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Dastgerdi AK, Esrafilian A, Carty CP, Nasseri A, Barzan M, Korhonen RK, Astori I, Hall W, Saxby DJ. Surgical parameters influence paediatric knee kinematics and cartilage stresses in anterior cruciate ligament reconstruction: Navigating subject-specific variability using neuromusculoskeletal-finite element modelling analysis. Knee Surg Sports Traumatol Arthrosc 2024. [PMID: 39105430 DOI: 10.1002/ksa.12413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 06/13/2024] [Accepted: 07/17/2024] [Indexed: 08/07/2024]
Abstract
PURPOSE Anterior cruciate ligament (ACL) rupture is increasingly common in paediatric and adolescent populations, typically requiring surgical ACL reconstruction (ACLR) to restore knee stability. However, ACLR substantially alters knee biomechanics (e.g., motion and tissue mechanics) placing the patient at elevated risk of early-onset knee osteoarthritis. METHODS This study employed a linked neuromusculoskeletal (NMSK)-finite element (FE) model to determine effects of four critical ACLR surgical parameters (graft type, size, location and pre-tension) on tibial articular cartilage stresses in three paediatric knees of different sizes during walking. Optimal surgical combinations were defined by minimal kinematic and tibial cartilage stress deviations in comparison to a corresponding intact healthy knee, with substantial deviations defined by normalized root mean square error (nRMSE) > 10%. RESULTS Results showed unique trends of principal stress deviations across knee sizes with small knee showing least deviation from intact knee, followed by large- and medium-sized knees. The nRMSE values for cartilage stresses displayed notable variability across different knees. Surgical combination yielding the highest nRMSE in comparison to the one with lowest nRMSE resulted in an increase of maximum principal stress on the medial tibial cartilage by 18.0%, 6.0% and 1.2% for small, medium and large knees, respectively. Similarly, there was an increase of maximum principal stress on lateral tibial cartilage by 11.2%, 4.1% and 12.7% for small, medium and large knees, respectively. Knee phenotype and NMSK factors contributed to deviations in knee kinematics and tibial cartilage stresses. Although optimal surgical configurations were found for each knee size, no generalizable trends emerged emphasizing the subject-specific nature of the knee and neuromuscular system. CONCLUSION Study findings underscore subject-specific complexities in ACLR biomechanics, necessitating personalized surgical planning for effective restoration of native motion and tissue mechanics. Future research should expand investigations to include a broader spectrum of subject-specific factors to advance personalized surgical planning. LEVEL OF EVIDENCE Level III.
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Affiliation(s)
- Ayda Karimi Dastgerdi
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Gold Coast, Queensland, Australia
| | - Amir Esrafilian
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Christopher P Carty
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Gold Coast, Queensland, Australia
- Department of Orthopedics, Children's Health Queensland Hospital and Health Service, Brisbane, Queensland, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Gold Coast, Queensland, Australia
| | - Martina Barzan
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Gold Coast, Queensland, 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, Queensland, Australia
| | - Wayne Hall
- School of Engineering and Built Environment, Mechanical Engineering and Industrial Design, Griffith University, Gold Coast, Queensland, Australia
| | - David John Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Gold Coast, Queensland, Australia
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Ding Y, Zhang H, Jiang Q, Li T, Liu J, Lu Z, Yang G, Cui H, Lou F, Dong Z, Shuai M, Ding Y. Finite element analysis of endoscopic cross-overtop decompression for single-segment lumbar spinal stenosis based on real clinical cases. Front Bioeng Biotechnol 2024; 12:1393005. [PMID: 38903190 PMCID: PMC11186988 DOI: 10.3389/fbioe.2024.1393005] [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: 02/28/2024] [Accepted: 05/21/2024] [Indexed: 06/22/2024] Open
Abstract
Introduction: For severe degenerative lumbar spinal stenosis (DLSS), the conventional percutaneous endoscopic translaminar decompression (PEID) has some limitations. The modified PEID, Cross-Overtop decompression, ensures sufficient decompression without excessive damage to the facet joints and posterior complex integrity. Objectives: To evaluate the biomechanical properties of Cross-Overtop and provide practical case validation for final decision-making in severe DLSS treatment. Methods: A finite element (FE) model of L4-L5 (M0) was established, and the validity was verified against prior studies. Endo-ULBD (M1), Endo-LOVE (M2), and Cross-Overtop (M3) models were derived from M0 using the experimental protocol. L4-L5 segments in each model were evaluated for the range of motion (ROM) and disc Von Mises stress extremum. The real clinical Cross-Overtop model was constructed based on clinical CT images, disregarding paraspinal muscle influence. Subsequent validation using actual FE analysis results enhances the credibility of the preceding virtual FE analysis. Results: Compared with M0, ROM in surgical models were less than 10°, and the growth rate of ROM ranged from 0.10% to 11.56%, while those of disc stress ranged from 0% to 15.75%. Compared with preoperative, the growth rate of ROM and disc stress were 2.66%-11.38% and 1.38%-9.51%, respectively. The ROM values in both virtual and actual models were less than 10°, verifying the affected segment stability after Cross-Overtop decompression. Conclusion: Cross-Overtop, designed for fully expanding the central canal and contralateral recess, maximizing the integrity of the facet joints and posterior complex, does no significant effect on the affected segmental biomechanics and can be recommended as an effective endoscopic treatment for severe DLSS.
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Affiliation(s)
- Yiwei Ding
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Hanshuo Zhang
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
- Navy Clinical College, Anhui Medical University, Hefei, Anhui, China
| | - Qiang Jiang
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
- Chinese PLA Medical School, Beijing, China
| | - Tusheng Li
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
| | - Jiang Liu
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
- Navy Clinical College, Anhui Medical University, Hefei, Anhui, China
| | - Zhengcao Lu
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
| | - Guangnan Yang
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
- Department of Orthopedics, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Hongpeng Cui
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
| | - Fengtong Lou
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
| | - Zhifeng Dong
- Mechanical and Electronic Engineering Department, China University of Mining and Technology, Beijing, China
| | - Mei Shuai
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Yu Ding
- Orthopedics, TCM Senior Department, The Sixth Medical Center of PLA General Hospital, Beijing, China
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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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4
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Dastgerdi AK, Esrafilian A, Carty CP, Nasseri A, Barzan M, Korhonen RK, Astori I, Hall W, Saxby DJ. Sensitivity analysis of paediatric knee kinematics to the graft surgical parameters during anterior cruciate ligament reconstruction: A sequentially linked neuromusculoskeletal-finite element analysis. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 248:108132. [PMID: 38503071 DOI: 10.1016/j.cmpb.2024.108132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/26/2024] [Accepted: 03/08/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND AND OBJECTIVE Incidence of paediatric anterior cruciate ligament (ACL) rupture has increased substantially over recent decades. Following ACL rupture, ACL reconstruction (ACLR) surgery is typically performed to restore passive knee stability. This surgery involves replacing the failed ACL with a graft, however, surgeons must select from range of surgical parameters (e.g., type, size, insertion, and pre-tension) with no robust evidence guiding these decisions. This study presents a systemmatic computational approach to study effects of surgical parameter variation on kinematics of paediatric knees. METHODS This study used sequentially-linked neuromusculoskeletal (NMSK) finite element (FE) models of three paediatric knees to estimate the: (i) sensitivity of post-operative knee kinematics to four surgical parameters (type, size, insertion, and pre-tension) through multi-input multi-output sensitivity analysis; (ii) influence of motion and loading conditions throughout stance phase of walking gait on sensitivity indices; and (iii) influence of subject-specific anatomy (i.e., knee size) on sensitivivty indices. A previously validated FE model of the intact knee for each subject served as a reference against which ACLR knee kinematics were compared. RESULTS Sensitivity analyses revealed significant influences of surgical parameters on ACLR knee kinematics, albeit without discernible trend favouring any one parameter. Graft size and pre-tension were primary drivers of variation in knee translations and rotations, however, their effects fluctuated across stance indicating motion and loading conditions affect system sensitivity to surgical parameters. Importantly, the sensitivity of knee kinematics to surgical parameter varied across subjects, indicating geometry (i.e., knee size) influenced system sensitivity. Notably, alterations in graft parameters yielded substantial effects on kinematics (normalized root-mean-square-error > 10 %) compared to intact knee models, indicating surgical parameters vary post-operative knee kinematics. CONCLUSIONS Overall, this initial study highlights the importance of surgical parameter selection on post-operative kinematics in the paediatric ACLR knee, and provides evidence of the need for personalized surgical planning to ultimately enhance patient outcomes.
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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, 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
| | - 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, 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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5
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Diamond LE, Grant T, Uhlrich SD. Osteoarthritis year in review 2023: Biomechanics. Osteoarthritis Cartilage 2024; 32:138-147. [PMID: 38043858 DOI: 10.1016/j.joca.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 12/05/2023]
Abstract
Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.
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Affiliation(s)
- Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Tamara Grant
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Scott D Uhlrich
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
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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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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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8
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Liu H, Gong H, Chen P, Zhang L, Cen H, Fan Y. Biomechanical effects of typical lower limb movements of Chen-style Tai Chi on knee joint. Med Biol Eng Comput 2023; 61:3087-3101. [PMID: 37624535 DOI: 10.1007/s11517-023-02906-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 08/09/2023] [Indexed: 08/26/2023]
Abstract
The load and stress distribution on cartilage and meniscus of the knee joint in typical lower limb movements of Chen-style Tai Chi (TC) and deep squat (DS) were analyzed using finite element (FE) analysis. The loadings for this analysis consisted of muscle forces and ground reaction force (GRF), which were calculated through the inverse dynamic approach based on kinematics and force plate measurements obtained from motion capture experiments. Thirteen experienced practitioners performed four typical TC movements, namely, single whip (SW), brush knee and twist step (BKTS), stretch down (SD), and part the wild horse's mane (PWHM), which exhibit lower posture and greater lower limb force compared to other TC styles. The results indicated that TC required greater lower limb muscle strength than DS, resulting in greater knee joint forces. The stress on the medial cartilage in SW and BKTS fell within a range conductive to maintaining the balance between anabolism and catabolism of cartilage matrix. This was due to the fact that SW and BKTS reduce the medial to total tibiofemoral contact force ratios through knee abduction, which may effectively alleviate mild medial knee osteoarthritis (KOA). However, the greater medial contact force ratios observed in SD and PWHM resulted in great contact stresses that may aggravate the pain of patients with KOA. To mitigate these effects, practitioners should consider elevating their postures appropriately to reduce knee flexion angles, especially during the single-leg support phase. This adjustment can decrease the required muscle strength, load and stress on the knee joint.
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Affiliation(s)
- Haibo Liu
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China
| | - He Gong
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China.
| | - Peng Chen
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China
| | - Le Zhang
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China
| | - Haipeng Cen
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China
| | - Yubo Fan
- Key Laboratory for Biomechanics and Mechanobiology (Beihang University) of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, No.37, Xueyuan Road, Haidian District, Beijing, 100083, People's Republic of China
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9
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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: 3] [Impact Index Per Article: 3.0] [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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Saxby DJ, Pizzolato C, Diamond LE. A Digital Twin Framework for Precision Neuromusculoskeletal Health Care: Extension Upon Industrial Standards. J Appl Biomech 2023; 39:347-354. [PMID: 37567581 DOI: 10.1123/jab.2023-0114] [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: 04/29/2023] [Revised: 07/10/2023] [Accepted: 07/17/2023] [Indexed: 08/13/2023]
Abstract
There is a powerful global trend toward deeper integration of digital twins into modern life driven by Industry 4.0 and 5.0. Defense, agriculture, engineering, manufacturing, and urban planning sectors have thoroughly incorporated digital twins to great benefit across their respective product lifecycles. Despite clear benefits, a digital twin framework for health and medical sectors is yet to emerge. This paper proposes a digital twin framework for precision neuromusculoskeletal health care. We build upon the International Standards Organization framework for digital twins for manufacturing by presenting best available computational models within a digital twin framework for clinical application. We map a use case for modeling Achilles tendon mechanobiology, highlighting how current modeling practices align with our proposed digital twin framework. Similarly, we map a use case for advanced neurorehabilitation technology, highlighting the role of a digital twin in control of systems where human and machine are interfaced. Future work must now focus on creating an informatic representation to govern how digital data are passed to, from, and within the digital twin, as well as specific standards to declare which measurement systems and modeling methods are acceptable to move toward widespread use of the digital twin framework for precision neuromusculoskeletal health care.
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Affiliation(s)
- David J Saxby
- Giffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Parklands,Australia
- School of Health Sciences and Social Work, Griffith University, Parklands,Australia
| | - Claudio Pizzolato
- Giffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Parklands,Australia
- School of Health Sciences and Social Work, Griffith University, Parklands,Australia
| | - Laura E Diamond
- Giffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Parklands,Australia
- School of Health Sciences and Social Work, Griffith University, Parklands,Australia
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11
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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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Wang S, Hase K, Funato T. Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb. Front Bioeng Biotechnol 2023; 11:1130219. [PMID: 37533695 PMCID: PMC10392837 DOI: 10.3389/fbioe.2023.1130219] [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: 12/23/2022] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.
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Affiliation(s)
- Sentong Wang
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
- Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
| | - Kazunori Hase
- Faculty of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
| | - Tetsuro Funato
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
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13
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Kothurkar R, Lekurwale R, Gad M, Rathod CM. Finite element analysis of a healthy knee joint at deep squatting for the study of tibiofemoral and patellofemoral contact. J Orthop 2023; 40:7-16. [PMID: 37143926 PMCID: PMC10151221 DOI: 10.1016/j.jor.2023.04.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/20/2023] [Accepted: 04/20/2023] [Indexed: 05/06/2023] Open
Abstract
Background In non-western countries, deep squatting is a daily activity, and prolonged deep squatting is common among occupational squatters. Household tasks, taking a bath, socializing, using toilets, and performing religious acts are among the activities frequently carried out while squatting by the Asian population. High knee loading is responsible for a knee injury and osteoarthritis. Finite element analysis is an effective tool to determine stresses on the knee joint. Methods Magnetic Resonance Imaging (MRI) and Computed Tomographic (CT) images were acquired of one adult without knee injuries. The CT images were acquired at the fully extended knee and one more set of images was acquired with the knee at a deeply flexed knee position. The MRI was acquired with the fully extended knee. 3-Dimensional models of bones were created using CT and soft tissue using MRI with the help of 3D Slicer software. Kinematics and finite element analysis of the knee was performed for standing and deep squatting posture using Ansys Workbench 2022. Results High peak stresses were observed at deep squatting compared to standing along with the reduction in the contact area. Peak von Mises stresses on femoral cartilage, tibial cartilage, patellar cartilage, and meniscus were increased from 3.3 MPa to 19.9 MPa, 2.9 MPa to 12.4 MPa, 1.5 MPa to 16.7 MPa and 15.8 MPa to 32.8 MPa respectively during deep squatting. Posterior translation of 7.01 mm, and 12.58 mm was observed for medial and lateral femoral condyle respectively from full extension to 153° knee flexion. Conclusions Increased stresses in the knee joint at deep squat posture may cause cartilage damage. A sustained deep squat posture should be avoided for healthy knee joints. More posterior translations of the medial femoral condyle at higher knee flexion angle warrant further investigation.
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Affiliation(s)
- Rohan Kothurkar
- Department of Mechanical Engineering, K. J. Somaiya College of Engineering, Mumbai, India
| | - Ramesh Lekurwale
- Department of Mechanical Engineering, K. J. Somaiya College of Engineering, Mumbai, India
| | - Mayuri Gad
- St. Xavier's Gait Lab, Xavier Institute of Engineering, Mumbai, India
| | - Chasanal M. Rathod
- St. Xavier's Gait Lab, Xavier Institute of Engineering, Mumbai, India
- Department of Orthopaedics, SRCC Children's Hospital, Haji Ali, Mumbai, India
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14
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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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15
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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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