pacing, the heart can be activated asynchronously. The result is discoordinated contraction and a reduction in the ability to pump blood. There is considerable interest in using computer simulations to understand how asynchronous electrical activation affects cardiac deformation, and how pathologies of the cardiac conduction system can be treated by pacing the heart. We present the MultiPatch module for simulating the effects of asynchronous electrical activation on cardiac contraction in the relatively simple CircAdapt model of the heart and circulation. We quantitatively compare model simulations to deformation patterns recorded during an experimental study of pacing-induced electrical asynchrony. We then demonstrate a ‘patient-specific’ simulation of deformation in a patient with a conduction disorder called left bundle-branch block. We use timings from endocardial mapping of electrical activation in a patient as an input for the model, and compare the resulting simulated deformation patterns to tagged magnetic resonance imaging recordings from the same patient. The model qualitatively reproduces deformation as observed in the patient. We conclude that the MultiPatch module makes CircAdapt appropriate for simulation of dyssynchronous heart failure in patients.
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Affiliation(s)
- John Walmsley
- Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
- * E-mail:
| | - Theo Arts
- Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
| | - Nicolas Derval
- Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France
| | - Pierre Bordachar
- Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France
| | - Hubert Cochet
- Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France
| | - Sylvain Ploux
- Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France
| | - Frits W. Prinzen
- Department of Physiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
| | - Tammo Delhaas
- Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands
- Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France
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18
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Palamara S, Vergara C, Catanzariti D, Faggiano E, Pangrazzi C, Centonze M, Nobile F, Maines M, Quarteroni A. Computational generation of the Purkinje network driven by clinical measurements: the case of pathological propagations. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2014; 30:1558-77. [PMID: 25319252 DOI: 10.1002/cnm.2689] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2014] [Revised: 09/25/2014] [Accepted: 09/25/2014] [Indexed: 05/16/2023]
Abstract
To properly describe the electrical activity of the left ventricle, it is necessary to model the Purkinje fibers, responsible for the fast and coordinate ventricular activation, and their interaction with the muscular propagation. The aim of this work is to propose a methodology for the generation of a patient-specific Purkinje network driven by clinical measurements of the activation times related to pathological propagations. In this case, one needs to consider a strongly coupled problem between the network and the muscle, where the feedback from the latter to the former cannot be neglected as in a normal propagation. We apply the proposed strategy to data acquired on three subjects, one of them suffering from muscular conduction problems owing to a scar and the other two with a muscular pre-excitation syndrome (Wolff-Parkinson-White). To assess the accuracy of the proposed method, we compare the results obtained by using the patient-specific Purkinje network generated by our strategy with the ones obtained by using a non-patient-specific network. The results show that the mean absolute errors in the activation time is reduced for all the cases, highlighting the importance of including a patient-specific Purkinje network in computational models.
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Affiliation(s)
- Simone Palamara
- Modellistica e Calcolo Scientifico (MOX), Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
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19
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Patient-specific generation of the Purkinje network driven by clinical measurements of a normal propagation. Med Biol Eng Comput 2014; 52:813-26. [PMID: 25151397 DOI: 10.1007/s11517-014-1183-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Accepted: 08/08/2014] [Indexed: 10/24/2022]
Abstract
The propagation of the electrical signal in the Purkinje network is the starting point for the activation of the ventricular muscular cells leading to the contraction of the ventricle. In the computational models, describing the electrical activity of the ventricle is therefore important to account for the Purkinje fibers. Until now, the inclusion of such fibers has been obtained either by using surrogates such as space-dependent conduction properties or by generating a network based on an a priori anatomical knowledge. The aim of this work was to propose a new method for the generation of the Purkinje network using clinical measures of the activation times on the endocardium related to a normal electrical propagation, allowing to generate a patient-specific network. The measures were acquired by means of the EnSite NavX system. This system allows to measure for each point of the ventricular endocardium the time at which the activation front, that spreads through the ventricle, has reached the subjacent muscle. We compared the accuracy of the proposed method with the one of other strategies proposed so far in the literature for three subjects with a normal electrical propagation. The results showed that with our method we were able to reduce the absolute errors, intended as the difference between the measured and the computed data, by a factor in the range 9-25 %, with respect to the best of the other strategies. This highlighted the reliability of the proposed method and the importance of including a patient-specific Purkinje network in computational models.
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20
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Lekadir K, Pashaei A, Hoogendoorn C, Pereanez M, Albà X, Frangi AF. Effect of statistically derived fiber models on the estimation of cardiac electrical activation. IEEE Trans Biomed Eng 2014; 61:2740-8. [PMID: 24893365 DOI: 10.1109/tbme.2014.2327025] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Myocardial fiber orientation plays a critical role in the electrical activation and subsequent contraction of the heart. To increase the clinical potential of electrophysiological (EP) simulation for the study of cardiac phenomena and the planning of interventions, accurate personalization of the fibers is a necessary yet challenging task. Due to the difficulties associated with the in vivo imaging of cardiac fiber structure, researchers have developed alternative techniques to personalize fibers. Thus far, cardiac simulation was performed mainly based on rule-based fiber models. More recently, there has been a significant interest in data-driven and statistically derived fiber models. In particular, our predictive method in [1] allows us to estimate the unknown subject-specific fiber orientation based on the more easily available shape information. The aim of this work is to estimate the effect of using such statistical predictive models for the estimation of cardiac electrical activation times and patterns. To this end, we perform EP simulations based on a database of ten canine ex vivo diffusion tensor imaging (DTI) datasets that include normal and failing cases. To assess the strength of the fiber models under varying conditions, we consider both sinus rhythm and biventricular pacing simulations. The results show that 1) the statistically derived fibers improve the estimation of the local activation times by an average of 53.7% over traditional rule-based models, and that 2) the obtained electrical activations are consistently similar to those of the DTI-based fibers.
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Myocardial motion and deformation patterns in an experimental swine model of acute LBBB/CRT and chronic infarct. Int J Cardiovasc Imaging 2014; 30:875-87. [DOI: 10.1007/s10554-014-0403-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2013] [Accepted: 03/15/2014] [Indexed: 10/25/2022]
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Lamata P, Sinclair M, Kerfoot E, Lee A, Crozier A, Blazevic B, Land S, Lewandowski AJ, Barber D, Niederer S, Smith N. An automatic service for the personalization of ventricular cardiac meshes. J R Soc Interface 2013; 11:20131023. [PMID: 24335562 PMCID: PMC3869175 DOI: 10.1098/rsif.2013.1023] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Computational cardiac physiology has great potential to improve the management of cardiovascular diseases. One of the main bottlenecks in this field is the customization of the computational model to the anatomical and physiological status of the patient. We present a fully automatic service for the geometrical personalization of cardiac ventricular meshes with high-order interpolation from segmented images. The method is versatile (able to work with different species and disease conditions) and robust (fully automatic results fulfilling accuracy and quality requirements in 87% of 255 cases). Results also illustrate the capability to minimize the impact of segmentation errors, to overcome the sparse resolution of dynamic studies and to remove the sometimes unnecessary anatomical detail of papillary and trabecular structures. The smooth meshes produced can be used to simulate cardiac function, and in particular mechanics, or can be used as diagnostic descriptors of anatomical shape by cardiologists. This fully automatic service is deployed in a cloud infrastructure, and has been made available and accessible to the scientific community.
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Affiliation(s)
- Pablo Lamata
- Department of Biomedical Engineering, King's College of London, St Thomas' Hospital, , London SE1 7EH, UK
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