scholarly journals A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Michael D. Harris ◽  
Adam J. Cyr ◽  
Azhar A. Ali ◽  
Clare K. Fitzpatrick ◽  
Paul J. Rullkoetter ◽  
...  
Keyword(s):  
Knee Joint ◽  
Knee Laxity ◽  
Experimental Tests ◽  
Population Based ◽  
Knee Mechanics ◽  
Ligament Strain ◽  
Subject Specific ◽  
Joint Biomechanics ◽  
The Individual

Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community.

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
David Leandro Dejtiar ◽  
Christine Mary Dzialo ◽  
Peter Heide Pedersen ◽  
Kenneth Krogh Jensen ◽  
Martin Kokholm Fleron ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Knee Joint ◽  
Joint Model ◽  
Joint Kinematics ◽  
Contact Forces ◽  
Joint Mechanics ◽  
X Ray ◽  
Knee Mechanics ◽  
Subject Specific

Abstract Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.

Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke

2014 ◽  
pp. 161-180
Author(s):  
Hujing Hu ◽  
Le Li
Keyword(s):  
Voluntary Movement ◽  
Imaging Techniques ◽  
Movement Trajectory ◽  
Fitting Procedure ◽  
Emg Signal ◽  
Subject Specific ◽  
Elbow Movement ◽  
The Individual ◽  
Neuromusculoskeletal Modeling

Neuromusculoskeletal modeling provides insights into the muscular system which are not always obtained through experiment or observation alone. One of the major challenges in neuromusculoskeletal modeling is to accurately estimate the musculotendon parameters on a subject-specific basis. The latest medical imaging techniques such as ultrasound for the estimation of musculotendon parameters would provide an alternative method to obtain the muscle architecture parameters noninvasively. In this chapter, the feasibility of using ultrasonography to measure the musculotendon parameters of elbow muscles is validated. These parameters help to build a subject-specific EMG-driven model, which could predict the individual muscle force and elbow voluntary movement trajectory using the input of EMG signal without any trajectory fitting procedure involved. The results demonstrate the feasibility of using EMG-driven neuromusculoskeletal modeling with ultrasound-measured data for prediction of voluntary elbow movement for both unimpaired subjects and persons after stroke.

PATELLA TRACKING WITH PERIPATELLAR SOFT TISSUE STABILIZERS AS A FUNCTION OF DYNAMIC SUBJECT-SPECIFIC KNEE FLEXION

2011 ◽  
Vol 11 (05) ◽  
pp. 1025-1043 ◽  
Author(s):  
J. H. MÜLLER ◽  
C. SCHEFFER ◽  
A. ELVIN ◽  
P. J. ERASMUS ◽  
E. M. DILLON
Keyword(s):  
Knee Flexion ◽  
Load Ratio ◽  
Quadriceps Tendon ◽  
Musculoskeletal Modeling ◽  
Musculoskeletal Models ◽  
Subject Specific ◽  
Joint Biomechanics ◽  
Load Component ◽  
Patella Tracking

Musculoskeletal modeling has found wide application in joint biomechanics investigations. This technique has been improved by incorporating subject-specific skeletal elements and passive patellofemoral stabilizers in a dynamic analysis. After trochlear engagement, the volunteers' patellae displaced laterally, whereas tilt was subject specific. Comparison of the tilt and mediolateral position values to in vivo MRI values at 30° knee flexion showed a mean accuracy of 84.4% and 96.9%, respectively. Medial patellofemoral ligament tension decreased with knee flexion, while the patellar tendon–quadriceps tendon ratio ranged from 0.4 to 1.2. The patellofemoral contact load–quadriceps tendon load ratio ranged from 0.7 to 1.3, whereas the mediolateral load component–resultant load ratio ranged from 0 to 0.4. Three validated subject-specific musculoskeletal models facilitated the analysis of patellofemoral biomechanics: Subject-specific patella tracking and passive stabilizer response was analyzed as a function of dynamic knee flexion.

An in vivo subject-specific 3D functional knee joint model using combined MR imaging

2012 ◽  
Vol 8 (5) ◽  
pp. 741-750 ◽  
Author(s):  
Bailiang Chen ◽  
Tryphon Lambrou ◽  
Amaka C. Offiah ◽  
Pedro A. Gondim Teixeira ◽  
Martin Fry ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Knee Joint ◽  
Joint Model ◽  
Subject Specific

scholarly journals Validated Computational Framework for Evaluation of In Vivo Knee Mechanics

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Azhar A. Ali ◽  
Erin M. Mannen ◽  
Paul J. Rullkoetter ◽  
Kevin B. Shelburne
Keyword(s):  
Fe Simulation ◽  
Knee Extension ◽  
Musculoskeletal Modeling ◽  
Whole Body ◽  
Knee Ligament ◽  
Knee Mechanics ◽  
Flexion Extension ◽  
Subject Specific ◽  
The Impact

Abstract Dynamic, in vivo evaluations of knee mechanics are important for understanding knee injury and repair, and developing successful treatments. Computational models have been used with in vivo experiments to quantify joint mechanics, but they are typically not predictive. The current study presents a novel integrated approach with high-speed stereo radiography, musculoskeletal modeling, and finite element (FE) modeling for evaluation of subject-specific, in vivo knee mechanics in a healthy subject performing a seated knee extension and weight-bearing lunge. Whole-body motion capture, ground reaction forces, and radiography-based kinematics were used to drive musculoskeletal and predictive FE models for load-controlled simulation of in vivo knee mechanics. A predictive simulation of knee mechanics was developed in four stages: (1) in vivo measurements of one subject performing a lunge and a seated knee extension, (2) rigid-body musculoskeletal modeling to determine muscle forces, (3) FE simulation of knee extension for knee-ligament calibration, and (4) predictive FE simulation of a lunge. FE models predicted knee contact and ligament mechanics and evaluated the impact of cruciate ligament properties on joint kinematics and loading. Calibrated model kinematics demonstrated good agreement to the experimental motion with root-mean-square differences of tibiofemoral flexion–extension &lt;3 deg, internal–external &lt;4 deg, and anterior–posterior &lt;2 mm. Ligament reference strain and attachment locations were the most critical properties in the calibration process. The current work advances previous in vivo knee modeling through simulation of dynamic activities, modeling of subject-specific knee behavior, and development of a load-controlled knee model.

scholarly journals In vivo personalized finite element modeling of the knee joint derived from MRI images

2009 ◽  
pp. 81-92
Author(s):  
Morgan Sangeux ◽  
Frédéric Marin ◽  
Fabrice Charleux ◽  
Marie-Christine Ho Ba Tho
Keyword(s):  
Finite Element ◽  
Knee Joint ◽  
Finite Element Modeling ◽  
Movement Analysis ◽  
Nonlinear Finite Element ◽  
Joint Movement ◽  
Treatment Procedure ◽  
Element Modeling ◽  
Subject Specific

This paper adresses the methodology used to model the knee joint in vivo from MRI images. The knee joint model obtained is subject specific. The paper presents all the treatment procedure: Geometrical acquisitions, Joint movement analysis, Meshing techniques and nonlinear finite element modeling with contact between the bones, the cartilage and the menisci. The model provides the contact pressure applied on the various components of the joint for one normal subject.

scholarly journals Computational Knee Ligament Modeling Using Experimentally Determined Zero-Load Lengths

2012 ◽  
Vol 6 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Katherine H Bloemker ◽  
Trent M Guess ◽  
Lorin Maletsky ◽  
Kevin Dodd
Keyword(s):  
Knee Joint ◽  
Range Of Motion ◽  
Computational Models ◽  
Knee Kinematics ◽  
Specific Method ◽  
Knee Ligament ◽  
Knee Simulator ◽  
Subject Specific

This study presents a subject-specific method of determining the zero-load lengths of the cruciate and collateral ligaments in computational knee modeling. Three cadaver knees were tested in a dynamic knee simulator. The cadaver knees also underwent manual envelope of motion testing to find their passive range of motion in order to determine the zero-load lengths for each ligament bundle. Computational multibody knee models were created for each knee and model kinematics were compared to experimental kinematics for a simulated walk cycle. One-dimensional non-linear spring damper elements were used to represent cruciate and collateral ligament bundles in the knee models. This study found that knee kinematics were highly sensitive to altering of the zero-load length. The results also suggest optimal methods for defining each of the ligament bundle zero-load lengths, regardless of the subject. These results verify the importance of the zero-load length when modeling the knee joint and verify that manual envelope of motion measurements can be used to determine the passive range of motion of the knee joint. It is also believed that the method described here for determining zero-load length can be used for in vitro or in vivo subject-specific computational models.

scholarly journals An Anatomical-Based Subject-Specific Model of In-Vivo Knee Joint 3D Kinematics From Medical Imaging

2020 ◽  
Vol 10 (6) ◽  
pp. 2100 ◽  
Author(s):  
Fabrizio Nardini ◽  
Claudio Belvedere ◽  
Nicola Sancisi ◽  
Michele Conconi ◽  
Alberto Leardini ◽  
...  
Keyword(s):  
Knee Joint ◽  
Spatial Models ◽  
Knee Kinematics ◽  
Specific Model ◽  
Absolute Difference ◽  
Joint Motion ◽  
Parallel Mechanisms ◽  
Biomechanical Models ◽  
Subject Specific

Biomechanical models of the knee joint allow the development of accurate procedures as well as novel devices to restore the joint natural motion. They are also used within musculoskeletal models to perform clinical gait analysis on patients. Among relevant knee models in the literature, the anatomy-based spatial parallel mechanisms represent the joint motion using rigid links for the ligaments’ isometric fibres and point contacts for the articular surfaces. To customize analyses, therapies and devices, there is the need to define subject-specific models, but relevant procedures and their accuracy are still questioned. A procedure is here proposed and validated to define a customized knee model based on a spatial parallel mechanism. Computed tomography, magnetic resonance and 3D-video-fluoroscopy were performed on a healthy volunteer to define the personalized model geometry. The model was then validated by comparing the measured and the replicated joint motion. The model showed mean absolute difference and standard deviations in translations and rotations, respectively of 0.98 ± 0.40 mm and 0.68 ± 0.29 ° for the tibia–femur motion, and of 0.77 ± 0.15 mm and 2.09 ± 0.69 ° for the patella–femur motion. These results show that accurate personalized spatial models of knee kinematics can be obtained from in-vivo imaging.

scholarly journals Predictions of Anterior Cruciate Ligament Dynamics From Subject-Specific Musculoskeletal Models and Dynamic Biplane Radiography

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
James P. Charles ◽  
Freddie H. Fu ◽  
William J. Anderst
Keyword(s):  
Anterior Cruciate Ligament ◽  
Knee Joint ◽  
Cruciate Ligament ◽  
Knee Ligament ◽  
Functional Activities ◽  
Musculoskeletal Models ◽  
Subject Specific ◽  
Force Peak ◽  
Anterior Cruciate

Abstract In vivo knee ligament forces are important to consider for informing rehabilitation or clinical interventions. However, they are difficult to directly measure during functional activities. Musculoskeletal models and simulations have become the primary methods by which to estimate in vivo ligament loading. Previous estimates of anterior cruciate ligament (ACL) forces range widely, suggesting that individualized anatomy may have an impact on these predictions. Using ten subject-specific (SS) lower limb musculoskeletal models, which include individualized musculoskeletal geometry, muscle architecture, and six degree-of-freedom knee joint kinematics from dynamic biplane radiography (DBR), this study provides SS estimates of ACL force (anteromedial-aACL; and posterolateral-pACL bundles) during the full gait cycle of treadmill walking. These forces are compared to estimates from scaled-generic (SG) musculoskeletal models to assess the effect of musculoskeletal knee joint anatomy on predicted forces and the benefit of SS modeling in this context. On average, the SS models demonstrated a double force peak during stance (0.39–0.43 xBW per bundle), while only a single force peak during stance was observed in the SG aACL. No significant differences were observed between continuous SG and SS ACL forces; however, root mean-squared differences between SS and SG predictions ranged from 0.08 xBW to 0.27 xBW, suggesting SG models do not reliably reflect forces predicted by SS models. Force predictions were also found to be highly sensitive to ligament resting length, with ±10% variations resulting in force differences of up to 84%. Overall, this study demonstrates the sensitivity of ACL force predictions to SS anatomy, specifically musculoskeletal joint geometry and ligament resting lengths, as well as the feasibility for generating SS musculoskeletal models for a group of subjects to predict in vivo tissue loading during functional activities.

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