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Shi B, Barzan M, Nasseri A, Maharaj JN, Diamond LE, Saxby DJ. Automatic generation of knee kinematic models from medical imaging. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 256:108370. [PMID: 39180912 DOI: 10.1016/j.cmpb.2024.108370] [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: 04/17/2024] [Revised: 08/07/2024] [Accepted: 08/08/2024] [Indexed: 08/27/2024]
Abstract
BACKGROUND AND OBJECTIVE Three-dimensional spatial mechanisms have been used to accurately predict passive knee kinematics, and have shown potential to be used in optimized multibody kinematic models. Such multi-body models are anatomically consistent and can accurately predict passive knee kinematics, but require extensive medical image processing and thus are not widely adopted. This study aimed to automate the generation of kinematic models of tibiofemoral (TFJ) and patellofemoral (PFJ) joints from segmented magnetic resonance imaging (MRI) and compare them against a corresponding manual pipeline. METHODS From segmented MRI of eight healthy participants (four females; aged 14.0 ± 2.6 years), geometric parameters (i.e., articular surfaces, ligament attachments) were determined both automatically and manually, and then assembled into TFJ and PFJ kinematic models to predict passive kinematics. The TFJ model was a six-link mechanism with deformable ligamentous constraints, whereas PFJ was a modified hinge. The ligament length changes through TFJ flexion were prescribed to literature strain profile. The geometric parameters were optimized to ensure physiological kinematic predictions through a Multiple Objective Particle Swarm Optimization. RESULTS Geometric parameters showed strong agreement between automatic and manual pipelines (median error of 2.8 mm for anatomical landmarks and 1.5 mm for ligament lengths). Predicted TFJ and PFJ kinematics from the two pipelines were not statistically different, except for tibial superior/inferior translation near terminal TFJ extension. The TFJ kinematics predicted from the automatic pipeline had mean errors of 3.6° and 12.4° for adduction/abduction and internal/external rotation, respectively, and <7 mm mean translational error compared to the manual pipeline. Predicted PFJ had <9° mean rotational errors and <6 mm mean translational errors. CONCLUSIONS The automatic pipeline developed and presented here can predict passive knee kinematics comparable to a manual pipeline, but removes laborious manual processing and provides a systematic approach to model creation.
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Affiliation(s)
- Beichen Shi
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia.
| | - Martina Barzan
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia
| | - Jayishni N Maharaj
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast campus Griffith University QLD 4222, Australia; School of Health Sciences and Social Work, Gold Coast campus Griffith University, Parklands Dr Southport QLD 4222, Australia
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Lloyd D. The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries. Sports Biomech 2024; 23:1284-1312. [PMID: 34496728 DOI: 10.1080/14763141.2021.1959947] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 07/20/2021] [Indexed: 01/13/2023]
Abstract
This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.
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Affiliation(s)
- David Lloyd
- School of Health Sciences and Social Work, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), in the Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Griffith University, Australia
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Pan F, Khoo K, Maso Talou GD, Song F, McGhee D, Doyle AJ, Nielsen PMF, Nash MP, Babarenda Gamage TP. Quantifying changes in shoulder orientation between the prone and supine positions from magnetic resonance imaging. Clin Biomech (Bristol, Avon) 2024; 111:106157. [PMID: 38103526 DOI: 10.1016/j.clinbiomech.2023.106157] [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: 03/31/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Predicting breast tissue motion using biomechanical models can provide navigational guidance during breast cancer treatment procedures. These models typically do not account for changes in posture between procedures. Difference in shoulder position can alter the shape of the pectoral muscles and breast. A greater understanding of the differences in the shoulder orientation between prone and supine could improve the accuracy of breast biomechanical models. METHODS 19 landmarks were placed on the sternum, clavicle, scapula, and humerus of the shoulder girdle in prone and supine breast MRIs (N = 10). These landmarks were used in an optimization framework to fit subject-specific skeletal models and compare joint angles of the shoulder girdle between these positions. FINDINGS The mean Euclidean distance between joint locations from the fitted skeletal model and the manually identified joint locations was 15.7 mm ± 2.7 mm. Significant differences were observed between prone and supine. Compared to supine position, the shoulder girdle in the prone position had the lateral end of the clavicle in more anterior translation (i.e., scapula more protracted) (P < 0.05), the scapula in more protraction (P < 0.01), the scapula in more upward rotation (associated with humerus elevation) (P < 0.05); and the humerus more elevated (P < 0.05) for both the left and right sides. INTERPRETATION Shoulder girdle orientation was found to be different between prone and supine. These differences would affect the shape of multiple pectoral muscles, which would affect breast shape and the accuracy of biomechanical models.
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Affiliation(s)
- Fangchao Pan
- Auckland Bioengineering Institute, University of Auckland, New Zealand
| | - Kejia Khoo
- Auckland Bioengineering Institute, University of Auckland, New Zealand
| | | | - Freda Song
- Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Deirdre McGhee
- Biomechanics Research Laboratory, University of Wollongong, NSW, Australia
| | - Anthony J Doyle
- Anatomy and Medical Imaging, Faculty of Medical and Health Sciences, University of Auckland, New Zealand; Te Whatu Ora, Health New Zealand, New Zealand
| | - Poul M F Nielsen
- Auckland Bioengineering Institute, University of Auckland, New Zealand; Department of Engineering Science and Biomedical Engineering, University of Auckland, New Zealand
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, New Zealand; Department of Engineering Science and Biomedical Engineering, University of Auckland, New Zealand
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Guitteny S, Aissaoui R, Dumas R. Can a Musculoskeletal Model Adapted to Knee Implant Geometry Improve Prediction of 3D Contact Forces and Moments? Ann Biomed Eng 2023:10.1007/s10439-023-03216-y. [PMID: 37101092 DOI: 10.1007/s10439-023-03216-y] [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: 01/09/2023] [Accepted: 04/19/2023] [Indexed: 04/28/2023]
Abstract
Tibiofemoral contact loads are crucial parameters in the onset and progression of osteoarthrosis. While contact loads are frequently estimated from musculoskeletal models, their customization is often limited to scaling musculoskeletal geometry or adapting muscle lines. Moreover, studies have usually focused on superior-inferior contact force without investigating three-dimensional contact loads. Using experimental data from six patients with instrumented total knee arthroplasty (TKA), this study customized a lower limb musculoskeletal model to consider the positioning and the geometry of the implant at knee level. Static optimization was performed to estimate tibiofemoral contact forces and contact moments as well as musculotendinous forces. Predictions from both a generic and a customized model were compared to the instrumented implant measurements. Both models accurately predict superior-inferior (SI) force and abduction-adduction (AA) moment. Notably, the customization improves prediction of medial-lateral (ML) force and flexion-extension (FE) moments. However, there is subject-dependent variability in the prediction of anterior-posterior (AP) force. The customized models presented here predict loads on all joint axes and in most cases improve prediction. Unexpectedly, this improvement was more limited for patients with more rotated implants, suggesting a need for further model adaptations such as muscle wrapping or redefinition of hip and ankle joint centers and axes.
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Affiliation(s)
- Sacha Guitteny
- Univ Lyon, Univ Claude Bernard Lyon 1, Univ Gustave Eiffel, LBMC UMR_T 9406, 69622, Lyon, France
| | - Rachid Aissaoui
- Laboratoire de Recherche en Imagerie Et Orthopédie (LIO), Département Génie des Systèmes, Ecole de Technologie Supérieure, Montréal, Canada
| | - Raphael Dumas
- Univ Lyon, Univ Claude Bernard Lyon 1, Univ Gustave Eiffel, LBMC UMR_T 9406, 69622, Lyon, France.
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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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Davico G, Lloyd DG, Carty CP, Killen BA, Devaprakash D, Pizzolato C. Multi-level personalization of neuromusculoskeletal models to estimate physiologically plausible knee joint contact forces in children. Biomech Model Mechanobiol 2022; 21:1873-1886. [PMID: 36229699 DOI: 10.1007/s10237-022-01626-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 08/05/2022] [Indexed: 11/02/2022]
Abstract
Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models.
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Affiliation(s)
- Giorgio Davico
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy. .,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy. .,School of Allied Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - David G Lloyd
- School of Allied Health Sciences and Social Work, Griffith University, Gold Coast, Australia.,Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia
| | - Christopher P Carty
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia.,Department of Orthopaedics, Queensland Children's Hospital, Children's Health Queensland Hospital and Health Service, Brisbane, Australia
| | - Bryce A Killen
- School of Allied Health Sciences and Social Work, Griffith University, Gold Coast, Australia.,Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - Daniel Devaprakash
- School of Allied Health Sciences and Social Work, Griffith University, Gold Coast, Australia.,Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia
| | - Claudio Pizzolato
- School of Allied Health Sciences and Social Work, Griffith University, Gold Coast, Australia.,Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia
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Shi B, Barzan M, Nasseri A, Carty CP, Lloyd DG, Davico G, Maharaj JN, Diamond LE, Saxby DJ. Development of predictive statistical shape models for paediatric lower limb bones. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 225:107002. [PMID: 35882107 DOI: 10.1016/j.cmpb.2022.107002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 06/24/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE Accurate representation of bone shape is important for subject-specific musculoskeletal models as it may influence modelling of joint kinematics, kinetics, and muscle dynamics. Statistical shape modelling is a method to estimate bone shape from minimal information, such as anatomical landmarks, and to avoid the time and cost associated with reconstructing bone shapes from comprehensive medical imaging. Statistical shape models (SSM) of lower limb bones have been developed and validated for adult populations but are not applicable to paediatric populations. This study aimed to develop SSM for paediatric lower limb bones and evaluate their reconstruction accuracy using sparse anatomical landmarks. METHODS We created three-dimensional models of 56 femurs, 29 pelves, 56 tibias, 56 fibulas, and 56 patellae through segmentation of magnetic resonance images taken from 29 typically developing children (15 females; 13 ± 3.5 years). The SSM for femur, pelvis, tibia, fibula, patella, haunch (i.e., combined femur and pelvis), and shank (i.e., combined tibia and fibula) were generated from manual segmentation of comprehensive magnetic resonance images to describe the shape variance of the cohort. We implemented a leave-one-out cross-validation method wherein SSM were used to reconstruct novel bones (i.e., those not included in SSM generation) using full- (i.e., full segmentation) and sparse- (i.e., anatomical landmarks) input, and then compared these reconstructions against bones segmented from magnetic resonance imaging. Reconstruction performance was evaluated using root mean squared errors (RMSE, mm), Jaccard index (0-1), Dice similarity coefficient (DSC) (0-1), and Hausdorff distance (mm). All results reported in this abstract are mean ± standard deviation. RESULTS Femurs, pelves, tibias, fibulas, and patellae reconstructed via SSM using full-input had RMSE between 0.89 ± 0.10 mm (patella) and 1.98 ± 0.38 mm (pelvis), Jaccard indices between 0.77 ± 0.03 (pelvis) and 0.90 ± 0.02 (tibia), DSC between 0.87 ± 0.02 (pelvis) and 0.95 ± 0.01 (tibia), and Hausdorff distances between 2.45 ± 0.57 mm (patella) and 9.01 ± 2.36 mm (pelvis). Reconstruction using sparse-input had RMSE ranging from 1.33 ± 0.61 mm (patella) to 3.60 ± 1.05 mm (pelvis), Jaccard indices ranging from 0.59 ± 0.10 (pelvis) to 0.83 ± 0.03 (tibia), DSC ranging from 0.74 ± 0.08 (pelvis) to 0.90 ± 0.02 (tibia), and Hausdorff distances ranging from 3.21 ± 1.19 mm (patella) to 12.85 ± 3.24 mm (pelvis). CONCLUSIONS The SSM of paediatric lower limb bones showed reconstruction accuracy consistent with previously developed SSM and outperformed adult-based SSM when used to reconstruct paediatric bones.
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Affiliation(s)
- Beichen Shi
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia.
| | - Martina Barzan
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia
| | - Christopher P Carty
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; Department of Orthopaedic Surgery, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia
| | - David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia; Queensland and Advanced Design and Prototyping Technologies Institute, Griffith University, Gold Coast, QLD, Australia
| | - Giorgio Davico
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy; Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Jayishni N Maharaj
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia
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Kondo T, Yagi Y, Saito H, Kanazawa T, Saito Y. [Evaluation of a Bone Coordinate System Constructed Using MR Image Composing]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2022; 78:593-598. [PMID: 35466119 DOI: 10.6009/jjrt.2022-1232] [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] [Indexed: 06/14/2023]
Abstract
PURPOSE To evaluate the accuracy of a bone coordinate system constructed using MR image composing. METHOD A femoral coordinate system constructed using image composing of MR images of a whole bovine femur was evaluated using CT images. The MR images were acquired by moving the table and were processed with 3D distortion correction and composing. To evaluate the reproducibility of the measurements, the same operator repeated the construction of the femoral coordinate system. In addition, distortions in the MR images were evaluated in comparison with those in the CT images. RESULT The center position of the femoral coordinate system constructed using the MR image composing was 1.6±0.9 mm on the X-axis, 1.5±0.8 mm on the Y-axis, and 0.2±0.3 mm on the Z-axis, and the rotation of each axis was 1° or less. The distortion of the composed MR image was about 0.3%. CONCLUSION The femoral coordinate system constructed using MR image composing had the same accuracy as a system constructed with CT images. The effect of MR image composing on the construction of the femoral coordinate system was small.
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Affiliation(s)
- Tatsuya Kondo
- School of Health Sciences, Faculty of Medicine, Niigata University
| | - Yuta Yagi
- Division of Radiology, Niigata University Medical & Dental Hospital
| | - Hiroaki Saito
- Division of Radiology, Niigata University Medical & Dental Hospital
| | - Tsutomu Kanazawa
- Division of Radiology, Niigata University Medical & Dental Hospital
| | - Yutaro Saito
- Clinical Radiology Service, Tochigi Medical Center Shimotsuga
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Barták V, Štědrý J, Hornová J, Heřt J, Tichý P, Hromádka R. Biomechanical Study Concerning the Types of Resection in Arthrodesis of First Metatarsophalangeal Joint. J Foot Ankle Surg 2021; 59:1135-1138. [PMID: 32732150 DOI: 10.1053/j.jfas.2019.01.024] [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: 02/07/2018] [Revised: 01/01/2019] [Accepted: 01/29/2019] [Indexed: 02/03/2023]
Abstract
This work concerns a biomechanical study aiming to ascertain the optimal type of joint resection when performing a joint arthrodesis. A 3-dimensional digital model of the first metatarsophalangeal joint including the entire first metatarsal bone and proximal phalanx using CT scans of the forefoot was created. Using this computer model, 4 types of resections; ball-and-socket, flat-on-flat, wedge 90°, and wedge 100° were simulated. Parameters measured using this model were the force necessary to separate the 2 fused surfaces, the surface area of the resected surfaces and the shortening of the first ray. By measuring the reactive force necessary to separate the phalanx from the first metatarsal, the 90° wedge resection was found to be the most stable, with comparable results in the case of the 100° wedge resection. Wedge resections are also more favorable when comparing the shortening of the first ray. Wedge resections, though being more technically difficult to perform prove to be the most stable for metatarsophalangeal joint-1 arthrodesis using this model.
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Affiliation(s)
- Vladislav Barták
- Surgeon, FN Motol Teaching Hospital, Department of Orthopaedic Surgery, 1st Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic.
| | - Jan Štědrý
- Surgeon, FN Motol Teaching Hospital, Department of Orthopaedic Surgery, 1st Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
| | - Jana Hornová
- Engineer, Faculty of Mechanical Engineering, Department of Mechanics, Biomechanics and Mechatronics, Czech Technical University, Prague, Czech Republic
| | - Jan Heřt
- Surgeon, FN Motol Teaching Hospital, Department of Orthopaedic Surgery, 1st Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
| | - Petr Tichý
- Engineer, Faculty of Mechanical Engineering, Department of Mechanics, Biomechanics and Mechatronics, Czech Technical University, Prague, Czech Republic
| | - Rastislav Hromádka
- Surgeon, FN Motol Teaching Hospital, Department of Orthopaedic Surgery, 1st Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic; Assisting Professor, Institute of Anatomy, 1st Faculty of Medicine, Charles University, Prague, Czech Republic
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Arredondo-Soto M, García-Murillo MA, Vidal-Lesso A, Jesús Cervantes-Sánchez J, Moreno HA. A Novel Kinematic Model of the Tibiofemoral Joint Based on a Parallel Mechanism. J Biomech Eng 2021; 143:061004. [PMID: 33537720 DOI: 10.1115/1.4050034] [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: 05/16/2020] [Indexed: 11/08/2022]
Abstract
This paper presents a complete kinematic model of the tibiofemoral joint (TFJ) based on a RRPP + 4-SPS parallel mechanism, where R, P, and S stand for revolute, prismatic, and spherical joints, respectively. The model accounts for the contact between tibia and femur, and the four major ligaments: anterior cruciate, posterior cruciate, medial collateral, and lateral collateral, with anatomical significance in their length variations. An experimental flexion passive motion task is performed, and the kinematic model is tested to determine its capability to reproduce the workspace of the motion task. In addition, an optimization process is performed to simulate prescribed ligament length variations during the motion task. The proposed kinematic model is capable to reproduce with high accuracy an experimental three-dimensional workspace, and at the same time, to simulate prescribed ligament length variation during the spatial flexion task. Prescribed ligament length variations are achieved through an optimization process of the ligament insertion points. This model can be used to improve the multibody kinematic optimization (MKO) process during gait analysis, and also in the design of rehabilitation devices as well as trajectories to accelerate the recovery of injured ligaments. The model shows potential to predict ligament length variations during different motion tasks, and can serve as a basis to develop complex models for kinetostatic and dynamic analyses without dealing with computationally expensive models.
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Affiliation(s)
- Mauricio Arredondo-Soto
- Department of Mechanical Engineering, University of Guanajuato, Salamanca, GTO 36885, Mexico
| | - Mario A García-Murillo
- Department of Mechanical Engineering, University of Guanajuato, Salamanca, GTO 36885, Mexico
| | - Agustín Vidal-Lesso
- Department of Mechanical Engineering, University of Guanajuato, Salamanca, GTO 36885, Mexico
| | | | - Hector A Moreno
- Faculty of Mechanical and Electrical Engineering, Autonomous University of Coahuila U.N., Monclova, COAH 25750, Mexico
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11
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Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries. J Biomech 2020; 116:110186. [PMID: 33515872 DOI: 10.1016/j.jbiomech.2020.110186] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 10/06/2020] [Accepted: 12/11/2020] [Indexed: 02/07/2023]
Abstract
The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.
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12
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Automated creation and tuning of personalised muscle paths for OpenSim musculoskeletal models of the knee joint. Biomech Model Mechanobiol 2020; 20:521-533. [PMID: 33098487 DOI: 10.1007/s10237-020-01398-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 10/15/2020] [Indexed: 12/11/2022]
Abstract
Computational modelling is an invaluable tool for investigating features of human locomotion and motor control which cannot be measured except through invasive techniques. Recent research has focussed on creating personalised musculoskeletal models using population-based morphing or directly from medical imaging. Although progress has been made, robust definition of two critical model parameters remains challenging: (1) complete tibiofemoral (TF) and patellofemoral (PF) joint motions, and (2) muscle tendon unit (MTU) pathways and kinematics (i.e. lengths and moment arms). The aim of this study was to develop an automated framework, using population-based morphing approaches to create personalised musculoskeletal models, consisting of personalised bone geometries, TF and PF joint mechanisms, and MTU pathways and kinematics. Informed from medical imaging, personalised rigid body TF and PF joint mechanisms were created. Using atlas- and optimisation-based methods, personalised MTU pathways and kinematics were created with the aim of preventing MTU penetration into bones and achieving smooth MTU kinematics that follow patterns from existing literature. This framework was integrated into the Musculoskeletal Atlas Project Client software package to create and optimise models for 6 participants with incrementally increasing levels of personalisation with the aim of improving MTU kinematics and pathways. Three comparisons were made: (1) non-optimised (Model 1) and optimised models (Model 3) with generic joint mechanisms; (2) non-optimised (Model 2) and optimised models (Model 4) with personalised joint mechanisms; and (3) both optimised models (Model 3 and 4). Following optimisation, improvements were consistently shown in pattern similarity to cadaveric data in comparison (1) and (2). For comparison (3), a number of comparisons showed no significant difference between the two compared models. Importantly, optimisation did not produce statistically significantly worse results in any case.
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13
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Machine learning methods to support personalized neuromusculoskeletal modelling. Biomech Model Mechanobiol 2020; 19:1169-1185. [DOI: 10.1007/s10237-020-01367-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 07/08/2020] [Indexed: 12/19/2022]
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14
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The relationship between tibiofemoral geometry and musculoskeletal function during normal activity. Gait Posture 2020; 80:374-382. [PMID: 32622207 DOI: 10.1016/j.gaitpost.2020.06.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 06/09/2020] [Accepted: 06/16/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND The effect of tibiofemoral geometry on musculoskeletal function is important to movement biomechanics. RESEARCH QUESTION We hypothesised that tibiofemoral geometry determines tibiofemoral motion and musculoskeletal function. We then aimed at 1) modelling tibiofemoral motion during normal activity as a function of tibiofemoral geometry in healthy adults; and 2) quantifying the effect of tibiofemoral geometry on musculoskeletal function. METHODS We used motion data for six activity types and CT images of the knee from 12 healthy adults. Geometrical variation of the tibia and femoral articular surfaces were measured in the CT images. The geometry-based tibiofemoral motion was calculated by fitting a parallel mechanism to geometrical variation in the cohort. Matched musculoskeletal models embedding the geometry-based tibiofemoral joint motion and a common generic tibiofemoral motion of reference were generated and used to calculate joint angles, net joint moments, muscle and joint forces for the six activities analysed. The tibiofemoral model was validated against bi-planar fluoroscopy measurements for walking for all the six planes of motion. The effect of tibiofemoral geometry on musculoskeletal function was the difference between the geometry-based model and the model of reference. RESULTS The geometry-based tibiofemoral motion described the pattern and the variation during walking for all six motion components, except the pattern of anterior tibial translation. Tibiofemoral geometry had moderate effect on cohort-averages of musculoskeletal function (R2 = 0.60-1), although its effect was high in specific instances of the model, outputs and activities analysed, reaching 2.94 BW for the ankle reaction force during stair descent. In conclusion, tibiofemoral geometry is a major determinant of tibiofemoral motion during walking. SIGNIFICANCE Geometrical variations of the tibiofemoral joint are important for studying musculoskeletal function during normal activity in specific individuals but not for studying cohort averages of musculoskeletal function. This finding expands current knowledge of movement biomechanics.
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An Anatomical-Based Subject-Specific Model of In-Vivo Knee Joint 3D Kinematics From Medical Imaging. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10062100] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Biomechanical models of the knee joint allow the development of accurate procedures as well as novel devices to restore the joint natural motion. They are also used within musculoskeletal models to perform clinical gait analysis on patients. Among relevant knee models in the literature, the anatomy-based spatial parallel mechanisms represent the joint motion using rigid links for the ligaments’ isometric fibres and point contacts for the articular surfaces. To customize analyses, therapies and devices, there is the need to define subject-specific models, but relevant procedures and their accuracy are still questioned. A procedure is here proposed and validated to define a customized knee model based on a spatial parallel mechanism. Computed tomography, magnetic resonance and 3D-video-fluoroscopy were performed on a healthy volunteer to define the personalized model geometry. The model was then validated by comparing the measured and the replicated joint motion. The model showed mean absolute difference and standard deviations in translations and rotations, respectively of 0.98 ± 0.40 mm and 0.68 ± 0.29 ° for the tibia–femur motion, and of 0.77 ± 0.15 mm and 2.09 ± 0.69 ° for the patella–femur motion. These results show that accurate personalized spatial models of knee kinematics can be obtained from in-vivo imaging.
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16
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Increasing level of neuromusculoskeletal model personalisation to investigate joint contact forces in cerebral palsy: A twin case study. Clin Biomech (Bristol, Avon) 2020; 72:141-149. [PMID: 31877532 DOI: 10.1016/j.clinbiomech.2019.12.011] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 11/15/2019] [Accepted: 12/16/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Cerebral palsy is a complex neuromuscular disorder that affects the sufferers in multiple different ways. Neuromusculoskeletal models are promising tools that can be used to plan patient-specific treatments for cerebral palsy. However, current neuromusculoskeletal models are typically scaled from generic adult templates that poorly represent paediatric populations. Furthermore, muscle activations are commonly computed via optimisation methods, which may not reproduce co-contraction observed in cerebral palsy. Alternatively, calibrated EMG-informed approaches within OpenSim can capture pathology-related muscle activation abnormalities, possibly enabling more feasible estimations of muscle and joint contact forces. METHODS Two identical twin brothers, aged 13, one with unilateral cerebral palsy and the other typically developing, were enrolled in the study. Four neuromusculoskeletal models with increasing subject-specificity were built in OpenSim and CEINMS combining literature findings, experimental motion capture, EMG and MR data for both participants. The physiological and biomechanical validity of each model was assessed by quantifying its ability to track experimental joint moments and muscle excitations. FINDINGS All developed models accurately tracked external joint moments; however EMG-informed models better tracked muscle excitations compared to neural solutions generated by static optimisation. Calibrating muscle-tendon unit parameters with EMG data allowed for more physiologically plausible joint contact forces estimates. Further scaling the maximal isometric force of muscles with MR-derived muscle volumes did not affect model predictions. INTERPRETATION Given their ability to identify atypical joint contact forces profiles and accurately reproduce experimental data, calibrated EMG-informed models should be preferred over generic models using optimisation methods in informing the management of cerebral palsy.
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Davico G, Pizzolato C, Killen BA, Barzan M, Suwarganda EK, Lloyd DG, Carty CP. Best methods and data to reconstruct paediatric lower limb bones for musculoskeletal modelling. Biomech Model Mechanobiol 2019; 19:1225-1238. [DOI: 10.1007/s10237-019-01245-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Accepted: 10/25/2019] [Indexed: 11/28/2022]
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18
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Dzialo CM, Pedersen PH, Jensen KK, de Zee M, Andersen MS. Evaluation of predicted patellofemoral joint kinematics with a moving-axis joint model. Med Eng Phys 2019; 73:85-91. [PMID: 31474509 DOI: 10.1016/j.medengphy.2019.08.001] [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: 12/20/2018] [Revised: 07/27/2019] [Accepted: 08/15/2019] [Indexed: 10/26/2022]
Abstract
The main objectives of this study were to expand the moving-axis joint model concept to the patellofemoral joint and evaluate the patellar motion against experimental patellofemoral kinematics. The experimental data was obtained through 2D-to-3D bone reconstruction of EOS images and segmented MRI data utilizing an iterative closest point optimization technique. Six knee model variations were developed using the AnyBody Modeling System and subject-specific bone geometries. These models consisted of various combinations of tibiofemoral (hinge, moving-axis, and interpolated) and patellofemoral (hinge and moving-axis) joint types. The newly introduced interpolated tibiofemoral joint is calibrated from the five EOS quasi-static lunge positions. The patellofemoral axis of the hinge model was defined by performing surface fits to the patellofemoral contact area; and the moving-axis model was defined based upon the position of the patellofemoral joint at 0° and 90° tibiofemoral-flexion. In between these angles, the patellofemoral axis moved linearly as a function of tibiofemoral-flexion, while outside these angles, the axis remained fixed. When using a moving-axis tibiofemoral joint, a hinge patellofemoral joint offers (-5.12 ± 1.23 mm, 5.81 ± 0.97 mm, 14.98 ± 2.30°, -4.35 ± 1.95°) mean differences (compared to EOS) while a moving-axis patellofemoral model provides (-2.69 ± 1.04 mm, 1.13 ± 0.80 mm, 12.63 ± 2.03°, 1.74 ± 1.46°) in terms of lateral-shift, superior translation, patellofemoral-flexion, and patellar-rotation, respectively. Furthermore, the model predictive capabilities increased as a direct result of adding more calibrated positions to the tibiofemoral model (hinge-1, moving-axis-2, and interpolated-5). Overall, a novel subject-specific moving-axis patellofemoral model has been established; that produces realistic patellar motion and is computationally fast enough for clinical applications.
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Affiliation(s)
- C M Dzialo
- AnyBody Technology, A/S Niels Jernes Vej 10, DK 9220 Aalborg, Denmark; Department of Materials and Production, Aalborg University, Fibigerstræde 16, DK-9220 Aalborg, Denmark.
| | - P H Pedersen
- Department of Orthopedic Surgery, Aalborg University Hospital, Hobrovej 18-22, DK-9000 Aalborg, Denmark
| | - K K Jensen
- Department of Radiology, Aalborg University Hospital, Hobrovej 18-22, DK-9000 Aalborg, Denmark
| | - M de Zee
- Department of Health Science and Technology, Sport Sciences, Aalborg University, Fredrik Bajers Vej 7D, DK-9220 Aalborg, Denmark
| | - M S Andersen
- Department of Materials and Production, Aalborg University, Fibigerstræde 16, DK-9220 Aalborg, Denmark
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Barzan M, Modenese L, Carty CP, Maine S, Stockton CA, Sancisi N, Lewis A, Grant J, Lloyd DG, Brito da Luz S. Development and validation of subject-specific pediatric multibody knee kinematic models with ligamentous constraints. J Biomech 2019; 93:194-203. [DOI: 10.1016/j.jbiomech.2019.07.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 05/16/2019] [Accepted: 07/02/2019] [Indexed: 01/08/2023]
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20
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Jacquelin E, Brizard D, Dumas R. A screening method to analyse the sensitivity of a lower limb multibody kinematic model. Comput Methods Biomech Biomed Engin 2019; 22:925-935. [PMID: 30999767 DOI: 10.1080/10255842.2019.1604950] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The study presents a screening method used to identify the influential parameters of a lower limb model including ligaments, at low numerical cost. Concerning multibody kinematics optimisation, the ligament parameters (isometric length) were found the most influential ones in a previous study. The screening method tested if they remain influential with minimised length variations. The most important parameters for tibiofemoral kinematics were the skin markers, segment lengths and joint parameters, including two ligaments. This was confirmed by a quantitative sensitivity analysis. The screening method has the potential to be used as a stand-alone procedure for a sensitivity analysis.
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Affiliation(s)
- Eric Jacquelin
- a Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406 , Lyon , France
| | - Denis Brizard
- a Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406 , Lyon , France
| | - Raphael Dumas
- a Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406 , Lyon , France
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21
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Suwarganda EK, Diamond LE, Lloyd DG, Besier TF, Zhang J, Killen BA, Savage TN, Saxby DJ. Minimal medical imaging can accurately reconstruct geometric bone models for musculoskeletal models. PLoS One 2019; 14:e0205628. [PMID: 30742643 PMCID: PMC6370181 DOI: 10.1371/journal.pone.0205628] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 01/18/2019] [Indexed: 12/12/2022] Open
Abstract
Accurate representation of subject-specific bone anatomy in lower-limb musculoskeletal models is important for human movement analyses and simulations. Mathematical methods can reconstruct geometric bone models using incomplete imaging of bone by morphing bone model templates, but the validity of these methods has not been fully explored. The purpose of this study was to determine the minimal imaging requirements for accurate reconstruction of geometric bone models. Complete geometric pelvis and femur models of 14 healthy adults were reconstructed from magnetic resonance imaging through segmentation. From each complete bone segmentation, three sets of incomplete segmentations (set 1 being the most incomplete) were created to test the effect of imaging incompleteness on reconstruction accuracy. Geometric bone models were reconstructed from complete sets, three incomplete sets, and two motion capture-based methods. Reconstructions from (in)complete sets were generated using statistical shape modelling, followed by host-mesh and local-mesh fitting through the Musculoskeletal Atlas Project Client. Reconstructions from motion capture-based methods used positional data from skin surface markers placed atop anatomic landmarks and estimated joint centre locations as target points for statistical shape modelling and linear scaling. Accuracy was evaluated with distance error (mm) and overlapping volume similarity (%) between complete bone segmentation and reconstructed bone models, and statistically compared using a repeated measure analysis of variance (p<0.05). Motion capture-based methods produced significantly higher distance error than reconstructions from (in)complete sets. Pelvis volume similarity reduced significantly with the level of incompleteness: complete set (92.70±1.92%), set 3 (85.41±1.99%), set 2 (81.22±3.03%), set 1 (62.30±6.17%), motion capture-based statistical shape modelling (41.18±9.54%), and motion capture-based linear scaling (26.80±7.19%). A similar trend was observed for femur volume similarity. Results indicate that imaging two relevant bone regions produces overlapping volume similarity >80% compared to complete segmented bone models, and improve analyses and simulation over current standard practice of linear scaling musculoskeletal models.
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Affiliation(s)
- Edin K. Suwarganda
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - Laura E. Diamond
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - David G. Lloyd
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - Thor F. Besier
- Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, Auckland, New Zealand
| | - Ju Zhang
- Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, Auckland, New Zealand
| | - Bryce A. Killen
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
| | - Trevor N. Savage
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
- Department of Rheumatology, Kolling Institute of Medical Research, Institute of Bone and Joint Research, University of Sydney, Sydney, New South Wales, Australia
| | - David J. Saxby
- School of Allied Health Sciences, Griffith University, Gold Coast, Queensland, Australia
- Gold Coast Orthopaedic Research, Engineering and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
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A calibrated EMG-informed neuromusculoskeletal model can appropriately account for muscle co-contraction in the estimation of hip joint contact forces in people with hip osteoarthritis. J Biomech 2019; 83:134-142. [DOI: 10.1016/j.jbiomech.2018.11.042] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 11/13/2018] [Accepted: 11/23/2018] [Indexed: 11/20/2022]
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Subject-specific calibration of neuromuscular parameters enables neuromusculoskeletal models to estimate physiologically plausible hip joint contact forces in healthy adults. J Biomech 2018; 80:111-120. [DOI: 10.1016/j.jbiomech.2018.08.023] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Revised: 08/15/2018] [Accepted: 08/22/2018] [Indexed: 12/29/2022]
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Modenese L, Montefiori E, Wang A, Wesarg S, Viceconti M, Mazzà C. Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling. J Biomech 2018; 73:108-118. [DOI: 10.1016/j.jbiomech.2018.03.039] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2017] [Revised: 02/09/2018] [Accepted: 03/21/2018] [Indexed: 11/24/2022]
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25
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Development and validation of a subject-specific moving-axis tibiofemoral joint model using MRI and EOS imaging during a quasi-static lunge. J Biomech 2018; 72:71-80. [DOI: 10.1016/j.jbiomech.2018.02.032] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 02/21/2018] [Accepted: 02/23/2018] [Indexed: 11/18/2022]
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26
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Zeighami A, Aissaoui R, Dumas R. Knee medial and lateral contact forces in a musculoskeletal model with subject-specific contact point trajectories. J Biomech 2018; 69:138-145. [PMID: 29397108 DOI: 10.1016/j.jbiomech.2018.01.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2017] [Revised: 01/08/2018] [Accepted: 01/14/2018] [Indexed: 01/27/2023]
Abstract
Contact point (CP) trajectory is a crucial parameter in estimating medial/lateral tibio-femoral contact forces from the musculoskeletal (MSK) models. The objective of the present study was to develop a method to incorporate the subject-specific CP trajectories into the MSK model. Ten healthy subjects performed 45 s treadmill gait trials. The subject-specific CP trajectories were constructed on the tibia and femur as a function of extension-flexion using low-dose bi-plane X-ray images during a quasi-static squat. At each extension-flexion position, the tibia and femur CPs were superimposed in the three directions on the medial side, and in the anterior-posterior and proximal-distal directions on the lateral side to form the five kinematic constraints of the knee joint. The Lagrange multipliers associated to these constraints directly yielded the medial/lateral contact forces. The results from the personalized CP trajectory model were compared against the linear CP trajectory and sphere-on-plane CP trajectory models which were adapted from the commonly used MSK models. Changing the CP trajectory had a remarkable impact on the knee kinematics and changed the medial and lateral contact forces by 1.03 BW and 0.65 BW respectively, in certain subjects. The direction and magnitude of the medial/lateral contact force were highly variable among the subjects and the medial-lateral shift of the CPs alone could not determine the increase/decrease pattern of the contact forces. The suggested kinematic constraints are adaptable to the CP trajectories derived from a variety of joint models and those experimentally measured from the 3D imaging techniques.
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Affiliation(s)
- A Zeighami
- Laboratoire de Recherche en Imagerie et Orthopédie (LIO), École de Technologie Supérieure (ÉTS), Center de Recherche du CHUM, Montréal, Québec, Canada.
| | - R Aissaoui
- Laboratoire de Recherche en Imagerie et Orthopédie (LIO), École de Technologie Supérieure (ÉTS), Center de Recherche du CHUM, Montréal, Québec, Canada.
| | - R Dumas
- Université Lyon, Université Claude Bernard Lyon 1, IFSTTAR, UMR_T9406, LBMC, F69622 Lyon, France.
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27
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Pizzolato C, Lloyd DG, Barrett RS, Cook JL, Zheng MH, Besier TF, Saxby DJ. Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation. Front Comput Neurosci 2017; 11:96. [PMID: 29093676 PMCID: PMC5651250 DOI: 10.3389/fncom.2017.00096] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 10/04/2017] [Indexed: 12/20/2022] Open
Abstract
Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading.
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Affiliation(s)
- Claudio Pizzolato
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia
- Gold Coast Orthopaedic Research and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - David G. Lloyd
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia
- Gold Coast Orthopaedic Research and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Rod S. Barrett
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia
- Gold Coast Orthopaedic Research and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Jill L. Cook
- La Trobe Sport and Exercise Medicine Research Centre, La Trobe University, Melbourne, VIC, Australia
| | - Ming H. Zheng
- Centre for Orthopaedic Translational Research, School of Surgery, University of Western Australia, Nedlands, WA, Australia
| | - Thor F. Besier
- Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - David J. Saxby
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia
- Gold Coast Orthopaedic Research and Education Alliance, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
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Pizzolato C, Reggiani M, Saxby DJ, Ceseracciu E, Modenese L, Lloyd DG. Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces. IEEE Trans Neural Syst Rehabil Eng 2017; 25:1612-1621. [PMID: 28436878 DOI: 10.1109/tnsre.2017.2683488] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.
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