A Subject-Specific Musculoskeletal Modeling Framework to Predict In Vivo Mechanics of Total Knee Arthroplasty

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Marco A. Marra ◽  
Valentine Vanheule ◽  
René Fluit ◽  
Bart H. F. J. M. Koopman ◽  
John Rasmussen ◽  
...  
Keyword(s):  
Knee Kinematics ◽  
Contact Forces ◽  
Grand Challenge ◽  
Modeling Framework ◽  
Trial Simulation ◽  
Subject Specific ◽  
Joint Contact ◽  
Total Knee ◽  
The Right

Musculoskeletal (MS) models should be able to integrate patient-specific MS architecture and undergo thorough validation prior to their introduction into clinical practice. We present a methodology to develop subject-specific models able to simultaneously predict muscle, ligament, and knee joint contact forces along with secondary knee kinematics. The MS architecture of a generic cadaver-based model was scaled using an advanced morphing technique to the subject-specific morphology of a patient implanted with an instrumented total knee arthroplasty (TKA) available in the fifth “grand challenge competition to predict in vivo knee loads” dataset. We implemented two separate knee models, one employing traditional hinge constraints, which was solved using an inverse dynamics technique, and another one using an 11-degree-of-freedom (DOF) representation of the tibiofemoral (TF) and patellofemoral (PF) joints, which was solved using a combined inverse dynamic and quasi-static analysis, called force-dependent kinematics (FDK). TF joint forces for one gait and one right-turn trial and secondary knee kinematics for one unloaded leg-swing trial were predicted and evaluated using experimental data available in the grand challenge dataset. Total compressive TF contact forces were predicted by both hinge and FDK knee models with a root-mean-square error (RMSE) and a coefficient of determination (R2) smaller than 0.3 body weight (BW) and equal to 0.9 in the gait trial simulation and smaller than 0.4 BW and larger than 0.8 in the right-turn trial simulation, respectively. Total, medial, and lateral TF joint contact force predictions were highly similar, regardless of the type of knee model used. Medial (respectively lateral) TF forces were over- (respectively, under-) predicted with a magnitude error of M < 0.2 (respectively > −0.4) in the gait trial, and under- (respectively, over-) predicted with a magnitude error of M > −0.4 (respectively < 0.3) in the right-turn trial. Secondary knee kinematics from the unloaded leg-swing trial were overall better approximated using the FDK model (average Sprague and Geers' combined error C = 0.06) than when using a hinged knee model (C = 0.34). The proposed modeling approach allows detailed subject-specific scaling and personalization and does not contain any nonphysiological parameters. This modeling framework has potential applications in aiding the clinical decision-making in orthopedics procedures and as a tool for virtual implant design.

scholarly journals Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Trent M. Guess ◽  
Antonis P. Stylianou ◽  
Mohammad Kia
Keyword(s):  
Femoral Component ◽  
Gait Cycle ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Grand Challenge ◽  
Subject Specific ◽  
The Right ◽  
Anterior Posterior ◽  
Rms Errors

Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the “Grand Challenge Competition to Predict in-vivo Knee Loads” for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, “Grand Challenge Competition to Predict in vivo Knee Loads,” J. Orthop. Res., 30, pp. 503–513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.

scholarly journals Prediction of knee loading in native knee and total knee arthroplasty : a forward dynamics computational study

2019 ◽  
Author(s):  
◽  
Swithin Samuel Razu
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Muscle Forces ◽  
Model Predictions ◽  
Subject Specific ◽  
Joint Contact ◽  
Total Knee

"The goal of this dissertation is to develop a musculoskeletal model and corroborate model predictions to experimentally measured in vivo knee contact forces, in order to study the biomechanical consequences of two different total knee arthroplasty designs. The two main contributions of this dissertation are: (1) Corroboration to experimental data: The development of an EMG-driven, full-body, musculoskeletal model with subject-specific leg geometries including deformable contacts, ligaments, 6DOF knee joint, and a shoe-floor model that can concurrently predict muscle forces, ligament forces, and joint contact forces. Model predictions of tibiofemoral joint contact forces were evaluated against the subject-specific in vivo measurements from the instrumented TKR for three distinctly different styles of over ground gait. (2) Virtual surgery in TKA: The musculoskeletal modeling methodology was then used to develop a model for one healthy participant with a native knee and then virtually replacing the native knee with fixed-bearing and mobile-bearing total knee arthroplasty designs performing gait and step-up tasks. This approach minimized the biomechanical impact of variations in sex, geometry, implant size, design and positioning, ligament location and tension, and muscle forces found across patients. The differences in biomechanics were compared for the two designs. 1.2 Significance of this Research The world health organization ranks musculoskeletal disorders as the second largest contributor to disability worldwide. Conservative estimates put the national cost of direct care for musculoskeletal disease at $212.7 billion a year [1]. Many people who suffer from neuromuscular or musculoskeletal diseases may benefit from the insights gained from surgery simulations, since musculoskeletal reconstructions are commonly performed on these individuals. Improved surgical outcomes will benefit these individuals not only in the short-term, but also in the long-term, since their future rehabilitation needs may be reduced. For example, although total knee arthroplasty is a common surgical procedure for the treatment of osteoarthritis with over 700,000 procedures performed each year [2], many patients are unhappy with the ultimate results [3]. Ten to 30% of patients report [4] pain, dissatisfaction with function, and the need for further surgery such as revision after the initial surgery resulting in costs exceeding $11 billion [5]. Potentially, simulation studies that quantify the important biomechanical variables will reduce the need for revision surgeries in patients."--Introduction.

Intra-Articular Knee Contact Force Estimation During Walking Using Force-Reaction Elements and Subject-Specific Joint Model2

2016 ◽  
Vol 138 (2) ◽  
Author(s):  
Yihwan Jung ◽  
Cong-Bo Phan ◽  
Seungbum Koo
Keyword(s):  
Contact Force ◽  
Inverse Dynamics ◽  
Reaction Force ◽  
Muscle Tension ◽  
Contact Forces ◽  
Contact Model ◽  
Grand Challenge ◽  
Subject Specific ◽  
Mean Square Errors

Joint contact forces measured with instrumented knee implants have not only revealed general patterns of joint loading but also showed individual variations that could be due to differences in anatomy and joint kinematics. Musculoskeletal human models for dynamic simulation have been utilized to understand body kinetics including joint moments, muscle tension, and knee contact forces. The objectives of this study were to develop a knee contact model which can predict knee contact forces using an inverse dynamics-based optimization solver and to investigate the effect of joint constraints on knee contact force prediction. A knee contact model was developed to include 32 reaction force elements on the surface of a tibial insert of a total knee replacement (TKR), which was embedded in a full-body musculoskeletal model. Various external measurements including motion data and external force data during walking trials of a subject with an instrumented knee implant were provided from the Sixth Grand Challenge Competition to Predict in vivo Knee Loads. Knee contact forces in the medial and lateral portions of the instrumented knee implant were also provided for the same walking trials. A knee contact model with a hinge joint and normal alignment could predict knee contact forces with root mean square errors (RMSEs) of 165 N and 288 N for the medial and lateral portions of the knee, respectively, and coefficients of determination (R2) of 0.70 and −0.63. When the degrees-of-freedom (DOF) of the knee and locations of leg markers were adjusted to account for the valgus lower-limb alignment of the subject, RMSE values improved to 144 N and 179 N, and R2 values improved to 0.77 and 0.37, respectively. The proposed knee contact model with subject-specific joint model could predict in vivo knee contact forces with reasonable accuracy. This model may contribute to the development and improvement of knee arthroplasty.

The Effect of the Tibiofemoral Contact Path Centroid Location on TKR Contact Forces

2010 ◽  
Author(s):  
Hannah J. Lundberg ◽  
Markus A. Wimmer
Keyword(s):  
Knee Joint ◽  
Tibial Plateau ◽  
Soft Tissues ◽  
Three Dimensional ◽  
Solution Space ◽  
Contact Forces ◽  
Detailed Knowledge ◽  
Joint Contact ◽  
Total Knee

Detailed knowledge of in vivo knee contact forces and the contribution from muscles, ligaments, and other soft-tissues to knee joint function are essential for evaluating total knee replacement (TKR) designs. We have recently developed a mathematical model for calculating knee joint contact forces using parametric methodology (Lundberg et al., 2009). The numerical model calculates a “solution space” of three-dimensional contact forces for both the medial and lateral compartments of the tibial plateau. The solution spaces are physiologically meaningful, and represent the result of balancing the external moments and forces by different strategies.

Calculated Axial Forces at the Knee in Total Knee Replacement Patients During Chair and Stair Activities

2012 ◽  
Author(s):  
Hannah J. Lundberg ◽  
Christopher B. Knowlton ◽  
Diego Orozco ◽  
Markus A. Wimmer
Keyword(s):  
Total Knee Replacement ◽  
Knee Replacement ◽  
Contact Forces ◽  
Force Output ◽  
Stair Ascent ◽  
Numeric Model ◽  
Axial Forces ◽  
Joint Contact ◽  
Total Knee

Knowledge of in vivo knee contact forces is essential for evaluating total knee replacement (TKR) designs. This is particularly true for activities other than walking, because there is still a limited understanding of its impact on wear. It has been shown that wear scars from retrieved implants have obvious differences compared with simulator tested components in both size of worn area and in damage mode. The divergence could be related to the omission of other activities than walking when testing components in the simulator. The purpose of this study was to use a parametric numerical model for predicting joint contact forces during stair ascent/descent and chair sitting/rising and compare those to measured forces from a database. We hypothesized that the contact force output of the numeric model would be similar to the measured forces.

Influence of the Level of Muscular Redundancy on the Validity of a Musculoskeletal Model

2016 ◽  
Vol 138 (2) ◽  
Author(s):  
Florent Moissenet ◽  
Laurence Chèze ◽  
Raphaël Dumas
Keyword(s):  
Gait Pattern ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Generic Model ◽  
Grand Challenge ◽  
Contact Points ◽  
Lateral Contact ◽  
Musculoskeletal Models ◽  
Joint Contact

While recent literature has clearly demonstrated that an extensive personalization of the musculoskeletal models was necessary to reach high accuracy, several components of the generic models may be further investigated before defining subject-specific parameters. Among others, the choice in muscular geometry and thus the level of muscular redundancy in the model may have a noticeable influence on the predicted musculotendon and joint contact forces. In this context, the aim of this study was to investigate if the level of muscular redundancy can contribute or not to reduce inaccuracies in tibiofemoral contact forces predictions. For that, the dataset disseminated through the Sixth Grand Challenge Competition to Predict In Vivo Knee Loads was applied to a versatile 3D lower limb musculoskeletal model in which two muscular geometries (i.e., two different levels of muscular redundancy) were implemented. This dataset provides tibiofemoral implant measurements for both medial and lateral compartments and thus allows evaluation of the validity of the model predictions. The results suggest that an increase of the level of muscular redundancy corresponds to a better accuracy of total tibiofemoral contact force whatever the gait pattern investigated. However, the medial and lateral contact forces ratio and accuracy were not necessarily improved when increasing the level of muscular redundancy and may thus be attributed to other parameters such as the location of contact points. To conclude, the muscular geometry, among other components of the generic model, has a noticeable impact on joint contact forces predictions and may thus be correctly chosen even before trying to personalize the model.

scholarly journals An Electromyogram-Driven Musculoskeletal Model of the Knee to Predict in Vivo Joint Contact Forces During Normal and Novel Gait Patterns

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Kurt Manal ◽  
Thomas S. Buchanan
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Contact Forces ◽  
Grand Challenge ◽  
Normal Walking ◽  
Gait Patterns ◽  
Internal Joint ◽  
Model Predictions ◽  
Joint Contact

Computational models that predict internal joint forces have the potential to enhance our understanding of normal and pathological movement. Validation studies of modeling results are necessary if such models are to be adopted by clinicians to complement patient treatment and rehabilitation. The purposes of this paper are: (1) to describe an electromyogram (EMG)-driven modeling approach to predict knee joint contact forces, and (2) to evaluate the accuracy of model predictions for two distinctly different gait patterns (normal walking and medial thrust gait) against known values for a patient with a force recording knee prosthesis. Blinded model predictions and revised model estimates for knee joint contact forces are reported for our entry in the 2012 Grand Challenge to predict in vivo knee loads. The EMG-driven model correctly predicted that medial compartment contact force for the medial thrust gait increased despite the decrease in knee adduction moment. Model accuracy was high: the difference in peak loading was less than 0.01 bodyweight (BW) with an R2 = 0.92. The model also predicted lateral loading for the normal walking trial with good accuracy exhibiting a peak loading difference of 0.04 BW and an R2 = 0.44. Overall, the EMG-driven model captured the general shape and timing of the contact force profiles and with accurate input data the model estimated joint contact forces with sufficient accuracy to enhance the interpretation of joint loading beyond what is possible from data obtained from standard motion capture studies.

scholarly journals Evaluation of a Surrogate Contact Model in Force-Dependent Kinematic Simulations of Total Knee Replacement

2017 ◽  
Vol 139 (8) ◽  
Author(s):  
Marco A. Marra ◽  
Michael S. Andersen ◽  
Michael Damsgaard ◽  
Bart F. J. M. Koopman ◽  
Dennis Janssen ◽  
...  
Keyword(s):  
Total Knee Replacement ◽  
Knee Replacement ◽  
Reference Model ◽  
Knee Kinematics ◽  
Contact Model ◽  
Related Factors ◽  
Joint Contact ◽  
Total Knee ◽  
Parametric Analyses

Knowing the forces in the human body is of great clinical interest and musculoskeletal (MS) models are the most commonly used tool to estimate them in vivo. Unfortunately, the process of computing muscle, joint contact, and ligament forces simultaneously is computationally highly demanding. The goal of this study was to develop a fast surrogate model of the tibiofemoral (TF) contact in a total knee replacement (TKR) model and apply it to force-dependent kinematic (FDK) simulations of activities of daily living (ADLs). Multiple domains were populated with sample points from the reference TKR contact model, based on reference simulations and design-of-experiments. Artificial neural networks (ANN) learned the relationship between TF pose and loads from the medial and lateral sides of the TKR implant. Normal and right-turn gait, rising-from-a-chair, and a squat were simulated using both surrogate and reference contact models. Compared to the reference contact model, the surrogate contact model predicted TF forces with a root-mean-square error (RMSE) lower than 10 N and TF moments lower than 0.3 N·m over all simulated activities. Secondary knee kinematics were predicted with RMSE lower than 0.2 mm and 0.2 deg. Simulations that used the surrogate contact model ran on average three times faster than those using the reference model, allowing the simulation of a full gait cycle in 4.5 min. This modeling approach proved fast and accurate enough to perform extensive parametric analyses, such as simulating subject-specific variations and surgical-related factors in TKR.

Grand Challenge Competition: A Parametric Numerical Model to Predict In Vivo Medial and Lateral Knee Forces in Walking Gaits

2012 ◽  
Author(s):  
Christopher B. Knowlton ◽  
Markus A. Wimmer ◽  
Hannah J. Lundberg
Keyword(s):  
Knee Joint ◽  
Computational Models ◽  
Soft Tissues ◽  
Numerical Models ◽  
Contact Forces ◽  
Grand Challenge ◽  
Total Knee Replacements ◽  
Lateral Contact ◽  
Total Knee

Numerical models are necessary to estimate forces through the knee joint during activities of daily living. However, the numerous muscles and soft tissues crossing the knee joint result in a computationally indeterminate problem. The recent availability of measured contact force data from telemeterized total knee replacements (TKRs) has given researchers the chance to validate models, but telemeterized TKRs represent only a few patients with a specific implant type. Computational models remain necessary to bridge the gap between the small instrumented patient population with a particular implant and larger patient populations executing various activities. Abstracted gait data from another lab tests the versatility of any model to accurately predict forces of TKR patients performing a variety of gaits with disparate implant types. In this study, we calculate and examine the differences between medial and lateral contact forces in level walking and medial thrust gait trials from a freely provided dataset1.

Elevated Joint Contact Forces in ACL-Reconstructed Knees: A Finite Element Analysis Driven by In Vivo Kinematic Data

2003 ◽  
Author(s):  
George Papaioannou ◽  
William Anderst ◽  
Scott Tashman
Keyword(s):  
Finite Element ◽  
High Speed ◽  
Knee Kinematics ◽  
Poor Quality ◽  
Contact Forces ◽  
Element Analysis ◽  
Human Cartilage ◽  
Joint Contact ◽  
Contact Pressures

Assessment of in vivo human cartilage loading generally requires computer modeling, since loads usually cannot be directly measured. The utility of these models for assessing knee behavior during complex activities has been limited by the relatively poor quality of experimental data on in vivo knee function. We have developed a method combining high-accuracy knee kinematics (from high-speed stereo-radiography) with subject-specific finite-element models to estimate in vivo cartilage contact pressures during stressful tasks. When applied to ACL reconstruction, significantly higher contact pressures were found in reconstructed knees as compared to the contralateral (uninjured) knees of the same individuals.

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