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 Various Knee Model Measurement Techniques to Find the Knee Geometries

2016 ◽  
Vol 3 (3) ◽  
pp. 4-6
Author(s):  
Kavinaya C ◽  
Ashuthoshkumar L
Keyword(s):  
Computational Models ◽  
Measurement Techniques ◽  
Knee Kinematics ◽  
Load Measurement ◽  
Knee Simulator ◽  
Subject Specific ◽  
The Subject ◽  
Model Measurement

Computation of knee modeling is a subject-specific techniquethatdefining the zero-load measurements of the cruciate and indemnity ligaments.The dynamic knee simulator was used to test the three carcass knees. The carcass knees also experiencedphysicalsachet of motion testing to discovery their inactivesort of motion in order to regulate the zero-load measurements for everymuscle bundle. Compotation multibody knee representations were shaped for each knee and classical kinematics were likened to investigational kinematics for a replicated walk series. Simple-minded non-linear mechanisminhibition elements were used to characterize cruciate and deposited particles in musclepackages in the knee representations. This learningoriginate that knee kinematics was enormously sensitive to changing of the zero-load measurement. The domino effects also recommendoptimum methods for describing each of the muscle bundle zero-load measurements, irrespective of the subject. These consequencesvalidate the significance ofthe zero-load length when modeling the knee united and verify that physicalcloak of motion dimensions can be usedto determine the passive range of motion of the knee joint. It is also supposed that the method defined here forresponsible zero-load measurement can be used for in vitro or in vivo subject-specific computational models.

Modeling of a Dynamic Knee Simulator With Advanced PID Controller to Evaluate Joint Loading Conditions

2014 ◽  
Author(s):  
Fallon Fitzwater ◽  
Amber Lenz ◽  
Lorin Maletsky
Keyword(s):  
Computational Models ◽  
Total Joint Replacement ◽  
External Loading ◽  
Loading Conditions ◽  
Dynamic Simulations ◽  
Knee Simulator ◽  
Joint Loads ◽  
External Loads

In-vitro dynamic knee simulators allow researchers to investigate changes in natural knee biomechanics due to pathologies, injuries or total joint replacement. The advent of the instrumented tibia, which directly measures knee loads in-vivo, has provided a wealth data for various activities that in-vitro studies now aim to replicate [1, 2]. Dynamic knee simulators, such as the Kansas Knee Simulator (KKS), achieve these physiological loads at the joint by applying external loads to either bone ends or musculature. Determining the external loading conditions necessary to replicate activity specific joint loads, obtained from instrumented tibia data, during dynamic simulations are calculated using 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.

scholarly journals An Evidence-Based Systematic Review of Human Knee Post-Traumatic Osteoarthritis (PTOA): Timeline of Clinical Presentation and Disease Markers, Comparison of Knee Joint PTOA Models and Early Disease Implications

2021 ◽  
Vol 22 (4) ◽  
pp. 1996 ◽  
Author(s):  
Christine M. Khella ◽  
Rojiar Asgarian ◽  
Judith M. Horvath ◽  
Bernd Rolauffs ◽  
Melanie L. Hart
Keyword(s):  
Synovial Fluid ◽  
Knee Joint ◽  
Ex Vivo ◽  
Disease Process ◽  
Early Disease ◽  
Knee Trauma ◽  
Post Traumatic ◽  
Acute Knee

Understanding the causality of the post-traumatic osteoarthritis (PTOA) disease process of the knee joint is important for diagnosing early disease and developing new and effective preventions or treatments. The aim of this review was to provide detailed clinical data on inflammatory and other biomarkers obtained from patients after acute knee trauma in order to (i) present a timeline of events that occur in the acute, subacute, and chronic post-traumatic phases and in PTOA, and (ii) to identify key factors present in the synovial fluid, serum/plasma and urine, leading to PTOA of the knee in 23–50% of individuals who had acute knee trauma. In this context, we additionally discuss methods of simulating knee trauma and inflammation in in vivo, ex vivo articular cartilage explant and in vitro chondrocyte models, and answer whether these models are representative of the clinical inflammatory stages following knee trauma. Moreover, we compare the pro-inflammatory cytokine concentrations used in such models and demonstrate that, compared to concentrations in the synovial fluid after knee trauma, they are exceedingly high. We then used the Bradford Hill Framework to present evidence that TNF-α and IL-6 cytokines are causal factors, while IL-1β and IL-17 are credible factors in inducing knee PTOA disease progresssion. Lastly, we discuss beneficial infrastructure for future studies to dissect the role of local vs. systemic inflammation in PTOA progression with an emphasis on early disease.

Current trends in mathematical modeling of tumor–microenvironment interactions: a survey of tools and applications

2010 ◽  
Vol 235 (4) ◽  
pp. 411-423 ◽  
Author(s):  
Katarzyna A Rejniak ◽  
Lisa J McCawley
Keyword(s):  
Mathematical Modeling ◽  
Protein Interactions ◽  
Computational Models ◽  
Chemical Species ◽  
Tumor Stroma ◽  
Cellular Functions ◽  
Complex Interactions ◽  
Expanding Population

In its simplest description, a tumor is comprised of an expanding population of transformed cells supported by a surrounding microenvironment termed the tumor stroma. The tumor microcroenvironment has a very complex composition, including multiple types of stromal cells, a dense network of various extracellular matrix (ECM) fibers interpenetrated by the interstitial fluid and gradients of several chemical species that either are dissolved in the fluid or are bound to the ECM structure. In order to study experimentally such complex interactions between multiple players, cancer is dissected and considered at different scales of complexity, such as protein interactions, biochemical pathways, cellular functions or whole organism studies. However, the integration of information acquired from these studies into a common description is as difficult as the disease itself. Computational models of cancer can provide cancer researchers with invaluable tools that are capable of integrating the complexity into organizing principles as well as suggesting testable hypotheses. We will focus in this Minireview on mathematical models in which the whole cell is a main modeling unit. We will present a current stage of such cell-focused mathematical modeling incorporating different stromal components and their interactions with growing tumors, and discuss what modeling approaches can be undertaken to complement the in vivo and in vitro experimentation.

Electrophysiological characterization and computational models of HVC neurons in the zebra finch

2013 ◽  
Vol 110 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Arij Daou ◽  
Matthew T. Ross ◽  
Frank Johnson ◽  
Richard L. Hyson ◽  
Richard Bertram
Keyword(s):  
Computational Models ◽  
Premotor Cortex ◽  
Brain Slices ◽  
Ionic Currents ◽  
Proper Name ◽  
Using Data ◽  
Electrophysiological Characterization

The nucleus HVC (proper name) within the avian analog of mammal premotor cortex produces stereotyped instructions through the motor pathway leading to precise, learned vocalization by songbirds. Electrophysiological characterization of component HVC neurons is an important requirement in building a model to understand HVC function. The HVC contains three neural populations: neurons that project to the RA (robust nucleus of arcopallium), neurons that project to Area X (of the avian basal ganglia), and interneurons. These three populations are interconnected with specific patterns of excitatory and inhibitory connectivity, and they fire with characteristic patterns both in vivo and in vitro. We performed whole cell current-clamp recordings on HVC neurons within brain slices to examine their intrinsic firing properties and determine which ionic currents are responsible for their characteristic firing patterns. We also developed conductance-based models for the different neurons and calibrated the models using data from our brain slice work. These models were then used to generate predictions about the makeup of the ionic currents that are responsible for the different responses to stimuli. These predictions were then tested and verified in the slice using pharmacological manipulations. The model and the slice work highlight roles of a hyperpolarization-activated inward current ( Ih), a low-threshold T-type Ca2+ current ( ICa-T), an A-type K+ current ( IA), a Ca2+-activated K+ current ( ISK), and a Na+-dependent K+ current ( IKNa) in driving the characteristic neural patterns observed in the three HVC neuronal populations. The result is an improved characterization of the HVC neurons responsible for song production in the songbird.

scholarly journals Mending a broken heart: In vitro, in vivo and in silico models of congenital heart disease

2021 ◽  
Vol 14 (3) ◽  
pp. dmm047522
Author(s):  
Abdul Jalil Rufaihah ◽  
Ching Kit Chen ◽  
Choon Hwai Yap ◽  
Citra N. Z. Mattar
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Computational Models ◽  
Developing Heart ◽  
Heterogenous Group ◽  
In Silico Models ◽  
Large Animals

ABSTRACTBirth defects contribute to ∼0.3% of global infant mortality in the first month of life, and congenital heart disease (CHD) is the most common birth defect among newborns worldwide. Despite the significant impact on human health, most treatments available for this heterogenous group of disorders are palliative at best. For this reason, the complex process of cardiogenesis, governed by multiple interlinked and dose-dependent pathways, is well investigated. Tissue, animal and, more recently, computerized models of the developing heart have facilitated important discoveries that are helping us to understand the genetic, epigenetic and mechanobiological contributors to CHD aetiology. In this Review, we discuss the strengths and limitations of different models of normal and abnormal cardiogenesis, ranging from single-cell systems and 3D cardiac organoids, to small and large animals and organ-level computational models. These investigative tools have revealed a diversity of pathogenic mechanisms that contribute to CHD, including genetic pathways, epigenetic regulators and shear wall stresses, paving the way for new strategies for screening and non-surgical treatment of CHD. As we discuss in this Review, one of the most-valuable advances in recent years has been the creation of highly personalized platforms with which to study individual diseases in clinically relevant settings.

scholarly journals The anterolateral ligament is a secondary stabilizer in the knee joint

2019 ◽  
Vol 8 (11) ◽  
pp. 509-517 ◽  
Author(s):  
Kyoung-Tak Kang ◽  
Yong-Gon Koh ◽  
Kyoung-Mi Park ◽  
Chong-Hyuck Choi ◽  
Min Jung ◽  
...  
Keyword(s):  
Knee Joint ◽  
Muscle Activation ◽  
Cruciate Ligament ◽  
Knee Kinematics ◽  
Anterolateral Ligament ◽  
Loading Conditions ◽  
Joint Stability ◽  
Musculoskeletal Models ◽  
Subject Specific ◽  
Cycle Loading

Objectives The aim of this study was to investigate the biomechanical effect of the anterolateral ligament (ALL), anterior cruciate ligament (ACL), or both ALL and ACL on kinematics under dynamic loading conditions using dynamic simulation subject-specific knee models. Methods Five subject-specific musculoskeletal models were validated with computationally predicted muscle activation, electromyography data, and previous experimental data to analyze effects of the ALL and ACL on knee kinematics under gait and squat loading conditions. Results Anterior translation (AT) significantly increased with deficiency of the ACL, ALL, or both structures under gait cycle loading. Internal rotation (IR) significantly increased with deficiency of both the ACL and ALL under gait and squat loading conditions. However, the deficiency of ALL was not significant in the increase of AT, but it was significant in the increase of IR under the squat loading condition. Conclusion The results of this study confirm that the ALL is an important lateral knee structure for knee joint stability. The ALL is a secondary stabilizer relative to the ACL under simulated gait and squat loading conditions. Cite this article: Bone Joint Res 2019;8:509–517.

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