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El-Nashar H, Sabry M, Tseng YT, Francis N, Latif N, Parker KH, Moore JE, Yacoub MH. Multiscale structure and function of the aortic valve apparatus. Physiol Rev 2024; 104:1487-1532. [PMID: 37732828 DOI: 10.1152/physrev.00038.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 08/30/2023] [Accepted: 09/01/2023] [Indexed: 09/22/2023] Open
Abstract
Whereas studying the aortic valve in isolation has facilitated the development of life-saving procedures and technologies, the dynamic interplay of the aortic valve and its surrounding structures is vital to preserving their function across the wide range of conditions encountered in an active lifestyle. Our view is that these structures should be viewed as an integrated functional unit, here referred to as the aortic valve apparatus (AVA). The coupling of the aortic valve and root, left ventricular outflow tract, and blood circulation is crucial for AVA's functions: unidirectional flow out of the left ventricle, coronary perfusion, reservoir function, and support of left ventricular function. In this review, we explore the multiscale biological and physical phenomena that underlie the simultaneous fulfillment of these functions. A brief overview of the tools used to investigate the AVA, such as medical imaging modalities, experimental methods, and computational modeling, specifically fluid-structure interaction (FSI) simulations, is included. Some pathologies affecting the AVA are explored, and insights are provided on treatments and interventions that aim to maintain quality of life. The concepts explained in this article support the idea of AVA being an integrated functional unit and help identify unanswered research questions. Incorporating phenomena through the molecular, micro, meso, and whole tissue scales is crucial for understanding the sophisticated normal functions and diseases of the AVA.
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Affiliation(s)
- Hussam El-Nashar
- Aswan Heart Research Centre, Magdi Yacoub Foundation, Cairo, Egypt
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Malak Sabry
- Aswan Heart Research Centre, Magdi Yacoub Foundation, Cairo, Egypt
- Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Yuan-Tsan Tseng
- Heart Science Centre, Magdi Yacoub Institute, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Nadine Francis
- Aswan Heart Research Centre, Magdi Yacoub Foundation, Cairo, Egypt
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Najma Latif
- Heart Science Centre, Magdi Yacoub Institute, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Kim H Parker
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - James E Moore
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Magdi H Yacoub
- Aswan Heart Research Centre, Magdi Yacoub Foundation, Cairo, Egypt
- Heart Science Centre, Magdi Yacoub Institute, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
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Bennati L, Giambruno V, Renzi F, Di Nicola V, Maffeis C, Puppini G, Luciani GB, Vergara C. Turbulent blood dynamics in the left heart in the presence of mitral regurgitation: a computational study based on multi-series cine-MRI. Biomech Model Mechanobiol 2023; 22:1829-1846. [PMID: 37400622 PMCID: PMC10613156 DOI: 10.1007/s10237-023-01735-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/04/2023] [Indexed: 07/05/2023]
Abstract
In this work, we performed a computational image-based study of blood dynamics in the whole left heart, both in a healthy subject and in a patient with mitral valve regurgitation. We elaborated multi-series cine-MRI with the aim of reconstructing the geometry and the corresponding motion of left ventricle, left atrium, mitral and aortic valves, and aortic root of the subjects. This allowed us to prescribe such motion to computational blood dynamics simulations where, for the first time, the whole left heart motion of the subject is considered, allowing us to obtain reliable subject-specific information. The final aim is to investigate and compare between the subjects the occurrence of turbulence and the risk of hemolysis and of thrombi formation. In particular, we modeled blood with the Navier-Stokes equations in the arbitrary Lagrangian-Eulerian framework, with a large eddy simulation model to describe the transition to turbulence and a resistive method to manage the valve dynamics, and we used a finite element discretization implemented in an in-house code for the numerical solution.
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Affiliation(s)
- Lorenzo Bennati
- Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Ludovico Antonio Scuro 10, 37134, Verona, Italy
| | - Vincenzo Giambruno
- Division of Cardiac Surgery, Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - Francesca Renzi
- Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Ludovico Antonio Scuro 10, 37134, Verona, Italy
| | - Venanzio Di Nicola
- Division of Cardiac Surgery, Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - Caterina Maffeis
- Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Ludovico Antonio Scuro 10, 37134, Verona, Italy
| | - Giovanni Puppini
- Department of Radiology, University of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - Giovanni Battista Luciani
- Division of Cardiac Surgery, Department of Surgery, Dentistry, Pediatrics, and Obstetrics/Gynecology, University of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - Christian Vergara
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
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Zingaro A, Vergara C, Dede' L, Regazzoni F, Quarteroni A. A comprehensive mathematical model for cardiac perfusion. Sci Rep 2023; 13:14220. [PMID: 37648701 PMCID: PMC10469210 DOI: 10.1038/s41598-023-41312-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023] Open
Abstract
The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, valve modeling, and a multicompartment Darcy model of perfusion. We consider a fully coupled electromechanical model of the left heart that provides input for a fully coupled Navier-Stokes-Darcy Model for myocardial perfusion. The fluid dynamics problem is modeled in a left heart geometry that includes large epicardial coronaries, while the multicompartment Darcy model is set in a biventricular myocardium. Using a realistic and detailed cardiac geometry, our simulations demonstrate the biophysical fidelity of our model in describing cardiac perfusion. Specifically, we successfully validate the model reliability by comparing in-silico coronary flow rates and average myocardial blood flow with clinically established values ranges reported in relevant literature. Additionally, we investigate the impact of a regurgitant aortic valve on myocardial perfusion, and our results indicate a reduction in myocardial perfusion due to blood flow taken away by the left ventricle during diastole. To the best of our knowledge, our work represents the first instance where electromechanics, hemodynamics, and perfusion are integrated into a single computational framework.
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Affiliation(s)
- Alberto Zingaro
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
- ELEM Biotech S.L., Pier01, Palau de Mar, Plaça Pau Vila, 1, 08003, Barcelona, Spain.
| | - Christian Vergara
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Luca Dede'
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Francesco Regazzoni
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Alfio Quarteroni
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Station 8, Av. Piccard, CH-1015, Lausanne, Switzerland
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Kong F, Shadden SC. Learning Whole Heart Mesh Generation From Patient Images for Computational Simulations. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:533-545. [PMID: 36327186 DOI: 10.1109/tmi.2022.3219284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Patient-specific cardiac modeling combines geometries of the heart derived from medical images and biophysical simulations to predict various aspects of cardiac function. However, generating simulation-suitable models of the heart from patient image data often requires complicated procedures and significant human effort. We present a fast and automated deep-learning method to construct simulation-suitable models of the heart from medical images. The approach constructs meshes from 3D patient images by learning to deform a small set of deformation handles on a whole heart template. For both 3D CT and MR data, this method achieves promising accuracy for whole heart reconstruction, consistently outperforming prior methods in constructing simulation-suitable meshes of the heart. When evaluated on time-series CT data, this method produced more anatomically and temporally consistent geometries than prior methods, and was able to produce geometries that better satisfy modeling requirements for cardiac flow simulations. Our source code and pretrained networks are available at https://github.com/fkong7/HeartDeformNets.
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Karabelas E, Longobardi S, Fuchsberger J, Razeghi O, Rodero C, Strocchi M, Rajani R, Haase G, Plank G, Niederer S. Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models. IEEE Trans Biomed Eng 2022; 69:3216-3223. [PMID: 35353691 PMCID: PMC9491017 DOI: 10.1109/tbme.2022.3163428] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/19/2022] [Indexed: 11/15/2022]
Abstract
Computational Fluid Dynamics (CFD) is used to assist in designing artificial valves and planning procedures, focusing on local flow features. However, assessing the impact on overall cardiovascular function or predicting longer-term outcomes may requires more comprehensive whole heart CFD models. Fitting such models to patient data requires numerous computationally expensive simulations, and depends on specific clinical measurements to constrain model parameters, hampering clinical adoption. Surrogate models can help to accelerate the fitting process while accounting for the added uncertainty. We create a validated patient-specific four-chamber heart CFD model based on the Navier-Stokes-Brinkman (NSB) equations and test Gaussian Process Emulators (GPEs) as a surrogate model for performing a variance-based global sensitivity analysis (GSA). GSA identified preload as the dominant driver of flow in both the right and left side of the heart, respectively. Left-right differences were seen in terms of vascular outflow resistances, with pulmonary artery resistance having a much larger impact on flow than aortic resistance. Our results suggest that GPEs can be used to identify parameters in personalized whole heart CFD models, and highlight the importance of accurate preload measurements.
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Affiliation(s)
- Elias Karabelas
- Institute of Mathematics and Scientific ComputingUniversity of GrazAustria
| | - Stefano Longobardi
- Cardiac Electromechanics Research Group, School of Biomedical Engineering and Imaging SciencesKing’s College LondonU.K.
| | - Jana Fuchsberger
- Institute of Mathematics and Scientific ComputingUniversity of GrazAustria
| | - Orod Razeghi
- Research IT Services DepartmentUniversity College LondonU.K.
| | - Cristobal Rodero
- Cardiac Electromechanics Research Group, School of Biomedical Engineering and Imaging SciencesKing’s College LondonU.K.
| | - Marina Strocchi
- Cardiac Electromechanics Research Group, School of Biomedical Engineering and Imaging SciencesKing’s College LondonU.K.
| | - Ronak Rajani
- Department of Adult EchocardiographyGuy’s and St Thomas’ Hospitals NHS Foundation TrustU.K.
| | - Gundolf Haase
- Institute of Mathematics and Scientific ComputingUniversity of GrazAustria
| | - Gernot Plank
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Division BiophysicsMedical University of GrazAustria
| | - Steven Niederer
- Cardiac Electromechanics Research Group, School of Biomedical Engineering and Imaging SciencesKing’s College LondonSE1 7EHLondonU.K.
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Marx L, Niestrawska JA, Gsell MA, Caforio F, Plank G, Augustin CM. Robust and efficient fixed-point algorithm for the inverse elastostatic problem to identify myocardial passive material parameters and the unloaded reference configuration. JOURNAL OF COMPUTATIONAL PHYSICS 2022; 463:111266. [PMID: 35662800 PMCID: PMC7612790 DOI: 10.1016/j.jcp.2022.111266] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Image-based computational models of the heart represent a powerful tool to shed new light on the mechanisms underlying physiological and pathological conditions in cardiac function and to improve diagnosis and therapy planning. However, in order to enable the clinical translation of such models, it is crucial to develop personalized models that are able to reproduce the physiological reality of a given patient. There have been numerous contributions in experimental and computational biomechanics to characterize the passive behavior of the myocardium. However, most of these studies suffer from severe limitations and are not applicable to high-resolution geometries. In this work, we present a novel methodology to perform an automated identification of in vivo properties of passive cardiac biomechanics. The highly-efficient algorithm fits material parameters against the shape of a patient-specific approximation of the end-diastolic pressure-volume relation (EDPVR). Simultaneously, an unloaded reference configuration is generated, where a novel line search strategy to improve convergence and robustness is implemented. Only clinical image data or previously generated meshes at one time point during diastole and one measured data point of the EDPVR are required as an input. The proposed method can be straightforwardly coupled to existing finite element (FE) software packages and is applicable to different constitutive laws and FE formulations. Sensitivity analysis demonstrates that the algorithm is robust with respect to initial input parameters.
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Affiliation(s)
- Laura Marx
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Justyna A. Niestrawska
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Federica Caforio
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
- Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Corresponding author at: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstrasse 6/D04, 8010 Graz, Austria. (C.M.Augustin)
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7
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Caforio F, Augustin CM, Alastruey J, Gsell MAF, Plank G. A coupling strategy for a first 3D-1D model of the cardiovascular system to study the effects of pulse wave propagation on cardiac function. COMPUTATIONAL MECHANICS 2022; 70:703-722. [PMID: 36124206 PMCID: PMC9477941 DOI: 10.1007/s00466-022-02206-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
A key factor governing the mechanical performance of the heart is the bidirectional coupling with the vascular system, where alterations in vascular properties modulate the pulsatile load imposed on the heart. Current models of cardiac electromechanics (EM) use simplified 0D representations of the vascular system when coupling to anatomically accurate 3D EM models is considered. However, these ignore important effects related to pulse wave transmission. Accounting for these effects requires 1D models, but a 3D-1D coupling remains challenging. In this work, we propose a novel, stable strategy to couple a 3D cardiac EM model to a 1D model of blood flow in the largest systemic arteries. For the first time, a personalised coupled 3D-1D model of left ventricle and arterial system is built and used in numerical benchmarks to demonstrate robustness and accuracy of our scheme over a range of time steps. Validation of the coupled model is performed by investigating the coupled system's physiological response to variations in the arterial system affecting pulse wave propagation, comprising aortic stiffening, aortic stenosis or bifurcations causing wave reflections. Our first 3D-1D coupled model is shown to be efficient and robust, with negligible additional computational costs compared to 3D-0D models. We further demonstrate that the calibrated 3D-1D model produces simulated data that match with clinical data under baseline conditions, and that known physiological responses to alterations in vascular resistance and stiffness are correctly replicated. Thus, using our coupled 3D-1D model will be beneficial in modelling studies investigating wave propagation phenomena.
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Affiliation(s)
- Federica Caforio
- Institute of Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Jordi Alastruey
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, King’s Health Partners, St. Thomas’ Hospital, London, SE1 7EH UK
| | - Matthias A. F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
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Karabelas E, Gsell MA, Haase G, Plank G, Augustin CM. An accurate, robust, and efficient finite element framework with applications to anisotropic, nearly and fully incompressible elasticity. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2022; 394:114887. [PMID: 35432634 PMCID: PMC7612621 DOI: 10.1016/j.cma.2022.114887] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative split of the deformation gradient into a volumetric and an isochoric part is a very common approach. However, the finite element analysis of such problems often suffers from severe volumetric locking effects and numerical instabilities. In this paper, we present novel methods to overcome volumetric locking phenomena for using stabilized P1-P1 elements. We introduce different stabilization techniques and demonstrate the high robustness and computational efficiency of the chosen methods. In two benchmark problems from the literature as well as an advanced application to cardiac electromechanics, we compare the approach to standard linear elements and show the accuracy and versatility of the methods to simulate anisotropic, nearly and fully incompressible materials. We demonstrate the potential of this numerical framework to accelerate accurate simulations of biological tissues to the extent of enabling patient-specific parameterization studies, where numerous forward simulations are required.
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Affiliation(s)
- Elias Karabelas
- Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Gundolf Haase
- Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Correspondence to: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstrasse 6/IV, Graz 8010, Austria. (C.M. Augustin)
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Obermeier L, Vellguth K, Schlief A, Tautz L, Bruening J, Knosalla C, Kuehne T, Solowjowa N, Goubergrits L. CT-Based Simulation of Left Ventricular Hemodynamics: A Pilot Study in Mitral Regurgitation and Left Ventricle Aneurysm Patients. Front Cardiovasc Med 2022; 9:828556. [PMID: 35391837 PMCID: PMC8980692 DOI: 10.3389/fcvm.2022.828556] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 02/03/2022] [Indexed: 12/30/2022] Open
Abstract
BackgroundCardiac CT (CCT) is well suited for a detailed analysis of heart structures due to its high spatial resolution, but in contrast to MRI and echocardiography, CCT does not allow an assessment of intracardiac flow. Computational fluid dynamics (CFD) can complement this shortcoming. It enables the computation of hemodynamics at a high spatio-temporal resolution based on medical images. The aim of this proposed study is to establish a CCT-based CFD methodology for the analysis of left ventricle (LV) hemodynamics and to assess the usability of the computational framework for clinical practice.Materials and MethodsThe methodology is demonstrated by means of four cases selected from a cohort of 125 multiphase CCT examinations of heart failure patients. These cases represent subcohorts of patients with and without LV aneurysm and with severe and no mitral regurgitation (MR). All selected LVs are dilated and characterized by a reduced ejection fraction (EF). End-diastolic and end-systolic image data was used to reconstruct LV geometries with 2D valves as well as the ventricular movement. The intraventricular hemodynamics were computed with a prescribed-motion CFD approach and evaluated in terms of large-scale flow patterns, energetic behavior, and intraventricular washout.ResultsIn the MR patients, a disrupted E-wave jet, a fragmentary diastolic vortex formation and an increased specific energy dissipation in systole are observed. In all cases, regions with an impaired washout are visible. The results furthermore indicate that considering several cycles might provide a more detailed view of the washout process. The pre-processing times and computational expenses are in reach of clinical feasibility.ConclusionThe proposed CCT-based CFD method allows to compute patient-specific intraventricular hemodynamics and thus complements the informative value of CCT. The method can be applied to any CCT data of common quality and represents a fair balance between model accuracy and overall expenses. With further model enhancements, the computational framework has the potential to be embedded in clinical routine workflows, to support clinical decision making and treatment planning.
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Affiliation(s)
- Lukas Obermeier
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
- *Correspondence: Lukas Obermeier
| | - Katharina Vellguth
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Adriano Schlief
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Lennart Tautz
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Jan Bruening
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christoph Knosalla
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Titus Kuehne
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Department of Congenital Heart Disease, German Heart Center Berlin, Berlin, Germany
| | - Natalia Solowjowa
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Leonid Goubergrits
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
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Fumagalli I, Vitullo P, Vergara C, Fedele M, Corno AF, Ippolito S, Scrofani R, Quarteroni A. Image-Based Computational Hemodynamics Analysis of Systolic Obstruction in Hypertrophic Cardiomyopathy. Front Physiol 2022; 12:787082. [PMID: 35069249 PMCID: PMC8773089 DOI: 10.3389/fphys.2021.787082] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/13/2021] [Indexed: 12/01/2022] Open
Abstract
Hypertrophic Cardiomyopathy (HCM) is a pathological condition characterized by an abnormal thickening of the myocardium. When affecting the medio-basal portion of the septum, it is named Hypertrophic Obstructive Cardiomyopathy (HOCM) because it induces a flow obstruction in the left ventricular outflow tract. In any type of HCM, the myocardial function can become compromised, possibly resulting in cardiac death. In this study, we investigated with computational analysis the hemodynamics of patients with different types of HCM. The aim was quantifying the effects of this pathology on the intraventricular blood flow and pressure gradients, and providing information potentially useful to guide the indication and the modality of the surgical treatment (septal myectomy). We employed an image-based computational approach, integrating fluid dynamics simulations with geometric and functional data, reconstructed from standard cardiac cine-MRI acquisitions. We showed that with our approach we can better understand the patho-physiological behavior of intraventricular blood flow dynamics due to the abnormal morphological and functional aspect of the left ventricle. The main results of our investigation are: (a) a detailed patient-specific analysis of the blood velocity, pressure and stress distribution associated to HCM; (b) a computation-based classification of patients affected by HCM that can complement the current clinical guidelines for the diagnosis and treatment of HOCM.
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Affiliation(s)
- Ivan Fumagalli
- MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
| | - Piermario Vitullo
- MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
| | - Christian Vergara
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica “Giulio Natta”, Politecnico di Milano, Milan, Italy
| | - Marco Fedele
- MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
| | - Antonio F. Corno
- Children’s Heart Institute, Hermann Children’s Hospital, McGovern Medical School, University of Texas Health, Houston, TX, United States
| | | | | | - Alfio Quarteroni
- MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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11
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Hatoum H, Singh-Gryzbon S, Esmailie F, Ruile P, Neumann FJ, Blanke P, Thourani VH, Yoganathan AP, Dasi LP. Predictive Model for Thrombus Formation After Transcatheter Valve Replacement. Cardiovasc Eng Technol 2021; 12:576-588. [PMID: 34859378 PMCID: PMC11034843 DOI: 10.1007/s13239-021-00596-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 11/09/2021] [Indexed: 12/27/2022]
Abstract
PURPOSE Leaflet thrombosis is a significant adverse event after transcatheter aortic valve (TAV) replacement (TAVR). The purpose of our study was to present a semi-empirical, mathematical model that links patient-specific anatomic, valve, and flow parameters to predict likelihood of leaflet thrombosis. METHODS The two main energy sources of neo-sinus (NS) washout after TAVR include the jet flow downstream of the TAV and NS geometric change in volume due to the leaflets opening and closing. Both are highly dependent on patient anatomic and hemodynamic factors. As rotation of blood flow is prevalent in both the sinus of Valsalva and then the NS, we adopted the vorticity flux or circulation (Г) as a metric quantifying overall washout. Leaflet thrombus volumes were segmented based on hypo-attenuating leaflet thickening (HALT) in post-TAVR patient's gated computed tomography. Г was assessed using dimensional scaling as well as computational fluid dynamics (CFD) respectively and correlated to the thrombosis volumes using sensitivity and specificity analysis. RESULTS Г in the NS, that accounted for patient flow and anatomic conditions derived from scaling arguments significantly better predicted the occurrence of leaflet thrombus than CFD derived measures such as stasis volumes or wall shear stress. Given results from the six patient datasets considered herein, a threshold Г value of 28.0 yielded a sensitivity and specificity of 100% where patients with Gamma < 28 developed valve thrombosis. A 10% error in measurements of all variables can bring the sensitivity specificity down to 87%. CONCLUSION A predictive model relating likelihood of valve thrombosis using Г in the NS was developed with promising sensitivity and specificity. With further studies and improvements, this predictive technology may lead to alerting physicians on the risk for thrombus formation following TAVR.
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Affiliation(s)
- Hoda Hatoum
- Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA
| | - Shelly Singh-Gryzbon
- Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA
- Department of Chemical & Process Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago
| | - Fateme Esmailie
- Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA
| | - Philipp Ruile
- Department of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Franz-Josef Neumann
- Department of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany
| | - Philipp Blanke
- University of British Columbia and St. Paul's Hospital in Vancouver, Vancouver, Canada
| | - Vinod H Thourani
- Department of Cardiovascular Surgery, Marcus Heart Valve Center, Piedmont Heart Institute, Atlanta, GA, USA
| | - Ajit P Yoganathan
- Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA
| | - Lakshmi Prasad Dasi
- Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA.
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12
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Augustin CM, Gsell MA, Karabelas E, Willemen E, Prinzen FW, Lumens J, Vigmond EJ, Plank G. A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021; 386:114092. [PMID: 34630765 PMCID: PMC7611781 DOI: 10.1016/j.cma.2021.114092] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D-0D model to a limit cycle under baseline conditions, the model's ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.
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Affiliation(s)
- Christoph M. Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Erik Willemen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Frits W. Prinzen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Edward J. Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
- Correspondence to: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstrasse 6/IV, Graz 8010, Austria. (G. Plank)
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13
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Augustin CM, Gsell MAF, Karabelas E, Willemen E, Prinzen FW, Lumens J, Vigmond EJ, Plank G. A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021; 386:114092. [PMID: 34630765 DOI: 10.1016/jxma.2021.114092] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D-0D model to a limit cycle under baseline conditions, the model's ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.
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Affiliation(s)
- Christoph M Augustin
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Matthias A F Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Erik Willemen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Frits W Prinzen
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Joost Lumens
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, Netherlands
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
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14
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Bakir AA, Al Abed A, Lovell NH, Dokos S. Multiphysics computational modelling of the cardiac ventricles. IEEE Rev Biomed Eng 2021; 15:309-324. [PMID: 34185649 DOI: 10.1109/rbme.2021.3093042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Development of cardiac multiphysics models has progressed significantly over the decades and simulations combining multiple physics interactions have become increasingly common. In this review, we summarise the progress in this field focusing on various approaches of integrating ventricular structures. electrophysiological properties, myocardial mechanics, as well as incorporating blood hemodynamics and the circulatory system. Common coupling approaches are discussed and compared, including the advantages and shortcomings of each. Currently used strategies for patient-specific implementations are highlighted and potential future improvements considered.
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15
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Wisneski AD, Wang Y, Deuse T, Hill AC, Pasta S, Sack KL, Yao J, Guccione JM. Impact of Aortic Stenosis on Myofiber Stress: Translational Application of Left Ventricle-Aortic Coupling Simulation. Front Physiol 2020; 11:574211. [PMID: 33013489 PMCID: PMC7506067 DOI: 10.3389/fphys.2020.574211] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 08/19/2020] [Indexed: 12/19/2022] Open
Abstract
The severity of aortic stenosis (AS) has traditionally been graded by measuring hemodynamic parameters of transvalvular pressure gradient, ejection jet velocity, or estimating valve orifice area. Recent research has highlighted limitations of these criteria at effectively grading AS in presence of left ventricle (LV) dysfunction. We hypothesized that simulations coupling the aorta and LV could provide meaningful insight into myocardial biomechanical derangements that accompany AS. A realistic finite element model of the human heart with a coupled lumped-parameter circulatory system was used to simulate AS. Finite element analysis was performed with Abaqus FEA. An anisotropic hyperelastic model was assigned to LV passive properties, and a time-varying elastance function governed the LV active response. Global LV myofiber peak systolic stress (mean ± standard deviation) was 9.31 ± 10.33 kPa at baseline, 13.13 ± 10.29 kPa for moderate AS, and 16.18 ± 10.59 kPa for severe AS. Mean LV myofiber peak systolic strains were −22.40 ± 8.73%, −22.24 ± 8.91%, and −21.97 ± 9.18%, respectively. Stress was significantly elevated compared to baseline for moderate (p < 0.01) and severe AS (p < 0.001), and when compared to each other (p < 0.01). Ventricular regions that experienced the greatest systolic stress were (severe AS vs. baseline) basal inferior (39.87 vs. 30.02 kPa; p < 0.01), mid-anteroseptal (32.29 vs. 24.79 kPa; p < 0.001), and apex (27.99 vs. 23.52 kPa; p < 0.001). This data serves as a reference for future studies that will incorporate patient-specific ventricular geometries and material parameters, aiming to correlate LV biomechanics to AS severity.
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Affiliation(s)
- Andrew D Wisneski
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Yunjie Wang
- Thornton Tomassetti Lifesciences Division, Santa Clara, CA, United States
| | - Tobias Deuse
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Arthur C Hill
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Salvatore Pasta
- Department of Engineering, Universita degli Studi di Palermo, Palermo, Italy
| | - Kevin L Sack
- Cardiovascular Research Division, Medtronic Inc., Minneapolis, MN, United States
| | - Jiang Yao
- Dassault Systèmes Simulia, Johnston, RI, United States
| | - Julius M Guccione
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
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16
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Hirschhorn M, Tchantchaleishvili V, Stevens R, Rossano J, Throckmorton A. Fluid–structure interaction modeling in cardiovascular medicine – A systematic review 2017–2019. Med Eng Phys 2020; 78:1-13. [DOI: 10.1016/j.medengphy.2020.01.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 01/18/2020] [Accepted: 01/26/2020] [Indexed: 01/06/2023]
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17
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Neic A, Gsell MA, Karabelas E, Prassl AJ, Plank G. Automating image-based mesh generation and manipulation tasks in cardiac modeling workflows using Meshtool. SOFTWAREX 2020; 11:100454. [PMID: 32607406 PMCID: PMC7326605 DOI: 10.1016/j.softx.2020.100454] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Advanced cardiac modeling studies rely on the ability to generate and functionalize personalized in silico models from tomographic multi-label image stacks. Eventually, this is used for building virtual cohorts that capture the variability in size, shape, and morphology of individual hearts. Typical modeling workflows involve a multitude of interactive mesh manipulation steps, rendering model generation expensive. Meshtool is software specifically designed for automating all complex mesh manipulation tasks emerging in such workflows by implementing algorithms for tasks describable as operations on label fields and/or geometric features. We illustrate how Meshtool increases efficiency and reduces costs by offering an automatable, high performance mesh manipulation toolbox.
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Affiliation(s)
- Aurel Neic
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- NumeriCor GmbH, Graz, Austria
| | - Matthias A.F. Gsell
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Anton J. Prassl
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
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18
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Karabelas E, Haase G, Plank G, Augustin CM. Versatile stabilized finite element formulations for nearly and fully incompressible solid mechanics. COMPUTATIONAL MECHANICS 2020; 65:193-215. [PMID: 31975744 PMCID: PMC6974529 DOI: 10.1007/s00466-019-01760-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Computational formulations for large strain, polyconvex, nearly incompressible elasticity have been extensively studied, but research on enhancing solution schemes that offer better tradeoffs between accuracy, robustness, and computational efficiency remains to be highly relevant. In this paper, we present two methods to overcome locking phenomena, one based on a displacement-pressure formulation using a stable finite element pairing with bubble functions, and another one using a simple pressure-projection stabilized ℙ1 - ℙ1 finite element pair. A key advantage is the versatility of the proposed methods: with minor adjustments they are applicable to all kinds of finite elements and generalize easily to transient dynamics. The proposed methods are compared to and verified with standard benchmarks previously reported in the literature. Benchmark results demonstrate that both approaches provide a robust and computationally efficient way of simulating nearly and fully incompressible materials.
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Affiliation(s)
- Elias Karabelas
- Institute for Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Gundolf Haase
- Institute for Mathematics and Scientific Computing, NAWI Graz, University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Gernot Plank
- Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Christoph M. Augustin
- Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA USA
- Present Address: Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Neue Stiftingtalstraße 6 (MC1.D.)/IV, 8010 Graz, Austria
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