Individual Differences in Women During Walking Affect Tibial Response to Load Carriage: The Importance of Individualized Musculoskeletal Finite-Element Models

Predicting Tibia-Fibula Geometry and Density From Anatomical Landmarks Via Statistical Appearance Model: Influence of Errors on Finite Element-Calculated Bone Strain

State-of-the-art participant-specific finite element models require advanced medical imaging to quantify bone geometry and density distribution; access to and cost of imaging is prohibitive to the use of this approach. Statistical appearance models may enable estimation of participants' geometry and density in the absence of medical imaging. The purpose of this study was to: (1) quantify errors associated with predicting tibia-fibula geometry and density distribution from skin-mounted landmarks using a statistical appearance model and (2) quantify how those errors propagate to finite element-calculated bone strain. Participant-informed models of the tibia and fibula were generated for thirty participants from height and sex and from twelve skin-mounted landmarks using a statistical appearance model. Participant-specific running loads, calculated using gait data and a musculoskeletal model, were applied to participant-informed and CT-based models to predict bone strain using the finite element method. Participant-informed meshes illustrated median geometry and density distribution errors of 4.39-5.17 mm and 0.116-0.142 g/cm3, respectively, resulting in large errors in strain distribution (median RMSE = 476-492 με), peak strain (limits of agreement =±27-34%), and strained volume (limits of agreement =±104-202%). These findings indicate that neither skin-mounted landmark nor height and sex-based predictions could adequately approximate CT-derived participant-specific geometry, density distribution, or finite element-predicted bone strain and therefore should not be used for analyses comparing between groups or individuals.

Biomechanical Consequences of Walking With the Suspended Backpacks

OBJECTIVE

This article aimed to investigate the biomechanical mechanisms underlying the energetic advantages of the suspended backpacks during load carriage.

METHODS

In this study, we examined eight adults walking with a 15 kg load at 5 km/h with a designed suspended backpack, in which the load could be switched to locked and suspended with four combinations of stiffness. Mechanical work and metabolic cost were measured during load carriage.

RESULTS

The results showed that the suspended backpacks led to an average reduction of 23.35% in positive work, 24.77% in negative work, and a 12.51% decrease in metabolic cost across all suspended load conditions. Notably, the decreased mechanical work predominantly occurred during single support (averaging 84.19% and 71.16% for positive and negative work, respectively), rather than during double support.

CONCLUSION

Walking with the suspended backpack induced a phase shift between body movement and load movement, altering the human-load interaction. This adjustment caused the body and load to move against each other, resulting in flatter trajectories of the human-load system center of mass (COM) velocities and corresponding profiles in ground reaction forces (GRFs), along with reduced vertical excursions of the trunk. Consequently, this interplay led to flatter trajectories in mechanical work rate and reduced mechanical work, ultimately contributing to the observed reduction in energetic expenditure.

SIGNIFICANCE

Understanding these mechanisms is essential for the development of more effective load-carrying devices and strategies in various applications, particularly for enhancing walking abilities during load carriage.

Development of a three-dimensional muscle-driven lower limb model developed using an improved CFD-FE method

Analysis of the musculoskeletal movements (gait analysis) is needed in many scenarios. The in vivo method has some difficulties. For example, recruiting human subjects for the gait analysis is challenging due to many issues. In addition, when plenty of subjects are required, the follow-up experiments take a long period and the dropout of subjects always occurs. An efficient and reliable in silico simulation platform for gait analysis has been desired for a long time. Therefore, a technique using three-dimensional (3D) muscle modeling to drive the 3D musculoskeletal model was developed and the application of the technique in the simulation of lower limb movements was demonstrated. A finite element model of the lower limb with anatomically high fidelity was developed from the MRI data, where the main muscles, the bones, the subcutaneous tissues, and the skin were reconstructed. To simulate the active behavior of 3D muscles, an active, fiber-reinforced hyperelastic muscle model was developed using the user-defined material (VUMAT) model. Two typical movements, that is, hip abduction and knee lifting, were simulated by activating the responsible muscles. The results show that it is reasonable to use the improved CFD-FE method proposed in the present study to simulate the active contraction of the muscle, and it is feasible to simulate the movements by activating the relevant muscles. The results from the present technique closely match the physiological scenario and thus the technique developed has a great potential to be used in the in silico human simulation platform for many purposes.

Differences in running biomechanics between young, healthy men and women carrying external loads

During U.S. Army basic combat training (BCT), women are more prone to lower-extremity musculoskeletal injuries, including stress fracture (SF) of the tibia, with injury rates two to four times higher than those in men. There is evidence to suggest that the different injury rates are, in part, due to sex-specific differences in running biomechanics, including lower-extremity joint kinematics and kinetics, which are not fully understood, particularly when running with external load. To address this knowledge gap, we collected computed tomography images and motion-capture data from 41 young, healthy adults (20 women and 21 men) running on an instrumented treadmill at 3.0 m/s with loads of 0.0 kg, 11.3 kg, or 22.7 kg. Using individualized computational models, we quantified the running biomechanics and estimated tibial SF risk over 10 weeks of BCT, for each load condition. Across all load conditions, compared to men, women had a significantly smaller flexion angle at the trunk (16.9%-24.6%) but larger flexion angles at the ankle (14.0%-14.7%). Under load-carriage conditions, women had a larger flexion angle at the hip (17.7%-23.5%). In addition, women had a significantly smaller hip extension moment (11.8%-20.0%) and ankle plantarflexion moment (10.2%-14.3%), but larger joint reaction forces (JRFs) at the hip (16.1%-22.0%), knee (9.1%-14.2%), and ankle (8.2%-12.9%). Consequently, we found that women had a greater increase in tibial strain and SF risk than men as load increases, indicating higher susceptibility to injuries. When load carriage increased from 0.0 kg to 22.7 kg, SF risk increased by about 250% in women but only 133% in men. These results provide quantitative evidence to support the Army's new training and testing doctrine, as it shifts to a more personalized approach that shall account for sex and individual differences.

Tibial-fibular geometry and density variations associated with elevated bone strain and sex disparities in young active adults

Tibial stress fracture is a common injury in runners and military personnel. Elevated bone strain is believed to be associated with the development of stress fractures and is influenced by bone geometry and density. The purpose of this study was to characterize tibial-fibular geometry and density variations in young active adults, and to quantify the influence of these variations on finite element-predicted bone strain. A statistical appearance model characterising tibial-fibular geometry and density was developed from computed tomography scans of 48 young physically active adults. The model was perturbed ±1 and 2 standard deviations along each of the first five principal components to create finite element models. Average male and female finite element models, controlled for scale, were also generated. Muscle and joint forces in running, calculated using inverse dynamics-based static optimization, were applied to the finite element models. The resulting 95th percentile pressure-modified von Mises strain (peak strain) and strained volume (volume of elements above 4000 με) were quantified. Geometry and density variations described by principal components resulted in up to 12.0% differences in peak strain and 95.4% differences in strained volume when compared to the average tibia-fibula model. The average female illustrated 5.5% and 41.3% larger peak strain and strained volume, respectively, when compared to the average male, suggesting that sexual dimorphism in bone geometry may indeed contribute to greater stress fracture risk in females. Our findings identified important features in subject-specific geometry and density associated with elevated bone strain that may have implications for stress fracture risk.

Multidirectional basketball activities load different regions of the tibia: A subject-specific muscle-driven finite element study

The tibia is a common site for bone stress injuries, which are believed to develop from microdamage accumulation to repetitive sub-yield strains. There is a need to understand how the tibia is loaded in vivo to understand how bone stress injuries develop and design exercises to build a more robust bone. Here, we use subject-specific, muscle-driven, finite element simulations of 11 basketball players to calculate strain and strain rate distributions at the midshaft and distal tibia during six activities: walking, sprinting, lateral cut, jumping after landing, changing direction from forward-to-backward sprinting, and changing direction while side shuffling. Maximum compressive strains were at least double maximum tensile strains during the stance phase of all activities. Sprinting and lateral cut had the highest compressive (-2,862 ± 662 με and -2,697 ± 495 με, respectively) and tensile (973 ± 208 με and 942 ± 223 με, respectively) strains. These activities also had the highest strains rates (peak compressive strain rate = 64,602 ± 19,068 με/s and 37,961 ± 14,210 με/s, respectively). Compressive strains principally occurred in the posterior tibia for all activities; however, tensile strain location varied. Activities involving a change in direction increased tensile loads in the anterior tibia. These observations may guide preventative and management strategies for tibial bone stress injuries. In terms of prevention, the strain distributions suggest individuals should perform activities involving changes in direction during growth to adapt different parts of the tibia and develop a more fatigue resistant bone. In terms of management, the greater strain and strain rates during sprinting than jumping suggests jumping activities may be commenced earlier than full pace running. The greater anterior tensile strains during changes in direction suggest introduction of these types of activities should be delayed during recovery from an anterior tibial bone stress injury, which have a high-risk of healing complications.

In silicomodeling of tibial fatigue life in physically active males and females during different exercise protocols

Preventing bone stress injuries (BSI) requires a deep understanding of the condition's underlying causes and risk factors. Subject-specific computer modeling studies of gait mechanics, including the effect of changes in running speed, stride length, and landing patterns on tibial stress injury formation can provide essential insights into BSI prevention. This study aimed to computationally examine the effect of different exercise protocols on tibial fatigue life in male and female runners during prolonged walking and running at three different speeds. To achieve these aims, we combined subject-specific magnetic resonance imaging (MRI), gait data, finite element analysis, and a fatigue life prediction algorithm, including repair and adaptation's influence. The algorithm predicted a steep increase in the likelihood of developing a BSI within the first 40 days of activity. In five of the six subjects simulated, faster running speeds corresponded with higher tibial strains and higher probability of failure. Our simulations also showed that female subjects had a higher mean peak probability of failure in all four gait conditions than the male subjects studied. The approach used in this study could lay the groundwork for studies in larger populations and patient-specific clinical tools and decision support systems to reduce BSIs in athletes, military personnel, and other active individuals.

In vivo strains at the middle and distal thirds of the tibia during exertional activities

There is a known variance in the incidence and anatomical site of tibial stress fractures among infantry recruits and athletes who train according to established uniform training programs. To better understand the biomechanical basis for this variance, we conducted in vivo axial strain measurements using instrumented bone staples affixed in the medial cortex, aligned along the long axis of the tibia at the level of the mid and distal third of the bone in four male subjects. Strain measurements were made during treadmill walking, treadmill running, drop jumps from a 45 cm height onto a force plate and serial vertical jumps on a force plate. Significance levels for the main effects of location, type of activity and their interaction were determined by quasi-parametric methodologies. Compared to walking, running and vertical jumping peak axial tensile strain (με) was 1.94 (p = 0.009) and 3.92 times (p < 0.001) higher, respectively. Peak axial compression strain (με) values were found to be greater at the distal third than at the mid tibia for walking, running and vertical jumping (PR = 1.95, p-value<0.001). Peak axial compression and tension strains varied significantly between the subjects (all with p < 0.001), after controlling for strain gauge location and activity type.

The study findings help explain the variance in the anatomical location of tibial stress fractures among participants doing the same uniform training and offers evidence of individual biomechanical susceptibility to tibial stress fracture. The study data can provide guidance when developing a generalized finite element model for mechanical tibial loading. For subject specific decisions, individualized musculoskeletal finite element models may be necessary.

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In vivo strains were measured simultaneously at the middle and distal tibial thirds.

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Compression and tension varied between subjects controlling for location and activity.

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Compared to walking, running and jumping tension was 1.94 and 3.92 higher.

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Compression strains were greater at the distal third than at the mid tibia.

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The data can be used to develop a generalized FE model for mechanical tibial loading.

A statistical shape model of the tibia-fibula complex: sexual dimorphism and effects of age on reconstruction accuracy from anatomical landmarks

A statistical shape model was created for a young adult population and used to predict tibia and fibula geometries from bony landmarks. Reconstruction errors with respect to CT data were quantified and compared to isometric scaling. Shape differences existed between sexes. The statistical shape model estimated tibia-fibula geometries from landmarks with high accuracy (RMSE = 1.51-1.62 mm), improving upon isometric scaling (RMSE = 1.78 mm). Reconstruction errors increased when the model was applied to older adults (RMSE = 2.11-2.17 mm). Improvements in geometric accuracy with shape model reconstruction changed hamstring moment arms 25-35% (1.0-1.3 mm) in young adults.

Total Knee Replacement: Subject-Specific Modeling, Finite Element Analysis, and Evaluation of Dynamic Activities

This study presents a semi-automatic framework to create subject-specific total knee replacement finite element models, which can be used to analyze locomotion patterns and evaluate knee dynamics. In recent years, much scientific attention was attracted to pre-clinical optimization of customized total knee replacement operations through computational modeling to minimize post-operational adverse effects. However, the time-consuming and laborious process of developing a subject-specific finite element model poses an obstacle to the latter. One of this work's main goals is to automate the finite element model development process, which speeds up the proposed framework and makes it viable for practical applications. This pipeline's reliability was ratified by developing and validating a subject-specific total knee replacement model based on the 6th SimTK Grand Challenge data set. The model was validated by analyzing contact pressures on the tibial insert in relation to the patient's gait and analysis of tibial contact forces, which were found to be in accordance with the ones provided by the Grand Challenge data set. Subsequently, a sensitivity analysis was carried out to assess the influence of modeling choices on tibial insert's contact pressures and determine possible uncertainties on the models produced by the framework. Parameters, such as the position of ligament origin points, ligament stiffness, reference strain, and implant-bone alignment were used for the sensitivity study. Notably, it was found that changes in the alignment of the femoral component in reference to the knee bones significantly affect the load distribution at the tibiofemoral joint, with an increase of 206.48% to be observed at contact pressures during 5° internal rotation. Overall, the models produced by this pipeline can be further used to optimize and personalize surgery by evaluating the best surgical parameters in a simulated manner before the actual surgery.

Stressed volume estimated by finite element analysis predicts the fatigue life of human cortical bone: The role of vascular canals as stress concentrators

The fatigue life of cortical bone can vary several orders of magnitude, even in identical loading conditions. A portion of this variability is likely related to intracortical microarchitecture and the role of vascular canals as stress concentrators. The size, spatial distribution, and density of canals determine the peak magnitude and volume of stress concentrations. This study utilized a combination of experimental fatigue testing and image-based finite element (FE) analysis to establish the relationship between the stressed volume (i.e., volume of bone above yield stress) associated with vascular canals and the fatigue life of cortical bone. Thirty-six cortical bone samples were prepared from human femora and tibiae from five donors. Samples were allocated to four loading groups, corresponding to stress ranges of 60, 70, 80, and 90 MPa, then cyclically loaded in zero-compression until fracture. Porosity, canal diameter, canal separation, and canal number for each sample was quantified using X-ray microscopy (XRM) after testing. FE models were created from XRM images and used to calculate the stressed volume. Stressed volume was a good predictor of fatigue life, accounting for 67% of the scatter in fatigue-life measurements. An increase in stressed volume was most strongly associated with higher levels of intracortical porosity and larger canal diameters. The findings from this study suggest that a large portion of the fatigue-life variance of cortical bone in zero-compression is driven by intracortical microarchitecture, and that fatigue failure may be predicted by quantifying the stress concentrations associated with vascular canals.

A Dynamic Jaw Model With a Finite-Element Temporomandibular Joint

The masticatory region is an important human motion system that is essential for basic human tasks like mastication, speech or swallowing. An association between temporomandibular disorders (TMDs) and high temporomandibular joint (TMJ) stress has been suggested, but in vivo joint force measurements are not feasible to directly test this assumption. Consequently, biomechanical computer simulation remains as one of a few means to investigate this complex system. To thoroughly examine orofacial biomechanics, we developed a novel, dynamic computer model of the masticatory system. The model combines a muscle driven rigid body model of the jaw region with a detailed finite element model (FEM) disk and elastic foundation (EF) articular cartilage. The model is validated using high-resolution MRI data for protrusion and opening that were collected from the same volunteer. Joint stresses for a clenching task as well as protrusive and opening movements are computed. Simulations resulted in mandibular positions as well as disk positions and shapes that agree well with the MRI data. The model computes reasonable disk stress patterns for dynamic tasks. Moreover, to the best of our knowledge this model presents the first ever contact model using a combination of EF layers and a FEM body, which results in a clear decrease in computation time. In conclusion, the presented model is a valuable tool for the investigation of the human TMJ and can potentially help in the future to increase the understanding of the masticatory system and the relationship between TMD and joint stress and to highlight potential therapeutic approaches for the restoration of orofacial function.