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Fernandez J, Shim V, Schneider M, Choisne J, Handsfield G, Yeung T, Zhang J, Hunter P, Besier T. A Narrative Review of Personalized Musculoskeletal Modeling Using the Physiome and Musculoskeletal Atlas Projects. J Appl Biomech 2023; 39:304-317. [PMID: 37607721 DOI: 10.1123/jab.2023-0079] [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: 03/28/2023] [Revised: 07/02/2023] [Accepted: 07/24/2023] [Indexed: 08/24/2023]
Abstract
In this narrative review, we explore developments in the field of computational musculoskeletal model personalization using the Physiome and Musculoskeletal Atlas Projects. Model geometry personalization; statistical shape modeling; and its impact on segmentation, classification, and model creation are explored. Examples include the trapeziometacarpal and tibiofemoral joints, Achilles tendon, gastrocnemius muscle, and pediatric lower limb bones. Finally, a more general approach to model personalization is discussed based on the idea of multiscale personalization called scaffolds.
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Affiliation(s)
- Justin Fernandez
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
- Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland,New Zealand
| | - Vickie Shim
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Marco Schneider
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Julie Choisne
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Geoff Handsfield
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Ted Yeung
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Ju Zhang
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
- Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland,New Zealand
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2
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O'Rourke D, Bucci F, Burton WS, Al-Dirini R, Taylor M, Martelli S. Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression. J Orthop Res 2023. [PMID: 36722422 DOI: 10.1002/jor.25526] [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: 05/03/2022] [Revised: 12/22/2022] [Accepted: 01/30/2023] [Indexed: 02/02/2023]
Abstract
Tibiofemoral geometry influences knee passive motion and understanding their relationship can provide insight into knee function and mechanisms of injury. However, the complexity of the geometric constraints has made characterizing the relationship challenging. The aim of this study was to determine the tibiofemoral bone geometries that explain the variation in passive motion using a partial least squares regression (PLSR) model. The PLSR model was developed for 29 healthy cadaver specimens (10 female, 19 male) with femur and tibia geometries retrieved from MRI images and six degree-of-freedom tibiofemoral kinematics determined during a flexion cycle with minimal medial pressure. The first 13 partial least squares (PLS) components explained 90% of the variation in the kinematics and accounted for 89% of the variation in geometry. The first three PLS components which shared geometric changes to particular surface congruencies of the tibial and femoral condyles explained the most amount of variation in the kinematics, primarily in anterior-posterior translation. Meanwhile, variations in femoral condyle width and the intercondylar space, tibia plateau size and conformity, and tibia eminences heights in PLS 2 and 4 explained the greatest amount of variation in internal-external rotation. PLS 4 exhibiting variation in overall size of the knee accounted for greatest amount of variation in geometry (50%) and had the greatest influence on the abduction-adduction motion and some on internal-external rotation but, overall, explained only a small proportion of the kinematics (10%). Elucidating the complex relationship between tibiofemoral bone geometry and passive kinematics may help personalize treatments for improved functional outcomes in patients.
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Affiliation(s)
- Dermot O'Rourke
- Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.,School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, South Australia, Australia
| | - Francesca Bucci
- Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - William S Burton
- Center for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, United States
| | - Rami Al-Dirini
- Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Mark Taylor
- Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Saulo Martelli
- Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
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Li X, Gu X, Jiang Z, Duan H, Zhou J, Chang Y, Lu K, Chen B. Statistical modeling: Assessing the anatomic variability of knee joint space width. J Biomech 2023; 147:111420. [PMID: 36652892 DOI: 10.1016/j.jbiomech.2022.111420] [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: 07/11/2022] [Revised: 12/02/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022]
Abstract
Population-based knee joint space width (JSW) assessments are promising for the prevention and early diagnosis of osteoarthritis. This study aimed to establish the statistical shape and alignment model (SSAM) of knee joints for assessing anatomic variation in knee JSW in the healthy Chinese male population. CT scans of asymptomatic knee joints of healthy male participants (n = 107) were collected for manual segmentation to create mesh samples. The as-scanned positional error was reduced by a standard processing flow of deformable mesh registration. Principal component analysis (PCA) was performed to create a tibiofemoral SSAM that was trained on all mesh samples. The anatomic variability of the JSW in the healthy Chinese male population was then assessed using the SSAM with regression analysis and 3D analysis by color-coded mapping. Almost all PCA modes had a linear influence on the anatomic variation of the medial and lateral JSW. The JSW variability within the SSAM was mainly explained by mode 1 (45.1 % of variation), demonstrating that this mode had the greatest influence on JSW variation. 3D assessment of the JSW showed that the minimum medial JSW varied from 2.76 to 3.23 mm, and its site shifted a short distance on the medial tibial plateau. The root-mean-square fitting and generalization errors of the SSAM were below 1 mm. This study will benefit the design and optimization of prosthetic devices, and may be applicable to the prevention and early diagnosis of osteoarthritis.
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Affiliation(s)
- Xiaohu Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
| | - Xuelian Gu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
| | - Ziang Jiang
- Department of Orthopaedic Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China.
| | - Huabing Duan
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
| | - Jincheng Zhou
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
| | - Yihao Chang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
| | - Ke Lu
- Department of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, Jiangsu 215300, China.
| | - Bo Chen
- Department of Orthopaedics, Shanghai Key Laboratory for Prevention and Treatment of Bone and Joint Diseases, Shanghai Institute of Traumatology and Orthopaedics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China.
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Gibbons KD, Malbouby V, Alvarez O, Fitzpatrick CK. Robust automatic hexahedral cartilage meshing framework enables population-based computational studies of the knee. Front Bioeng Biotechnol 2022; 10:1059003. [PMID: 36568304 PMCID: PMC9780478 DOI: 10.3389/fbioe.2022.1059003] [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: 09/30/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Osteoarthritis of the knee is increasingly prevalent as our population ages, representing an increasing financial burden, and severely impacting quality of life. The invasiveness of in vivo procedures and the high cost of cadaveric studies has left computational tools uniquely suited to study knee biomechanics. Developments in deep learning have great potential for efficiently generating large-scale datasets to enable researchers to perform population-sized investigations, but the time and effort associated with producing robust hexahedral meshes has been a limiting factor in expanding finite element studies to encompass a population. Here we developed a fully automated pipeline capable of taking magnetic resonance knee images and producing a working finite element simulation. We trained an encoder-decoder convolutional neural network to perform semantic image segmentation on the Imorphics dataset provided through the Osteoarthritis Initiative. The Imorphics dataset contained 176 image sequences with varying levels of cartilage degradation. Starting from an open-source swept-extrusion meshing algorithm, we further developed this algorithm until it could produce high quality meshes for every sequence and we applied a template-mapping procedure to automatically place soft-tissue attachment points. The meshing algorithm produced simulation-ready meshes for all 176 sequences, regardless of the use of provided (manually reconstructed) or predicted (automatically generated) segmentation labels. The average time to mesh all bones and cartilage tissues was less than 2 min per knee on an AMD Ryzen 5600X processor, using a parallel pool of three workers for bone meshing, followed by a pool of four workers meshing the four cartilage tissues. Of the 176 sequences with provided segmentation labels, 86% of the resulting meshes completed a simulated flexion-extension activity. We used a reserved testing dataset of 28 sequences unseen during network training to produce simulations derived from predicted labels. We compared tibiofemoral contact mechanics between manual and automated reconstructions for the 24 pairs of successful finite element simulations from this set, resulting in mean root-mean-squared differences under 20% of their respective min-max norms. In combination with further advancements in deep learning, this framework represents a feasible pipeline to produce population sized finite element studies of the natural knee from subject-specific models.
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Shalhoub S, Cyr A, Maletsky LP. Correlation between knee anatomy and joint laxity using principal component analysis. J Orthop Res 2022; 40:2502-2509. [PMID: 35220608 DOI: 10.1002/jor.25294] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 08/04/2021] [Accepted: 01/06/2022] [Indexed: 02/04/2023]
Abstract
Knee articular geometry and surface morphology greatly affect knee joint mechanics. Intra-subject variations in bone morphology and the passive range of motion have been well documented in the literature; however, the relationship between these two characteristics is not well understood. The objective of this study was to describe the correlation between knee joint anatomical features and passive range of motion using a statistical model. A principal component model was developed using femoral and tibial articular geometry, knee joint initial stance position, and the passive laxity envelope obtained from 27 cadaveric knees. The results from the principal component analysis showed high correlation between the anatomical features and the tibiofemoral passive envelope; an increase in the average femoral condyle radii, an increase in slope of the tibial spine, and a higher tibial plateau concavity correlated with a decrease in varus-valgus and internal-external range of motion. Understanding the correlation between anatomical features and tibiofemoral laxity could aid in the development of orthopedic implant designs by quantifying the effect of perturbing specific anatomical features on knee laxity and identifying specific implant femoral and tibial articular geometry necessary to obtain a targeted passive range of motion.
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Affiliation(s)
- Sami Shalhoub
- Bioengineering Graduate Program, University of Kansas, Lawrence, Kansas, USA
| | - Adam Cyr
- Bioengineering Graduate Program, University of Kansas, Lawrence, Kansas, USA.,Center for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA
| | - Lorin P Maletsky
- Department of Mechanical Engineering, University of Kansas, Lawrence, Kansas, USA
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Cartilage thickness and bone shape variations as a function of sex, height, body mass, and age in young adult knees. Sci Rep 2022; 12:11707. [PMID: 35810204 PMCID: PMC9271066 DOI: 10.1038/s41598-022-15585-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 06/27/2022] [Indexed: 11/22/2022] Open
Abstract
The functional relationship between bone and cartilage is modulated by mechanical factors. Scarce data exist on the relationship between bone shape and the spatial distribution of cartilage thickness. The aim of the study was to characterise the coupled variation in knee bone morphology and cartilage thickness distributions in knees with healthy cartilage and investigate this relationship as a function of sex, height, body mass, and age. MR images of 51 knees from young adults (28.4 ± 4.1 years) were obtained from a previous study and used to train a statistical shape model of the femur, tibia, and patella and their cartilages. Five multiple linear regression models were fitted to characterise morphology as a function of sex, height, body mass, and age. A logistic regression classifier was fitted to characterise morphological differences between males and females, and tenfold cross-validation was performed to evaluate the models’ performance. Our results showed that cartilage thickness and its distribution were coupled to bone morphology. The first five shape modes captured over 90% of the variance and described coupled changes to the bone and spatial distribution of cartilage thickness. Mode 1 (size) was correlated to sex (p < 0.001) and height (p < 0.0001). Mode 2 (aspect ratio) was also correlated to sex (p = 0.006) and height (p = 0.017). Mode 4 (condylar depth) was correlated to sex only (p = 0.024). A logistic regression model trained on modes 1, 2, and 4 could classify sex with an accuracy of 92.2% (95% CI [81.1%, 97.8%]). No other modes were influenced by sex, height, body mass, or age. This study demonstrated the coupled relationship between bone and cartilage, showing that cartilage is thicker with increased bone size, diaphysis size, and decreased femoral skew. Our results show that sex and height influence bone shape and the spatial distribution of cartilage thickness in a healthy young adult population, but body mass and age do not.
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Polamalu SK, Musahl V, Debski RE. Tibiofemoral bony morphology features associated with ACL injury and sex utilizing three-dimensional statistical shape modeling. J Orthop Res 2022; 40:87-94. [PMID: 33325047 DOI: 10.1002/jor.24952] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/30/2020] [Accepted: 12/14/2020] [Indexed: 02/04/2023]
Abstract
Statistical shape modeling was employed to assess three-dimensional (3D) bony morphology between distal femurs and proximal tibiae of anterior cruciate ligament (ACL) injured knees, the contralateral uninjured knees of ACL injured subjects, and knees with no history of injury. Surface models were created by segmenting bone from bilateral computed-tomography scans of 20 subjects of their ACL injured knees and non-injured contralateral knees, and 20 knees of control subjects with no history of a knee injury. Correspondence particles were placed on each surface, and a principal component analysis determined modes of variation in the positions of the correspondence particles describing anatomical variation. ANOVAs assessed the statistical differences of 3D bony morphological features with main effects of injury state and sex. ACL injured knees were determined to have a more lateral femoral mechanical axis and a greater angle between the long axis and condylar axis of the femur. A smaller anterior-posterior dimension of the lateral tibial plateau was also associated with ACL injured knees. Results of this study demonstrate that there are more bony morphological features predisposing individuals for ACL injury than previously established. These bony morphological parameters may cause greater internal and valgus torques increasing stresses in the ACL. No differences were determined between the ACL injured knees and their uninjured contralateral knees demonstrating that knees of ACL injured individuals are at similar risk for injury. Further understanding of the effect of bony morphology on the risk for ACL injury could improve individualized ACL injury treatment and prevention.
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Affiliation(s)
- Sene K Polamalu
- Departments of Orthopaedic Surgery and Bioengineering, Orthopaedic Robotics Laboratory, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Volker Musahl
- Departments of Orthopaedic Surgery and Bioengineering, Orthopaedic Robotics Laboratory, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Richard E Debski
- Departments of Orthopaedic Surgery and Bioengineering, Orthopaedic Robotics Laboratory, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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3D Geometric Shape Reconstruction for Revision TKA and UKA Knees Using Gaussian Process Regression. Ann Biomed Eng 2021; 49:3685-3697. [PMID: 34694499 DOI: 10.1007/s10439-021-02871-3] [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: 07/02/2021] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
Revision knee surgery is complicated by distortion of previous components and removal of additional bone, potentially causing misalignment and inappropriate selection of implants. In this study, we reconstructed the native femoral and tibial surface shapes in simulated total/unicompartmental knee arthroplasty (TKA/UKA) for 20 femurs and 20 tibias using a statistical inference method based on Gaussian Process regression. Compared to the true geometry, the average absolute errors (mean absolute distances) in the prediction of resected femur bones in TKA, medial UKA, and lateral UKA were 1.0 ± 0.3 mm, 1.0 ± 0.3 mm, and 0.8 ± 0.2 mm, respectively, while those in the prediction of tibia resections in the corresponding surgeries were 1.0 ± 0.4 mm, 0.8 ± 0.2 mm, and 0.7 ± 0.2 mm, respectively. Furthermore, it was found that the prediction accuracy depends on the size and gender of the resected bone. For example, the prediction accuracy for UKA cuts was significantly better than that for TKA cuts (p < 0.05). The female and male cuts were often overfit and underfit, respectively. The data indicated that this reconstruction approach can be a viable option for planning of revision surgeries, especially when contralateral anatomy is pathological or cannot be available.
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Armstrong JR, Campbell JQ, Petrella AJ. A comparison of Cartesian-only vs. Cartesian-spherical hybrid coordinates for statistical shape modeling in the lumbar spine. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 204:106056. [PMID: 33784547 DOI: 10.1016/j.cmpb.2021.106056] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 03/12/2021] [Indexed: 06/12/2023]
Abstract
OBJECTIVE The purpose of this study was to compare two methods for quantifying differences in geometric shapes of human lumbar vertebra using statistical shape modeling (SSM). METHODS A novel 3D implementation of a previously published 2D, nonlinear SSM was implemented and compared to a commonly used, Cartesian method of SSM. The nonlinear method, or Hybrid SSM, and Cartesian SSM were applied to lumbar vertebra shapes from a cohort of 18 full lumbar triangle meshes derived from CT scans. The comparison included traditional metrics for cumulative variance, generality, and specificity and results from application-based biomechanics using finite element simulation. RESULTS The Hybrid SSM has less compactness - likely due to the increased number of mathematical constraints in the SSM formulation. Similar results were found between methods for specificity and generality. Compared to the previously validated, manually-segmented FE model, both SSM methods produced similar and agreeable results. CONCLUSION Visual, statistical, and biomechanical findings did not convincingly support the superiority of the Hybrid SSM over the simpler Cartesian SSM. SIGNIFICANCE This work suggests that, of the two methods compared, the Cartesian SSM is adequate to capture the variations in shape of the posterior spinal structures for biomechanical modeling applications.
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Affiliation(s)
- Jeffrey R Armstrong
- Colorado School of Mines and works as a DRM/DFSS Program Manager for Medtronic Navigation, Louisville, CO, USA.
| | | | - Anthony J Petrella
- Mechanical Engineering with the Colorado School of Mines, Golden, CO, USA
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Ninos G, Bartzis V, Merlemis N, Sarris IE. Uncertainty quantification implementations in human hemodynamic flows. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 203:106021. [PMID: 33721602 DOI: 10.1016/j.cmpb.2021.106021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 02/19/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE Human hemodynamic modeling is usually influenced by uncertainties occurring from a considerable unavailability of information linked to the boundary conditions and the physical properties used in the numerical models. Calculating the effect of these uncertainties on the numerical findings along the cardiovascular system is a demanding process due to the complexity of the morphology of the body and the area dynamics. To cope with all these difficulties, Uncertainty Quantification (UQ) methods seem to be an ideal tool. RESULTS This study focuses on analyzing and summarizing some of the recent research efforts and directions of implementing UQ in human hemodynamic flows by analyzing 139 research papers. Initially, the suitability of applying this approach is analyzed and demonstrated. Then, an overview of the most significant research work in various fields of biomedical hemodynamic engineering is presented. Finally, it is attempted to identify any possible forthcoming directions for research and methodological progress of UQ in biomedical sciences. CONCLUSION This review concludes that by finding the best statistical methods and parameters to represent the propagated uncertainties, while achieving a good interpretation of the interaction between input-output, is crucial for implementing UQ in biomedical sciences.
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Affiliation(s)
- G Ninos
- Department of Biomedical Sciences, University of West Attica, 12243, Athens, Greece; Department of Mechanical Engineering, University of West Attica, 12244, Athens, Greece.
| | - V Bartzis
- Department of Food Science & Technology, University of West Attica, 12243, Athens, Greece
| | - N Merlemis
- Deptartment of Surveying and Geoinformatics Engineering, University of West Attica, 12243 Athens, Greece
| | - I E Sarris
- Department of Mechanical Engineering, University of West Attica, 12244, Athens, Greece
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Zhang X, Yuan S, Wang J, Liao B, Liang D. Biomechanical characteristics of tibio-femoral joint after partial medial meniscectomy in different flexion angles: a finite element analysis. BMC Musculoskelet Disord 2021; 22:322. [PMID: 33794839 PMCID: PMC8017646 DOI: 10.1186/s12891-021-04187-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 03/22/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Recent studies have pointed out that arthroscopy, the commonly-used surgical procedure for meniscal tears, may lead to an elevated risk of knee osteoarthritis (KOA). The biomechanical factors of KOA can be clarified by the biomechanical analysis after arthroscopic partial meniscectomy (APM). This study aimed to elucidate the cartilage stress and meniscus displacement of the tibiofemoral joint under flexion and rotation loads after APM. METHODS A detailed finite element model of the knee bone, cartilage, meniscus, and major ligaments was established by combining computed tomography and magnetic resonance images. Vertical load and front load were applied to simulate different knee buckling angles. At the same time, by simulating flexion of different degrees and internal and external rotations, the stresses on tibiofemoral articular cartilage and meniscus displacement were evaluated. RESULTS Generally, the contact stress on both the femoral tibial articular cartilage and the meniscus increased with the increased flexion degree. Moreover, the maximum stress on the tibial plateau gradually moved backward. The maximum position shift value of the lateral meniscus was larger than that of the medial meniscus. CONCLUSION Our finite element model provides a realistic three-dimensional model to evaluate the influence of different joint range of motion and rotating tibiofemoral joint stress distribution. The decreased displacement of the medial meniscus may explain the higher pressure on the knee components. These characteristics of the medial tibiofemoral joint indicate the potential biomechanical risk of knee degeneration.
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Affiliation(s)
- Xiaohui Zhang
- Guangzhou University of Chinese Medicine, 12 Airport Road, Guangzhou, 510405, Guangdong Province, China
| | - Shuo Yuan
- Guangzhou University of Chinese Medicine, 12 Airport Road, Guangzhou, 510405, Guangdong Province, China
| | - Jun Wang
- Gaosun Medical Imaging Diagnosis Center of Guangdong Province, 117 Liuhua Road, Guangzhou, 515500, Guangdong Province, China
| | - Bagen Liao
- Department of Sports Medicine, Guangzhou Sport University, 1268 Guangzhou Avenue 1268, Guangzhou, 515500, Guangdong Province, China
| | - De Liang
- Guangzhou University of Chinese Medicine, 12 Airport Road, Guangzhou, 510405, Guangdong Province, China.
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Regularized multi-structural shape modeling of the knee complex based on deep functional maps. Comput Med Imaging Graph 2021; 89:101890. [PMID: 33756303 DOI: 10.1016/j.compmedimag.2021.101890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/13/2021] [Accepted: 02/19/2021] [Indexed: 11/20/2022]
Abstract
The incorporation of a-priori knowledge on the shape of anatomical structures and their variation through Statistical Shape Models (SSMs) has shown to be very effective in guiding highly uncertain image segmentation problems. In this paper, we construct multiple-structure SSMs of purely geometric nature, that describe the relationship between adjacent anatomical components through Canonical Correlation Analysis. Shape inference is then conducted based on a regularization term on the shape likelihood providing more reliable structure representations. A fundamental prerequisite for performing statistical shape analysis on a set of objects is the identification of corresponding points on their associated surfaces. We address the correspondence problem using the recently proposed Functional Maps framework, which is a generalization of point-to-point correspondence to manifolds. Additionally, we show that, by incorporating techniques from the deep learning theory into this framework, we can further enhance the ability of SSMs to better capture the shape variation in a given dataset. The efficiency of our approach is illustrated through the creation of 3D models of the human knee complex in two application scenarios: incomplete or noisy shape reconstruction and missing structure estimation.
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13
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Caprara S, Carrillo F, Snedeker JG, Farshad M, Senteler M. Automated Pipeline to Generate Anatomically Accurate Patient-Specific Biomechanical Models of Healthy and Pathological FSUs. Front Bioeng Biotechnol 2021; 9:636953. [PMID: 33585436 PMCID: PMC7876284 DOI: 10.3389/fbioe.2021.636953] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 01/11/2021] [Indexed: 12/29/2022] Open
Abstract
State-of-the-art preoperative biomechanical analysis for the planning of spinal surgery not only requires the generation of three-dimensional patient-specific models but also the accurate biomechanical representation of vertebral joints. The benefits offered by computational models suitable for such purposes are still outweighed by the time and effort required for their generation, thus compromising their applicability in a clinical environment. In this work, we aim to ease the integration of computerized methods into patient-specific planning of spinal surgery. We present the first pipeline combining deep learning and finite element methods that allows a completely automated model generation of functional spine units (FSUs) of the lumbar spine for patient-specific FE simulations (FEBio). The pipeline consists of three steps: (a) multiclass segmentation of cropped 3D CT images containing lumbar vertebrae using the DenseVNet network, (b) automatic landmark-based mesh fitting of statistical shape models onto 3D semantic segmented meshes of the vertebral models, and (c) automatic generation of patient-specific FE models of lumbar segments for the simulation of flexion-extension, lateral bending, and axial rotation movements. The automatic segmentation of FSUs was evaluated against the gold standard (manual segmentation) using 10-fold cross-validation. The obtained Dice coefficient was 93.7% on average, with a mean surface distance of 0.88 mm and a mean Hausdorff distance of 11.16 mm (N = 150). Automatic generation of finite element models to simulate the range of motion (ROM) was successfully performed for five healthy and five pathological FSUs. The results of the simulations were evaluated against the literature and showed comparable ROMs in both healthy and pathological cases, including the alteration of ROM typically observed in severely degenerated FSUs. The major intent of this work is to automate the creation of anatomically accurate patient-specific models by a single pipeline allowing functional modeling of spinal motion in healthy and pathological FSUs. Our approach reduces manual efforts to a minimum and the execution of the entire pipeline including simulations takes approximately 2 h. The automation, time-efficiency and robustness level of the pipeline represents a first step toward its clinical integration.
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Affiliation(s)
- Sebastiano Caprara
- Department of Orthopedics, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Fabio Carrillo
- Institute for Biomechanics, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
- Research in Orthopedic Computer Science, University Hospital Balgrist, Zurich, Switzerland
| | - Jess G. Snedeker
- Department of Orthopedics, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Mazda Farshad
- Department of Orthopedics, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
| | - Marco Senteler
- Department of Orthopedics, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
- Institute for Biomechanics, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
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Uzuner S, Li L, Kucuk S, Memisoglu K. Changes in Knee Joint Mechanics After Medial Meniscectomy Determined With a Poromechanical Model. J Biomech Eng 2020; 142:1084014. [PMID: 32451526 DOI: 10.1115/1.4047343] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Indexed: 11/08/2022]
Abstract
The menisci play a vital role in the mechanical function of knee joint. Unfortunately, meniscal tears often occur. Meniscectomy is a surgical treatment for meniscal tears; however, mechanical changes in the knee joint after meniscectomy is a risk factor to osteoarthritis (OA). The objective of this study was to investigate the altered cartilage mechanics of different medial meniscectomies using a poromechanical model of the knee joint. The cartilaginous tissues were modeled as nonlinear fibril-reinforced porous materials with full saturation. The ligaments were considered as anisotropic hyperelastic and reinforced by a fibrillar collagen network. A compressive creep load of ¾ body weight was applied in full extension of the right knee during 200 s standing. Four finite element models were developed to simulate different meniscectomies of the joint using the intact model as the reference for comparison. The modeling results showed a higher load support in the lateral than medial compartment in the intact joint, and the difference in the load share between the compartments was augmented with medial meniscectomy. Similarly, the contact and fluid pressures were higher in the lateral compartment. On the other hand, the medial meniscus in the normal joint experienced more loading than the lateral one. Furthermore, the contact pressure distribution changed with creep, resulting in a load transfer between cartilage and meniscus within each compartment while the total load born by the compartment remained unchanged. This study has quantified the altered contact mechanics on the type and size of meniscectomies, which may be used to understand meniscal tear or support surgical decisions.
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Affiliation(s)
- Sabri Uzuner
- Department of Mechatronics, Dr. Engin PAK Cumayeri Vocational School, University of Duzce, Cumayeri, Duzce, Marmara 81700, Turkey
| | - LePing Li
- Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive, N.W., Calgary, AB T2N 1N4, Canada
| | - Serdar Kucuk
- Department of Biomedical Engineering, University of Kocaeli, Izmit, Kocaeli, Marmara 41001, Turkey
| | - Kaya Memisoglu
- Medical Faculty, Department of Orthopedics and Traumatology, University of Kocaeli, Izmit, Kocaeli, Marmara 41001, Turkey
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15
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Black RA, Houston G. 40th Anniversary Issue: Reflections on papers from the archive on "Biomechanics". Med Eng Phys 2020; 72:70-71. [PMID: 31554579 DOI: 10.1016/j.medengphy.2019.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Richard A Black
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, Scotland, UK.
| | - Gregor Houston
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, Scotland, UK
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16
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Erdemir A, Besier TF, Halloran JP, Imhauser CW, Laz PJ, Morrison TM, Shelburne KB. Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy. J Biomech Eng 2020; 141:2730179. [PMID: 31166589 DOI: 10.1115/1.4043346] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Indexed: 12/26/2022]
Abstract
Recent explorations of knee biomechanics have benefited from computational modeling, specifically leveraging advancements in finite element analysis and rigid body dynamics of joint and tissue mechanics. A large number of models have emerged with different levels of fidelity in anatomical and mechanical representation. Adapted modeling and simulation processes vary widely, based on justifiable choices in relation to anticipated use of the model. However, there are situations where modelers' decisions seem to be subjective, arbitrary, and difficult to rationalize. Regardless of the basis, these decisions form the "art" of modeling, which impact the conclusions of simulation-based studies on knee function. These decisions may also hinder the reproducibility of models and simulations, impeding their broader use in areas such as clinical decision making and personalized medicine. This document summarizes an ongoing project that aims to capture the modeling and simulation workflow in its entirety-operation procedures, deviations, models, by-products of modeling, simulation results, and comparative evaluations of case studies and applications. The ultimate goal of the project is to delineate the art of a cohort of knee modeling teams through a publicly accessible, transparent approach and begin to unravel the complex array of factors that may lead to a lack of reproducibility. This manuscript outlines our approach along with progress made so far. Potential implications on reproducibility, on science, engineering, and training of modeling and simulation, on modeling standards, and on regulatory affairs are also noted.
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Affiliation(s)
- Ahmet Erdemir
- Department of Biomedical Engineering and Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH 44195 e-mail:
| | - Thor F Besier
- Department of Engineering Science, Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand
| | - Jason P Halloran
- Department of Mechanical Engineering, Center for Human Machine Systems, Cleveland State University, Cleveland, OH 44115
| | - Carl W Imhauser
- Department of Biomechanics, Hospital for Special Surgery, New York, NY 10021
| | - Peter J Laz
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, Denver, CO 80210
| | - Tina M Morrison
- Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD 20993
| | - Kevin B Shelburne
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, Denver, CO 80210
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17
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Cerveri P, Belfatto A, Manzotti A. Predicting Knee Joint Instability Using a Tibio-Femoral Statistical Shape Model. Front Bioeng Biotechnol 2020; 8:253. [PMID: 32363179 PMCID: PMC7182437 DOI: 10.3389/fbioe.2020.00253] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 03/12/2020] [Indexed: 11/13/2022] Open
Abstract
Statistical shape models (SSMs) are a well established computational technique to represent the morphological variability spread in a set of matching surfaces by means of compact descriptive quantities, traditionally called "modes of variation" (MoVs). SSMs of bony surfaces have been proposed in biomechanics and orthopedic clinics to investigate the relation between bone shape and joint biomechanics. In this work, an SSM of the tibio-femoral joint has been developed to elucidate the relation between MoVs and bone angular deformities causing knee instability. The SSM was built using 99 bony shapes (distal femur and proximal tibia surfaces obtained from segmented CT scans) of osteoarthritic patients. Hip-knee-ankle (HKA) angle, femoral varus-valgus (FVV) angle, internal-external femoral rotation (IER), tibial varus-valgus (TVV) angles, and tibial slope (TS) were available across the patient set. Discriminant analysis (DA) and logistic regression (LR) classifiers were adopted to underline specific MoVs accounting for knee instability. First, it was found that thirty-four MoVs were enough to describe 95% of the shape variability in the dataset. The most relevant MoVs were the one encoding the height of the femoral and tibial shafts (MoV #2) and the one representing variations of the axial section of the femoral shaft and its bending in the frontal plane (MoV #5). Second, using quadratic DA, the sensitivity results of the classification were very accurate, being all >0.85 (HKA: 0.96, FVV: 0.99, IER: 0.88, TVV: 1, TS: 0.87). The results of the LR classifier were mostly in agreement with DA, confirming statistical significance for MoV #2 (p = 0.02) in correspondence to IER and MoV #5 in correspondence to HKA (p = 0.0001), FVV (p = 0.001), and TS (p = 0.02). We can argue that the SSM successfully identified specific MoVs encoding ranges of alignment variability between distal femur and proximal tibia. This discloses the opportunity to use the SSM to predict potential misalignment in the knee for a new patient by processing the bone shapes, removing the need for measuring clinical landmarks as the rotation centers and mechanical axes.
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Affiliation(s)
- Pietro Cerveri
- Department of Electronics, Information and Bioengineering, Polytechnic University of Milan, Milan, Italy
| | - Antonella Belfatto
- Department of Electronics, Information and Bioengineering, Polytechnic University of Milan, Milan, Italy
| | - Alfonso Manzotti
- Orthopaedic and Trauma Department, "Luigi Sacco" Hospital, ASST FBF-Sacco, Milan, Italy
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18
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Audenaert EA, Khanduja V, Claes P, Malviya A, Steenackers G. Mechanics of Psoas Tendon Snapping. A Virtual Population Study. Front Bioeng Biotechnol 2020; 8:264. [PMID: 32292780 PMCID: PMC7118580 DOI: 10.3389/fbioe.2020.00264] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 03/13/2020] [Indexed: 12/24/2022] Open
Abstract
Internal snapping of the psoas tendon is a frequently reported condition, especially in young adolescents involved in sports. It is defined as an increased tendon excursion over bony or soft tissue prominence causing local irritation and inflammation of the tendon leading to groin pain and often is accompanied by an audible snap. Due to the lack of detailed dynamic visualization means, the exact mechanism of the condition remains poorly understood and different theories have been postulated related to the etiology and its location about the hip. In the present study we simulated psoas tendon behavior in a virtual population of 40,000 anatomies and compared tendon movement during combined abduction, flexion and external rotation and back to neutral extension and adduction. At risk phenotyopes for tendon snapping were defined as the morphologies presenting with excess tendon movement. There were little differences in tendon movement between the male and female models. In both populations, abnormal tendon excursion correlated with changes in mainly the femoral anatomy (male r = 0.72, p < 0.001, female r = 0.66, p < 0.001): increased anteversion and valgus as well as a decreasing femoral offset and ischiofemoral distance. The observed combination of shape components correlating with excess tendon movement in essence presented with a medial positioning of the minor trochanter. This finding suggest that psoas snapping and ischiofemoral impingement are possibly two presentations of a similar underlying rotational dysplasia of the femur.
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Affiliation(s)
- Emmanuel A Audenaert
- Department of Orthopedic Surgery and Traumatology, Ghent University Hospital, Ghent, Belgium.,Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom.,Op3Mech Research Group, Department of Electromechanics, University of Antwerp, Antwerp, Belgium.,Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Vikas Khanduja
- Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Peter Claes
- Medical Imaging Research Center (MIRC), University Hospitals Leuven, Leuven, Belgium.,Department of Electrical Engineering/Processing Speech and Images, KU Leuven, Leuven, Belgium.,Department of Human Genetics, KU Leuven, Leuven, Belgium.,Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
| | - Ajay Malviya
- Department of Orthopedic Surgery and Traumatology, Northumbria National Health Service Foundation Trust, Newcastle upon Tyne, United Kingdom.,Department of Regenerative Medicine, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Gunther Steenackers
- Op3Mech Research Group, Department of Electromechanics, University of Antwerp, Antwerp, Belgium
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19
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Comparison of Biomechanical Performance of Five Different Treatment Approaches for Fixing Posterior Pelvic Ring Injury. JOURNAL OF HEALTHCARE ENGINEERING 2020; 2020:5379593. [PMID: 32076495 PMCID: PMC6996702 DOI: 10.1155/2020/5379593] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 11/18/2019] [Accepted: 01/06/2020] [Indexed: 12/03/2022]
Abstract
Background A large number of pelvic injuries are seriously unstable, with mortality rates reaching 19%. Approximately 60% of pelvic injuries are related to the posterior pelvic ring. However, the selection of a fixation method for a posterior pelvic ring injury remains a challenging problem for orthopedic surgeons. The aim of the present study is to investigate the biomechanical performance of five different fixation approaches for posterior pelvic ring injury and thus provide guidance on the choice of treatment approach in a clinical setting. Methods A finite element (FE) model, including the L3-L5 lumbar vertebrae, sacrum, and full pelvis, was created from CT images of a healthy adult. Tile B and Tile C types of pelvic fractures were created in the model. Five different fixation methods for fixing the posterior ring injury (PRI) were simulated: TA1 (conservative treatment), TA2 (S1 screw fixation), TA3 (S1 + S2 screw fixation), TA4 (plate fixation), and TA5 (modified triangular osteosynthesis). Based on the fixation status (fixed or nonfixed) of the anterior ring and the fixation method for PRI, 20 different FE models were created. An upright standing loading scenario was simulated, and the resultant displacements at the sacroiliac joint were compared between different models. Results When TA5 was applied, the resultant displacements at the sacroiliac joint were the smallest (1.5 mm, 1.6 mm, 1.6 mm, and 1.7 mm) for all the injury cases. The displacements induced by TA3 and TA2 were similar to those induced by TA5. TA4 led to larger displacements at the sacroiliac joint (2.3 mm, 2.4 mm, 4.8 mm, and 4.9 mm), and TA1 was the worst case (3.1 mm, 3.2 mm, 6.3 mm, and 6.5 mm). Conclusions The best internal fixation method for PRI is the triangular osteosynthesis approach (TA5), followed by S1 + S2 screw fixation (TA3), S1 screw fixation (TA2), and plate fixation (TA4).
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20
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Grant TM, Diamond LE, Pizzolato C, Killen BA, Devaprakash D, Kelly L, Maharaj JN, Saxby DJ. Development and validation of statistical shape models of the primary functional bone segments of the foot. PeerJ 2020; 8:e8397. [PMID: 32117607 PMCID: PMC7006516 DOI: 10.7717/peerj.8397] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 12/16/2019] [Indexed: 12/15/2022] Open
Abstract
Introduction Musculoskeletal models are important tools for studying movement patterns, tissue loading, and neuromechanics. Personalising bone anatomy within models improves analysis accuracy. Few studies have focused on personalising foot bone anatomy, potentially incorrectly estimating the foot’s contribution to locomotion. Statistical shape models have been created for a subset of foot-ankle bones, but have not been validated. This study aimed to develop and validate statistical shape models of the functional segments in the foot: first metatarsal, midfoot (second-to-fifth metatarsals, cuneiforms, cuboid, and navicular), calcaneus, and talus; then, to assess reconstruction accuracy of these shape models using sparse anatomical data. Methods Magnetic resonance images of 24 individuals feet (age = 28 ± 6 years, 52% female, height = 1.73 ± 0.8 m, mass = 66.6 ± 13.8 kg) were manually segmented to generate three-dimensional point clouds. Point clouds were registered and analysed using principal component analysis. For each bone segment, a statistical shape model and principal components were created, describing population shape variation. Statistical shape models were validated by assessing reconstruction accuracy in a leave-one-out cross validation. Statistical shape models were created by excluding a participant’s bone segment and used to reconstruct that same excluded bone using full segmentations and sparse anatomical data (i.e. three discrete points on each segment), for all combinations in the dataset. Tali were not reconstructed using sparse anatomical data due to a lack of externally accessible landmarks. Reconstruction accuracy was assessed using Jaccard index, root mean square error (mm), and Hausdorff distance (mm). Results Reconstructions generated using full segmentations had mean Jaccard indices between 0.77 ± 0.04 and 0.89 ± 0.02, mean root mean square errors between 0.88 ± 0.19 and 1.17 ± 0.18 mm, and mean Hausdorff distances between 2.99 ± 0.98 mm and 6.63 ± 3.68 mm. Reconstructions generated using sparse anatomical data had mean Jaccard indices between 0.67 ± 0.06 and 0.83 ± 0.05, mean root mean square error between 1.21 ± 0.54 mm and 1.66 ± 0.41 mm, and mean Hausdorff distances between 3.21 ± 0.94 mm and 7.19 ± 3.54 mm. Jaccard index was higher (P < 0.01) and root mean square error was lower (P < 0.01) in reconstructions from full segmentations compared to sparse anatomical data. Hausdorff distance was lower (P < 0.01) for midfoot and calcaneus reconstructions using full segmentations compared to sparse anatomical data. Conclusion For the first time, statistical shape models of the primary functional segments of the foot were developed and validated. Foot segments can be reconstructed with minimal error using full segmentations and sparse anatomical landmarks. In future, larger training datasets could increase statistical shape model robustness, extending use to paediatric or pathological populations.
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Affiliation(s)
- Tamara M Grant
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.,Griffith Centre for Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Laura E Diamond
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.,Griffith Centre for Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Claudio Pizzolato
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.,Griffith Centre for Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Bryce A Killen
- Human Movement Biomechanics Research Group, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Daniel Devaprakash
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.,Griffith Centre for Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Luke Kelly
- School of Human Movement and Nutritional Sciences, University of Queensland, Brisbane, QLD, Australia
| | - Jayishni N Maharaj
- School of Human Movement and Nutritional Sciences, University of Queensland, Brisbane, QLD, Australia
| | - David J Saxby
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD, Australia.,Griffith Centre for Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
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21
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Computational framework for population-based evaluation of TKR-implanted patellofemoral joint mechanics. Biomech Model Mechanobiol 2020; 19:1309-1317. [PMID: 32020408 DOI: 10.1007/s10237-020-01295-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 01/20/2020] [Indexed: 10/25/2022]
Abstract
Differences in patient anatomy are known to influence joint mechanics. Accordingly, intersubject anatomical variation is an important consideration when assessing the design of joint replacement implants. The objective of this study was to develop a computational workflow to perform population-based evaluations of total knee replacement implant mechanics considering variation in patient anatomy and to assess the potential for an efficient sampling strategy to support design phase screening analyses. The approach generated virtual subject anatomies using a statistical shape model of the knee and performed virtual implantation to size and align the implants. A finite-element analysis simulated a deep knee bend activity and predicted patellofemoral (PF) mechanics. The study predicted bounds of performance for kinematics and contact mechanics and investigated relationships between patient factors and outputs. For example, the patella was less flexed throughout the deep knee bend activity for patients with an alta patellar alignment. The results also showed the PF range of motions in AP and ML were generally larger with increasing femoral component size. Comparison of the 10-90% bounds between sampling strategies agreed reasonably, suggesting that Latin Hypercube sampling can be used for initial screening evaluations and followed up by more intensive Monte Carlo simulation for refined designs. The platform demonstrated a functional workflow to consider variation in joint anatomy to support robust implant design.
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22
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Zhou C, Willing R. Multiobjective Design Optimization of a Biconcave Mobile-Bearing Lumbar Total Artificial Disk Considering Spinal Kinematics, Facet Joint Loading, and Metal-on-Polyethylene Contact Mechanics. J Biomech Eng 2019; 142:1046996. [DOI: 10.1115/1.4045048] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Indexed: 12/30/2022]
Abstract
Abstract
Total disk arthroplasty (TDA) using an artificial disk (AD) is an attractive surgical technique for the treatment of spinal disorders, since it can maintain or restore spinal motion (unlike interbody fusion). However, adverse surgical outcomes of contemporary lumbar TDAs have been reported. We previously proposed a new mobile-bearing AD design concept featuring a biconcave ultrahigh-molecular-weight polyethylene (UHMWPE) mobile core. The objective of this study was to develop an artificial neural network (NN) based multiobjective optimization framework to refine the biconcave-core AD design considering multiple TDA performance metrics, simultaneously. We hypothesized that there is a tradeoff relationship between the performance metrics in terms of range of motion (ROM), facet joint force (FJF), and polyethylene contact pressure (PCP). By searching the resulting three-dimensional (3D) Pareto frontier after multiobjective optimization, it was found that there was a “best-tradeoff” AD design, which could balance all the three metrics, without excessively sacrificing each metric. However, for each single-objective optimum AD design, only one metric was optimal, and distinct sacrifices were observed in the other two metrics. For a commercially available biconvex-core AD design, the metrics were even worse than the poorest outcomes of the single-objective optimum AD designs. Therefore, multiobjective design optimization could be useful for achieving native lumbar segment biomechanics and minimal PCPs, as well as for improving the existing lumbar motion-preserving surgical treatments.
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Affiliation(s)
- Chaochao Zhou
- Department of Mechanical Engineering, State University of New York at Binghamton, Binghamton, NY 13902-6000
| | - Ryan Willing
- Department of Mechanical Engineering, State University of New York at Binghamton, Binghamton, NY 13902-6000; Department of Mechanical and Materials Engineering, Western University, Thompson Engineering Building, Room TEB 363, London, ON N6A 5B9, Canada
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23
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Relationship between lower lumbar spine shape and patient bone metabolic activity as characterised by 18F NaF bio-markers. Comput Biol Med 2019; 116:103529. [PMID: 31715382 DOI: 10.1016/j.compbiomed.2019.103529] [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] [Received: 07/20/2019] [Revised: 10/31/2019] [Accepted: 10/31/2019] [Indexed: 11/20/2022]
Abstract
Chronic lower lumbar pain has been associated with elevated bone metabolic activity in the spine. Diagnosis of bone metabolic activity is currently through integrating Positron Emission Tomography (PET) with Sodium Fluoride (18F-NaF) biomarkers. It has been reported that numerous observable pathologies including lumbar fusion, disc abnormalities and scoliosis have often been associated with increased 18F-NaF uptake. The aim of this study was to identify what features of lower lumbar shape most strongly correlate with 18F-NaF uptake. Following a principal component analysis of 23 patients who presented with lumbar pain and underwent 18F-NaF PET-CT, it was revealed that three modes interpreted as (i) sacral tilt, (ii) vertebral disc spacing and (iii) spine size were the three characteristics that described 88.7% of spine shape in our study population. 18F-NaF was described by two modes including 18F-NaF intensity and spatial variation (anterior-inferior to posterior-superior). 18F-NaF was most sensitive to sacral tilt followed by vertebral disc spacing. A predictive model derived from that spine population was able to predict 18F-NaF 'hot-spot' locations with 85 ± 5% accuracy and with 71 ± 3% accuracy for the 18F-NaF magnitude. These results suggest that patients reporting with lower lumbar pain and who present with increased sacral tilt profiles and/or reduced disc spacing are good candidates for further 18F-NaF PET-CT imaging, evidenced by the high association between those shape profiles and 18F-NaF uptake.
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24
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Yeung S, Fernandez JW, Handsfield GG, Walker C, Besier TF, Zhang J. Rapid muscle volume prediction using anthropometric measurements and population-derived statistical models. Biomech Model Mechanobiol 2019; 19:1239-1249. [PMID: 31667655 DOI: 10.1007/s10237-019-01243-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 10/21/2019] [Indexed: 12/01/2022]
Abstract
Knowledge of subject-specific muscle volumes may be used as surrogates for evaluating muscle strength and power generated by 'fat-free' muscle mass. This study presents population-based statistical learning approaches for predicting 'fat-free' muscle volume from known anthropometric measurements. Using computed tomography (CT) imaging data to obtain lower-limb muscle volumes from 50 men and women, this study evaluated six statistical learning methods for predicting muscle volumes from anthropometric measurements: (i) stepwise regression, (ii) linear support vector machine (SVM), (iii) 2nd-order polynomial SVM, (iv) linear partial least squares regression (PLSR), (v) quadratic PLSR, and (vi) 3rd-order spline fit PLSR. These techniques have successfully been demonstrated in bioengineering applications and freely available in open-source toolkits. Analysis revealed that separating a general population into sexes and/or cohorts based on adipose level may improve prediction accuracies. The most important measures that statistically influence muscle volume predictions were shank girth, followed by sex and finally leg length, as identified using stepwise regression. SVM learning predicted muscle volume with an accuracy of 85 ± 4% when using linear interpolation, but performed poorly with an accuracy of 59 ± 6% using polynomial interpolation. The simpler linear PLSR exhibited muscle volume prediction accuracy of 87 ± 2%, while quadratic PLSR was slightly reduced at 82 ± 3%. For the spline fit PLSR, high accuracy was observed on the training data set (~ 99%) but over-fitting (a drawback of high-interpolation methods) resulted in erroneous predictions on testing data, and hence, the model was deemed unsuitable. In conclusion, use of linear PLSR models with variables of sex, leg length, and shank girth is a useful tool for predicting 'fat-free' muscle volume.
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Affiliation(s)
- S Yeung
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - J W Fernandez
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.,Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| | - G G Handsfield
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - C Walker
- Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| | - T F Besier
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.,Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| | - J Zhang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
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25
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Durastanti G, Leardini A, Siegler S, Durante S, Bazzocchi A, Belvedere C. Comparison of cartilage and bone morphological models of the ankle joint derived from different medical imaging technologies. Quant Imaging Med Surg 2019; 9:1368-1382. [PMID: 31559166 DOI: 10.21037/qims.2019.08.08] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Accurate geometrical models of bones and cartilage are necessary in biomechanical modelling of human joints, and in planning and designing of joint replacements. Image-based subject-specific model development requires image segmentation, spatial filtering and 3-dimensional rendering. This is usually based on computed tomography (CT) for bone models, on magnetic resonance imaging (MRI) for cartilage models. This process has been reported extensively in the past, but no studies have ever compared the accuracy and quality of these models when obtained also by merging different imaging modalities. The scope of the present work is to provide this comparative analysis in order to identify optimal imaging modality and registration techniques for producing 3-dimensional bone and cartilage models of the ankle joint. Methods One cadaveric leg was instrumented with multimodal markers and scanned using five different imaging modalities: a standard, a dual-energy and a cone-beam CT (CBCT) device, and a 1.5 and 3.0 Tesla MRI devices. Bone, cartilage, and combined bone and cartilage models were produced from each of these imaging modalities, and registered in space according to matching model surfaces or to corresponding marker centres. To assess the quality in overall model reconstruction, distance map analyses were performed and the difference between model surfaces obtained from the different imaging modalities and registration techniques was measured. Results The registration between models worked better with model surface matching than corresponding marker positions, particularly with MRI. The best bone models were obtained with the CBCT. Models with cartilage were defined better with the 3.0 Tesla than the 1.5 Tesla. For the combined bone and cartilage models, the colour maps and the numerical results from distance map analysis (DMA) showed that the smallest distances and the largest homogeneity were obtained from the CBCT and the 3.0 T MRI via model surface registration. Conclusions These observations are important in producing accurate bone and cartilage models from medical imaging and relevant for applications such as designing of custom-made ankle replacements or, more in general, of implants for total as well as focal joint replacements.
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Affiliation(s)
- Gilda Durastanti
- Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Alberto Leardini
- Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Sorin Siegler
- Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, USA
| | - Stefano Durante
- Nursing, Technical and Rehabilitation Assistance Service, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Alberto Bazzocchi
- Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Claudio Belvedere
- Movement Analysis Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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26
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Clouthier AL, Smith CR, Vignos MF, Thelen DG, Deluzio KJ, Rainbow MJ. The effect of articular geometry features identified using statistical shape modelling on knee biomechanics. Med Eng Phys 2019; 66:47-55. [PMID: 30850334 DOI: 10.1016/j.medengphy.2019.02.009] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 02/04/2019] [Accepted: 02/11/2019] [Indexed: 01/17/2023]
Abstract
Articular geometry in the knee varies widely among people which has implications for risk of injury and pathology. The goals of this work were to develop a framework to systematically vary geometry in a multibody knee model and to use this framework to investigate the effect of morphological features on dynamic knee kinematics and contact mechanics. A statistical shape model of the tibiofemoral and patellofemoral joints was created from magnetic resonance images of 14 asymptomatic knees. The shape model was then used to generate 37 unique multibody knee models based on -3 to +3 standard deviations of the scores for the first six principal components identified. Each multibody model was then incorporated into a lower extremity musculoskeletal model and the Concurrent Optimization of Muscle Activations and Kinematics (COMAK) routine was used to simulate knee mechanics for overground walking. Changes in articular geometry affected knee function, resulting in differences up to 17° in orientation, 8 mm in translation, 0.7 BW in contact force, and 2.0 MPa in mean cartilage contact pressure. Understanding the relationship between shape and function in a joint could provide insight into the mechanisms behind injury and pathology and the variability in response to treatment.
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Affiliation(s)
- Allison L Clouthier
- Department of Mechanical and Materials Engineering, Queen's University, 130 Stuart St., McLaughlin Hall, Kingston, ON K7L 3N6, Canada.
| | - Colin R Smith
- Department of Mechanical Engineering, University of Wisconsin-Madison, 1513 University Ave, Madison, WI 53706, USA
| | - Michael F Vignos
- Department of Mechanical Engineering, University of Wisconsin-Madison, 1513 University Ave, Madison, WI 53706, USA
| | - Darryl G Thelen
- Department of Mechanical Engineering, University of Wisconsin-Madison, 1513 University Ave, Madison, WI 53706, USA
| | - Kevin J Deluzio
- Department of Mechanical and Materials Engineering, Queen's University, 130 Stuart St., McLaughlin Hall, Kingston, ON K7L 3N6, Canada
| | - Michael J Rainbow
- Department of Mechanical and Materials Engineering, Queen's University, 130 Stuart St., McLaughlin Hall, Kingston, ON K7L 3N6, Canada
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27
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Chen H, Sprengers AMJ, Kang Y, Verdonschot N. Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee. Med Biol Eng Comput 2018; 57:1015-1027. [PMID: 30520006 PMCID: PMC6477013 DOI: 10.1007/s11517-018-1936-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 07/08/2018] [Accepted: 11/24/2018] [Indexed: 11/29/2022]
Abstract
Patient-specific implant design and pre- and intra-operative planning is becoming increasingly important in the orthopaedic field. For clinical feasibility of these techniques, fast and accurate segmentation of bone structures from MRI is essential. However, manual segmentation is time intensive and subject to inter- and intra-observer variation. The challenge in developing automatic segmentation algorithms for MRI data mainly exists in the inhomogeneity problem and the low contrast among cortical bone and adjacent tissues. In this paper, we proposed a method for automatic segmentation of knee bone structures for MRI data with a 3D local intensity clustering-based level set and a novel approach to determine the cortical boundary utilizing the normal vector of the trabecular surface. Application to clinical imaging data shows that our method is robust to MRI inhomogeneity. In comparing our method to manual segmentation in 18 femurs and tibiae, we found a dice similarity coefficient (DSC) of 0.9611 ± 0.0052 for the femurs and 0.9591 ± 0.0173 for tibiae. The average surface distance error was 0.4649 ± 0.1430 mm for the femurs and 0.4712 ± 0.2113 mm for the tibiae. The results of the automatic technique thus strongly corresponded to the manual segmentation using less than 3% of the time and with virtually no workload. ᅟ ![]()
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Affiliation(s)
- Hao Chen
- Department of Biomechanical Engineering, University of Twente, Drienerlolaan 5, 7500 AE, Enschede, the Netherlands.
| | - André M J Sprengers
- Department of Biomechanical Engineering, University of Twente, Drienerlolaan 5, 7500 AE, Enschede, the Netherlands.,Orthopaedic Research Laboratory, Radboud University Medical Center, Geert Grooteplein-Zuid 10, 6525 GA, Nijmegen, the Netherlands
| | - Yan Kang
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang, 110169, China
| | - Nico Verdonschot
- Department of Biomechanical Engineering, University of Twente, Drienerlolaan 5, 7500 AE, Enschede, the Netherlands.,Orthopaedic Research Laboratory, Radboud University Medical Center, Geert Grooteplein-Zuid 10, 6525 GA, Nijmegen, the Netherlands
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28
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Chang L, Shen S, Zhang Z, Song X, Jiang Q. Study on the relationship between age and the concentrations of heavy metal elements in human bone. ANNALS OF TRANSLATIONAL MEDICINE 2018; 6:320. [PMID: 30363972 DOI: 10.21037/atm.2018.08.09] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Excessive amounts of heavy metals such as cadmium, chromium, cobalt, lead, thallium, and manganese are extremely harmful to the human body. These elements can accumulate in bone and impact bone metabolism. In this study, we investigated the relationship between age and the concentrations of these elements in human bone and blood. Methods Bone and blood samples were obtained from both older and younger patients. The concentrations of the elements under investigation were measured by inductively coupled plasma mass spectrometry (ICP-MS), and the specific concentrations in the bone and blood were then calculated. Results The results showed that with increasing age, the concentrations of chromium, cobalt, and thallium in bone decreased significantly, while the concentration of cadmium in bone markedly increased. However, there was no clear correlation between age and the concentrations of these heavy metals in blood. Notably, there was a close correlation between the concentration of cobalt in bone and the presence of osteopenia. Conclusions Senescence of the human body is accompanied by the shifting of cobalt, chromium, and thallium from the bone to the outer- bone. However, the concentration of cadmium in bone increases with age. These changes are very likely to be related to the equilibrium of bone metabolism in senescent individuals. In addition, only cobalt was shown to be significantly related to osteopenia.
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Affiliation(s)
- Liang Chang
- Department of Sports Medicine and Adult Reconstructive Surgery, Drum Tower Hospital affiliated to Medical School of Nanjing University, Nanjing 210000, China.,Joint Research Center for Bone and Joint Disease, Model Animal Research Center (MARC), Nanjing University, Nanjing 210093, China
| | - Sheng Shen
- Department of Sports Medicine and Adult Reconstructive Surgery, Drum Tower Hospital affiliated to Medical School of Nanjing University, Nanjing 210000, China
| | - Zhe Zhang
- Department of Sports Medicine and Adult Reconstructive Surgery, Drum Tower Hospital affiliated to Medical School of Nanjing University, Nanjing 210000, China.,Joint Research Center for Bone and Joint Disease, Model Animal Research Center (MARC), Nanjing University, Nanjing 210093, China
| | - Xiaoxiao Song
- Department of Sports Medicine and Adult Reconstructive Surgery, Drum Tower Hospital affiliated to Medical School of Nanjing University, Nanjing 210000, China.,Joint Research Center for Bone and Joint Disease, Model Animal Research Center (MARC), Nanjing University, Nanjing 210093, China
| | - Qing Jiang
- Department of Sports Medicine and Adult Reconstructive Surgery, Drum Tower Hospital affiliated to Medical School of Nanjing University, Nanjing 210000, China.,Joint Research Center for Bone and Joint Disease, Model Animal Research Center (MARC), Nanjing University, Nanjing 210093, China
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29
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Statistical shape modeling characterizes three-dimensional shape and alignment variability in the lumbar spine. J Biomech 2018; 69:146-155. [DOI: 10.1016/j.jbiomech.2018.01.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 12/15/2017] [Accepted: 01/14/2018] [Indexed: 11/15/2022]
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30
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Peng Y, Zhang Z, Gao Y, Chen Z, Xin H, Zhang Q, Fan X, Jin Z. Concurrent prediction of ground reaction forces and moments and tibiofemoral contact forces during walking using musculoskeletal modelling. Med Eng Phys 2018; 52:31-40. [DOI: 10.1016/j.medengphy.2017.11.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 11/02/2017] [Accepted: 11/22/2017] [Indexed: 11/25/2022]
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31
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Woods C, Fernee C, Browne M, Zakrzewski S, Dickinson A. The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research. PLoS One 2017; 12:e0186754. [PMID: 29216199 PMCID: PMC5720725 DOI: 10.1371/journal.pone.0186754] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2017] [Accepted: 10/07/2017] [Indexed: 01/15/2023] Open
Abstract
This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets.
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Affiliation(s)
- Christopher Woods
- Bioengineering Sciences Research Group, University of Southampton, Highfield Campus, Highfield, Southampton, United Kingdom
| | - Christianne Fernee
- Department of Archaeology, University of Southampton, Avenue Campus, Highfield, Southampton, United Kingdom
| | - Martin Browne
- Bioengineering Sciences Research Group, University of Southampton, Highfield Campus, Highfield, Southampton, United Kingdom
| | - Sonia Zakrzewski
- Department of Archaeology, University of Southampton, Avenue Campus, Highfield, Southampton, United Kingdom
| | - Alexander Dickinson
- Bioengineering Sciences Research Group, University of Southampton, Highfield Campus, Highfield, Southampton, United Kingdom
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32
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An Approach to Developing Customized Total Knee Replacement Implants. JOURNAL OF HEALTHCARE ENGINEERING 2017; 2017:9298061. [PMID: 29238512 PMCID: PMC5697132 DOI: 10.1155/2017/9298061] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 10/09/2017] [Indexed: 11/21/2022]
Abstract
Total knee replacement (TKR) has been performed for patients with end-stage knee joint arthritis to relieve pain and gain functions. Most knee replacement patients can gain satisfactory knee functions; however, the range of motion of the implanted knee is variable. There are many designs of TKR implants; it has been suggested by some researchers that customized implants could offer a better option for patients. Currently, the 3-dimensional knee model of a patient can be created from magnetic resonance imaging (MRI) or computed tomography (CT) data using image processing techniques. The knee models can be used for patient-specific implant design, biomechanical analysis, and creating bone cutting guide blocks. Researchers have developed patient-specific musculoskeletal lower limb model with total knee replacement, and the models can be used to predict muscle forces, joint forces on knee condyles, and wear of tibial polyethylene insert. These available techniques make it feasible to create customized implants for individual patients. Methods and a workflow of creating a customized total knee replacement implant for improving TKR kinematics and functions are discussed and presented in this paper.
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33
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Smoger LM, Shelburne KB, Cyr AJ, Rullkoetter PJ, Laz PJ. Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking. J Biomech 2017; 58:187-194. [PMID: 28554493 PMCID: PMC5532741 DOI: 10.1016/j.jbiomech.2017.05.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Revised: 04/12/2017] [Accepted: 05/08/2017] [Indexed: 12/16/2022]
Abstract
Complications in the patellofemoral (PF) joint of patients with total knee replacements include patellar subluxation and dislocation, and remain a cause for revision. Kinematic measurements to assess these complications and evaluate implant designs require the accuracy of dynamic stereo-radiographic systems with 3D-2D registration techniques. While tibiofemoral kinematics are typically derived by tracking metallic implants, PF kinematic measurements are difficult as the patellar implant is radiotransparent and a representation of the resected patella bone requires either pre-surgical imaging and precise implant placement or post-surgical imaging. Statistical shape models (SSMs), used to characterize anatomic variation, provide an alternative means to obtain the representation of the resected patella for use in kinematic tracking. Using a virtual platform of a stereo-radiographic system, the objectives of this study were to evaluate the ability of an SSM to predict subject-specific 3D implanted patellar geometries from simulated 2D image profiles, and to formulate an effective data collection methodology for PF kinematics by considering accuracy for a variety of patient pose scenarios. An SSM of the patella was developed for 50 subjects and a leave-one-out approach compared SSM-predicted and actual geometries; average 3D errors were 0.45±0.07mm (mean±standard deviation), which is comparable to the accuracy of traditional segmentation. Further, initial imaging of the patella in five unique stereo radiographic perspectives yielded the most accurate representation. The ability to predict the remaining patellar geometry of the implanted PF joint with radiographic images and SSM, instead of CT, can reduce radiation exposure and streamline in vivo kinematic evaluations.
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Affiliation(s)
- Lowell M Smoger
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - Kevin B Shelburne
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - Adam J Cyr
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - Paul J Rullkoetter
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - Peter J Laz
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA.
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34
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Zhang J, Besier TF. Accuracy of femur reconstruction from sparse geometric data using a statistical shape model. Comput Methods Biomech Biomed Engin 2016; 20:566-576. [PMID: 27998170 DOI: 10.1080/10255842.2016.1263301] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Sparse geometric information from limited field-of-view medical images is often used to reconstruct the femur in biomechanical models of the hip and knee. However, the full femur geometry is needed to establish boundary conditions such as muscle attachment sites and joint axes which define the orientation of joint loads. Statistical shape models have been used to estimate the geometry of the full femur from varying amounts of sparse geometric information. However, the effect that different amounts of sparse data have on reconstruction accuracy has not been systematically assessed. In this study, we compared shape model and linear scaling reconstruction of the full femur surface from varying proportions of proximal and distal partial femur geometry in combination with morphometric and landmark data. We quantified reconstruction error in terms of surface-to-surface error as well as deviations in the reconstructed femur's anatomical coordinate system which is important for biomechanical models. Using a partial proximal femur surface, mean shape model-based reconstruction surface error was 1.8 mm with 0.15° or less anatomic axis error, compared to 19.1 mm and 2.7-5.6° for linear scaling. Similar results were found when using a partial distal surface. However, varying amounts of proximal or distal partial surface data had a negligible effect on reconstruction accuracy. Our results show that given an appropriate set of sparse geometric data, a shape model can reconstruct full femur geometry with far greater accuracy than simple scaling.
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Affiliation(s)
- Ju Zhang
- a Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand
| | - Thor F Besier
- a Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand.,b Department of Engineering Science , University of Auckland , Auckland , New Zealand
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35
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Zhang J, Fernandez J, Hislop-Jambrich J, Besier TF. Lower limb estimation from sparse landmarks using an articulated shape model. J Biomech 2016; 49:3875-3881. [DOI: 10.1016/j.jbiomech.2016.10.021] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2015] [Revised: 07/08/2016] [Accepted: 10/16/2016] [Indexed: 10/20/2022]
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36
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Mangado N, Piella G, Noailly J, Pons-Prats J, Ballester MÁG. Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation. Front Bioeng Biotechnol 2016; 4:85. [PMID: 27872840 PMCID: PMC5097915 DOI: 10.3389/fbioe.2016.00085] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 10/19/2016] [Indexed: 11/13/2022] Open
Abstract
Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.
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Affiliation(s)
- Nerea Mangado
- Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain
| | - Gemma Piella
- Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain
| | - Jérôme Noailly
- Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain
| | - Jordi Pons-Prats
- International Center for Numerical Methods in Engineering (CIMNE) , Barcelona , Spain
| | - Miguel Ángel González Ballester
- Simbiosys Group, Universitat Pompeu Fabra, Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
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37
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Automated finite element modeling of the lumbar spine: Using a statistical shape model to generate a virtual population of models. J Biomech 2016; 49:2593-2599. [DOI: 10.1016/j.jbiomech.2016.05.013] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Revised: 03/22/2016] [Accepted: 05/15/2016] [Indexed: 11/20/2022]
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38
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Fernandez J, Zhang J, Heidlauf T, Sartori M, Besier T, Röhrle O, Lloyd D. Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling. Interface Focus 2016; 6:20150084. [PMID: 27051510 DOI: 10.1098/rsfs.2015.0084] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.
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Affiliation(s)
- J Fernandez
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - J Zhang
- Auckland Bioengineering Institute , University of Auckland , Auckland , New Zealand
| | - T Heidlauf
- Institut für Mechanik (Bau) , University of Stuttgart , Stuttgart , Germany
| | - M Sartori
- Department of Neurorehabilitation Engineering , University Medical Center Göttingen , Göttingen , Germany
| | - T Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - O Röhrle
- Institut für Mechanik (Bau) , University of Stuttgart , Stuttgart , Germany
| | - D Lloyd
- Centre for Musculoskeletal Research, Menzies Health Institute Queensland, Griffith University, Queensland, Australia; School of Rehabilitation Sciences, Griffith University, Queensland, Australia
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39
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Abstract
Virtual representations of the knee joint can provide clinicians, scientists, and engineers the tools to explore mechanical functions of the knee and its tissue structures in health and disease. Modeling and simulation approaches such as finite element analysis also provide the possibility to understand the influence of surgical procedures and implants on joint stresses and tissue deformations. A large number of knee joint models are described in the biomechanics literature. However, freely accessible, customizable, and easy-to-use models are scarce. Availability of such models can accelerate clinical translation of simulations, where labor-intensive reproduction of model development steps can be avoided. Interested parties can immediately utilize readily available models for scientific discovery and clinical care. Motivated by this gap, this study aims to describe an open source and freely available finite element representation of the tibiofemoral joint, namely Open Knee, which includes the detailed anatomical representation of the joint's major tissue structures and their nonlinear mechanical properties and interactions. Three use cases illustrate customization potential of the model, its predictive capacity, and its scientific and clinical utility: prediction of joint movements during passive flexion, examining the role of meniscectomy on contact mechanics and joint movements, and understanding anterior cruciate ligament mechanics. A summary of scientific and clinically directed studies conducted by other investigators are also provided. The utilization of this open source model by groups other than its developers emphasizes the premise of model sharing as an accelerator of simulation-based medicine. Finally, the imminent need to develop next-generation knee models is noted. These are anticipated to incorporate individualized anatomy and tissue properties supported by specimen-specific joint mechanics data for evaluation, all acquired in vitro from varying age groups and pathological states.
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Affiliation(s)
- Ahmet Erdemir
- Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA,Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, USA
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40
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Campbell JQ, Petrella AJ. An Automated Method for Landmark Identification and Finite-Element Modeling of the Lumbar Spine. IEEE Trans Biomed Eng 2015; 62:2709-16. [DOI: 10.1109/tbme.2015.2444811] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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41
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Smoger LM, Fitzpatrick CK, Clary CW, Cyr AJ, Maletsky LP, Rullkoetter PJ, Laz PJ. Statistical modeling to characterize relationships between knee anatomy and kinematics. J Orthop Res 2015; 33:1620-30. [PMID: 25991502 PMCID: PMC4591110 DOI: 10.1002/jor.22948] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 05/13/2015] [Indexed: 02/04/2023]
Abstract
The mechanics of the knee are complex and dependent on the shape of the articular surfaces and their relative alignment. Insight into how anatomy relates to kinematics can establish biomechanical norms, support the diagnosis and treatment of various pathologies (e.g., patellar maltracking) and inform implant design. Prior studies have used correlations to identify anatomical measures related to specific motions. The objective of this study was to describe relationships between knee anatomy and tibiofemoral (TF) and patellofemoral (PF) kinematics using a statistical shape and function modeling approach. A principal component (PC) analysis was performed on a 20-specimen dataset consisting of shape of the bone and cartilage for the femur, tibia and patella derived from imaging and six-degree-of-freedom TF and PF kinematics from cadaveric testing during a simulated squat. The PC modes characterized links between anatomy and kinematics; the first mode captured scaling and shape changes in the condylar radii and their influence on TF anterior-posterior translation, internal-external rotation, and the location of the femoral lowest point. Subsequent modes described relations in patella shape and alta/baja alignment impacting PF kinematics. The complex interactions described with the data-driven statistical approach provide insight into knee mechanics that is useful clinically and in implant design.
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Affiliation(s)
- Lowell M. Smoger
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | | | - Chadd W. Clary
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA,University of Kansas, Lawrence, KS, USA,DePuy Synthes, Warsaw, IN, USA
| | - Adam J. Cyr
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA,University of Kansas, Lawrence, KS, USA
| | | | | | - Peter J. Laz
- Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
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42
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Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model. Med Eng Phys 2015; 37:995-1007. [DOI: 10.1016/j.medengphy.2015.08.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2014] [Revised: 07/24/2015] [Accepted: 08/03/2015] [Indexed: 11/21/2022]
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43
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Li JS, Tsai TY, Wang S, Li P, Kwon YM, Freiberg A, Rubash HE, Li G. Prediction of in vivo knee joint kinematics using a combined dual fluoroscopy imaging and statistical shape modeling technique. J Biomech Eng 2015; 136:124503. [PMID: 25320846 DOI: 10.1115/1.4028819] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Accepted: 10/16/2014] [Indexed: 11/08/2022]
Abstract
Using computed tomography (CT) or magnetic resonance (MR) images to construct 3D knee models has been widely used in biomedical engineering research. Statistical shape modeling (SSM) method is an alternative way to provide a fast, cost-efficient, and subject-specific knee modeling technique. This study was aimed to evaluate the feasibility of using a combined dual-fluoroscopic imaging system (DFIS) and SSM method to investigate in vivo knee kinematics. Three subjects were studied during a treadmill walking. The data were compared with the kinematics obtained using a CT-based modeling technique. Geometric root-mean-square (RMS) errors between the knee models constructed using the SSM and CT-based modeling techniques were 1.16 mm and 1.40 mm for the femur and tibia, respectively. For the kinematics of the knee during the treadmill gait, the SSM model can predict the knee kinematics with RMS errors within 3.3 deg for rotation and within 2.4 mm for translation throughout the stance phase of the gait cycle compared with those obtained using the CT-based knee models. The data indicated that the combined DFIS and SSM technique could be used for quick evaluation of knee joint kinematics.
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Inter-subject variability effects on the primary stability of a short cementless femoral stem. J Biomech 2015; 48:1032-42. [DOI: 10.1016/j.jbiomech.2015.01.037] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Revised: 12/20/2014] [Accepted: 01/26/2015] [Indexed: 01/13/2023]
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Bischoff JE, Dai Y, Goodlett C, Davis B, Bandi M. Incorporating population-level variability in orthopedic biomechanical analysis: a review. J Biomech Eng 2014; 136:021004. [PMID: 24337168 DOI: 10.1115/1.4026258] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2013] [Accepted: 12/16/2013] [Indexed: 11/08/2022]
Abstract
Effectively addressing population-level variability within orthopedic analyses requires robust data sets that span the target population and can be greatly facilitated by statistical methods for incorporating such data into functional biomechanical models. Data sets continue to be disseminated that include not just anatomical information but also key mechanical data including tissue or joint stiffness, gait patterns, and other inputs relevant to analysis of joint function across a range of anatomies and physiologies. Statistical modeling can be used to establish correlations between a variety of structural and functional biometrics rooted in these data and to quantify how these correlations change from health to disease and, finally, to joint reconstruction or other clinical intervention. Principal component analysis provides a basis for effectively and efficiently integrating variability in anatomy, tissue properties, joint kinetics, and kinematics into mechanistic models of joint function. With such models, bioengineers are able to study the effects of variability on biomechanical performance, not just on a patient-specific basis but in a way that may be predictive of a larger patient population. The goal of this paper is to demonstrate the broad use of statistical modeling within orthopedics and to discuss ways to continue to leverage these techniques to improve biomechanical understanding of orthopedic systems across populations.
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Andriacchi TP, Favre J, Erhart-Hledik JC, Chu CR. A systems view of risk factors for knee osteoarthritis reveals insights into the pathogenesis of the disease. Ann Biomed Eng 2014; 43:376-87. [PMID: 25224078 DOI: 10.1007/s10439-014-1117-2] [Citation(s) in RCA: 91] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2014] [Accepted: 09/06/2014] [Indexed: 01/05/2023]
Abstract
Early detection of osteoarthritis (OA) remains a critical yet unsolved multifaceted problem. To address the multifaceted nature of OA a systems model was developed to consolidate a number of observations on the biological, mechanical and structural components of OA and identify features common to the primary risk factors for OA (aging, obesity and joint trauma) that are present prior to the development of clinical OA. This analysis supports a unified view of the pathogenesis of OA such that the risk for developing OA emerges when one of the components of the disease (e.g., mechanical) becomes abnormal, and it is the interaction with the other components (e.g., biological and/or structural) that influences the ultimate convergence to cartilage breakdown and progression to clinical OA. The model, applied in a stimulus-response format, demonstrated that a mechanical stimulus at baseline can enhance the sensitivity of a biomarker to predict cartilage thinning in a 5 year follow-up in patients with knee OA. The systems approach provides new insight into the pathogenesis of the disease and offers the basis for developing multidisciplinary studies to address early detection and treatment at a stage in the disease where disease modification has the greatest potential for a successful outcome.
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Affiliation(s)
- Thomas P Andriacchi
- Department of Mechanical Engineering, Stanford University, Durand 227, Stanford, CA, 94305, USA,
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