1
|
Haggie L, Schmid L, Röhrle O, Besier T, McMorland A, Saini H. Linking cortex and contraction-Integrating models along the corticomuscular pathway. Front Physiol 2023; 14:1095260. [PMID: 37234419 PMCID: PMC10206006 DOI: 10.3389/fphys.2023.1095260] [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: 11/11/2022] [Accepted: 04/21/2023] [Indexed: 05/28/2023] Open
Abstract
Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.
Collapse
Affiliation(s)
- Lysea Haggie
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Laura Schmid
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Oliver Röhrle
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
- Stuttgart Center for Simulation Sciences (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Angus McMorland
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Exercise Sciences, University of Auckland, Auckland, New Zealand
| | - Harnoor Saini
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| |
Collapse
|
2
|
Raiola M, Sendra M, Torres M. Imaging Approaches and the Quantitative Analysis of Heart Development. J Cardiovasc Dev Dis 2023; 10:jcdd10040145. [PMID: 37103024 PMCID: PMC10144158 DOI: 10.3390/jcdd10040145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 03/25/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Heart morphogenesis is a complex and dynamic process that has captivated researchers for almost a century. This process involves three main stages, during which the heart undergoes growth and folding on itself to form its common chambered shape. However, imaging heart development presents significant challenges due to the rapid and dynamic changes in heart morphology. Researchers have used different model organisms and developed various imaging techniques to obtain high-resolution images of heart development. Advanced imaging techniques have allowed the integration of multiscale live imaging approaches with genetic labeling, enabling the quantitative analysis of cardiac morphogenesis. Here, we discuss the various imaging techniques used to obtain high-resolution images of whole-heart development. We also review the mathematical approaches used to quantify cardiac morphogenesis from 3D and 3D+time images and to model its dynamics at the tissue and cellular levels.
Collapse
Affiliation(s)
- Morena Raiola
- Cardiovascular Regeneration Program, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain
- Departamento de Ingeniería Biomedica, ETSI de Telecomunicaciones, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Miquel Sendra
- Cardiovascular Regeneration Program, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain
| | - Miguel Torres
- Cardiovascular Regeneration Program, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain
- Correspondence:
| |
Collapse
|
3
|
Ghosh S, Guglielmi G, Orfanidis I, Spill F, Hickey A, Hanssen E, Rajagopal V. Effects of altered cellular ultrastructure on energy metabolism in diabetic cardiomyopathy: an in silico study. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210323. [PMID: 36189807 PMCID: PMC9527921 DOI: 10.1098/rstb.2021.0323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Diabetic cardiomyopathy is a leading cause of heart failure in diabetes. At the cellular level, diabetic cardiomyopathy leads to altered mitochondrial energy metabolism and cardiomyocyte ultrastructure. We combined electron microscopy (EM) and computational modelling to understand the impact of diabetes-induced ultrastructural changes on cardiac bioenergetics. We collected transverse micrographs of multiple control and type I diabetic rat cardiomyocytes using EM. Micrographs were converted to finite-element meshes, and bioenergetics was simulated over them using a biophysical model. The simulations also incorporated depressed mitochondrial capacity for oxidative phosphorylation (OXPHOS) and creatine kinase (CK) reactions to simulate diabetes-induced mitochondrial dysfunction. Analysis of micrographs revealed a 14% decline in mitochondrial area fraction in diabetic cardiomyocytes, and an irregular arrangement of mitochondria and myofibrils. Simulations predicted that this irregular arrangement, coupled with the depressed activity of mitochondrial CK enzymes, leads to large spatial variation in adenosine diphosphate (ADP)/adenosine triphosphate (ATP) ratio profile of diabetic cardiomyocytes. However, when spatially averaged, myofibrillar ADP/ATP ratios of a cardiomyocyte do not change with diabetes. Instead, average concentration of inorganic phosphate rises by 40% owing to lower mitochondrial area fraction and dysfunction in OXPHOS. These simulations indicate that a disorganized cellular ultrastructure negatively impacts metabolite transport in diabetic cardiomyopathy. This article is part of the theme issue ‘The cardiomyocyte: new revelations on the interplay between architecture and function in growth, health, and disease’.
Collapse
Affiliation(s)
- Shouryadipta Ghosh
- CSIRO Data61, Commonwealth Scientific and Industrial Research Organisation, Research Way, Clayton, VIC 3168, Australia.,Department of Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia
| | - Giovanni Guglielmi
- Department of Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia.,School of Mathematics, University of Birmingham, Edgbaston B15 2TS, UK
| | - Ioannis Orfanidis
- Health Data Specialists, Grand Canal Docklands, Dublin D02 VK08, Republic of Ireland
| | - Fabian Spill
- School of Mathematics, University of Birmingham, Edgbaston B15 2TS, UK
| | - Anthony Hickey
- School of Biological Sciences, University of Auckland, Auckland, NZ 1042, New Zealand
| | - Eric Hanssen
- Ian Holmes Imaging Center and Department of Biochemistry and Pharmacology, Bio21 Institute, University of Melbourne, Parkville, VIC 3010, Australia
| | - Vijay Rajagopal
- Department of Biomedical Engineering, University of Melbourne, Parkville, VIC 3010, Australia
| |
Collapse
|
4
|
Saini H, Röhrle O. A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 226:107152. [PMID: 36194967 DOI: 10.1016/j.cmpb.2022.107152] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/25/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Many biomedical, clinical, and industrial applications may benefit from musculoskeletal simulations. Three-dimensional macroscopic muscle models (3D models) can more accurately represent muscle architecture than their 1D (line-segment) counterparts. Nevertheless, 3D models remain underutilised in academic, clinical, and commercial environments. Among the reasons for this is a lack of modelling and simulation standardisation, verification, and validation. Here, we strive towards a solution by providing an open-access, characterised, constitutive relation (CR) for 3D musculotendon models. METHODS The musculotendon complex is modelled following the state-of-the-art active stress approach and is treated as hyperelastic, transversely isotropic, and nearly incompressible. Furthermore, force-length and -velocity relationships are incorporated, and muscle activation is derived from motor-unit information. The CR was implemented within the commercial finite-element software package Abaqus as a user-subroutine. A masticatory system model with left and right masseters was used to demonstrate active and passive movement. RESULTS The CR was characterised by various experimental data sets and was able to capture a wide variety of passive and active behaviours. Furthermore, the masticatory simulations revealed that joint movement was sensitive to the muscle's in-fibre passive response. CONCLUSIONS This user-material provides a "plug and play" template for 3D neuro-musculoskeletal finite element modelling. We hope that this reduces modelling effort, fosters exchange, and contributes to the standardisation of such models.
Collapse
Affiliation(s)
- Harnoor Saini
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Pfaffenwalding 5a, 70569 Stuttgart, Germany.
| | - Oliver Röhrle
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Pfaffenwalding 5a, 70569 Stuttgart, Germany; Stuttgart Center for Simulation Sciences (SC SimTech), Pfaffenwaldring 5a, 70569 Stuttgart, Germany
| |
Collapse
|
5
|
Kim N, Pronto JD, Nickerson DP, Taberner AJ, Hunter PJ. A novel modular modeling approach for understanding different electromechanics between left and right heart in rat. Front Physiol 2022; 13:965054. [PMID: 36176770 PMCID: PMC9513479 DOI: 10.3389/fphys.2022.965054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/22/2022] [Indexed: 12/01/2022] Open
Abstract
While ion channels and transporters involved in excitation-contraction coupling have been linked and constructed as comprehensive computational models, validation of whether each individual component of a model can be reused has not been previously attempted. Here we address this issue while using a novel modular modeling approach to investigate the underlying mechanism for the differences between left ventricle (LV) and right ventricle (RV). Our model was developed from modules constructed using the module assembly principles of the CellML model markup language. The components of three existing separate models of cardiac function were disassembled as to create smaller modules, validated individually, and then the component parts were combined into a new integrative model of a rat ventricular myocyte. The model was implemented in OpenCOR using the CellML standard in order to ensure reproducibility. Simulated action potential (AP), Ca2+ transient, and tension were in close agreement with our experimental measurements: LV AP showed a prolonged duration and a more prominent plateau compared with RV AP; Ca2+ transient showed prolonged duration and slow decay in LV compared to RV; the peak value and relaxation of tension were larger and slower, respectively, in LV compared to RV. Our novel approach of module-based mathematical modeling has established that the ionic mechanisms underlying the APs and Ca2+ handling play a role in the variation in force production between ventricles. This simulation process also provides a useful way to reuse and elaborate upon existing models in order to develop a new model.
Collapse
Affiliation(s)
- Nari Kim
- NLRL for Innovative Cardiovascular Engineering, Department of Physiology, College of Medicine, Inje University, Busan, South Korea
- Cardiovascular and Metabolic Disease Center, Inje University, Busan, South Korea
- *Correspondence: Nari Kim,
| | - Julius D. Pronto
- NLRL for Innovative Cardiovascular Engineering, Department of Physiology, College of Medicine, Inje University, Busan, South Korea
- Cardiovascular and Metabolic Disease Center, Inje University, Busan, South Korea
| | - David P. Nickerson
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Andrew J. Taberner
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Peter J. Hunter
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| |
Collapse
|
6
|
Ebrahimi N, Osanlouy M, Bradley CP, Kubke MF, Gerneke DA, Hunter PJ. A method for investigating spatiotemporal growth patterns at cell and tissue levels during C-looping in the embryonic chick heart. iScience 2022; 25:104600. [PMID: 35800755 PMCID: PMC9253367 DOI: 10.1016/j.isci.2022.104600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 01/15/2022] [Accepted: 06/08/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Nazanin Ebrahimi
- University of Auckland, Auckland Bioengineering Institute, Auckland 1010, New Zealand
- Corresponding author
| | - Mahyar Osanlouy
- University of Auckland, Auckland Bioengineering Institute, Auckland 1010, New Zealand
| | - Chris P. Bradley
- University of Auckland, Auckland Bioengineering Institute, Auckland 1010, New Zealand
| | - M. Fabiana Kubke
- University of Auckland, Anatomy and Medical Imaging, Auckland 1010, New Zealand
| | - Dane A. Gerneke
- University of Auckland, Auckland Bioengineering Institute, Auckland 1010, New Zealand
| | - Peter J. Hunter
- University of Auckland, Auckland Bioengineering Institute, Auckland 1010, New Zealand
| |
Collapse
|
7
|
An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility. MATHEMATICS 2022. [DOI: 10.3390/math10081293] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios.
Collapse
|
8
|
Cortical tension initiates the positive feedback loop between cadherin and F-actin. Biophys J 2022; 121:596-606. [PMID: 35031276 PMCID: PMC8874026 DOI: 10.1016/j.bpj.2022.01.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/30/2021] [Accepted: 01/10/2022] [Indexed: 11/20/2022] Open
Abstract
Adherens junctions physically link two cells at their contact interface via extracellular binding between cadherin molecules and intracellular interactions between cadherins and the actin cytoskeleton. Cadherin and actomyosin cytoskeletal dynamics are regulated reciprocally by mechanical and chemical signals, which subsequently determine the strength of cell-cell adhesions and the emergent organization and stiffness of the tissues they form. However, an understanding of the integrated system is lacking. We present a new mechanistic computational model of intercellular junction maturation in a cell doublet to investigate the mechanochemical cross talk that regulates adherens junction formation and homeostasis. The model couples a two-dimensional lattice-based simulation of cadherin dynamics with a reaction-diffusion representation of the reorganising actomyosin network through its regulation by Rho signalling at the intracellular junction. We demonstrate that local immobilization of cadherin induces cluster formation in a cis-less-dependent manner. We then recapitulate the process of cell-cell contact formation. Our model suggests that cortical tension applied on the contact rim can explain the ring distribution of cadherin and actin filaments (F-actin) on the cell-cell contact of the cell doublet. Furthermore, we propose and test the hypothesis that cadherin and F-actin interact like a positive feedback loop, which is necessary for formation of the ring structure. Different patterns of cadherin distribution were observed as an emergent property of disturbances of this positive feedback loop. We discuss these findings in light of available experimental observations on underlying mechanisms related to cadherin/F-actin binding and the mechanical environment.
Collapse
|
9
|
Ebrahimi N, Bradley C, Hunter P. An integrative multiscale view of early cardiac looping. WIREs Mech Dis 2022; 14:e1535. [PMID: 35023324 DOI: 10.1002/wsbm.1535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 06/20/2021] [Accepted: 06/21/2021] [Indexed: 11/12/2022]
Abstract
The heart is the first organ to form and function during the development of an embryo. Heart development consists of a series of events believed to be highly conserved in vertebrates. Development of heart begins with the formation of the cardiac fields followed by a linear heart tube formation. The straight heart tube then undergoes a ventral bending prior to further bending and helical torsion to form a looped heart. The looping phase is then followed by ballooning, septation, and valve formation giving rise to a four-chambered heart in avians and mammals. The looping phase plays a central role in heart development. Successful looping is essential for proper alignment of the future cardiac chambers and tracts. As aberrant looping results in various congenital heart diseases, the mechanisms of cardiac looping have been studied for several decades by various disciplines. Many groups have studied anatomy, biology, genetics, and mechanical processes during heart looping, and have proposed multiple mechanisms. Computational modeling approaches have been utilized to examine the proposed mechanisms of the looping process. Still, the exact underlying mechanism(s) controlling the looping phase remain poorly understood. Although further experimental measurements are obviously still required, the need for more integrative computational modeling approaches is also apparent in order to make sense of the vast amount of experimental data and the complexity of multiscale developmental systems. Indeed, there needs to be an iterative interaction between experimentation and modeling in order to properly find the gap in the existing data and to validate proposed hypotheses. This article is categorized under: Cardiovascular Diseases > Genetics/Genomics/Epigenetics Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Molecular and Cellular Physiology.
Collapse
Affiliation(s)
- Nazanin Ebrahimi
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Christopher Bradley
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| |
Collapse
|
10
|
Maso Talou GD, Babarenda Gamage TP, Nash MP. Efficient Ventricular Parameter Estimation Using AI-Surrogate Models. Front Physiol 2021; 12:732351. [PMID: 34721062 PMCID: PMC8551833 DOI: 10.3389/fphys.2021.732351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/17/2021] [Indexed: 12/02/2022] Open
Abstract
The onset and progression of pathological heart conditions, such as cardiomyopathy or heart failure, affect its mechanical behaviour due to the remodelling of the myocardial tissues to preserve its functional response. Identification of the constitutive properties of heart tissues could provide useful biomarkers to diagnose and assess the progression of disease. We have previously demonstrated the utility of efficient AI-surrogate models to simulate passive cardiac mechanics. Here, we propose the use of this surrogate model for the identification of myocardial mechanical properties and intra-ventricular pressure by solving an inverse problem with two novel AI-based approaches. Our analysis concluded that: (i) both approaches were robust toward Gaussian noise when the ventricle data for multiple loading conditions were combined; and (ii) estimates of one and two parameters could be obtained in less than 9 and 18 s, respectively. The proposed technique yields a viable option for the translation of cardiac mechanics simulations and biophysical parameter identification methods into the clinic to improve the diagnosis and treatment of heart pathologies. In addition, the proposed estimation techniques are general and can be straightforwardly translated to other applications involving different anatomical structures.
Collapse
Affiliation(s)
- Gonzalo D Maso Talou
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.,Department of Engineering Science, University of Auckland, Auckland, New Zealand
| |
Collapse
|
11
|
Lloyd D. The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries. Sports Biomech 2021:1-29. [PMID: 34496728 DOI: 10.1080/14763141.2021.1959947] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 07/20/2021] [Indexed: 01/13/2023]
Abstract
This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.
Collapse
Affiliation(s)
- David Lloyd
- School of Health Sciences and Social Work, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), in the Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Griffith University, Australia
| |
Collapse
|
12
|
Plank G, Loewe A, Neic A, Augustin C, Huang YL, Gsell MAF, Karabelas E, Nothstein M, Prassl AJ, Sánchez J, Seemann G, Vigmond EJ. The openCARP simulation environment for cardiac electrophysiology. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106223. [PMID: 34171774 DOI: 10.1016/j.cmpb.2021.106223] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/28/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE Cardiac electrophysiology is a medical specialty with a long and rich tradition of computational modeling. Nevertheless, no community standard for cardiac electrophysiology simulation software has evolved yet. Here, we present the openCARP simulation environment as one solution that could foster the needs of large parts of this community. METHODS AND RESULTS openCARP and the Python-based carputils framework allow developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity. The continuously expanding openCARP user community is supported by tailored infrastructure. Documentation and training material facilitate access to this complementary research tool for new users. After a brief historic review, this paper summarizes requirements for a high-usability electrophysiology simulator and describes how openCARP fulfills them. We introduce the openCARP modeling workflow in a multi-scale example of atrial fibrillation simulations on single cell, tissue, organ and body level and finally outline future development potential. CONCLUSION As an open simulator, openCARP can advance the computational cardiac electrophysiology field by making state-of-the-art simulations accessible. In combination with the carputils framework, it offers a tailored software solution for the scientific community and contributes towards increasing use, transparency, standardization and reproducibility of in silico experiments.
Collapse
Affiliation(s)
- Gernot Plank
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | | | - Christoph Augustin
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Yung-Lin Huang
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg. Bad Krozingen, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias A F Gsell
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Elias Karabelas
- Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Mark Nothstein
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Anton J Prassl
- Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria
| | - Jorge Sánchez
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg. Bad Krozingen, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; Université Bordeaux, IMB, UMR 5251, F-33400 Talence, France
| |
Collapse
|
13
|
Simulation of Skeletal Muscles in Real-Time with Parallel Computing in GPU. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10062099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Modeling and simulation of the skeletal muscles are usually solved using the Finite Element method (FEM) which, although accurate, commonly needs a complex mesh and the solution is not processed in real-time. In this work, a meshfree model that simulates skeletal muscles considering their functioning and control based on electrical activity, their structure based on biological tissue, and that computes in real-time, is presented. Meshfree methods were used because they are able to surpass most of the limitations that are present in mesh-based methods. The muscular belly was modelled as a particle-based viscoelastic fluid, which is controlled using the monodomain model and shape matching. The smoothed particle hydrodynamics (SPH) method was used to solve both the fluid dynamics and the electrophysiological model. To analyze the accuracy of the method, a similar model was implemented with FEM. Both FEM and SPH methods provide similar solutions of the models in terms of pressure and displacement, with an error of around 0.09, with up to a 10% difference between them. Through the use of General-purpose computing on graphics processing units (GPGPU), real-time simulations that offer a viable alternative to mesh-based models for interactive biological tissue simulations was achieved.
Collapse
|
14
|
Wang ZJ, Wang VY, Babarenda Gamage TP, Rajagopal V, Cao JJ, Nielsen PMF, Bradley CP, Young AA, Nash MP. Efficient estimation of load-free left ventricular geometry and passive myocardial properties using principal component analysis. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2020; 36:e3313. [PMID: 31955509 DOI: 10.1002/cnm.3313] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 10/28/2019] [Accepted: 12/20/2019] [Indexed: 06/10/2023]
Abstract
Models of cardiac mechanics require a well-defined reference geometry from which deformations and hence myocardial strain and stress can be calculated. In the in vivo beating heart, the load-free (LF) geometry generally cannot be measured directly, since, in many cases, there is no stage at which the lumen pressures and contractile state are all zero. Therefore, there is a need for an efficient method to estimate the LF geometry, which is essential for an accurate mechanical simulation of left ventricular (LV) mechanics, and for estimations of passive and contractile constitutive parameters of the heart muscle. In this paper, we present a novel method for estimating both the LF geometry and the passive stiffness of the myocardium. A linear combination of principal components from a population of diastolic displacements is used to construct the LF geometry. For each estimate of the LF geometry and tissue stiffness, LV inflation is simulated, and the model predictions are compared with surface data at multiple stages during passive diastolic filling. The feasibility of this method was demonstrated using synthetically deformation data that were generated using LV models derived from clinical magnetic resonance image data, and the identifiability of the LF geometry and passive stiffness parameters were analysed using Hessian metrics. Applications of this method to clinical data would improve the accuracy of constitutive parameter estimation and allow a better simulation of LV wall strains and stresses.
Collapse
Affiliation(s)
- Zhinuo J Wang
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Vicky Y Wang
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | | | - J Jane Cao
- Heart Center, St Francis Hospital, New York, New York
| | - Poul M F Nielsen
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Chris P Bradley
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Alistair A Young
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| |
Collapse
|
15
|
Calder S, O'Grady G, Cheng LK, Du P. A Simulated Anatomically Accurate Investigation Into the Effects of Biodiversity on Electrogastrography. IEEE Trans Biomed Eng 2020; 67:868-875. [DOI: 10.1109/tbme.2019.2922449] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|
16
|
Hao P, Gao X, Li Z, Zhang J, Wu F, Bai C. Multi-branch fusion network for Myocardial infarction screening from 12-lead ECG images. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 184:105286. [PMID: 31891901 DOI: 10.1016/j.cmpb.2019.105286] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Revised: 12/08/2019] [Accepted: 12/12/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVE Myocardial infarction (MI) is a myocardial anoxic incapacitation caused by severe cardiovascular obstruction that can cause irreversible injury or even death. In medical field, the electrocardiogram (ECG) is a common and effective way to diagnose myocardial infarction, which often requires a wealth of medical knowledge. It is necessary to develop an approach that can detect the MI automatically. METHODS In this paper, we propose a multi-branch fusion framework for automatic MI screening from 12-lead ECG images, which consists of multi-branch network, feature fusion and classification network. First, we use text detection and position alignment to automatically separate twelve leads from ECG images. Then, those 12 leads are input into the multi-branch network constructed by a shallow neural network to get 12 feature maps. After concatenating those feature maps by depth fusion, classification is explored to judge the given ECG is MI or not. RESULTS Based on extensive experiments on an ECG image dataset, performances of different combinations of structures are analyzed. The proposed network is compared with other networks and also compared with physicians in the practical use. All the experiments verify that the proposed method is effective for MI screening based on ECG images, which achieves accuracy, sensitivity, specificity and F1-score of 94.73%, 96.41%, 95.94% and 93.79% respectively. CONCLUSIONS Rather than using the typical one-dimensional electrical ECG signal, this paper gives an effective model to screen MI by analyzing 12-lead ECG images. Extracting and analyzing these 12 leads from their corresponding ECG images is a good attempt in the application of MI screening.
Collapse
Affiliation(s)
- Pengyi Hao
- College of Computer Science and Technology, Zhejiang University of Technology, hangzhou, China.
| | - Xiang Gao
- College of Computer Science and Technology, Zhejiang University of Technology, hangzhou, China.
| | - Zhihe Li
- College of Computer Science and Technology, Zhejiang University of Technology, hangzhou, China.
| | - Jinglin Zhang
- School of Atmospheric Science, Nanjing University of Information Science, China.
| | - Fuli Wu
- College of Computer Science and Technology, Zhejiang University of Technology, hangzhou, China.
| | - Cong Bai
- College of Computer Science and Technology, Zhejiang University of Technology, hangzhou, China.
| |
Collapse
|
17
|
Huellebrand M, Messroghli D, Tautz L, Kuehne T, Hennemuth A. An extensible software platform for interdisciplinary cardiovascular imaging research. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 184:105277. [PMID: 31891904 DOI: 10.1016/j.cmpb.2019.105277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 11/21/2019] [Accepted: 12/11/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVE Cardiovascular imaging is an exponentially growing field with aspects ranging from image acquisition and analysis to disease characterization, and evaluation of therapy approaches.The transfer of innovative new technological and algorithmic solutions into clinical practice is still slow. In addition to the verification of solutions, their integration in the clinical processing workflow must be enabled for the assessment of clinical impact and risks. The goal of our software platform for cardiac image processing - CAIPI - is to support researchers from different specialties such as imaging physics, computer science, and medicine by a common extensible platform to address typical challenges and hurdles in interdisciplinary cardiovascular imaging research. It provides an integrated solution for method comparison, integrated analysis, and validation in the clinical context. The interface concept enables a combination with existing frameworks that address specific aspects of the pipeline, such as modeling (e.g., OpenCMISS, CARP) or image reconstruction (Gadgetron). METHODS In our platform, we developed a concept for import, integration, and management of cardiac image data. The integration approach considers the spatiotemporal properties of the beating heart through a specific data model. The solution is based on MeVisLab and provides functionalities for data retrieval and storage. Two types of plugins can be added. While ToolPlugins usually provide processing algorithms such as image correction and segmentation, AnalysisPlugins enable interactive data exploration and reporting. GUI integration concepts are presented for both plugin types. We developed domain-specific reporting and visualization tools (e.g., AHA segment model) to enable validation studies by clinical experts. The platform offers plugins for calculating and reporting quantitative parameters such as cardiac function, which can be used to, e.g., evaluate the effect of processing algorithms on clinical parameters. Export functionalities include quantitative measurements to Excel, image data to PACS, and STL models to modeling and simulation tools. RESULTS To demonstrate the applicability of this concept both for method development and clinical application, we present use cases representing different problems along the innovation chain in cardiac MR imaging. Validation of an image reconstruction method (MRI T1 mapping) Validation of an image correction method for real-time 2D-PC MRI Comparison of quantification methods for blood flow analysis Training and integration of machine learning solutions with expert annotations Clinical studies with new imaging techniques (flow measurements in the carotid arteries and peripheral veins as well as cerebral spinal fluid). CONCLUSION The presented platform can be used in interdisciplinary teams, in which engineers or data scientists perform the method validation, followed by clinical research studies in patient collectives. The demonstrated use cases show how it enables the transfer of innovations through validation in the cardiovascular application context.
Collapse
Affiliation(s)
- Markus Huellebrand
- Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany; Fraunhofer MEVIS, Bremen, Germany.
| | - Daniel Messroghli
- Department of Internal Medicine and Cardiology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Department of Internal Medicine - Cardiology, Deutsches Herzzentrum Berlin, Berlin, Germany; German Center for Cardiovascular Research (DZHK), partner site Berlin
| | - Lennart Tautz
- Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany; Fraunhofer MEVIS, Bremen, Germany
| | - Titus Kuehne
- Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany; German Center for Cardiovascular Research (DZHK), partner site Berlin; Department of Congenital Heart Disease and Paediatric Cardiology, Deutsches Herzzentrum Berlin, Berlin, Germany
| | - Anja Hennemuth
- Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany; Fraunhofer MEVIS, Bremen, Germany; German Center for Cardiovascular Research (DZHK), partner site Berlin
| |
Collapse
|
18
|
Camara O. Best (and Worst) Practices for Organizing a Challenge on Cardiac Biophysical Models During AI Summer: The CRT-EPiggy19 Challenge. STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART. MULTI-SEQUENCE CMR SEGMENTATION, CRT-EPIGGY AND LV FULL QUANTIFICATION CHALLENGES 2020. [DOI: 10.1007/978-3-030-39074-7_35] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
|
19
|
Schmid L, Klotz T, Siebert T, Röhrle O. Characterization of Electromechanical Delay Based on a Biophysical Multi-Scale Skeletal Muscle Model. Front Physiol 2019; 10:1270. [PMID: 31649554 PMCID: PMC6795131 DOI: 10.3389/fphys.2019.01270] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 09/19/2019] [Indexed: 01/20/2023] Open
Abstract
Skeletal muscles can be voluntary controlled by the somatic nervous system yielding an active contractile stress response. Thereby, the active muscle stresses are transmitted to the skeleton by a cascade of connective tissue and thus enable motion. In the context of joint perturbations as well as the assessment of the complexity of neural control, the initial phase of the muscle-tendon system's stress response has a particular importance and is analyzed by means of electromechanical delay (EMD). EMD is defined as the time lag between the stimulation of a muscle and a measurable change in force output. While EMD is believed to depend on multiple structures / phenomena, it is hard to separate their contributions experimentally. We employ a physiologically detailed, three-dimensional, multi-scale model of an idealized muscle-tendon system to analyze the influence of (i) muscle and tendon length, (ii) the material behavior of skeletal muscle and tendon tissue, (iii) the chemo-electro-mechanical behavior of the muscle fibers and (iv) neural control on EMD. Comparisons with experimental data show that simulated EMD values are within the physiological range, i.e., between 6.1 and 68.6 ms, and that the model is able to reproduce the characteristic EMD-stretch curve, yielding the minimum EMD at optimal length. Simulating consecutive recruitment of motor units increases EMD by more than 20 ms, indicating that during voluntary contractions neural control is the dominant factor determining EMD. In contrast, the muscle fiber action potential conduction velocity is found to influence EMD even of a 27 cm long muscle by not more than 3.7 ms. We further demonstrate that in conditions where only little pre-stretch is applied to a muscle-tendon system, the mechanical behavior of both muscle and tendon tissue considerably impacts EMD. Predicting EMD for different muscle and tendon lengths indicates that the anatomy of a specific muscle-tendon system is optimized for its function, i.e., shorter tendon lengths are beneficial to minimize the neural control effort for muscles primary acting as motor in concentric contractions.
Collapse
Affiliation(s)
- Laura Schmid
- Chair for Continuum Biomechanics and Mechanobiology, Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Thomas Klotz
- Chair for Continuum Biomechanics and Mechanobiology, Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Tobias Siebert
- Department of Motion and Exercise Science, Institute of Sport and Motion Science, University of Stuttgart, Stuttgart, Germany
| | - Oliver Röhrle
- Chair for Continuum Biomechanics and Mechanobiology, Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Center for Simulation Sciences (SC SimTech), University of Stuttgart, Stuttgart, Germany
| |
Collapse
|
20
|
Ladd D, Tilūnaitė A, Roderick HL, Soeller C, Crampin EJ, Rajagopal V. Assessing Cardiomyocyte Excitation-Contraction Coupling Site Detection From Live Cell Imaging Using a Structurally-Realistic Computational Model of Calcium Release. Front Physiol 2019; 10:1263. [PMID: 31632297 PMCID: PMC6783691 DOI: 10.3389/fphys.2019.01263] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/17/2019] [Indexed: 01/11/2023] Open
Abstract
Calcium signaling plays a pivotal role in cardiomyocytes, coupling electrical excitation to mechanical contraction of the heart. Determining locations of active calcium release sites, and how their recruitment changes in response to stimuli and in disease states is therefore of central interest in cardiac physiology. Current algorithms for detecting release sites from live cell imaging data are however not easily validated against a known “ground truth,” which makes interpretation of the output of such algorithms, in particular the degree of confidence in site detection, a challenging task. Computational models are capable of integrating findings from multiple sources into a consistent, predictive framework. In cellular physiology, such models have the potential to reveal structure and function beyond the temporal and spatial resolution limitations of individual experimental measurements. Here, we create a spatially detailed computational model of calcium release in an eight sarcomere section of a ventricular cardiomyocyte, using electron tomography reconstruction of cardiac ultrastructure and confocal imaging of protein localization. This provides a high-resolution model of calcium diffusion from intracellular stores, which can be used as a platform to simulate confocal fluorescence imaging in the context of known ground truth structures from the higher resolution model. We use this capability to evaluate the performance of a recently proposed method for detecting the functional response of calcium release sites in live cells. Model permutations reveal how calcium release site density and mitochondria acting as diffusion barriers impact the detection performance of the algorithm. We demonstrate that site density has the greatest impact on detection precision and recall, in particular affecting the effective detectable depth of sites in confocal data. Our findings provide guidance on how such detection algorithms may best be applied to experimental data and give insights into limitations when using two-dimensional microscopy images to analyse three-dimensional cellular structures.
Collapse
Affiliation(s)
- David Ladd
- Systems Biology Lab, Department of Biomedical Engineering, School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia.,ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, School of Chemical and Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia.,Cell Structure and Mechanobiology Group, Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia
| | - Agnė Tilūnaitė
- Systems Biology Lab, Department of Biomedical Engineering, School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
| | - H Llewelyn Roderick
- Laboratory of Experimental Cardiology, Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Christian Soeller
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
| | - Edmund J Crampin
- Systems Biology Lab, Department of Biomedical Engineering, School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia.,ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, School of Chemical and Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia
| | - Vijay Rajagopal
- Cell Structure and Mechanobiology Group, Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia
| |
Collapse
|
21
|
|
22
|
Röhrle O, Yavuz UŞ, Klotz T, Negro F, Heidlauf T. Multiscale modeling of the neuromuscular system: Coupling neurophysiology and skeletal muscle mechanics. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2019; 11:e1457. [PMID: 31237041 DOI: 10.1002/wsbm.1457] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 05/13/2019] [Accepted: 05/14/2019] [Indexed: 01/10/2023]
Abstract
Mathematical models and computer simulations have the great potential to substantially increase our understanding of the biophysical behavior of the neuromuscular system. This, however, requires detailed multiscale, and multiphysics models. Once validated, such models allow systematic in silico investigations that are not necessarily feasible within experiments and, therefore, have the ability to provide valuable insights into the complex interrelations within the healthy system and for pathological conditions. Most of the existing models focus on individual parts of the neuromuscular system and do not consider the neuromuscular system as an integrated physiological system. Hence, the aim of this advanced review is to facilitate the prospective development of detailed biophysical models of the entire neuromuscular system. For this purpose, this review is subdivided into three parts. The first part introduces the key anatomical and physiological aspects of the healthy neuromuscular system necessary for modeling the neuromuscular system. The second part provides an overview on state-of-the-art modeling approaches representing all major components of the neuromuscular system on different time and length scales. Within the last part, a specific multiscale neuromuscular system model is introduced. The integrated system model combines existing models of the motor neuron pool, of the sensory system and of a multiscale model describing the mechanical behavior of skeletal muscles. Since many sub-models are based on strictly biophysical modeling approaches, it closely represents the underlying physiological system and thus could be employed as starting point for further improvements and future developments. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.
Collapse
Affiliation(s)
- Oliver Röhrle
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Center for Simulation Sciences (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Utku Ş Yavuz
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.,Biomedical Signals and Systems, Universiteit Twente, Enschede, The Netherlands
| | - Thomas Klotz
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Center for Simulation Sciences (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Francesco Negro
- Department of Clinical and Experimental Sciences, Universià degli Studi di Brescia, Brescia, Italy
| | - Thomas Heidlauf
- EPS5 - Simulation and System Analysis, Hofer pdc GmbH, Stuttgart, Germany
| |
Collapse
|
23
|
Babarenda Gamage TP, Malcolm DTK, Maso Talou G, Mîra A, Doyle A, Nielsen PMF, Nash MP. An automated computational biomechanics workflow for improving breast cancer diagnosis and treatment. Interface Focus 2019; 9:20190034. [PMID: 31263540 DOI: 10.1098/rsfs.2019.0034] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/07/2019] [Indexed: 12/24/2022] Open
Abstract
Clinicians face many challenges when diagnosing and treating breast cancer. These challenges include interpreting and co-locating information between different medical imaging modalities that are used to identify tumours and predicting where these tumours move to during different treatment procedures. We have developed a novel automated breast image analysis workflow that integrates state-of-the-art image processing and machine learning techniques, personalized three-dimensional biomechanical modelling and population-based statistical analysis to assist clinicians during breast cancer detection and treatment procedures. This paper summarizes our recent research to address the various technical and implementation challenges associated with creating a fully automated system. The workflow is applied to predict the repositioning of tumours from the prone position, where diagnostic magnetic resonance imaging is performed, to the supine position where treatment procedures are performed. We discuss our recent advances towards addressing challenges in identifying the mechanical properties of the breast and evaluating the accuracy of the biomechanical models. We also describe our progress in implementing a prototype of this workflow in clinical practice. Clinical adoption of these state-of-the-art modelling techniques has significant potential for reducing the number of misdiagnosed breast cancers, while also helping to improve the treatment of patients.
Collapse
Affiliation(s)
| | - Duane T K Malcolm
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Gonzalo Maso Talou
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Anna Mîra
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Anthony Doyle
- Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Poul M F Nielsen
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.,Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.,Department of Engineering Science, University of Auckland, Auckland, New Zealand
| |
Collapse
|
24
|
Visualization of Myocardial Strain Pattern Uniqueness with Respect to Activation Time and Contractility: A Computational Study. DATA 2019. [DOI: 10.3390/data4020079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Speckle tracking echography is used to measure myocardial strain patterns in order to assess the state of myocardial tissue. Because electro-mechanical coupling in myocardial tissue is complex and nonlinear, and because of the measurement errors the uniqueness of strain patterns is questionable. In this study, the uniqueness of strain patterns was visualized in order to revel characteristics that may improve their interpretation. A computational model of sarcomere mechanics was used to generate a database of 1681 strain patterns, each simulated with a different set of sarcomere parameters: time of activation (TA) and contractility (Con). TA and Con ranged from −100 ms to 100 ms and 2% to 202% in 41 steps respectively, thus forming a two-dimensional 41 × 41 parameter space. Uniqueness of the strain pattern was assessed by using a cohort of similar strain patterns defined by a measurement error. The cohort members were then visualized in the parameter space. Each cohort formed one connected component (or blob) in the parameter space; however, large differences in the shape, size, and eccentricity of the blobs were found for different regions in the parameter space. The blobs were elongated along the TA direction (±50 ms) when contractility was low, and along the Con direction (±50%) when contractility was high. The uniqueness of the strain patterns can be assessed and visualized in the parameter space. The strain patterns in the studied database are not degenerated because a cohort of similar strain patterns forms only one connected blob in the parameter space. However, the elongation of the blobs means that estimations of TA when contractility is low and of Con when contractility is high have high uncertainty.
Collapse
|
25
|
Affiliation(s)
- Michael S Sacks
- Willerson Centre for Cardiovascular Modelling and Simulation, Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.
| |
Collapse
|
26
|
Wang CC, Chang CD, Jiang BC. Developing a Health Risk Evaluation Method for Triple H. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16071168. [PMID: 30939773 PMCID: PMC6480628 DOI: 10.3390/ijerph16071168] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 03/28/2019] [Accepted: 03/30/2019] [Indexed: 11/26/2022]
Abstract
The development of a health evaluation system from human-related data is an important issue in preventive medicine. Previously, most studies have focused on disease assessment and prevention in patients. However, even if certain risk factors are all within normal ranges, individuals may not necessarily be completely healthy. This study focused on healthy individuals to develop a new index to assess health risks; this index can be used for the prevention of multiple diseases in healthy people. The kernel density technique was proposed to estimate the distribution of common risk factors and to develop a health risk index. A dataset of hypertension, hyperlipidemia, and hyperglycemia (Triple H) data from the National Health Insurance Research Database in Taiwan was used to demonstrate the proposed analytical process. The results of risk factor changes after six weeks of exercise were used to calculate the health risk index. The results showed that the subjects experienced a 7.29% reduction in their health risk index after the exercise intervention. This finding demonstrates the potential impact of an important reference index on quantifying the effect of maintenance in healthy people.
Collapse
Affiliation(s)
- Chien-Chih Wang
- Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 24301, Taiwan.
| | - Cheng-Ding Chang
- Department of Industrial Engineering and Management, Yuan Ze University, Chung-Li 32003, Taiwan.
| | - Bernard C Jiang
- Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan.
| |
Collapse
|
27
|
Parker MD, Babarenda Gamage TP, HajiRassouliha A, Taberner AJ, Nash MP, Nielsen PMF. Surface deformation tracking and modelling of soft materials. Biomech Model Mechanobiol 2019; 18:1031-1045. [PMID: 30778884 DOI: 10.1007/s10237-019-01127-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 02/09/2019] [Indexed: 11/27/2022]
Abstract
Many computer vision algorithms have been presented to track surface deformations, but few have provided a direct comparison of measurements with other stereoscopic approaches and physics-based models. We have previously developed a phase-based cross-correlation algorithm to track dense distributions of displacements over three-dimensional surfaces. In the present work, we compare this algorithm with one that uses an independent tracking system, derived from an array of fluorescent microspheres. A smooth bicubic Hermite mesh was fitted to deformations obtained from the phase-based cross-correlation data. This mesh was then used to estimate the microsphere locations, which were compared to stereo reconstructions of the microsphere positions. The method was applied to a 35 mm × 35 mm × 35 mm soft silicone gel cube under indentation, with three square bands of microspheres placed around the indenter tip. At an indentation depth of 4.5 mm, the root-mean-square (RMS) differences between the reconstructed positions of the microspheres and their identified positions for the inner, middle, and outer bands were 60 µm, 20 µm, and 19 µm, respectively. The usefulness of the strain-tracking data for physics-based finite element modelling of large deformation mechanics was then demonstrated by estimating a neo-Hookean stiffness parameter for the gel. At the optimal constitutive parameter estimate, the RMS difference between the measured microsphere positions and their finite element model-predicted locations was 143 µm.
Collapse
Affiliation(s)
- Matthew D Parker
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | - Amir HajiRassouliha
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Andrew J Taberner
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Poul M F Nielsen
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
- Department of Engineering Science, University of Auckland, Auckland, New Zealand.
| |
Collapse
|
28
|
Ghosh S, Tran K, Delbridge LMD, Hickey AJR, Hanssen E, Crampin EJ, Rajagopal V. Insights on the impact of mitochondrial organisation on bioenergetics in high-resolution computational models of cardiac cell architecture. PLoS Comput Biol 2018; 14:e1006640. [PMID: 30517098 PMCID: PMC6296675 DOI: 10.1371/journal.pcbi.1006640] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 12/17/2018] [Accepted: 11/13/2018] [Indexed: 01/05/2023] Open
Abstract
Recent electron microscopy data have revealed that cardiac mitochondria are not arranged in crystalline columns but are organised with several mitochondria aggregated into columns of varying sizes spanning the cell cross-section. This raises the question—how does the mitochondrial arrangement affect the metabolite distributions within cardiomyocytes and what is its impact on force dynamics? Here, we address this question by employing finite element modeling of cardiac bioenergetics on computational meshes derived from electron microscope images. Our results indicate that heterogeneous mitochondrial distributions can lead to significant spatial variation across the cell in concentrations of inorganic phosphate, creatine (Cr) and creatine phosphate (PCr). However, our model predicts that sufficient activity of the creatine kinase (CK) system, coupled with rapid diffusion of Cr and PCr, maintains near uniform ATP and ADP ratios across the cell cross sections. This homogenous distribution of ATP and ADP should also evenly distribute force production and twitch duration with contraction. These results suggest that the PCr shuttle and associated enzymatic reactions act to maintain uniform force dynamics in the cell despite the heterogeneous mitochondrial organization. However, our model also predicts that under hypoxia activity of mitochondrial CK enzymes and diffusion of high-energy phosphate compounds may be insufficient to sustain uniform ATP/ADP distribution and hence force generation. Mammalian cardiomyocytes contain a high volume of mitochondria, which maintains the continuous and bulk supply of ATP to sustain normal heart function. Previously, cardiac mitochondria were understood to be distributed in a regular, crystalline pattern, which facilitated a steady supply of ATP at different workloads. Using electron microscopy images of cell cross sections, we recently found that they are not regularly distributed inside cardiomyocytes. We created new spatially accurate computational models of cardiac cell bioenergetics and tested whether this heterogeneous distribution of mitochondria causes non-uniform energy supply and contractile force production in the cardiomyocyte. We found that ATP and ADP concentrations remain uniform throughout the cell because of the activity of creatine kinase (CK) enzymes that convert ATP produced in the mitochondria into creatine phosphate. Creatine phosphate rapidly diffuses to the myofibril region where it can be converted back to ATP for the contraction cycle in a timely manner. This mechanism is called the phosphocreatine shuttle (PCr shuttle). The PCr shuttle ensures that different areas of the cell produce the same amount of force regardless of the mitochondrial distribution. However, our model also shows that when the cellular oxygen supply is limited—as can be the case in conditions such as heart failure—the PCr shuttle cannot maintain uniform ATP and ADP concentrations across the cell. This causes a non-uniform acto-myosin force distribution and non-uniform twitch duration across the cell cross section. Our study suggests that mechanisms other than the PCr shuttle may be necessary to maintain uniform supply of ATP in a hypoxic environment.
Collapse
Affiliation(s)
- Shouryadipta Ghosh
- Cell Structure and Mechanobiology Group, Dept. of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
- Systems Biology Laboratory, School of Mathematics and Statistics, and Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
| | - Kenneth Tran
- Auckland Bioengineering Institute, University of Auckland, Auckland New Zealand
| | | | | | - Eric Hanssen
- Advanced Microscopy Facility, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Australia
| | - Edmund J. Crampin
- Systems Biology Laboratory, School of Mathematics and Statistics, and Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
- ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, University of Melbourne, Melbourne, Australia
| | - Vijay Rajagopal
- Cell Structure and Mechanobiology Group, Dept. of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
- * E-mail:
| |
Collapse
|
29
|
Ho H, Yu HB, Gangsei LE, Kongsro J. A CT-image based pig atlas model and its potential applications in the meat industry. Meat Sci 2018; 148:1-4. [PMID: 30292698 DOI: 10.1016/j.meatsci.2018.09.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 08/08/2018] [Accepted: 09/17/2018] [Indexed: 10/28/2022]
Abstract
In this communication we present a novel pig atlas model which is represented by a parametric linear Lagrange or cubic Hermite mesh. The model is developed from data points digitized from a 3D pig CT image. In total 84 muscles and 121 bones are included in the atlas, representing the tissue structures most relevant to the industry. We discuss its potential applications in virtual meat cuts and statistical shape analysis for pig breeding and genetics companies.
Collapse
Affiliation(s)
- H Ho
- Auckland Bioengineering Institute, The University of Auckland, New Zealand.
| | - H B Yu
- Auckland Bioengineering Institute, The University of Auckland, New Zealand
| | - L E Gangsei
- Animalia, Norwegian Meat and Poultry Research Centre, Norway; Norwegian University of Life Sciences, Norway
| | | |
Collapse
|
30
|
Bradley CP, Emamy N, Ertl T, Göddeke D, Hessenthaler A, Klotz T, Krämer A, Krone M, Maier B, Mehl M, Rau T, Röhrle O. Enabling Detailed, Biophysics-Based Skeletal Muscle Models on HPC Systems. Front Physiol 2018; 9:816. [PMID: 30050446 PMCID: PMC6052132 DOI: 10.3389/fphys.2018.00816] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Accepted: 06/11/2018] [Indexed: 11/13/2022] Open
Abstract
Realistic simulations of detailed, biophysics-based, multi-scale models often require very high resolution and, thus, large-scale compute facilities. Existing simulation environments, especially for biomedical applications, are typically designed to allow for high flexibility and generality in model development. Flexibility and model development, however, are often a limiting factor for large-scale simulations. Therefore, new models are typically tested and run on small-scale compute facilities. By using a detailed biophysics-based, chemo-electromechanical skeletal muscle model and the international open-source software library OpenCMISS as an example, we present an approach to upgrade an existing muscle simulation framework from a moderately parallel version toward a massively parallel one that scales both in terms of problem size and in terms of the number of parallel processes. For this purpose, we investigate different modeling, algorithmic and implementational aspects. We present improvements addressing both numerical and parallel scalability. In addition, our approach includes a novel visualization environment which is based on the MegaMol framework and is capable of handling large amounts of simulated data. We present the results of a number of scaling studies at the Tier-1 supercomputer HazelHen at the High Performance Computing Center Stuttgart (HLRS). We improve the overall runtime by a factor of up to 2.6 and achieve good scalability on up to 768 cores.
Collapse
Affiliation(s)
- Chris P Bradley
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Nehzat Emamy
- Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany
| | - Thomas Ertl
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,Visualization Research Center of the University of Stuttgart, University of Stuttgart, Stuttgart, Germany
| | - Dominik Göddeke
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,Institute for Applied Analysis and Numerical Simulation, University of Stuttgart, Stuttgart, Germany
| | - Andreas Hessenthaler
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,SimTech Research Group on Continuum Biomechanics and Mechanobiology, Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
| | - Thomas Klotz
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,SimTech Research Group on Continuum Biomechanics and Mechanobiology, Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
| | - Aaron Krämer
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,Institute for Applied Analysis and Numerical Simulation, University of Stuttgart, Stuttgart, Germany
| | - Michael Krone
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,Visualization Research Center of the University of Stuttgart, University of Stuttgart, Stuttgart, Germany
| | - Benjamin Maier
- Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany
| | - Miriam Mehl
- Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany
| | - Tobias Rau
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,Visualization Research Center of the University of Stuttgart, University of Stuttgart, Stuttgart, Germany
| | - Oliver Röhrle
- Stuttgart Centre for Simulation Sciences, University of Stuttgart, Stuttgart, Germany.,SimTech Research Group on Continuum Biomechanics and Mechanobiology, Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
| |
Collapse
|
31
|
Rajagopal V, Bass G, Ghosh S, Hunt H, Walker C, Hanssen E, Crampin E, Soeller C. Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology. J Vis Exp 2018. [PMID: 29733314 DOI: 10.3791/56817] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
With the advent of three-dimensional (3D) imaging technologies such as electron tomography, serial-block-face scanning electron microscopy and confocal microscopy, the scientific community has unprecedented access to large datasets at sub-micrometer resolution that characterize the architectural remodeling that accompanies changes in cardiomyocyte function in health and disease. However, these datasets have been under-utilized for investigating the role of cellular architecture remodeling in cardiomyocyte function. The purpose of this protocol is to outline how to create an accurate finite element model of a cardiomyocyte using high resolution electron microscopy and confocal microscopy images. A detailed and accurate model of cellular architecture has significant potential to provide new insights into cardiomyocyte biology, more than experiments alone can garner. The power of this method lies in its ability to computationally fuse information from two disparate imaging modalities of cardiomyocyte ultrastructure to develop one unified and detailed model of the cardiomyocyte. This protocol outlines steps to integrate electron tomography and confocal microscopy images of adult male Wistar (name for a specific breed of albino rat) rat cardiomyocytes to develop a half-sarcomere finite element model of the cardiomyocyte. The procedure generates a 3D finite element model that contains an accurate, high-resolution depiction (on the order of ~35 nm) of the distribution of mitochondria, myofibrils and ryanodine receptor clusters that release the necessary calcium for cardiomyocyte contraction from the sarcoplasmic reticular network (SR) into the myofibril and cytosolic compartment. The model generated here as an illustration does not incorporate details of the transverse-tubule architecture or the sarcoplasmic reticular network and is therefore a minimal model of the cardiomyocyte. Nevertheless, the model can already be applied in simulation-based investigations into the role of cell structure in calcium signaling and mitochondrial bioenergetics, which is illustrated and discussed using two case studies that are presented following the detailed protocol.
Collapse
Affiliation(s)
- Vijay Rajagopal
- Cell Structure and Mechanobiology Group, University of Melbourne; Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne; Department of Biomedical Engineering, University of Melbourne;
| | - Gregory Bass
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne; Department of Biomedical Engineering, University of Melbourne
| | - Shouryadipta Ghosh
- Cell Structure and Mechanobiology Group, University of Melbourne; Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne; Department of Biomedical Engineering, University of Melbourne
| | - Hilary Hunt
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne; School of Mathematics and Statistics, Faculty of Science, University of Melbourne
| | - Cameron Walker
- Department of Engineering Science, University of Auckland
| | - Eric Hanssen
- Advanced Microscopy Facility, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne
| | - Edmund Crampin
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne; Department of Biomedical Engineering, University of Melbourne; School of Mathematics and Statistics, Faculty of Science, University of Melbourne; ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, University of Melbourne; School of Medicine, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne
| | | |
Collapse
|
32
|
Rajagopal V, Holmes WR, Lee PVS. Computational modeling of single-cell mechanics and cytoskeletal mechanobiology. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2018; 10:e1407. [PMID: 29195023 PMCID: PMC5836888 DOI: 10.1002/wsbm.1407] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 08/19/2017] [Accepted: 09/07/2017] [Indexed: 01/10/2023]
Abstract
Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state-of-the-art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed-forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.
Collapse
Affiliation(s)
- Vijay Rajagopal
- Cell Structure and Mechanobiology Group, Department of Biomedical EngineeringUniversity of MelbourneMelbourneAustralia
| | - William R. Holmes
- Department of Physics and AstronomyVanderbilt UniversityNashvilleTNUSA
| | - Peter Vee Sin Lee
- Cell and Tissue Biomechanics Laboratory, Department of Biomedical EngineeringUniversity of MelbourneMelbourneAustralia
| |
Collapse
|
33
|
Chase JG, Preiser JC, Dickson JL, Pironet A, Chiew YS, Pretty CG, Shaw GM, Benyo B, Moeller K, Safaei S, Tawhai M, Hunter P, Desaive T. Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them. Biomed Eng Online 2018; 17:24. [PMID: 29463246 PMCID: PMC5819676 DOI: 10.1186/s12938-018-0455-y] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 02/12/2018] [Indexed: 01/17/2023] Open
Abstract
Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.
Collapse
Affiliation(s)
- J. Geoffrey Chase
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
| | - Jean-Charles Preiser
- Department of Intensive Care, Erasme University of Hospital, 1070 Brussels, Belgium
| | - Jennifer L. Dickson
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
| | - Antoine Pironet
- GIGA In Silico Medicine, University of Liege, 4000 Liege, Belgium
| | - Yeong Shiong Chiew
- Department of Mechanical Engineering, School of Engineering, Monash University Malaysia, 47500 Selangor, Malaysia
| | - Christopher G. Pretty
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
| | - Geoffrey M. Shaw
- Department of Intensive Care, Christchurch Hospital, Christchurch, New Zealand
| | - Balazs Benyo
- Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, Budapest, Hungary
| | - Knut Moeller
- Department of Biomedical Engineering, Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany
| | - Soroush Safaei
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Merryn Tawhai
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Thomas Desaive
- GIGA In Silico Medicine, University of Liege, 4000 Liege, Belgium
| |
Collapse
|
34
|
Du P, Calder S, Angeli TR, Sathar S, Paskaranandavadivel N, O'Grady G, Cheng LK. Progress in Mathematical Modeling of Gastrointestinal Slow Wave Abnormalities. Front Physiol 2018; 8:1136. [PMID: 29379448 PMCID: PMC5775268 DOI: 10.3389/fphys.2017.01136] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 12/22/2017] [Indexed: 12/19/2022] Open
Abstract
Gastrointestinal (GI) motility is regulated in part by electrophysiological events called slow waves, which are generated by the interstitial cells of Cajal (ICC). Slow waves propagate by a process of "entrainment," which occurs over a decreasing gradient of intrinsic frequencies in the antegrade direction across much of the GI tract. Abnormal initiation and conduction of slow waves have been demonstrated in, and linked to, a number of GI motility disorders. A range of mathematical models have been developed to study abnormal slow waves and applied to propose novel methods for non-invasive detection and therapy. This review provides a general outline of GI slow wave abnormalities and their recent classification using multi-electrode (high-resolution) mapping methods, with a particular emphasis on the spatial patterns of these abnormal activities. The recently-developed mathematical models are introduced in order of their biophysical scale from cellular to whole-organ levels. The modeling techniques, main findings from the simulations, and potential future directions arising from notable studies are discussed.
Collapse
Affiliation(s)
- Peng Du
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Stefan Calder
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Timothy R. Angeli
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Shameer Sathar
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | - Gregory O'Grady
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Surgery, University of Auckland, Auckland, New Zealand
| | - Leo K. Cheng
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Surgery, Vanderbilt University, Nashville, TN, United States
| |
Collapse
|
35
|
Heidlauf T, Klotz T, Rode C, Siebert T, Röhrle O. A continuum-mechanical skeletal muscle model including actin-titin interaction predicts stable contractions on the descending limb of the force-length relation. PLoS Comput Biol 2017; 13:e1005773. [PMID: 28968385 PMCID: PMC5638554 DOI: 10.1371/journal.pcbi.1005773] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 10/12/2017] [Accepted: 09/12/2017] [Indexed: 11/18/2022] Open
Abstract
Contractions on the descending limb of the total (active + passive) muscle force-length relationship (i. e. when muscle stiffness is negative) are expected to lead to vast half-sarcomere-length inhomogeneities. This is however not observed in experiments-vast half-sarcomere-length inhomogeneities can be absent in myofibrils contracting in this range, and initial inhomogeneities can even decrease. Here we show that the absence of half-sarcomere-length inhomogeneities can be predicted when considering interactions of the semi-active protein titin with the actin filaments. Including a model of actin-titin interactions within a multi-scale continuum-mechanical model, we demonstrate that stability, accurate forces and nearly homogeneous half-sarcomere lengths can be obtained on the descending limb of the static total force-length relation. This could be a key to durable functioning of the muscle because large local stretches, that might harm, for example, the transverse-tubule system, are avoided.
Collapse
Affiliation(s)
- Thomas Heidlauf
- Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
- Stuttgart Research Centre for Simulation Technology (SRC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Thomas Klotz
- Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
- Stuttgart Research Centre for Simulation Technology (SRC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Christian Rode
- Institute of Motion Science, Friedrich-Schiller-University, Jena, Germany
| | - Tobias Siebert
- Department of Sport and Motion Science, University of Stuttgart, Stuttgart, Germany
| | - Oliver Röhrle
- Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany
- Stuttgart Research Centre for Simulation Technology (SRC SimTech), University of Stuttgart, Stuttgart, Germany
| |
Collapse
|
36
|
Ghosh S, Crampin EJ, Hanssen E, Rajagopal V. A computational study of the role of mitochondrial organization on cardiac bioenergetics. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2017:2696-2699. [PMID: 29060455 DOI: 10.1109/embc.2017.8037413] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
All cells in the body have a specific shape and internal organization which is specific to that cell's function. Heart cells are rod-shaped, and contain arrays of contractile protines (myofibrils) and mitochondria (organelles that produce energy) that are aligned along the length of the rod. This arrangement is presumed to allow the cell to generate maximal contractile force for each heartbeat and for energy metabolites to be readily available to generate this force. Heart disease phenotypes, such as diabetic cardiomyopathy and heart failure, exhibit altered organization of mitochondria. However, physiological and computational studies have predominantly investigated the effect of the biochemical changes that accompany the disease alone, such as reduced rates of ATP production by mitochondria. We present a modeling study that examines the effect of mitochondrial organization on energy metabolite distribution during the heartbeat. A 2D micrograph of the cell cross-section was selected from a 3D image stack of structural data of a cardiac cell. The image was used to generate a 2D finite element model, on which mitochondrial oxidative phosphorylation and energy metabolite diffusion was modelled. Results illustrate that mitochondrial density can induce heterogeneity in the distribution of metabolites across the cell area. We discuss the implications of these findings and avenues for future, more indepth studies.
Collapse
|
37
|
Leonelli FM. Whole heart modeling - Spatiotemporal dynamics of electrical wave conduction and propagation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:5575-5578. [PMID: 28269518 DOI: 10.1109/embc.2016.7591990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Cardiac electrical activities are varying in both space and time. Human heart consists of a fractal network of muscle cells, Purkinje fibers, arteries and veins. Whole-heart modeling of electrical wave conduction and propagation involves a greater level of complexity. Our previous work developed a computer model of the anatomically realistic heart and simulated the electrical conduction with the use of cellular automata. However, simplistic assumptions and rules limit its ability to provide an accurate approximation of real-world dynamics on the complex heart surface, due to sensitive dependence of nonlinear dynamical systems on initial conditions. In this paper, we propose new reaction-diffusion methods and pattern recognition tools to simulate and model spatiotemporal dynamics of electrical wave conduction and propagation on the complex heart surface, which include (i) whole heart model; (ii) 2D isometric graphing of 3D heart geometry; (iii) reaction-diffusion modeling of electrical waves in 2D graph, and (iv) spatiotemporal pattern recognition. Experimental results show that the proposed numerical solution has strong potentials to model the space-time dynamics of electrical wave conduction in the whole heart, thereby achieving a better understanding of disease-altered cardiac mechanisms.
Collapse
|
38
|
Du P, Yassi R, Gregersen H, Windsor JA, Hunter PJ. The virtual esophagus: investigating esophageal functions in silico. Ann N Y Acad Sci 2016; 1380:19-26. [PMID: 27310396 DOI: 10.1111/nyas.13089] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Revised: 04/11/2016] [Accepted: 04/17/2016] [Indexed: 12/24/2022]
Abstract
Esophageal and gastroesophageal junction (GEJ) diseases are highly prevalent worldwide and are a significant socioeconomic burden. Recently, applications of multiscale mathematical models of the upper gastrointestinal tract have gained attention. These in silico investigations can contribute to the development of a virtual esophagus modeling framework as part of the larger GIome and Physiome initiatives. There are also other modeling investigations that have potential screening and treatment applications. These models incorporate detailed anatomical models of the esophagus and GEJ, tissue biomechanical properties and bolus transport, sensory properties, and, potentially, bioelectrical models of the neural and myogenic pathways of esophageal and GEJ functions. A next step is to improve the integration between the different components of the virtual esophagus, encoding standards, and simulation environments to perform more realistic simulations of normal and pathophysiological functions. Ultimately, the models will be validated and will provide predictive evaluations of the effects of novel endoscopic, surgical, and pharmaceutical treatment options and will facilitate the clinical translation of these treatments.
Collapse
Affiliation(s)
- Peng Du
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
| | - Rita Yassi
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Hans Gregersen
- GIOME Center, College of Bioengineering, Chongqing University, Chongqing, China
| | - John A Windsor
- Department of Surgery, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.,HBP/Upper GI Unit, Department of General Surgery, Auckland City Hospital, Auckland, New Zealand
| | - Peter J Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| |
Collapse
|
39
|
Calder S, O'Grady G, Cheng LK. A Theoretical Analysis of Electrogastrography (EGG) Signatures Associated With Gastric Dysrhythmias. IEEE Trans Biomed Eng 2016; 64:1592-1601. [PMID: 28113227 DOI: 10.1109/tbme.2016.2614277] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Routine screening and accurate diagnosis of chronic gastrointestinal motility disorders represent a significant problem in current clinical practice. The electrogastrography (EGG) provides a noninvasive option for assessing gastric slow waves, as a means of diagnosing gastric dysrhythmias, but its uptake in motility practice has been limited partly due to an incomplete sensitivity and specificity. This paper presents the development of a human whole-organ gastric model to enable virtual (in silico) testing of gastric electrophysiological dispersion in order to improve the diagnostic accuracy of EGG. The model was developed to simulate normal gastric slow wave conduction as well as three types of dysrhythmias identified in recent high-resolution gastric mapping studies: conduction block, re-entry, and ectopic pacemaking. The stomach simulations were then applied in a torso model to identify predicted EGG signatures of normal and dysrhythmic slow wave profiles. The resulting EGG data were compared using percentage differences and correlation coefficients. Virtual EGG channels that demonstrated a percentage difference over 100% and a correlation coefficient less than ±0.2 (threshold relaxed to ±0.5 for the ectopic pacemaker case) were further investigated for their specific distinguishing features. In particular, anatomical locations from the epigastric region and specific channel configurations were identified that could be used to clinically diagnose the three classes of human gastric dysrhythmia. These locations and channels predicted by simulations present a promising methodology for improving the clinical reliability and applications of EGG.
Collapse
|
40
|
Safaei S, Bradley CP, Suresh V, Mithraratne K, Muller A, Ho H, Ladd D, Hellevik LR, Omholt SW, Chase JG, Müller LO, Watanabe SM, Blanco PJ, de Bono B, Hunter PJ. Roadmap for cardiovascular circulation model. J Physiol 2016; 594:6909-6928. [PMID: 27506597 DOI: 10.1113/jp272660] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 08/02/2016] [Indexed: 11/08/2022] Open
Abstract
Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well-established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers. In this paper we propose a roadmap for developing an open source cardiovascular circulation model. The model should be registered to the musculo-skeletal system. The computational infrastructure for the cardiovascular model should provide for near real-time computation of blood flow and pressure in all parts of the body. The model should deal with vascular beds in all tissues, and the computational infrastructure for the model should provide links into CellML models of cell function and tissue function. In this work we review the literature associated with 1D blood flow modelling in the cardiovascular system, discuss model encoding standards, software and a model repository. We then describe the coordinate systems used to define the vascular geometry, derive the equations and discuss the implementation of these coupled equations in the open source computational software OpenCMISS. Finally, some preliminary results are presented and plans outlined for the next steps in the development of the model, the computational software and the graphical user interface for accessing the model.
Collapse
Affiliation(s)
- Soroush Safaei
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | - Vinod Suresh
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.,Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Kumar Mithraratne
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Alexandre Muller
- ENSEEIHT, National Polytechnic Institute of Toulouse, Toulouse, France
| | - Harvey Ho
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - David Ladd
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Leif R Hellevik
- Faculty of Medicine, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Stig W Omholt
- Faculty of Medicine, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - J Geoffrey Chase
- Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Lucas O Müller
- LNCC/MCTI, National Laboratory for Scientific Computing, Petrópolis, Brazil
| | | | - Pablo J Blanco
- LNCC/MCTI, National Laboratory for Scientific Computing, Petrópolis, Brazil
| | - Bernard de Bono
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.,Institute of Health Informatics, University College London, London, UK
| | - Peter J Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| |
Collapse
|
41
|
Klika V, Gaffney EA, Chen YC, Brown CP. An overview of multiphase cartilage mechanical modelling and its role in understanding function and pathology. J Mech Behav Biomed Mater 2016; 62:139-157. [PMID: 27195911 DOI: 10.1016/j.jmbbm.2016.04.032] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Revised: 04/15/2016] [Accepted: 04/25/2016] [Indexed: 01/01/2023]
Abstract
There is a long history of mathematical and computational modelling with the objective of understanding the mechanisms governing cartilage׳s remarkable mechanical performance. Nonetheless, despite sophisticated modelling development, simulations of cartilage have consistently lagged behind structural knowledge and thus the relationship between structure and function in cartilage is not fully understood. However, in the most recent generation of studies, there is an emerging confluence between our structural knowledge and the structure represented in cartilage modelling. This raises the prospect of further refinement in our understanding of cartilage function and also the initiation of an engineering-level understanding for how structural degradation and ageing relates to cartilage dysfunction and pathology, as well as informing the potential design of prospective interventions. Aimed at researchers entering the field of cartilage modelling, we thus review the basic principles of cartilage models, discussing the underlying physics and assumptions in relatively simple settings, whilst presenting the derivation of relatively parsimonious multiphase cartilage models consistent with our discussions. We proceed to consider modern developments that start aligning the structure captured in the models with observed complexities. This emphasises the challenges associated with constitutive relations, boundary conditions, parameter estimation and validation in cartilage modelling programmes. Consequently, we further detail how both experimental interrogations and modelling developments can be utilised to investigate and reduce such difficulties before summarising how cartilage modelling initiatives may improve our understanding of cartilage ageing, pathology and intervention.
Collapse
Affiliation(s)
- Václav Klika
- Department of Mathematics, FNSPE, Czech Technical University in Prague, Prague, Czech Republic.
| | - Eamonn A Gaffney
- Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK.
| | - Ying-Chun Chen
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Cameron P Brown
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
| |
Collapse
|
42
|
Fernandez J, Zhang J, Heidlauf T, Sartori M, Besier T, Röhrle O, Lloyd D. Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling. Interface Focus 2016; 6:20150084. [PMID: 27051510 DOI: 10.1098/rsfs.2015.0084] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.
Collapse
Affiliation(s)
- J Fernandez
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - J Zhang
- Auckland Bioengineering Institute , University of Auckland , Auckland , New Zealand
| | - T Heidlauf
- Institut für Mechanik (Bau) , University of Stuttgart , Stuttgart , Germany
| | - M Sartori
- Department of Neurorehabilitation Engineering , University Medical Center Göttingen , Göttingen , Germany
| | - T Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - O Röhrle
- Institut für Mechanik (Bau) , University of Stuttgart , Stuttgart , Germany
| | - D Lloyd
- Centre for Musculoskeletal Research, Menzies Health Institute Queensland, Griffith University, Queensland, Australia; School of Rehabilitation Sciences, Griffith University, Queensland, Australia
| |
Collapse
|
43
|
Heidlauf T, Klotz T, Rode C, Altan E, Bleiler C, Siebert T, Röhrle O. A multi-scale continuum model of skeletal muscle mechanics predicting force enhancement based on actin-titin interaction. Biomech Model Mechanobiol 2016; 15:1423-1437. [PMID: 26935301 DOI: 10.1007/s10237-016-0772-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Accepted: 02/17/2016] [Indexed: 10/22/2022]
Abstract
Although recent research emphasises the possible role of titin in skeletal muscle force enhancement, this property is commonly ignored in current computational models. This work presents the first biophysically based continuum-mechanical model of skeletal muscle that considers, in addition to actin-myosin interactions, force enhancement based on actin-titin interactions. During activation, titin attaches to actin filaments, which results in a significant reduction in titin's free molecular spring length and therefore results in increased titin forces during a subsequent stretch. The mechanical behaviour of titin is included on the microscopic half-sarcomere level of a multi-scale chemo-electro-mechanical muscle model, which is based on the classic sliding-filament and cross-bridge theories. In addition to titin stress contributions in the muscle fibre direction, the continuum-mechanical constitutive relation accounts for geometrically motivated, titin-induced stresses acting in the muscle's cross-fibre directions. Representative simulations of active stretches under maximal and submaximal activation levels predict realistic magnitudes of force enhancement in fibre direction. For example, stretching the model by 20 % from optimal length increased the isometric force at the target length by about 30 %. Predicted titin-induced stresses in the muscle's cross-fibre directions are rather insignificant. Including the presented development in future continuum-mechanical models of muscle function in dynamic situations will lead to more accurate model predictions during and after lengthening contractions.
Collapse
Affiliation(s)
- Thomas Heidlauf
- Institute of Applied Mechanics (CE), Pfaffenwaldring 7, 70569, Stuttgart, Germany.
| | - Thomas Klotz
- Institute of Applied Mechanics (CE), Pfaffenwaldring 7, 70569, Stuttgart, Germany
| | - Christian Rode
- Institute of Motion Science, Friedrich-Schiller-University, Seidelstr. 20, 07749, Jena, Germany
| | - Ekin Altan
- Institute of Applied Mechanics (CE), Pfaffenwaldring 7, 70569, Stuttgart, Germany
| | - Christian Bleiler
- Institute of Applied Mechanics (CE), Pfaffenwaldring 7, 70569, Stuttgart, Germany
| | - Tobias Siebert
- Department of Sport and Motion Science, University of Stuttgart, Allmandring 28, 70569, Stuttgart, Germany
| | - Oliver Röhrle
- Institute of Applied Mechanics (CE), Pfaffenwaldring 7, 70569, Stuttgart, Germany
| |
Collapse
|
44
|
Clancy CE, Chen-Izu Y, Bers DM, Belardinelli L, Boyden PA, Csernoch L, Despa S, Fermini B, Hool LC, Izu L, Kass RS, Lederer WJ, Louch WE, Maack C, Matiazzi A, Qu Z, Rajamani S, Rippinger CM, Sejersted OM, O'Rourke B, Weiss JN, Varró A, Zaza A. Deranged sodium to sudden death. J Physiol 2015; 593:1331-45. [PMID: 25772289 DOI: 10.1113/jphysiol.2014.281204] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Accepted: 10/14/2014] [Indexed: 12/19/2022] Open
Abstract
In February 2014, a group of scientists convened as part of the University of California Davis Cardiovascular Symposium to bring together experimental and mathematical modelling perspectives and discuss points of consensus and controversy on the topic of sodium in the heart. This paper summarizes the topics of presentation and discussion from the symposium, with a focus on the role of aberrant sodium channels and abnormal sodium homeostasis in cardiac arrhythmias and pharmacotherapy from the subcellular scale to the whole heart. Two following papers focus on Na(+) channel structure, function and regulation, and Na(+)/Ca(2+) exchange and Na(+)/K(+) ATPase. The UC Davis Cardiovascular Symposium is a biannual event that aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The focus on Na(+) in the 2014 symposium stemmed from the multitude of recent studies that point to the importance of maintaining Na(+) homeostasis in the heart, as disruption of homeostatic processes are increasingly identified in cardiac disease states. Understanding how disruption in cardiac Na(+)-based processes leads to derangement in multiple cardiac components at the level of the cell and to then connect these perturbations to emergent behaviour in the heart to cause disease is a critical area of research. The ubiquity of disruption of Na(+) channels and Na(+) homeostasis in cardiac disorders of excitability and mechanics emphasizes the importance of a fundamental understanding of the associated mechanisms and disease processes to ultimately reveal new targets for human therapy.
Collapse
Affiliation(s)
- Colleen E Clancy
- Department of Pharmacology, University of California, Davis, Genome Building Rm 3503, Davis, CA, 95616-8636, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
45
|
Land S, Gurev V, Arens S, Augustin CM, Baron L, Blake R, Bradley C, Castro S, Crozier A, Favino M, Fastl TE, Fritz T, Gao H, Gizzi A, Griffith BE, Hurtado DE, Krause R, Luo X, Nash MP, Pezzuto S, Plank G, Rossi S, Ruprecht D, Seemann G, Smith NP, Sundnes J, Rice JJ, Trayanova N, Wang D, Jenny Wang Z, Niederer SA. Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour. Proc Math Phys Eng Sci 2015; 471:20150641. [PMID: 26807042 PMCID: PMC4707707 DOI: 10.1098/rspa.2015.0641] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the actively contracting material. A large number of independent simulation codes have been developed, but a consistent way of verifying the accuracy and replicability of simulations is lacking. To aid in the verification of current and future cardiac mechanics solvers, this study provides three benchmark problems for cardiac mechanics. These benchmark problems test the ability to accurately simulate pressure-type forces that depend on the deformed objects geometry, anisotropic and spatially varying material properties similar to those seen in the left ventricle and active contractile forces. The benchmark was solved by 11 different groups to generate consensus solutions, with typical differences in higher-resolution solutions at approximately 0.5%, and consistent results between linear, quadratic and cubic finite elements as well as different approaches to simulating incompressible materials. Online tools and solutions are made available to allow these tests to be effectively used in verification of future cardiac mechanics software.
Collapse
Affiliation(s)
- Sander Land
- Department of Biomedical Engineering, King's College London , London, UK
| | - Viatcheslav Gurev
- Thomas J. Watson Research Center, IBM Research, Yorktown Heights , NY 10598, USA
| | - Sander Arens
- Department of Physics and Astronomy , Ghent University , Ghent, Belgium
| | | | - Lukas Baron
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology , Karlsruhe, Germany
| | - Robert Blake
- Department of Biomedical Engineering and Institute for Computational Medicine , Johns Hopkins University , Baltimore, MD 21218, USA
| | - Chris Bradley
- Auckland Bioengineering Institute, University of Auckland , Auckland, New Zealand
| | - Sebastian Castro
- Department of Structural and Geotechnical Engineering , Pontifica Universidad Católica de Chile , Chile
| | - Andrew Crozier
- Institute of Biophysics, Medical University of Graz , Graz, Austria
| | - Marco Favino
- Center for Computational Medicine in Cardiology , Institute of Computational Science, Università della Svizzera italiana , Lugano, Switzerland
| | - Thomas E Fastl
- Department of Biomedical Engineering, King's College London , London, UK
| | - Thomas Fritz
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology , Karlsruhe, Germany
| | - Hao Gao
- School of Mathematics and Statistics, University of Glasgow , Glasgow, UK
| | - Alessio Gizzi
- Department of Engineering, Nonlinear Physics and Mathematical Modeling Lab , University Campus Bio-Medico of Rome , Rome, Italy
| | - Boyce E Griffith
- Interdisciplinary Applied Mathematics Center , University of North Carolina at Chapel Hill , Chapel Hill, NC, USA
| | - Daniel E Hurtado
- Department of Structural and Geotechnical Engineering , Pontifica Universidad Católica de Chile , Chile
| | - Rolf Krause
- Center for Computational Medicine in Cardiology , Institute of Computational Science, Università della Svizzera italiana , Lugano, Switzerland
| | - Xiaoyu Luo
- School of Mathematics and Statistics, University of Glasgow , Glasgow, UK
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Simone Pezzuto
- Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland; Simula Research Laboratory, Fornebu, Norway
| | - Gernot Plank
- Institute of Biophysics, Medical University of Graz , Graz, Austria
| | - Simone Rossi
- Civil and Environmental Engineering Department , Duke University , Durham, NC 27708-0287, USA
| | - Daniel Ruprecht
- Center for Computational Medicine in Cardiology , Institute of Computational Science, Università della Svizzera italiana , Lugano, Switzerland
| | - Gunnar Seemann
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology , Karlsruhe, Germany
| | - Nicolas P Smith
- Department of Biomedical Engineering, King's College London, London, UK; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | | | - J Jeremy Rice
- Thomas J. Watson Research Center, IBM Research, Yorktown Heights , NY 10598, USA
| | - Natalia Trayanova
- Department of Biomedical Engineering and Institute for Computational Medicine , Johns Hopkins University , Baltimore, MD 21218, USA
| | - Dafang Wang
- Department of Biomedical Engineering and Institute for Computational Medicine , Johns Hopkins University , Baltimore, MD 21218, USA
| | - Zhinuo Jenny Wang
- Auckland Bioengineering Institute, University of Auckland , Auckland, New Zealand
| | - Steven A Niederer
- Department of Biomedical Engineering, King's College London , London, UK
| |
Collapse
|
46
|
Punzalan FR, Kunieda Y, Amano A. Program Code Generator for Cardiac Electrophysiology Simulation with Automatic PDE Boundary Condition Handling. PLoS One 2015; 10:e0136821. [PMID: 26356082 PMCID: PMC4565589 DOI: 10.1371/journal.pone.0136821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 08/10/2015] [Indexed: 11/21/2022] Open
Abstract
Clinical and experimental studies involving human hearts can have certain limitations. Methods such as computer simulations can be an important alternative or supplemental tool. Physiological simulation at the tissue or organ level typically involves the handling of partial differential equations (PDEs). Boundary conditions and distributed parameters, such as those used in pharmacokinetics simulation, add to the complexity of the PDE solution. These factors can tailor PDE solutions and their corresponding program code to specific problems. Boundary condition and parameter changes in the customized code are usually prone to errors and time-consuming. We propose a general approach for handling PDEs and boundary conditions in computational models using a replacement scheme for discretization. This study is an extension of a program generator that we introduced in a previous publication. The program generator can generate code for multi-cell simulations of cardiac electrophysiology. Improvements to the system allow it to handle simultaneous equations in the biological function model as well as implicit PDE numerical schemes. The replacement scheme involves substituting all partial differential terms with numerical solution equations. Once the model and boundary equations are discretized with the numerical solution scheme, instances of the equations are generated to undergo dependency analysis. The result of the dependency analysis is then used to generate the program code. The resulting program code are in Java or C programming language. To validate the automatic handling of boundary conditions in the program code generator, we generated simulation code using the FHN, Luo-Rudy 1, and Hund-Rudy cell models and run cell-to-cell coupling and action potential propagation simulations. One of the simulations is based on a published experiment and simulation results are compared with the experimental data. We conclude that the proposed program code generator can be used to generate code for physiological simulations and provides a tool for studying cardiac electrophysiology.
Collapse
Affiliation(s)
| | - Yoshitoshi Kunieda
- Department of Computer Science, College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan
| | - Akira Amano
- Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, Shiga, Japan
- * E-mail:
| |
Collapse
|
47
|
Rajagopal V, Bass G, Walker CG, Crossman DJ, Petzer A, Hickey A, Siekmann I, Hoshijima M, Ellisman MH, Crampin EJ, Soeller C. Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes. PLoS Comput Biol 2015; 11:e1004417. [PMID: 26335304 PMCID: PMC4559435 DOI: 10.1371/journal.pcbi.1004417] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 06/26/2015] [Indexed: 11/18/2022] Open
Abstract
Spatio-temporal dynamics of intracellular calcium, [Ca2+]i, regulate the contractile function of cardiac muscle cells. Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease. However, current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected. Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters, which act as the major mediators of contractile Ca2+ release, upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils. We applied this method to computationally combine confocal-scale (~ 200 nm) data of RyR clusters with 3D electron microscopy data (~ 30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. Using this hybrid-scale spatial model, we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient (first 30 ms after initiation). At 30 ms, the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal, F/F0, reached values similar to that found in the literature ([Ca2+]i ≈1 μM; F/F0≈5.5). However, our model predicted the variation in [Ca2+]i to be between 0.3 and 12.7 μM (~3 to 100 fold from resting value of 0.1 μM) and the corresponding F/F0 signal ranging from 3 to 9.5. We demonstrate in this study that: (i) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria; (ii) but also to heterogeneous local densities of RyR clusters. Further, we show that: (iii) these structure-induced heterogeneities in [Ca2+]i can appear in line scan data. Finally, using our unique method for generating RyR cluster distributions, we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes. Calcium (Ca2+) acts as a signal for many functions in the heart cell, from its primary role in triggering contractions during the heartbeat to acting as a signal for cell growth. Cellular function is tightly coupled to its ultra-structural organization. Spatially-realistic and biophysics-based computational models can provide quantitative insights into structure-function relationships in Ca2+ signaling. We developed a novel computational model of a rat ventricular myocyte that integrates structural information from confocal and electron microscopy datasets that were independently acquired and includes: myofibrils (protein complexes that contract during the heartbeat), mitochondria (organelles that provide energy for contraction), and ryanodine receptors (RyR, ion channels that release the Ca2+ required to trigger myofibril contraction from intracellular stores). Using this model, we examined [Ca2+]i dynamics throughout the cell cross-section at a much higher resolution than previously possible. We estimated the size of structural maladaptation that would cause disease-related alterations in [Ca2+]i dynamics. Using our methods for data integration, we also tested whether reducing the density of RyRs in human cardiomyocytes (~40% relative to rat) would have a significant effect on [Ca2+]i. We found that Ca2+ release patterns between the two species are similar, suggesting Ca2+ dynamics are robust to variations in cell ultrastructure.
Collapse
Affiliation(s)
- Vijay Rajagopal
- Department of Mechanical Engineering, University of Melbourne, Melbourne, Australia
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
- * E-mail:
| | - Gregory Bass
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
| | - Cameron G. Walker
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - David J. Crossman
- Department of Physiology, University of Auckland, Auckland, New Zealand
| | - Amorita Petzer
- School of Biological Sciences, University of Auckland, Auckland. New Zealand
| | - Anthony Hickey
- School of Biological Sciences, University of Auckland, Auckland. New Zealand
| | - Ivo Siekmann
- Department of Mechanical Engineering, University of Melbourne, Melbourne, Australia
| | - Masahiko Hoshijima
- Department of Medicine, University of California San Diego, San Diego, United States of America
- National Center for Microscopy and Imaging Research, University of California San Diego, San Diego, United States of America
| | - Mark H. Ellisman
- National Center for Microscopy and Imaging Research, University of California San Diego, San Diego, United States of America
| | - Edmund J. Crampin
- Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia
- School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, Australia
- School of Medicine, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
- ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, University of Melbourne, Melbourne, Australia
| | - Christian Soeller
- Department of Physiology, University of Auckland, Auckland, New Zealand
- Biomedical Physics, University of Exeter, Exeter, United Kingdom
| |
Collapse
|
48
|
|
49
|
Mordhorst M, Heidlauf T, Röhrle O. Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model. Interface Focus 2015; 5:20140076. [PMID: 25844148 DOI: 10.1098/rsfs.2014.0076] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation-contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons.
Collapse
Affiliation(s)
- Mylena Mordhorst
- Institute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany
| | - Thomas Heidlauf
- Institute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany
| | - Oliver Röhrle
- Institute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany
| |
Collapse
|
50
|
de Bono B, Safaei S, Grenon P, Nickerson DP, Alexander S, Helvensteijn M, Kok JN, Kokash N, Wu A, Yu T, Hunter P, Baldock RA. The Open Physiology workflow: modeling processes over physiology circuitboards of interoperable tissue units. Front Physiol 2015; 6:24. [PMID: 25759670 PMCID: PMC4338662 DOI: 10.3389/fphys.2015.00024] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 01/14/2015] [Indexed: 01/11/2023] Open
Abstract
A key challenge for the physiology modeling community is to enable the searching, objective comparison and, ultimately, re-use of models and associated data that are interoperable in terms of their physiological meaning. In this work, we outline the development of a workflow to modularize the simulation of tissue-level processes in physiology. In particular, we show how, via this approach, we can systematically extract, parcellate and annotate tissue histology data to represent component units of tissue function. These functional units are semantically interoperable, in terms of their physiological meaning. In particular, they are interoperable with respect to [i] each other and with respect to [ii] a circuitboard representation of long-range advective routes of fluid flow over which to model long-range molecular exchange between these units. We exemplify this approach through the combination of models for physiology-based pharmacokinetics and pharmacodynamics to quantitatively depict biological mechanisms across multiple scales. Links to the data, models and software components that constitute this workflow are found at http://open-physiology.org/.
Collapse
Affiliation(s)
- Bernard de Bono
- Centre for Health Informatics and Multiprofessional Education, University College London London, UK ; Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Soroush Safaei
- Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Pierre Grenon
- Centre for Health Informatics and Multiprofessional Education, University College London London, UK
| | - David P Nickerson
- Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Samuel Alexander
- Centre for Health Informatics and Multiprofessional Education, University College London London, UK
| | - Michiel Helvensteijn
- Leiden Institute of Advanced Computer Science, University of Leiden Leiden, Netherlands
| | - Joost N Kok
- Leiden Institute of Advanced Computer Science, University of Leiden Leiden, Netherlands
| | - Natallia Kokash
- Leiden Institute of Advanced Computer Science, University of Leiden Leiden, Netherlands
| | - Alan Wu
- Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Tommy Yu
- Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland Auckland, New Zealand
| | - Richard A Baldock
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh Edinburgh, UK
| |
Collapse
|