Knee joint kinematics and kinetics during the hop and cut after soft tissue artifact suppression: Time to reconsider ACL injury mechanisms?

The recent development of a soft tissue artifact (STA) suppression method allows us to re-evaluate the tibiofemoral kinematics currently linked to non-contact knee injuries. The purpose of this study was therefore to evaluate knee joint kinematics and kinetics in six degrees of freedom (DoF) during the loading phases of a jump lunge and side cut using this in silico method. Thirty-five healthy adults completed these movements and their surface marker trajectories were then scaled and processed with OpenSim’s inverse kinematics (IK) and inverse dynamics tools. Knee flexion angle-dependent kinematic constraints defined based on previous bone pin (BP) marker trajectories were then applied to the OpenSim model during IK and these constrained results were then processed with the standard inverse dynamics tool. Significant differences for all hip, knee, and ankle DoF were observed after STA suppression for both the jump lunge and side cut. Using clinically relevant effect size estimates, we conclude that STA contamination had led to misclassifications in hip transverse plane angles, knee frontal and transverse plane angles, medial/lateral and distractive/compressive knee translations, and knee frontal plane moments between the NoBP and the BP IK solutions. Our results have substantial clinical implications since past research has used joint kinematics and kinetics contaminated by STA to identify risk factors for musculoskeletal injuries.     

Hip and knee joint kinematics during a diagonal jump landing in anterior cruciate ligament reconstructed females

Anterior cruciate ligament (ACL) injury is a common injury encountered by sport medicine clinicians. Surgical reconstruction is the recommended treatment of choice for those athletes wishing to return to full-contact sports participation and for sports requiring multi-directional movement patterns. The aim of ACL reconstruction is to restore knee joint mechanical stability such that the athlete can return to sporting participation. However, knowledge regarding the extent to which lower limb kinematic profiles are restored following ACL reconstruction is limited. In the present study the hip and knee joint kinematic profiles of 13 ACL reconstructed (ACL-R) and 16 non-injured control subjects were investigated during the performance of a diagonal jump landing task. The ACL-R group exhibited significantly less peak knee joint flexion (P=0.01). Significant between group differences were noted for time averaged hip joint sagittal plane (P<0.05) and transverse plane (P<0.05) kinematic profiles, as well as knee joint frontal plane (P<0.05) and sagittal plane (P<0.05) kinematic profiles. These results suggest that aberrant hip and knee joint kinematic profiles are present following ACL reconstruction, which could influence future injury risk.     

Effect of implementing magnetic resonance imaging for patient-specific OpenSim models on lower-body kinematics and knee ligament lengths

BackgroundOpenSim models are typically based on cadaver findings that are generalized to represent a wide range of populations, which curbs their validity. Patient-specific modelling through incorporating magnetic resonance imaging (MRI) improves the model’s biofidelity with respect to joint alignment and articulations, muscle wrapping, and ligament insertions. The purpose of this study was to determine if the inclusion of an MRI-based knee model would elicit differences in lower limb kinematics and resulting knee ligament lengths during a side cut task.MethodsEleven participants were analyzed with the popular Rajagopal OpenSim model, two variations of the same model to include three and six degrees of freedom knee (DOF), and a fourth version featuring a four DOF MRI-based knee model. These four models were used in an inverse kinematics analysis of a side cut task and the resulting lower limb kinematics and knee ligament lengths were analyzed.ResultsThe MRI-based model was more responsive to the movement task than the original Rajagopal model while less susceptible to soft tissue artifact than the unconstrained six DOF model. Ligament isometry was greatest in the original Rajagopal model and smallest in the six DOF model.ConclusionsWhen using musculoskeletal modelling software, one must acutely consider the model choice as the resulting kinematics and ligament lengths are dependent on this decision. The MRI-based knee model is responsive to the kinematics and ligament lengths of highly dynamic tasks and may prove to be the most valid option for continuing with late-stage modelling operations such as static optimization.     

Paradoxical nature of mineralocorticoid receptor antagonism by progestins

Progesterone, but not the synthetic progestagen R-5020, was as good as aldosterone in displacing the mineralocorticoid from its specific receptor in rat kidney both in classical competition studies and in aldosterone binding to MR₁ and MR₂ components of MR during physical separation. Paradoxically, at equimolar (10^?8 M) concentrations, both gestagens (progesterone = 1, R-5020 = 20) were preferentially bound to the MR₄ component which coeluted with serum bound ¹⁴C-corticosterone (or ¹⁴C-progesterone), which could not be labelled with aldosterone in the kidney, and which could not be detected in the liver and the serum under any condition. The MR₁ entity, at 10^?8 M, was saturated as: aldosterone = 2, R-5020 = 1 = progesterone. Thus, the agonist and the antagonist function in mineralocorticoid action may be expressed by two or more distinct and different sites.     

A Biomechanical Model of the Scapulothoracic Joint to Accurately Capture Scapular Kinematics during Shoulder Movements

The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models.     

Influence of joint constraints on lower limb kinematics estimation from skin markers using global optimization

In order to obtain the lower limb kinematics from skin-based markers, the soft tissue artefact (STA) has to be compensated. Global optimization (GO) methods rely on a predefined kinematic model and attempt to limit STA by minimizing the differences between model predicted and skin-based marker positions. Thus, the reliability of GO methods depends directly on the chosen model, whose influence is not well known yet.This study develops a GO method that allows to easily implement different sets of joint constraints in order to assess their influence on the lower limb kinematics during gait. The segment definition was based on generalized coordinates giving only linear or quadratic joint constraints. Seven sets of joint constraints were assessed, corresponding to different kinematic models at the ankle, knee and hip: SSS, USS, PSS, SHS, SPS, UHS and PPS (where S, U and H stand for spherical, universal and hinge joints and P for parallel mechanism). GO was applied to gait data from five healthy males.Results showed that the lower limb kinematics, except hip kinematics, knee and ankle flexion–extension, significantly depend on the chosen ankle and knee constraints. The knee parallel mechanism generated some typical knee rotation patterns previously observed in lower limb kinematic studies. Furthermore, only the parallel mechanisms produced joint displacements.Thus, GO using parallel mechanism seems promising. It also offers some perspectives of subject-specific joint constraints.     

A calibrated EMG-informed neuromusculoskeletal model can appropriately account for muscle co-contraction in the estimation of hip joint contact forces in people with hip osteoarthritis

Abnormal hip joint contact forces (HJCF) are considered a primary mechanical contributor to the progression of hip osteoarthritis (OA). Compared to healthy controls, people with hip OA often present with altered muscle activation patterns and greater muscle co-contraction, both of which can influence HJCF. Neuromusculoskeletal (NMS) modelling is non-invasive approach to estimating HJCF, whereby different neural control solutions can be used to estimate muscle forces. Static optimisation, available within the popular NMS modelling software OpenSim, is a commonly used neural control solution, but may not account for an individual’s unique muscle activation patterns and/or co-contraction that are often evident in pathological population. Alternatively, electromyography (EMG)-assisted neural control solutions, available within CEINMS software, have been shown to account for individual activation patterns in healthy people. Nonetheless, their application in people with hip OA, with conceivably greater levels of co-contraction, is yet to be explored. The aim of this study was to compare HJCF estimations using static optimisation (in OpenSim) and EMG-assisted (in CEINMS) neural control solutions during walking in people with hip OA. EMG-assisted neural control solution was more consistent with both EMG and joint moment data than static optimisation, and also predicted significantly higher HJCF peaks (p < 0.001). The EMG-assisted neural control solution also accounted for more muscle co-contraction than static optimisation (p = 0.03), which probably contributed to these higher HJCF peaks. Findings suggest that the EMG-assisted neural control solution may estimate more physiologically plausible HJCF than static optimisation in a population with high levels of co-contraction, such as hip OA.     

An open source lower limb model: Hip joint validation

Musculoskeletal lower limb models have been shown to be able to predict hip contact forces (HCFs) that are comparable to in vivo measurements obtained from instrumented prostheses. However, the muscle recruitment predicted by these models does not necessarily compare well to measured electromyographic (EMG) signals. In order to verify if it is possible to accurately estimate HCFs from muscle force patterns consistent with EMG measurements, a lower limb model based on a published anatomical dataset (Klein Horsman et al., 2007. Clinical Biomechanics. 22, 239-247) has been implemented in the open source software OpenSim. A cycle-to-cycle hip joint validation was conducted against HCFs recorded during gait and stair climbing trials of four arthroplasty patients (Bergmann et al., 2001. Journal of Biomechanics. 34, 859-871). Hip joint muscle tensions were estimated by minimizing a polynomial function of the muscle forces. The resulting muscle activation patterns obtained by assessing multiple powers of the objective function were compared against EMG profiles from the literature. Calculated HCFs denoted a tendency to monotonically increase their magnitude when raising the power of the objective function; the best estimation obtained from muscle forces consistent with experimental EMG profiles was found when a quadratic objective function was minimized (average overestimation at experimental peak frame: 10.1% for walking, 7.8% for stair climbing). The lower limb model can produce appropriate balanced sets of muscle forces and joint contact forces that can be used in a range of applications requiring accurate quantification of both. The developed model is available at the website https://simtk.org/home/low_limb_london.     

Robustness of kinematic weighting and scaling concepts for musculoskeletal simulation

Musculoskeletal modelling is widely used to estimate internal loading conditions. In order to optimise robustness and reduce errors between the subject-specific reference motion data (RMD) and the musculoskeletal simulation, 90 permutations of kinetic and kinematic data were analysed during split squats. A ranking for the scaling and kinematic weighting concepts based on the RMS errors when including functional centres of rotation (fCoRs), joint angles, and skin markers, revealed that analyses should include fCoR in the scaling and the simulation processes, as well as an automated weighting procedure including all attached skin markers for optimal registration of the musculoskeletal model to the RMD.     

Increased hip adduction during running is associated with patellofemoral pain and differs between males and females: A case-control study

Patellofemoral pain is common amongst recreational runners and associated with altered running kinematics. However, it is currently unclear how sex may influence kinematic differences previously reported in runners with patellofemoral pain. This case-control study aimed to evaluate lower limb kinematics in males and females with and without patellofemoral pain during running. Lower limb 3D kinematics were assessed in 20 runners with patellofemoral pain (11 females, 9 males) and 20 asymptomatic runners (11 females, 9 males) during a 3 km treadmill run. Variables of interest included peak hip adduction, internal rotation and flexion angles; and peak knee flexion angle, given their previously reported association with patellofemoral pain. Age, height, mass, weekly run distance and step rate were not significantly different between groups. Mixed-sex runners with patellofemoral pain were found to run with a significantly greater peak hip adduction angle (mean difference = 4.9°, d = 0.91, 95% CI 1.4–8.2, p = 0.01) when compared to matched controls, but analyses for all other kinematic variables were non-significant. Females with patellofemoral pain ran with a significantly greater peak hip adduction angle compared to female controls (mean difference = 6.6°, p = 0.02, F = 3.41, 95% CI 0.4–12.8). Analyses for all other kinematic variables between groups (males and females with/without PFP) were non-significant. Differences in peak hip adduction between those with and without patellofemoral pain during running appear to be driven by females. This potentially highlights different kinematic treatment targets between males and females. Future research is encouraged to report lower limb kinematic variables in runners with patellofemoral pain separately for males and females.     

Ground reaction forces and lower-limb joint kinetics of turning gait in typically developing children

Turning is a common locomotor task essential to daily activity; however, very little is known about the forces and moments responsible for the kinematic adaptations occurring relative to straight-line gait in typically developing children. Thus, the aims of this study were to analyse ground reaction forces (GRFs), ground reaction free vertical torque (T_Z), and the lower-limb joint kinetics of 90° outside (step) and inside (spin) limb turns. Step, spin, and straight walking trials from fifty-four typically developing children were analysed. All children were fit with the Plug-in Gait and Oxford Foot Model marker sets while walking over force plates embedded in the walkway. Net internal joint moments and power were computed via a standard inverse dynamics approach. All dependent variables were statistically analysed over the entire curves using the mean difference 95% bootstrap confidence band approach. GRFs were directed medially for step turns and laterally for spin turns during the turning phase. Directions were reversed and magnitudes decreased during the approach phase. Step turns showed reduced ankle power generation, while spin turns showed large T_Z. Both strategies required large knee and hip coronal and transverse plane moments during swing. These kinetic differences highlight adaptations required to maintain stability and reorient the body towards the new walking direction during turning. From a clinical perspective, turning gait may better reveal weaknesses and motor control deficits than straight walking in pathological populations, such as children with cerebral palsy, and could potentially be implemented in standard gait analysis sessions.     

Sensitivity of a subject-specific musculoskeletal model to the uncertainties on the joint axes location

Subject-specific musculoskeletal models have become key tools in the clinical decision-making process. However, the sensitivity of the calculated solution to the unavoidable errors committed while deriving the model parameters from the available information is not fully understood. The aim of this study was to calculate the sensitivity of all the kinematics and kinetics variables to the inter-examiner uncertainty in the identification of the lower limb joint models. The study was based on the computer tomography of the entire lower-limb from a single donor and the motion capture from a body-matched volunteer. The hip, the knee and the ankle joint models were defined following the International Society of Biomechanics recommendations. Using a software interface, five expert anatomists identified on the donor's images the necessary bony locations five times with a three-day time interval. A detailed subject-specific musculoskeletal model was taken from an earlier study, and re-formulated to define the joint axes by inputting the necessary bony locations. Gait simulations were run using OpenSim within a Monte Carlo stochastic scheme, where the locations of the bony landmarks were varied randomly according to the estimated distributions. Trends for the joint angles, moments, and the muscle and joint forces did not substantially change after parameter perturbations. The highest variations were as follows: (a) 11° calculated for the hip rotation angle, (b) 1% BW × H calculated for the knee moment and (c) 0.33 BW calculated for the ankle plantarflexor muscles and the ankle joint forces. In conclusion, the identification of the joint axes from clinical images is a robust procedure for human movement modelling and simulation.     

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography

Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to video-radiography. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D registration for quantifying glenohumeral kinematics is unknown. We developed an automatic 2D-3D registration program that works with both CT- and MRI-based image volumes for quantifying joint motions. The purpose of this study was to use the proposed 2D-3D auto-registration algorithm to describe the humerus and scapula tracking accuracy of CT- and MRI-based registration relative to radiostereometric analysis (RSA) during dynamic biplanar video-radiography. The GH kinematic accuracy (RMS error) was 0.6–1.0 mm and 0.6–2.2° for the CT-based registration and 1.4–2.2 mm and 1.2–2.6° for MRI-based registration. Higher kinematic accuracy of CT-based registration was expected as MRI provides lower spatial resolution and bone contrast as compared to CT and suffers from spatial distortions. However, the MRI-based registration is within an acceptable accuracy for many clinical research questions.     

Development of a novel MATLAB-based framework for implementing mechanical joint stability constraints within OpenSim musculoskeletal models

The Static Optimization (SO) solver in OpenSim estimates muscle activations and forces that only equilibrate applied moments. In this study, SO was enhanced through an open-access MATLAB interface, where calculated muscle activations can additionally satisfy crucial mechanical stability requirements. This Stability-Constrained SO (SCSO) is applicable to many OpenSim models and can potentially produce more biofidelic results than SO alone, especially when antagonistic muscle co-contraction is required to stabilize body joints. This hypothesis was tested using existing models and experimental data in the literature. Muscle activations were calculated by SO and SCSO for a spine model during two series of static trials (i.e. simulation 1 and 2), and also for a lower limb model (supplementary material 2). In simulation 1, symmetric and asymmetric flexion postures were compared, while in simulation 2, various external load heights were compared, where increases in load height did not change the external lumbar flexion moment, but necessitated higher EMG activations. During the tasks in simulation 1, the predicted muscle activations by SCSO demonstrated less average deviation from the EMG data (6.8% −7.5%) compared to those from SO (10.2%). In simulation 2, SO predicts constant muscle activations and forces, while SCSO predicts increases in the average activations of back and abdominal muscles that better match experimental data. Although the SCSO results are sensitive to some parameters (e.g. musculotendon stiffness), when considering the strategy of the central nervous system in distributing muscle forces and in activating antagonistic muscles, the assigned activations by SCSO are more biofidelic than SO.     

Characterizing the balance-dexterity task as a concurrent bipedal task to investigate trunk control during dynamic balance

The purpose of the study was to characterize the Balance-Dexterity Task as a means to investigate a concurrent bipedal lower-extremity task and trunk control during dynamic balance. The task combines aspects of single-limb balance and the lower-extremity dexterity test by asking participants to stand on one limb while compressing an unstable spring with the contralateral limb to an individualized target force. Nineteen non-disabled participants completed the study, and performance measures for the demands of each limb – balance and dexterous force control – as well as kinematic and electromyographic measures of trunk control were collected. Given five practice trials, participants achieved compression forces ranging from 100 to 139 N (mean 121.2 ± 12.3 N), representing 14.4–23.0% of body weight (mean 18.7 ± 2.4%), which were then presented as target forces during test trials. Dexterous force control coefficient of variation and average magnitude of the center of pressure (COP) resultant velocity were associated such that greater variability in force control was accompanied by greater COP velocity (R = 0.598, p = 0.007). Trunk coupling, quantified as the coefficient of determination (R²) of a frontal plane thorax and pelvis angle-angle plot, varied independently of any measure of balance or dexterous force control. The Balance-Dexterity Task is a continuous, dynamic balance task where bipedal coordination and trunk coupling can be concurrently observed and studied.     

Muscle force estimation in clinical gait analysis using AnyBody and OpenSim

A variety of musculoskeletal models are applied in different modelling environments for estimating muscle forces during gait. Influence of different modelling assumptions and approaches on model outputs are still not fully understood, while direct comparisons of standard approaches have been rarely undertaken. This study seeks to compare joint kinematics, joint kinetics and estimated muscle forces of two standard approaches offered in two different modelling environments (AnyBody, OpenSim). It is hypothesised that distinctive differences exist for individual muscles, while summing up synergists show general agreement. Experimental data of 10 healthy participants (28 ± 5 years, 1.72 ± 0.08 m, 69 ± 12 kg) was used for a standard static optimisation muscle force estimation routine in AnyBody and OpenSim while using two gait-specific musculoskeletal models. Statistical parameter mapping paired t-test was used to compare joint angle, moment and muscle force waveforms in Matlab. Results showed differences especially in sagittal ankle and hip angles as well as sagittal knee moments. Differences were also found for some of the muscles, especially of the triceps surae group and the biceps femoris short head, which occur as a result of different anthropometric and anatomical definitions (mass and inertia of segments, muscle properties) and scaling procedures (static vs. dynamic). Understanding these differences and their cause is crucial to operate such modelling environments in a clinical setting. Future research should focus on alternatives to classical generic musculoskeletal models (e.g. implementation of functional calibration tasks), while using experimental data reflecting normal and pathological gait to gain a better understanding of variations and divergent behaviour between approaches.     

Skeletal kinematics of the midtarsal joint during walking: Midtarsal joint locking revisited

The kinematics of the human foot complex have been investigated to understand the weight bearing mechanism of the foot. This study aims to investigate midtarsal joint locking during walking by noninvasively measuring the movements of foot bones using a high-speed bi-planar fluoroscopic system. Eighteen healthy subjects volunteered for the study; the subjects underwent computed tomography imaging and bi-planar radiographs of the foot in order to measure the three-dimensional (3D) midtarsal joint kinematics using a 2D-to-3D registration method and anatomical coordinate system in each bone. The relative movements on bone surfaces were also calculated in the talonavicular and calcaneocuboid joints and quantified as surface relative velocity vectors on articular surfaces to understand the kinematic interactions in the midtarsal joint. The midtarsal joint performed a coupled motion in the early stance to pronate the foot to extreme pose in the range of motion during walking and maintained this pose during the mid-stance. In the terminal stance, the talonavicular joint performed plantar-flexion, inversion, and internal rotation while the calcaneocuboid joint performed mainly inversion. The midtarsal joint moved towards an extreme supinated pose, rather than a minimum motion in the terminal stance. The study provides a new perspective to understand the kinematics and kinetics of the movement of foot bones and so-called midtarsal joint locking, during walking. The midtarsal joint continuously moved towards extreme poses together with the activation of muscle forces, which would support the foot for more effective force transfer during push-off in the terminal stance.     

A chain kinematic model to assess the movement of lower-limb including wobbling masses

Computer simulation models have shown that wobbling mass on the lower limb affects the joint kinetics. Our objective was to propose a non-invasive method to estimate bones and wobbling mass kinematics in the lower limb during hopping. The chain kinematic model has set degrees of freedom at the joints and free wobbling bodies. By comparison to a model without wobbling bodies, the marker residual was reduced by 20% but the joint kinematics remains unchanged. Wobbling bodies’ displacements reached 6.9 ± 3.5° and 6.9 ± 2.4 mm relative to the modelled bones. This original method is a first step to assess wobbling mass effect on joint kinetics.     

An open-source model and solution method to predict co-contraction in the finger

A novel open-source biomechanical model of the index finger with an electromyography (EMG)-constrained static optimization solution method are developed with the goal of improving co-contraction estimates and providing means to assess tendon tension distribution through the finger. The Intrinsic model has four degrees of freedom and seven muscles (with a 14 component extensor mechanism). A novel plugin developed for the OpenSim modelling software applied the EMG-constrained static optimization solution method. Ten participants performed static pressing in three finger postures and five dynamic free motion tasks. Index finger 3D kinematics, force (5, 15, 30 N), and EMG (4 extrinsic muscles and first dorsal interosseous) were used in the analysis. The Intrinsic model predicted co-contraction increased by 29% during static pressing over the existing model. Further, tendon tension distribution patterns and forces, known to be essential to produce finger action, were determined by the model across all postures. The Intrinsic model and custom solution method improved co-contraction estimates to facilitate force propagation through the finger. These tools improve our interpretation of loads in the finger to develop better rehabilitation and workplace injury risk reduction strategies.     

Fetlock joint kinematics differ with age in Thoroughbred [was thoroughbred] racehorses

Fetlock joint kinematics during galloping in 2-, 3-, 4-, and 5-year-old Thoroughbreds in race training were quantified to determine if differences due to age could account for the observation that 2-year old Thoroughbred racehorses incur a high number of injuries to the bones and soft tissues in the distal forelimbs during training and at the outset of racing. Twelve Thoroughbred racehorses were videotaped in the sagittal plane at 250 frames/s during their daily galloping workout on a 7/8 mile sand-surface training track. Four galloping strides were recorded for each horse and subsequently digitized to determine fetlock joint angles of the leading forelimb during the limb support period of a stride. Four kinematic variables were measured from each stride's angular profile: angle of fetlock joint dorsi-flexion at mid-stance, negative angular velocity, positive angular velocity and time from hoof impact to mid-stance phase of limb support. The 2-year old Thoroughbreds had significantly quicker rates of dorsi-flexion of their fetlock joints than 3- (p=0.01), 4- (p=0.01), and 5-year old (p<0.01) Thoroughbreds following impact of the leading forelimb during moderate galloping (avg. 14 m/s). Higher rates of dorsi-flexion in young Thoroughbreds may reflect immaturity (lack of stiffness) of the suspensory apparatus tissues.