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Colebank MJ, Oomen PA, Witzenburg CM, Grosberg A, Beard DA, Husmeier D, Olufsen MS, Chesler NC. Guidelines for mechanistic modeling and analysis in cardiovascular research. Am J Physiol Heart Circ Physiol 2024; 327:H473-H503. [PMID: 38904851 DOI: 10.1152/ajpheart.00766.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 06/07/2024] [Accepted: 06/16/2024] [Indexed: 06/22/2024]
Abstract
Computational, or in silico, models are an effective, noninvasive tool for investigating cardiovascular function. These models can be used in the analysis of experimental and clinical data to identify possible mechanisms of (ab)normal cardiovascular physiology. Recent advances in computing power and data management have led to innovative and complex modeling frameworks that simulate cardiovascular function across multiple scales. While commonly used in multiple disciplines, there is a lack of concise guidelines for the implementation of computer models in cardiovascular research. In line with recent calls for more reproducible research, it is imperative that scientists adhere to credible practices when developing and applying computational models to their research. The goal of this manuscript is to provide a consensus document that identifies best practices for in silico computational modeling in cardiovascular research. These guidelines provide the necessary methods for mechanistic model development, model analysis, and formal model calibration using fundamentals from statistics. We outline rigorous practices for computational, mechanistic modeling in cardiovascular research and discuss its synergistic value to experimental and clinical data.
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Affiliation(s)
- Mitchel J Colebank
- Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center, Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States
| | - Pim A Oomen
- Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center, Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States
| | - Colleen M Witzenburg
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
| | - Anna Grosberg
- Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center, Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States
| | - Daniel A Beard
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, United States
| | - Dirk Husmeier
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Mette S Olufsen
- Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States
| | - Naomi C Chesler
- Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center, Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States
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Sharifi H, Mehri M, Mann CK, Campbell KS, Lee LC, Wenk JF. Multiscale Finite Element Modeling of Left Ventricular Growth in Simulations of Valve Disease. Ann Biomed Eng 2024; 52:2024-2038. [PMID: 38564074 DOI: 10.1007/s10439-024-03497-x] [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: 10/05/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024]
Abstract
Multiscale models of the cardiovascular system are emerging as effective tools for investigating the mechanisms that drive ventricular growth and remodeling. These models can predict how molecular-level mechanisms impact organ-level structure and function and could provide new insights that help improve patient care. MyoFE is a multiscale computer framework that bridges molecular and organ-level mechanisms in a finite element model of the left ventricle that is coupled with the systemic circulation. In this study, we extend MyoFE to include a growth algorithm, based on volumetric growth theory, to simulate concentric growth (wall thickening/thinning) and eccentric growth (chamber dilation/constriction) in response to valvular diseases. Specifically in our model, concentric growth is controlled by time-averaged total stress along the fiber direction over a cardiac cycle while eccentric growth responds to time-averaged intracellular myofiber passive stress over a cardiac cycle. The new framework correctly predicted different forms of growth in response to two types of valvular diseases, namely aortic stenosis and mitral regurgitation. Furthermore, the model predicted that LV size and function are nearly restored (reversal of growth) when the disease-mimicking perturbation was removed in the simulations for each valvular disorder. In conclusion, the simulations suggest that time-averaged total stress along the fiber direction and time-averaged intracellular myofiber passive stress can be used to drive concentric and eccentric growth in simulations of valve disease.
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Affiliation(s)
- Hossein Sharifi
- Department of Mechanical and Aerospace Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY, 40506-0503, USA
| | - Mohammad Mehri
- Department of Mechanical and Aerospace Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY, 40506-0503, USA
| | - Charles K Mann
- Department of Mechanical and Aerospace Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY, 40506-0503, USA
| | - Kenneth S Campbell
- Division of Cardiovascular Medicine and Department of Physiology, University of Kentucky, Lexington, KY, USA
| | - Lik Chuan Lee
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA
| | - Jonathan F Wenk
- Department of Mechanical and Aerospace Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY, 40506-0503, USA.
- Department of Surgery, University of Kentucky, Lexington, KY, USA.
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Fumagalli I, Pagani S, Vergara C, Dede’ L, Adebo DA, Del Greco M, Frontera A, Luciani GB, Pontone G, Scrofani R, Quarteroni A. The role of computational methods in cardiovascular medicine: a narrative review. Transl Pediatr 2024; 13:146-163. [PMID: 38323181 PMCID: PMC10839285 DOI: 10.21037/tp-23-184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 12/13/2023] [Indexed: 02/08/2024] Open
Abstract
Background and Objective Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data with physical knowledge of the processes underlying the heart function. These models have been increasingly employed in clinical practice to understand pathological mechanisms and their progression, design medical devices, support clinicians in improving therapies. Hinging upon a long-year experience in cardiovascular modeling, we have recently constructed a computational multi-physics and multi-scale integrated model of the heart for the investigation of its physiological function, the analysis of pathological conditions, and to support clinicians in both diagnosis and treatment planning. This narrative review aims to systematically discuss the role that such model had in addressing specific clinical questions, and how further impact of computational models on clinical practice are envisaged. Methods We developed computational models of the physical processes encompassed by the heart function (electrophysiology, electrical activation, force generation, mechanics, blood flow dynamics, valve dynamics, myocardial perfusion) and of their inherently strong coupling. To solve the equations of such models, we devised advanced numerical methods, implemented in a flexible and highly efficient software library. We also developed computational procedures for clinical data post-processing-like the reconstruction of the heart geometry and motion from diagnostic images-and for their integration into computational models. Key Content and Findings Our integrated computational model of the heart function provides non-invasive measures of indicators characterizing the heart function and dysfunctions, and sheds light on its underlying processes and their coupling. Moreover, thanks to the close collaboration with several clinical partners, we addressed specific clinical questions on pathological conditions, such as arrhythmias, ventricular dyssynchrony, hypertrophic cardiomyopathy, degeneration of prosthetic valves, and the way coronavirus disease 2019 (COVID-19) infection may affect the cardiac function. In multiple cases, we were also able to provide quantitative indications for treatment. Conclusions Computational models provide a quantitative and detailed tool to support clinicians in patient care, which can enhance the assessment of cardiac diseases, the prediction of the development of pathological conditions, and the planning of treatments and follow-up tests.
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Affiliation(s)
- Ivan Fumagalli
- MOX Laboratory, Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - Stefano Pagani
- MOX Laboratory, Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - Christian Vergara
- Laboratory of Biological Structures Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Politecnico di Milano, Milan, Italy
| | - Luca Dede’
- MOX Laboratory, Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - Dilachew A. Adebo
- Children’s Heart Institute, Hermann Children’s Hospital, University of Texas Health Science Center, McGovern Medical School, Houston, TX, USA
| | - Maurizio Del Greco
- Department of Cardiology, S. Maria del Carmine Hospital, Rovereto, Italy
| | - Antonio Frontera
- Electrophysiology Department, De Gasperis Cardio Center, ASST Great Metropolitan Hospital Niguarda, Milan, Italy
| | | | - Gianluca Pontone
- Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCSS, Milan, Italy
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | - Roberto Scrofani
- Cardiovascular Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alfio Quarteroni
- MOX Laboratory, Department of Mathematics, Politecnico di Milano, Milan, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Switzerland
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