1
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Peitola JPJ, Esrafilian A, Eskelinen ASA, Andersen MS, Korhonen RK. Sensitivity of knee cartilage biomechanics in finite element analysis to selected Musculoskeletal models. Comput Methods Biomech Biomed Engin 2024:1-12. [PMID: 38833005 DOI: 10.1080/10255842.2024.2360594] [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: 02/28/2024] [Accepted: 05/20/2024] [Indexed: 06/06/2024]
Abstract
Knee joint kinematics and kinetics analyzed by musculoskeletal (MS) modeling are often utilized in finite element (FE) models, estimating tissue-level mechanical responses. We compared knee cartilage stresses, strains, and centers of pressure of FE models driven by two widely used MS models, implemented in AnyBody and OpenSim. Minor discrepancies in the results were observed between the models. AnyBody-driven FE models showed slightly higher stresses in the medial tibial cartilage, while OpenSim-driven FE models estimated more anterior and lateral center of pressure. Recognizing these differences in the MS-FE models is important to ensure reliable analysis of cartilage mechanics and failure and simulation of rehabilitation.
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Affiliation(s)
- Joose P J Peitola
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Amir Esrafilian
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Atte S A Eskelinen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Michael S Andersen
- Department of Materials and Production, Aalborg University, Aalborg, Denmark
- Center for Mathematical Modeling of Knee Osteoarthritis, Aalborg University, Aalborg, Denmark
| | - Rami K Korhonen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
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2
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Li J, Xu J, Chen Z, Lu Y, Hua X, Jin Z. Computational modelling of articular joints with biphasic cartilage: recent advances, challenges and opportunities. Med Eng Phys 2024; 126:104130. [PMID: 38621832 DOI: 10.1016/j.medengphy.2024.104130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 02/16/2024] [Accepted: 02/25/2024] [Indexed: 04/17/2024]
Abstract
Biphasic models have been widely used to simulate the time-dependent biomechanical response of soft tissues. Modelling techniques of joints with biphasic weight-bearing soft tissues have been markedly improved over the last decade, enhancing our understanding of the function, degenerative mechanism and outcomes of interventions of joints. This paper reviews the recent advances, challenges and opportunities in computational models of joints with biphasic weight-bearing soft tissues. The review begins with an introduction of the function and degeneration of joints from a biomechanical aspect. Different constitutive models of articular cartilage, in particular biphasic materials, are illustrated in the context of the study of contact mechanics in joints. Approaches, advances and major findings of biphasic models of the hip and knee are presented, followed by a discussion of the challenges awaiting to be addressed, including the convergence issue, high computational cost and inadequate validation. Finally, opportunities and clinical insights in the areas of subject-specific modeling and tissue engineering are provided and discussed.
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Affiliation(s)
- Junyan Li
- Tribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, PR China.
| | - Jinghao Xu
- Tribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, PR China
| | - Zhenxian Chen
- Key Laboratory of Road Construction Technology and Equipment (Ministry of Education), Chang'an University, Xi'an, PR China
| | - Yongtao Lu
- Department of Engineering Mechanics, Dalian University of Technology, Dalian, PR China
| | - Xijin Hua
- Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom
| | - Zhongmin Jin
- Tribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, PR China; Sate Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, PR China; Institute of Medical and Biological Engineering, School of Mechanical Engineering, University of Leeds, Leeds, United Kingdom
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3
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Yan M, Liang T, Zhao H, Bi Y, Wang T, Yu T, Zhang Y. Model Properties and Clinical Application in the Finite Element Analysis of Knee Joint: A Review. Orthop Surg 2024; 16:289-302. [PMID: 38174410 PMCID: PMC10834231 DOI: 10.1111/os.13980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/21/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024] Open
Abstract
The knee is the most complex joint in the human body, including bony structures like the femur, tibia, fibula, and patella, and soft tissues like menisci, ligaments, muscles, and tendons. Complex anatomical structures of the knee joint make it difficult to conduct precise biomechanical research and explore the mechanism of movement and injury. The finite element model (FEM), as an important engineering analysis technique, has been widely used in many fields of bioengineering research. The FEM has advantages in the biomechanical analysis of objects with complex structures. Researchers can use this technology to construct a human knee joint model and perform biomechanical analysis on it. At the same time, finite element analysis can effectively evaluate variables such as stress, strain, displacement, and rotation, helping to predict injury mechanisms and optimize surgical techniques, which make up for the shortcomings of traditional biomechanics experimental research. However, few papers introduce what material properties should be selected for each anatomic structure of knee FEM to meet different research purposes. Based on previous finite element studies of the knee joint, this paper summarizes various modeling strategies and applications, serving as a reference for constructing knee joint models and research design.
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Affiliation(s)
- Mingyue Yan
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
- Institute of Sports Medicine and Health, Qingdao University, Qingdao, China
| | - Ting Liang
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
- Institute of Sports Medicine and Health, Qingdao University, Qingdao, China
| | - Haibo Zhao
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
- Institute of Sports Medicine and Health, Qingdao University, Qingdao, China
| | - Yanchi Bi
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
- Institute of Sports Medicine and Health, Qingdao University, Qingdao, China
| | - Tianrui Wang
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tengbo Yu
- Institute of Sports Medicine and Health, Qingdao University, Qingdao, China
- Department of Orthopedic Surgery, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, China
| | - Yingze Zhang
- Department of Orthopedics, The Third Hospital of Hebei Medical University, Shijiazhuang, China
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4
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Esrafilian A, Halonen KS, Dzialo CM, Mannisi M, Mononen ME, Tanska P, Woodburn J, Korhonen RK, Andersen MS. Effects of gait modifications on tissue-level knee mechanics in individuals with medial tibiofemoral osteoarthritis: A proof-of-concept study towards personalized interventions. J Orthop Res 2024; 42:326-338. [PMID: 37644668 PMCID: PMC10952410 DOI: 10.1002/jor.25686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 06/19/2023] [Accepted: 08/24/2023] [Indexed: 08/31/2023]
Abstract
Gait modification is a common nonsurgical approach to alter the mediolateral distribution of knee contact forces, intending to decelerate or postpone the progression of mechanically induced knee osteoarthritis (KOA). Nevertheless, the success rate of these approaches is controversial, with no studies conducted to assess alterations in tissue-level knee mechanics governing cartilage degradation response in KOA patients undertaking gait modifications. Thus, here we investigated the effect of different conventional gait conditions and modifications on tissue-level knee mechanics previously suggested as indicators of collagen network damage, cell death, and loss of proteoglycans in knee cartilage. Five participants with medial KOA were recruited and musculoskeletal finite element analyses were conducted to estimate subject-specific tissue mechanics of knee cartilages during two gait conditions (i.e., barefoot and shod) and six gait modifications (i.e., 0°, 5°, and 10° lateral wedge insoles, toe-in, toe-out, and wide stance). Based on our results, the optimal gait modification varied across the participants. Overall, toe-in, toe-out, and wide stance showed the greatest reduction in tissue mechanics within medial tibial and femoral cartilages. Gait modifications could effectually alter maximum principal stress (~20 ± 7%) and shear strain (~9 ± 4%) within the medial tibial cartilage. Nevertheless, lateral wedge insoles did not reduce joint- and tissue-level mechanics considerably. Significance: This proof-of-concept study emphasizes the importance of the personalized design of gait modifications to account for biomechanical risk factors associated with cartilage degradation.
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Affiliation(s)
- Amir Esrafilian
- Department of Technical PhysicsUniversity of Eastern FinlandKuopioFinland
| | - Kimmo S. Halonen
- Central hospital of Päijät‐HämeLahtiFinland
- Department of Materials and ProductionAalborg UniversityAalborgDenmark
| | | | | | - Mika E. Mononen
- Department of Technical PhysicsUniversity of Eastern FinlandKuopioFinland
| | - Petri Tanska
- Department of Technical PhysicsUniversity of Eastern FinlandKuopioFinland
| | - Jim Woodburn
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute QueenslandGriffith UniversityGold CoastQLDAustralia
| | - Rami K. Korhonen
- Department of Technical PhysicsUniversity of Eastern FinlandKuopioFinland
| | - Michael S. Andersen
- Department of Materials and ProductionAalborg UniversityAalborgDenmark
- Center for Mathematical Modeling of Knee Osteoarthritis (MathKOA), Department of Materials and ProductionAalborg UniversityAalborgDenmark
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5
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Jahangir S, Esrafilian A, Ebrahimi M, Stenroth L, Alkjær T, Henriksen M, Englund M, Mononen ME, Korhonen RK, Tanska P. Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties. J Biomech 2023; 160:111800. [PMID: 37797566 DOI: 10.1016/j.jbiomech.2023.111800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 08/25/2023] [Accepted: 09/12/2023] [Indexed: 10/07/2023]
Abstract
Fibril-reinforced poroviscoelastic material models are considered state-of-the-art in modeling articular cartilage biomechanics. Yet, cartilage material parameters are often based on bovine tissue properties in computational knee joint models, although bovine properties are distinctly different from those of humans. Thus, we aimed to investigate how cartilage mechanical responses are affected in the knee joint model during walking when fibril-reinforced poroviscoelastic properties of cartilage are based on human data instead of bovine. We constructed a finite element knee joint model in which tibial and femoral cartilages were modeled as fibril-reinforced poroviscoelastic material using either human or bovine data. Joint loading was based on subject-specific gait data. The resulting mechanical responses of knee cartilage were compared between the knee joint models with human or bovine fibril-reinforced poroviscoelastic cartilage properties. Furthermore, we conducted a sensitivity analysis to determine which fibril-reinforced poroviscoelastic material parameters have the greatest impact on cartilage mechanical responses in the knee joint during walking. In general, bovine cartilage properties yielded greater maximum principal stresses and fluid pressures (both up to 30%) when compared to the human cartilage properties during the loading response in both femoral and tibial cartilage sites. Cartilage mechanical responses were very sensitive to the collagen fibril-related material parameter variations during walking while they were unresponsive to proteoglycan matrix or fluid flow-related material parameter variations. Taken together, human cartilage material properties should be accounted for when the goal is to compare absolute mechanical responses of knee joint cartilage as bovine material parameters lead to substantially different cartilage mechanical responses.
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Affiliation(s)
- Sana Jahangir
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
| | - Amir Esrafilian
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | | | - Lauri Stenroth
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tine Alkjær
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark; The Parker Institute, Bispebjerg-Frederiksberg Hospital, Copenhagen, Denmark
| | - Marius Henriksen
- The Parker Institute, Bispebjerg-Frederiksberg Hospital, Copenhagen, Denmark
| | - Martin Englund
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Mika E Mononen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Rami K Korhonen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Petri Tanska
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
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6
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Karimi Dastgerdi A, Esrafilian A, Carty CP, Nasseri A, Yahyaiee Bavil A, Barzan M, Korhonen RK, Astori I, Hall W, Saxby DJ. Validation and evaluation of subject-specific finite element models of the pediatric knee. Sci Rep 2023; 13:18328. [PMID: 37884632 PMCID: PMC10603053 DOI: 10.1038/s41598-023-45408-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023] Open
Abstract
Finite element (FE) models have been widely used to investigate knee joint biomechanics. Most of these models have been developed to study adult knees, neglecting pediatric populations. In this study, an atlas-based approach was employed to develop subject-specific FE models of the knee for eight typically developing pediatric individuals. Initially, validation simulations were performed at four passive tibiofemoral joint (TFJ) flexion angles, and the resulting TFJ and patellofemoral joint (PFJ) kinematics were compared to corresponding patient-matched measurements derived from magnetic resonance imaging (MRI). A neuromusculoskeletal-(NMSK)-FE pipeline was then used to simulate knee biomechanics during stance phase of walking gait for each participant to evaluate model simulation of a common motor task. Validation simulations demonstrated minimal error and strong correlations between FE-predicted and MRI-measured TFJ and PFJ kinematics (ensemble average of root mean square errors < 5 mm for translations and < 4.1° for rotations). The FE-predicted kinematics were strongly correlated with published reports (ensemble average of Pearson's correlation coefficients (ρ) > 0.9 for translations and ρ > 0.8 for rotations), except for TFJ mediolateral translation and abduction/adduction rotation. For walking gait, NMSK-FE model-predicted knee kinematics, contact areas, and contact pressures were consistent with experimental reports from literature. The strong agreement between model predictions and experimental reports underscores the capability of sequentially linked NMSK-FE models to accurately predict pediatric knee kinematics, as well as complex contact pressure distributions across the TFJ articulations. These models hold promise as effective tools for parametric analyses, population-based clinical studies, and enhancing our understanding of various pediatric knee injury mechanisms. They also support intervention design and prediction of surgical outcomes in pediatric populations.
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Affiliation(s)
- Ayda Karimi Dastgerdi
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia.
| | - Amir Esrafilian
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Christopher P Carty
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia
- Department of Orthopedics, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia
| | - Alireza Yahyaiee Bavil
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia
| | - Martina Barzan
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia
| | - Rami K Korhonen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Ivan Astori
- Department of Orthopedics, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia
| | - Wayne Hall
- School of Engineering and Built Environment, Mechanical Engineering and Industrial Design, Griffith University, Gold Coast, QLD, Australia
| | - David John Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and the Advanced Design and Prototyping Technologies Institute (ADAPT), Griffith University, Gold Coast, QLD, Australia
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7
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Lloyd DG, Jonkers I, Delp SL, Modenese L. The History and Future of Neuromusculoskeletal Biomechanics. J Appl Biomech 2023; 39:273-283. [PMID: 37751904 DOI: 10.1123/jab.2023-0165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 09/28/2023]
Abstract
The Executive Council of the International Society of Biomechanics has initiated and overseen the commemorations of the Society's 50th Anniversary in 2023. This included multiple series of lectures at the ninth World Congress of Biomechanics in 2022 and XXIXth Congress of the International Society of Biomechanics in 2023, all linked to special issues of International Society of Biomechanics' affiliated journals. This special issue of the Journal of Applied Biomechanics is dedicated to the biomechanics of the neuromusculoskeletal system. The reader is encouraged to explore this special issue which comprises 6 papers exploring the current state-of the-art, and future directions and roles for neuromusculoskeletal biomechanics. This editorial presents a very brief history of the science of the neuromusculoskeletal system's 4 main components: the central nervous system, musculotendon units, the musculoskeletal system, and joints, and how they biomechanically integrate to enable an understanding of the generation and control of human movement. This also entails a quick exploration of contemporary neuromusculoskeletal biomechanics and its future with new fields of application.
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Affiliation(s)
- David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, School of Health Science and Social Work, Griffith University, Gold Coast, QLD, Australia
| | - Ilse Jonkers
- Institute of Physics-Based Modeling for in Silico Health, Human Movement Science Department, KU Leuven, Leuven, Belgium
| | - Scott L Delp
- Bioengineering, Mechanical Engineering and Orthopedic Surgery, and Wu Tsai Human Performance Alliance at Stanford, Stanford University, Stanford, CA, USA
| | - Luca Modenese
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia
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8
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Mohout I, Elahi SA, Esrafilian A, Killen BA, Korhonen RK, Verschueren S, Jonkers I. Signatures of disease progression in knee osteoarthritis: insights from an integrated multi-scale modeling approach, a proof of concept. Front Bioeng Biotechnol 2023; 11:1214693. [PMID: 37576991 PMCID: PMC10413555 DOI: 10.3389/fbioe.2023.1214693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction: Knee osteoarthritis (KOA) is characterized by articular cartilage degeneration. It has been widely accepted that the mechanical joint environment plays a significant role in the onset and progression of this disease. In silico models have been used to study the interplay between mechanical loading and cartilage degeneration, hereby relying mainly on two key mechanoregulatory factors indicative of collagen degradation and proteoglycans depletion. These factors are the strain in collagen fibril direction (SFD) and maximum shear strain (MSS) respectively. Methods: In this study, a multi-scale in silico modeling approach was used based on a synergy between musculoskeletal and finite element modeling to evaluate the SFD and MSS. These strains were evaluated during gait based on subject-specific gait analysis data collected at baseline (before a 2-year follow-up) for a healthy and progressive early-stage KOA subject with similar demographics. Results: The results show that both SFD and MSS factors allowed distinguishing between a healthy subject and a KOA subject, showing progression at 2 years follow-up, at the instance of peak contact force as well as during the stance phase of the gait cycle. At the peak of the stance phase, the SFD were found to be more elevated in the KOA patient with the median being 0.82% higher in the lateral and 0.4% higher in the medial compartment of the tibial cartilage compared to the healthy subject. Similarly, for the MSS, the median strains were found to be 3.6% higher in the lateral and 0.7% higher in the medial tibial compartment of the KOA patient compared to the healthy subject. Based on these intersubject SFD and MSS differences, we were additionally able to identify that the tibial compartment of the KOA subject at risk of progression. Conclusion/discussion: We confirmed the mechanoregulatory factors as potential biomarkers to discriminate patients at risk of disease progression. Future studies should evaluate the sensitivity of the mechanoregulatory factors calculated based on this multi-scale modeling workflow in larger patient and control cohorts.
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Affiliation(s)
- Ikram Mohout
- Department of Movement Science, Human Movement Biomechanics Research Group, Leuven, Belgium
| | - Seyed Ali Elahi
- Department of Movement Science, Human Movement Biomechanics Research Group, Leuven, Belgium
- Mechanical Engineering Department, Soft Tissue Biomechanics Group, Leuven, Belgium
| | - Amir Esrafilian
- Department of Technical Physics, Biophysics of Bone and Cartilage Research Group, University of Eastern Finland, Kuopio, Finland
| | - Bryce A. Killen
- Department of Movement Science, Human Movement Biomechanics Research Group, Leuven, Belgium
| | - Rami K. Korhonen
- Department of Technical Physics, Biophysics of Bone and Cartilage Research Group, University of Eastern Finland, Kuopio, Finland
| | - Sabine Verschueren
- Department of Rehabilitation Science, Research Group for Musculoskeletal Rehabilitation, Leuven, Belgium
| | - Ilse Jonkers
- Department of Movement Science, Human Movement Biomechanics Research Group, Leuven, Belgium
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9
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Raju V, Koorata PK. Computational assessment on the impact of collagen fiber orientation in cartilages on healthy and arthritic knee kinetics/kinematics. Med Eng Phys 2023; 117:103997. [PMID: 37331751 DOI: 10.1016/j.medengphy.2023.103997] [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: 09/14/2022] [Revised: 05/15/2023] [Accepted: 05/17/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND The inhomogeneous distribution of collagen fiber in cartilage can substantially influence the knee kinematics. This becomes vital for understanding the mechanical response of soft tissues, and cartilage deterioration including osteoarthritis (OA). Though the conventional computational models consider geometrical heterogeneity along with fiber reinforcements in the cartilage model as material heterogeneity, the influence of fiber orientation on knee kinetics and kinematics is not fully explored. This work examines how the collagen fiber orientation in the cartilage affects the healthy (intact knee) and arthritic knee response over multiple gait activities like running and walking. METHODS A 3D finite element knee joint model is used to compute the articular cartilage response during the gait cycle. A fiber-reinforced porous hyper elastic (FRPHE) material is used to model the soft tissue. A split-line pattern is used to implement the fiber orientation in femoral and tibial cartilage. Four distinct intact cartilage models and three OA models are simulated to assess the impact of the orientation of collagen fibers in a depth wise direction. The cartilage models with fibers oriented in parallel, perpendicular, and inclined to the articular surface are investigated for multiple knee kinematics and kinetics. FINDINGS The comparison of models with fiber orientation parallel to articulating surface for walking and running gait has the highest elastic stress and fluid pressure compared with inclined and perpendicular fiber-oriented models. Also, the maximum contact pressure is observed to be higher in the case of intact models during the walking cycle than for OA models. In contrast, the maximum contact pressure is higher during running in OA models than in intact models. Additionally, parallel-oriented models produce higher maximum stresses and fluid pressure for walking and running gait than proximal-distal-oriented models. Interestingly, during the walking cycle, the maximum contact pressure with intact models is approximately three times higher than on OA models. In contrast, the OA models exhibit higher contact pressure during the running cycle. INTERPRETATION Overall, the study indicates that collagen orientation is crucial for tissue responsiveness. This investigation provides insights into the development of tailored implants.
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Affiliation(s)
- Vaishakh Raju
- Applied Solid Mechanics Laboratory, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, 575025, India
| | - Poornesh Kumar Koorata
- Applied Solid Mechanics Laboratory, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, 575025, India.
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10
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Lloyd DG, Saxby DJ, Pizzolato C, Worsey M, Diamond LE, Palipana D, Bourne M, de Sousa AC, Mannan MMN, Nasseri A, Perevoshchikova N, Maharaj J, Crossley C, Quinn A, Mulholland K, Collings T, Xia Z, Cornish B, Devaprakash D, Lenton G, Barrett RS. Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision. J Sci Med Sport 2023:S1440-2440(23)00070-1. [PMID: 37149408 DOI: 10.1016/j.jsams.2023.04.001] [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: 05/31/2022] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 05/08/2023]
Abstract
OBJECTIVES The physical demands of military service place soldiers at risk of musculoskeletal injuries and are major concerns for military capability. This paper outlines the development new training technologies to prevent and manage these injuries. DESIGN Narrative review. METHODS Technologies suitable for integration into next-generation training devices were examined. We considered the capability of technologies to target tissue level mechanics, provide appropriate real-time feedback, and their useability in-the-field. RESULTS Musculoskeletal tissues' health depends on their functional mechanical environment experienced in military activities, training and rehabilitation. These environments result from the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing joint tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and strain), which may be enabled by real-time biofeedback. Recent research has shown that these biofeedback technologies are possible by integrating a patient's personalised digital twin and wireless wearable devices. Personalised digital twins are personalised neuromusculoskeletal rigid body and finite element models that work in real-time by code optimisation and artificial intelligence. Model personalisation is crucial in obtaining physically and physiologically valid predictions. CONCLUSIONS Recent work has shown that laboratory-quality biomechanical measurements and modelling can be performed outside the laboratory with a small number of wearable sensors or computer vision methods. The next stage is to combine these technologies into well-designed easy to use products.
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Affiliation(s)
- David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia.
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Matthew Worsey
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Dinesh Palipana
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Medicine, Dentistry and Health, Griffith University, Australia
| | - Matthew Bourne
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Ana Cardoso de Sousa
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Malik Muhammad Naeem Mannan
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Nataliya Perevoshchikova
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Jayishni Maharaj
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Claire Crossley
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Alastair Quinn
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Kyle Mulholland
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Tyler Collings
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Zhengliang Xia
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Bradley Cornish
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Daniel Devaprakash
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; VALD Performance, Australia
| | | | - Rodney S Barrett
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
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Esrafilian A, Stenroth L, Mononen ME, Vartiainen P, Tanska P, Karjalainen PA, Suomalainen JS, Arokoski JPA, Saxby DJ, Lloyd DG, Korhonen RK. Towards Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline. IEEE Trans Neural Syst Rehabil Eng 2022; 30:789-802. [PMID: 35286263 DOI: 10.1109/tnsre.2022.3159685] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Tissue-level mechanics (e.g., stress and strain) are important factors governing tissue remodeling and development of knee osteoarthritis (KOA), and hence, the success of physical rehabilitation. To date, no clinically feasible analysis toolbox has been introduced and used to inform clinical decision making with subject-specific in-depth joint mechanics of different activities. Herein, we utilized a rapid state-of-the-art electromyography-assisted musculoskeletal finite element analysis toolbox with fibril-reinforced poro(visco)elastic cartilages and menisci to investigate knee mechanics in different activities. Tissue mechanical responses, believed to govern collagen damage, cell death, and fixed charge density loss of proteoglycans, were characterized within 15 patients with KOA while various daily activities and rehabilitation exercises were performed. Results showed more inter-participant variation in joint mechanics during rehabilitation exercises compared to daily activities. Accordingly, the devised workflow may be used for designing subject-specific rehabilitation protocols. Further, results showed the potential to tailor rehabilitation exercises, or assess capacity for daily activity modifications, to optimally load knee tissue, especially when mechanically-induced cartilage degeneration and adaptation are of interest.
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Esrafilian A, Stenroth L, Mononen ME, Vartiainen P, Tanska P, Karjalainen PA, Suomalainen JS, Arokoski J, Saxby DJ, Lloyd DG, Korhonen RK. An EMG-assisted muscle-force driven finite element analysis pipeline to investigate joint- and tissue-level mechanical responses in functional activities: towards a rapid assessment toolbox. IEEE Trans Biomed Eng 2022; 69:2860-2871. [PMID: 35239473 DOI: 10.1109/tbme.2022.3156018] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography- (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was verified by comparing the estimated muscle activations and joint mechanics to existing experimental data. To determine the importance of EMG-assisted MS approach, results were compared to those from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments compared to the static-optimization-based MS-FE pipeline. Importantly, the developed pipeline showed great potential as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA. The template FE model of the study is freely available here.
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Bennett KJ, Pizzolato C, Martelli S, Bahl JS, Sivakumar A, Atkins GJ, Solomon LB, Thewlis D. EMG-informed neuromusculoskeletal models accurately predict knee loading measured using instrumented implants. IEEE Trans Biomed Eng 2022; 69:2268-2275. [DOI: 10.1109/tbme.2022.3141067] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Elastic, Dynamic Viscoelastic and Model-Derived Fibril-Reinforced Poroelastic Mechanical Properties of Normal and Osteoarthritic Human Femoral Condyle Cartilage. Ann Biomed Eng 2021; 49:2622-2634. [PMID: 34341898 PMCID: PMC8455392 DOI: 10.1007/s10439-021-02838-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 07/15/2021] [Indexed: 12/27/2022]
Abstract
Osteoarthritis (OA) degrades articular cartilage and weakens its function. Modern fibril-reinforced poroelastic (FRPE) computational models can distinguish the mechanical properties of main cartilage constituents, namely collagen, proteoglycans, and fluid, thus, they can precisely characterize the complex mechanical behavior of the tissue. However, these properties are not known for human femoral condyle cartilage. Therefore, we aimed to characterize them from human subjects undergoing knee replacement and from deceased donors without known OA. Multi-step stress-relaxation measurements coupled with sample-specific finite element analyses were conducted to obtain the FRPE material properties. Samples were graded using OARSI scoring to determine the severity of histopathological cartilage degradation. The results suggest that alterations in the FRPE properties are not evident in the moderate stages of cartilage degradation (OARSI 2-3) as compared with normal tissue (OARSI 0-1). Drastic deterioration of the FRPE properties was observed in severely degraded cartilage (OARSI 4). We also found that the FRPE properties of femoral condyle cartilage related to the collagen network (initial fibril-network modulus) and proteoglycan matrix (non-fibrillar matrix modulus) were greater compared to tibial and patellar cartilage in OA. These findings may inform cartilage tissue-engineering efforts and help to improve the accuracy of cartilage representations in computational knee joint models.
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