1
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Schwarz EL, Pfaller MR, Szafron JM, Latorre M, Lindsey SE, Breuer CK, Humphrey JD, Marsden AL. A Fluid-Solid-Growth Solver for Cardiovascular Modeling. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2023; 417:116312. [PMID: 38044957 PMCID: PMC10691594 DOI: 10.1016/j.cma.2023.116312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
We implement full, three-dimensional constrained mixture theory for vascular growth and remodeling into a finite element fluid-structure interaction (FSI) solver. The resulting "fluid-solid-growth" (FSG) solver allows long term, patient-specific predictions of changing hemodynamics, vessel wall morphology, tissue composition, and material properties. This extension from short term (FSI) to long term (FSG) simulations increases clinical relevance by enabling mechanobioloigcally-dependent studies of disease progression in complex domains.
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Affiliation(s)
- Erica L Schwarz
- Department of Bioengineering, Stanford Univeristy, Stanford, CA 94306, USA
| | - Martin R Pfaller
- Department of Pediatrics - Cardiology, Stanford Univeristy, Stanford, CA 94306, USA
| | - Jason M Szafron
- Department of Pediatrics - Cardiology, Stanford Univeristy, Stanford, CA 94306, USA
| | - Marcos Latorre
- Center for Research and Innovation in Bioengineering, Universitat Politècnica de València, València 46022, Spain
| | - Stephanie E Lindsey
- Department of Pediatrics - Cardiology, Stanford Univeristy, Stanford, CA 94306, USA
| | - Christopher K Breuer
- Department of Surgery, Nationwide Children's Hospital, Columbus, OH 43210, USA
- Center for Regenerative Medicine, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, OH 43215, USA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale Univeristy, New Haven, CT 06520, USA
| | - Alison L Marsden
- Department of Bioengineering, Stanford Univeristy, Stanford, CA 94306, USA
- Department of Pediatrics - Cardiology, Stanford Univeristy, Stanford, CA 94306, USA
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2
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Tilahun HG, Mullagura HN, Humphrey JD, Baek S. A biochemomechanical model of collagen turnover in arterial adaptations to hemodynamic loading. Biomech Model Mechanobiol 2023; 22:2063-2082. [PMID: 37505299 DOI: 10.1007/s10237-023-01750-1] [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: 01/31/2023] [Accepted: 07/06/2023] [Indexed: 07/29/2023]
Abstract
The production, removal, and remodeling of fibrillar collagen is fundamental to mechanical homeostasis in arteries, including dynamic morphological and microstructural changes that occur in response to sustained changes in blood flow and pressure under physiological conditions. These dynamic processes involve complex, coupled biological, chemical, and mechanical mechanisms that are not completely understood. Nevertheless, recent simulations using constrained mixture models with phenomenologically motivated constitutive relations have proven able to predict salient features of the progression of certain vascular adaptations as well as disease processes. Collagen turnover is modeled, in part, via stress-dependent changes in collagen half-life, typically within the range of 10-70 days. By contrast, in this work we introduce a biochemomechanical approach to model the cellular synthesis of procollagen as well as its transition from an intermediate state of assembled microfibrils to mature cross-linked fibers, with mechano-regulated removal. The resulting model can simulate temporal changes in geometry, composition, and stress during early vascular adaptation (weeks to months) for modest changes in blood flow or pressure. It is shown that these simulations capture salient features from data presented in the literature from different animal models.
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Affiliation(s)
- Hailu G Tilahun
- Department of Mechanical Engineering, Michigan State University, 3259 Engineering Building, East Lansing, MI, 48824, USA
| | - Haritha N Mullagura
- Department of Mechanical Engineering, Michigan State University, 3259 Engineering Building, East Lansing, MI, 48824, USA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Seungik Baek
- Department of Mechanical Engineering, Michigan State University, 3259 Engineering Building, East Lansing, MI, 48824, USA.
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3
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Navarrete Á, Utrera A, Rivera E, Latorre M, Celentano DJ, García-Herrera CM. An inverse fitting strategy to determine the constrained mixture model parameters: application in patient-specific aorta. Front Bioeng Biotechnol 2023; 11:1301988. [PMID: 38053847 PMCID: PMC10694237 DOI: 10.3389/fbioe.2023.1301988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/06/2023] [Indexed: 12/07/2023] Open
Abstract
The Constrained Mixture Model (CMM) is a novel approach to describe arterial wall mechanics, whose formulation is based on a referential physiological state. The CMM considers the arterial wall as a mixture of load-bearing constituents, each of them with characteristic mass fraction, material properties, and deposition stretch levels from its stress-free state to the in-vivo configuration. Although some reports of this model successfully assess its capabilities, they barely explore experimental approaches to model patient-specific scenarios. In this sense, we propose an iterative fitting procedure of numerical-experimental nature to determine material parameters and deposition stretch values. To this end, the model has been implemented in a finite element framework, and it is calibrated using reported experimental data of descending thoracic aorta. The main results obtained from the proposed procedure consist of a set of material parameters for each constituent. Moreover, a relationship between deposition stretches and residual strain measurements (opening angle and axial stretch) has been numerically proved, establishing a strong consistency between the model and experimental data.
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Affiliation(s)
- Álvaro Navarrete
- Departamento de Ingeniería Mecánica, Universidad de Santiago de Chile, USACH, Santiago de Chile, Chile
| | - Andrés Utrera
- Departamento de Ingeniería Mecánica, Universidad de Santiago de Chile, USACH, Santiago de Chile, Chile
| | - Eugenio Rivera
- Departamento de Ingeniería Mecánica, Universidad de Santiago de Chile, USACH, Santiago de Chile, Chile
| | - Marcos Latorre
- Center for Research and Innovation in Bioengineering, Universitat Politècnica de València, València, Spain
| | - Diego J. Celentano
- Departamento de Ingeniería Mecánica y Metalúrgica, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Claudio M. García-Herrera
- Departamento de Ingeniería Mecánica, Universidad de Santiago de Chile, USACH, Santiago de Chile, Chile
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4
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Gasser TC, Miller C, Polzer S, Roy J. A quarter of a century biomechanical rupture risk assessment of abdominal aortic aneurysms. Achievements, clinical relevance, and ongoing developments. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2023; 39:e3587. [PMID: 35347895 DOI: 10.1002/cnm.3587] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 01/28/2022] [Accepted: 03/03/2022] [Indexed: 05/12/2023]
Abstract
Abdominal aortic aneurysm (AAA) disease, the local enlargement of the infrarenal aorta, is a serious condition that causes many deaths, especially in men exceeding 65 years of age. Over the past quarter of a century, computational biomechanical models have been developed towards the assessment of AAA risk of rupture, technology that is now on the verge of being integrated within the clinical decision-making process. The modeling of AAA requires a holistic understanding of the clinical problem, in order to set appropriate modeling assumptions and to draw sound conclusions from the simulation results. In this article we summarize and critically discuss the proposed modeling approaches and report the outcome of clinical validation studies for a number of biomechanics-based rupture risk indices. Whilst most of the aspects concerning computational mechanics have already been settled, it is the exploration of the failure properties of the AAA wall and the acquisition of robust input data for simulations that has the greatest potential for the further improvement of this technology.
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Affiliation(s)
- T Christian Gasser
- Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Christopher Miller
- Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Stanislav Polzer
- Department of Applied Mechanics, VSB-Technical University of Ostrava, Ostrava-Poruba, Czech Republic
| | - Joy Roy
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Vascular Surgery, Karolinska University Hospital, Stockholm, Sweden
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5
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Tilahun HG, Mullagura HN, Humphrey JD, Baek S. A Biochemomechanical Model of Collagen Turnover in Arterial Adaptations to Hemodynamic Loading. RESEARCH SQUARE 2023:rs.3.rs-2535591. [PMID: 36798195 PMCID: PMC9934758 DOI: 10.21203/rs.3.rs-2535591/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
The production, removal, and remodeling of fibrillar collagen is fundamental to arterial homeostasis, including dynamic morphological and microstructural changes that occur in response to sustained changes in blood flow and pressure under physiological conditions. These dynamic processes involve complex, coupled biological, chemical, and mechanical mechanisms that are not completely understood. Nevertheless, recent simulations using constrained mixture models with phenomenologically motivated constitutive relations have demonstrated a capability to predict salient features of the progression of certain vascular adaptations and disease processes. Collagen turnover is modeled, in part, via stress-dependent changes in collagen half-life, typically taken within the range of 10â€"70 days. By contrast, in this work we introduce a biochemomechanical approach to model the cellular synthesis of procollagen as well as its transition from an intermediate state of assembled microfibrils to mature cross-linked fibers, with mechano-regulated removal. The resulting model can simulate temporal changes in geometry, composition, and stress during early vascular adaptation (weeks to months) for modest changes in blood flow or pressure. It is shown that these simulations capture salient features from data presented in the literature from different animal models.
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Affiliation(s)
- Hailu G. Tilahun
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA
| | - Haritha N. Mullagura
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA
| | - Jay D. Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Seungik Baek
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA
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6
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Loerakker S, Humphrey JD. Computer Model-Driven Design in Cardiovascular Regenerative Medicine. Ann Biomed Eng 2023; 51:45-57. [PMID: 35974236 PMCID: PMC9832109 DOI: 10.1007/s10439-022-03037-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/20/2022] [Indexed: 01/28/2023]
Abstract
Continuing advances in genomics, molecular and cellular mechanobiology and immunobiology, including transcriptomics and proteomics, and biomechanics increasingly reveal the complexity underlying native tissue and organ structure and function. Identifying methods to repair, regenerate, or replace vital tissues and organs remains one of the greatest challenges of modern biomedical engineering, one that deserves our very best effort. Notwithstanding the continuing need for improving standard methods of investigation, including cell, organoid, and tissue culture, biomaterials development and fabrication, animal models, and clinical research, it is increasingly evident that modern computational methods should play increasingly greater roles in advancing the basic science, bioengineering, and clinical application of regenerative medicine. This brief review focuses on the development and application of computational models of tissue and organ mechanobiology and mechanics for purposes of designing tissue engineered constructs and understanding their development in vitro and in situ. Although the basic approaches are general, for illustrative purposes we describe two recent examples from cardiovascular medicine-tissue engineered heart valves (TEHVs) and tissue engineered vascular grafts (TEVGs)-to highlight current methods of approach as well as continuing needs.
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Affiliation(s)
- Sandra Loerakker
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Jay D Humphrey
- Department of Biomedical Engineering and Vascular Biology & Therapeutics Program, Yale University and Yale School of Medicine, New Haven, CT, USA.
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7
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Goswami S, Li DS, Rego BV, Latorre M, Humphrey JD, Karniadakis GE. Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms. J R Soc Interface 2022; 19:20220410. [PMID: 36043289 PMCID: PMC9428523 DOI: 10.1098/rsif.2022.0410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 08/05/2022] [Indexed: 11/12/2022] Open
Abstract
Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta that can lead to life-threatening dissection or rupture. In vivo assessments of TAA progression are largely limited to measurements of aneurysm size and growth rate. There is promise, however, that computational modelling of the evolving biomechanics of the aorta could predict future geometry and properties from initiating mechanobiological insults. We present an integrated framework to train a deep operator network (DeepONet)-based surrogate model to identify TAA contributing factors using synthetic finite-element-based datasets. For training, we employ a constrained mixture model of aortic growth and remodelling to generate maps of local aortic dilatation and distensibility for multiple TAA risk factors. We evaluate the performance of the surrogate model for insult distributions varying from fusiform (analytically defined) to complex (randomly generated). We propose two frameworks, one trained on sparse information and one on full-field greyscale images, to gain insight into a preferred neural operator-based approach. We show that this continuous learning approach can predict the patient-specific insult profile associated with any given dilatation and distensibility map with high accuracy, particularly when based on full-field images. Our findings demonstrate the feasibility of applying DeepONet to support transfer learning of patient-specific inputs to predict TAA progression.
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Affiliation(s)
- Somdatta Goswami
- Division of Applied Mathematics, Brown University, Providence, RI, USA
| | - David S. Li
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Bruno V. Rego
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Marcos Latorre
- Centre for Research and Innovation in Bioengineering, Universitat Politècnica de València, València, Spain
| | - Jay D. Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - George Em Karniadakis
- Division of Applied Mathematics, Brown University, Providence, RI, USA
- School of Engineering, Brown University, Providence, RI, USA
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8
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Latorre M, Szafron JM, Ramachandra AB, Humphrey JD. In vivo development of tissue engineered vascular grafts: a fluid-solid-growth model. Biomech Model Mechanobiol 2022; 21:827-848. [PMID: 35179675 PMCID: PMC9133046 DOI: 10.1007/s10237-022-01562-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 01/24/2022] [Indexed: 11/02/2022]
Abstract
Methods of tissue engineering continue to advance, and multiple clinical trials are underway evaluating tissue engineered vascular grafts (TEVGs). Whereas initial concerns focused on suture retention and burst pressure, there is now a pressing need to design grafts to have optimal performance, including an ability to grow and remodel in response to changing hemodynamic loads. Toward this end, there is similarly a need for computational methods that can describe and predict the evolution of TEVG geometry, composition, and material properties while accounting for changes in hemodynamics. Although the ultimate goal is a fluid-solid-growth (FSG) model incorporating fully 3D growth and remodeling and 3D hemodynamics, lower fidelity models having high computational efficiency promise to play important roles, especially in the design of candidate grafts. We introduce here an efficient FSG model of in vivo development of a TEVG based on two simplifying concepts: mechanobiologically equilibrated growth and remodeling of the graft and an embedded control volume analysis of the hemodynamics. Illustrative simulations for a model Fontan conduit reveal the utility of this approach, which promises to be particularly useful in initial design considerations involving formal methods of optimization which otherwise add considerably to the computational expense.
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Affiliation(s)
- Marcos Latorre
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
- Center for Research and Innovation in Bioengineering, Universitat Politècnica de València, València, 46022, Spain.
| | - Jason M Szafron
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Abhay B Ramachandra
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Jay D Humphrey
- Vascular Biology and Therapeutics Program, Yale School of Medicine, New Haven, CT, 06520, USA
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9
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Laubrie JD, Mousavi SJ, Avril S. About prestretch in homogenized constrained mixture models simulating growth and remodeling in patient-specific aortic geometries. Biomech Model Mechanobiol 2022; 21:455-469. [PMID: 35067825 PMCID: PMC8940846 DOI: 10.1007/s10237-021-01544-3] [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: 06/29/2021] [Accepted: 10/01/2021] [Indexed: 11/10/2022]
Abstract
Evolution of mechanical and structural properties in the Ascending Thoracic Aorta (ATA) is the results of complex mechanobiological processes. In this work, we address some numerical challenges in order to elaborate computational models of these processes. For that, we extend the state of the art of homogenized constrained mixture (hCM) models. In these models, prestretches are assigned to the mixed constituents in order to ensure local mechanical equilibrium macroscopically, and to maintain a homeostatic level of tension in collagen fibers microscopically. Although the initial prestretches were assumed as homogeneous in idealized straight tubes, more elaborate prestretch distributions need to be considered for curved geometrical models such as patient-specific ATA. Therefore, we introduce prestretches having a three-dimensional gradient across the ATA geometry in the homeostatic reference state. We test different schemes with the objective to ensure stable growth and remodeling (G&R) simulations on patient-specific curved vessels. In these simulations, aneurysm progression is triggered by tissue changes in the constituents such as mass degradation of intramural elastin. The results show that the initial prestretches are not only critical for the stability of numerical simulations, but they also affect the G&R response. Eventually, we submit that initial conditions required for G&R simulations need to be identified regionally for ensuring realistic patient-specific predictions of aneurysm progression.
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10
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Sharifi H, Mann CK, Rockward AL, Mehri M, Mojumder J, Lee LC, Campbell KS, Wenk JF. Multiscale simulations of left ventricular growth and remodeling. Biophys Rev 2021; 13:729-746. [PMID: 34777616 PMCID: PMC8555068 DOI: 10.1007/s12551-021-00826-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/05/2021] [Indexed: 02/07/2023] Open
Abstract
Cardiomyocytes can adapt their size, shape, and orientation in response to altered biomechanical or biochemical stimuli. The process by which the heart undergoes structural changes-affecting both geometry and material properties-in response to altered ventricular loading, altered hormonal levels, or mutant sarcomeric proteins is broadly known as cardiac growth and remodeling (G&R). Although it is likely that cardiac G&R initially occurs as an adaptive response of the heart to the underlying stimuli, prolonged pathological changes can lead to increased risk of atrial fibrillation, heart failure, and sudden death. During the past few decades, computational models have been extensively used to investigate the mechanisms of cardiac G&R, as a complement to experimental measurements. These models have provided an opportunity to quantitatively study the relationships between the underlying stimuli (primarily mechanical) and the adverse outcomes of cardiac G&R, i.e., alterations in ventricular size and function. State-of-the-art computational models have shown promise in predicting the progression of cardiac G&R. However, there are still limitations that need to be addressed in future works to advance the field. In this review, we first outline the current state of computational models of cardiac growth and myofiber remodeling. Then, we discuss the potential limitations of current models of cardiac G&R that need to be addressed before they can be utilized in clinical care. Finally, we briefly discuss the next feasible steps and future directions that could advance the field of cardiac G&R.
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Affiliation(s)
- Hossein Sharifi
- Department of Mechanical Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY 40506-0503 USA
| | - Charles K. Mann
- Department of Mechanical Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY 40506-0503 USA
| | - Alexus L. Rockward
- Department of Mechanical Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY 40506-0503 USA
| | - Mohammad Mehri
- Department of Mechanical Engineering, University of Kentucky, 269 Ralph G. Anderson Building, Lexington, KY 40506-0503 USA
| | - Joy Mojumder
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI USA
| | - Lik-Chuan Lee
- Department of Mechanical Engineering, Michigan State University, East Lansing, MI USA
| | - Kenneth S. Campbell
- Department of Physiology & Division of Cardiovascular Medicine, University of Kentucky, Lexington, KY USA
| | - Jonathan F. Wenk
- Department of Mechanical 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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11
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Humphrey JD. Constrained Mixture Models of Soft Tissue Growth and Remodeling - Twenty Years After. JOURNAL OF ELASTICITY 2021; 145:49-75. [PMID: 34483462 PMCID: PMC8415366 DOI: 10.1007/s10659-020-09809-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 12/29/2020] [Indexed: 05/06/2023]
Abstract
Soft biological tissues compromise diverse cell types and extracellular matrix constituents, each of which can possess individual natural configurations, material properties, and rates of turnover. For this reason, mixture-based models of growth (changes in mass) and remodeling (change in microstructure) are well-suited for studying tissue adaptations, disease progression, and responses to injury or clinical intervention. Such approaches also can be used to design improved tissue engineered constructs to repair, replace, or regenerate tissues. Focusing on blood vessels as archetypes of soft tissues, this paper reviews a constrained mixture theory introduced twenty years ago and explores its usage since by contrasting simulations of diverse vascular conditions. The discussion is framed within the concept of mechanical homeostasis, with consideration of solid-fluid interactions, inflammation, and cell signaling highlighting both past accomplishments and future opportunities as we seek to understand better the evolving composition, geometry, and material behaviors of soft tissues under complex conditions.
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Affiliation(s)
- J D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520 USA
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12
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Irons L, Latorre M, Humphrey JD. From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling. Ann Biomed Eng 2021; 49:1701-1715. [PMID: 33415527 DOI: 10.1007/s10439-020-02713-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/15/2020] [Indexed: 02/06/2023]
Abstract
Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions-one for vessel-level growth and remodeling and one for cell-level signaling-and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations.
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Affiliation(s)
- Linda Irons
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
| | - Marcos Latorre
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
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13
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Weiss D, Cavinato C, Gray A, Ramachandra AB, Avril S, Humphrey JD, Latorre M. Mechanics-driven mechanobiological mechanisms of arterial tortuosity. SCIENCE ADVANCES 2020; 6:6/49/eabd3574. [PMID: 33277255 PMCID: PMC7821897 DOI: 10.1126/sciadv.abd3574] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 10/22/2020] [Indexed: 05/04/2023]
Abstract
Arterial tortuosity manifests in many conditions, including hypertension, genetic mutations predisposing to thoracic aortopathy, and vascular aging. Despite evidence that tortuosity disrupts efficient blood flow and that it may be an important clinical biomarker, underlying mechanisms remain poorly understood but are widely appreciated to be largely biomechanical. Many previous studies suggested that tortuosity may arise via an elastic structural buckling instability, but the novel experimental-computational approach used here suggests that tortuosity arises from mechanosensitive, cell-mediated responses to local aberrations in the microstructural integrity of the arterial wall. In particular, computations informed by multimodality imaging show that aberrations in elastic fiber integrity, collagen alignment, and collagen turnover can lead to a progressive loss of structural stability that entrenches during the development of tortuosity. Interpreted in this way, microstructural defects or irregularities of the arterial wall initiate the condition and hypertension is a confounding factor.
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Affiliation(s)
- Dar Weiss
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Cristina Cavinato
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Authia Gray
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | | | - Stephane Avril
- Mines Saint-Etienne, Centre CIS, INSERM, U 1059 Sainbiose University of Lyon, Univ Jean Monnet, Saint-Etienne, France
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
| | - Marcos Latorre
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
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14
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Latorre M, Humphrey JD. Numerical knockouts-In silico assessment of factors predisposing to thoracic aortic aneurysms. PLoS Comput Biol 2020; 16:e1008273. [PMID: 33079926 PMCID: PMC7598929 DOI: 10.1371/journal.pcbi.1008273] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 10/30/2020] [Accepted: 08/19/2020] [Indexed: 02/06/2023] Open
Abstract
Myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contribute to the development and enlargement of thoracic aortic aneurysms. Detailed analyses of clinical data and longitudinal studies of murine models continue to provide insight into the natural history of these potentially lethal conditions. Yet, because of the co-existence of multiple risk factors in most cases, it has been difficult to isolate individual effects of the many different factors or to understand how they act in combination. In this paper, we use a data-informed computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing risk factors both in isolation and in combination; these factors include localized losses of elastic fiber integrity, aberrant collagen remodeling, reduced smooth muscle contractility, and dysfunctional mechanosensing or mechanoregulation of extracellular matrix along with superimposed hypertension and aortic aging. In most cases, mild-to-severe localized losses in cellular function or matrix integrity give rise to varying degrees of local dilatations of the thoracic aorta, with enlargement typically exacerbated in cases wherein predisposing risk factors co-exist. The simulations suggest, for the first time, that effects of compromised smooth muscle contractility are more important in terms of dysfunctional mechanosensing and mechanoregulation of matrix than in vessel-level control of diameter and, furthermore, that dysfunctional mechanobiological control can yield lesions comparable to those in cases of compromised elastic fiber integrity. Particularly concerning, therefore, is that loss of constituents such as fibrillin-1, as in Marfan syndrome, can compromise both elastic fiber integrity and mechanosensing. Aneurysms are local dilatations of the arterial wall that are responsible for significant disability and death. Detailed analyses of clinical data continue to provide insight into the natural history of these potentially lethal conditions, with myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contributing to their development and enlargement. Yet, because of the co-existence of these risk factors in most cases, it has been difficult to isolate individual effects or to understand how they act in combination. In this paper, we use a computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing factors both in isolation and in combination as well as with superimposed hypertension and aging. The present study recovers many findings from mouse models but with new and important observations that promise to guide in vivo and ex vivo studies as we seek to understand and eventually better treat these complex, multi-factorial lesions, with data-informed patient-specific computations eventually the way forward.
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Affiliation(s)
- M. Latorre
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America
| | - J. D. Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America
- * E-mail:
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