Effect of different constraining boundary conditions on simulated femoral stresses and strains during gait.

Finite element analysis (FEA) is commonly used in orthopaedic research to estimate localised tissue stresses and strains. A variety of boundary conditions have been proposed for isolated femur analysis, but it remains unclear how these assumed constraints influence FEA predictions of bone biomechanics. This study compared the femoral head deflection (FHD), stresses, and strains elicited under four commonly used boundary conditions (fixed knee, mid-shaft constraint, springs, and isostatic methods) and benchmarked these mechanics against the gold standard inertia relief method for normal and pathological femurs (extreme anteversion and retroversion, coxa vara, and coxa valga). Simulations were performed for the stance phase of walking with the applied femoral loading determined from patient-specific neuromusculoskeletal models. Due to unrealistic biomechanics observed for the commonly used boundary conditions, we propose a novel biomechanical constraint method to generate physiological femur biomechanics. The biomechanical method yielded FHD (< 1 mm), strains (approaching 1000 µÎµ), and stresses (< 60 MPa), which were consistent with physiological observations and similar to predictions from the inertia relief method (average coefficient of determination = 0.97, average normalized root mean square error = 0.17). Our results highlight the superior performance of the biomechanical method compared to current methods of constraint for  both healthy and pathological femurs.

Sensitivity analysis of paediatric knee kinematics to the graft surgical parameters during anterior cruciate ligament reconstruction: A sequentially linked neuromusculoskeletal-finite element analysis.

BACKGROUND AND OBJECTIVE: Incidence of paediatric anterior cruciate ligament (ACL) rupture has increased substantially over recent decades. Following ACL rupture, ACL reconstruction (ACLR) surgery is typically performed to restore passive knee stability. This surgery involves replacing the failed ACL with a graft, however, surgeons must select from range of surgical parameters (e.g., type, size, insertion, and pre-tension) with no robust evidence guiding these decisions. This study presents a systemmatic computational approach to study effects of surgical parameter variation on kinematics of paediatric knees. METHODS: This study used sequentially-linked neuromusculoskeletal (NMSK) finite element (FE) models of three paediatric knees to estimate the: (i) sensitivity of post-operative knee kinematics to four surgical parameters (type, size, insertion, and pre-tension) through multi-input multi-output sensitivity analysis; (ii) influence of motion and loading conditions throughout stance phase of walking gait on sensitivity indices; and (iii) influence of subject-specific anatomy (i.e., knee size) on sensitivivty indices. A previously validated FE model of the intact knee for each subject served as a reference against which ACLR knee kinematics were compared. RESULTS: Sensitivity analyses revealed significant influences of surgical parameters on ACLR knee kinematics, albeit without discernible trend favouring any one parameter. Graft size and pre-tension were primary drivers of variation in knee translations and rotations, however, their effects fluctuated across stance indicating motion and loading conditions affect system sensitivity to surgical parameters. Importantly, the sensitivity of knee kinematics to surgical parameter varied across subjects, indicating geometry (i.e., knee size) influenced system sensitivity. Notably, alterations in graft parameters yielded substantial effects on kinematics (normalized root-mean-square-error > 10 %) compared to intact knee models, indicating surgical parameters vary post-operative knee kinematics. CONCLUSIONS: Overall, this initial study highlights the importance of surgical parameter selection on post-operative kinematics in the paediatric ACLR knee, and provides evidence of the need for personalized surgical planning to ultimately enhance patient outcomes.

The Biomechanics Research and Innovation Challenge: Development, Implementation, Uptake, and Reflections on the Inaugural Program.

Biomechanics as a discipline is ideally placed to increase awareness and participation of girls and women in science, technology, engineering, and mathematics. A nationwide Biomechanics and Research Innovation Challenge (BRInC) centered on mentoring and role modeling was developed to engage high school girls (mentees) and early-mid-career women (mentors) in the field of biomechanics through the completion of a 100-day research and/or innovation project. This manuscript describes the development, implementation, and uptake of the inaugural BRInC program and synthesizes the research and innovation projects undertaken, providing a framework for adoption of this program within the global biomechanics community. Eighty-seven high school girls in years 9 and 10 (age range: 14-16 y) were mentored in teams (n = 17) by women in biomechanics (n = 24). Using a design thinking approach, teams generated solutions to biomechanics-based problem(s)/research question(s). Eight key reflections on program strengths, as well as areas for improvement and planned changes for future iterations of the BRInC program, are outlined. These key reflections highlight the innovation, impact, and scalability of the program; the importance of a program framework and effective communication tools; and implementation of strategies to sustain the program as well as the importance of diversity and building a sense of community.

Validation and evaluation of subject-specific finite element models of the pediatric knee.

Finite element (FE) models have been widely used to investigate knee joint biomechanics. Most of these models have been developed to study adult knees, neglecting pediatric populations. In this study, an atlas-based approach was employed to develop subject-specific FE models of the knee for eight typically developing pediatric individuals. Initially, validation simulations were performed at four passive tibiofemoral joint (TFJ) flexion angles, and the resulting TFJ and patellofemoral joint (PFJ) kinematics were compared to corresponding patient-matched measurements derived from magnetic resonance imaging (MRI). A neuromusculoskeletal-(NMSK)-FE pipeline was then used to simulate knee biomechanics during stance phase of walking gait for each participant to evaluate model simulation of a common motor task. Validation simulations demonstrated minimal error and strong correlations between FE-predicted and MRI-measured TFJ and PFJ kinematics (ensemble average of root mean square errors < 5 mm for translations and < 4.1° for rotations). The FE-predicted kinematics were strongly correlated with published reports (ensemble average of Pearson's correlation coefficients (ρ) > 0.9 for translations and ρ > 0.8 for rotations), except for TFJ mediolateral translation and abduction/adduction rotation. For walking gait, NMSK-FE model-predicted knee kinematics, contact areas, and contact pressures were consistent with experimental reports from literature. The strong agreement between model predictions and experimental reports underscores the capability of sequentially linked NMSK-FE models to accurately predict pediatric knee kinematics, as well as complex contact pressure distributions across the TFJ articulations. These models hold promise as effective tools for parametric analyses, population-based clinical studies, and enhancing our understanding of various pediatric knee injury mechanisms. They also support intervention design and prediction of surgical outcomes in pediatric populations.

Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision.

OBJECTIVES: The physical demands of military service place soldiers at risk of musculoskeletal injuries and are major concerns for military capability. This paper outlines the development new training technologies to prevent and manage these injuries. DESIGN: Narrative review. METHODS: Technologies suitable for integration into next-generation training devices were examined. We considered the capability of technologies to target tissue level mechanics, provide appropriate real-time feedback, and their useability in-the-field. RESULTS: Musculoskeletal tissues' health depends on their functional mechanical environment experienced in military activities, training and rehabilitation. These environments result from the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing joint tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and strain), which may be enabled by real-time biofeedback. Recent research has shown that these biofeedback technologies are possible by integrating a patient's personalised digital twin and wireless wearable devices. Personalised digital twins are personalised neuromusculoskeletal rigid body and finite element models that work in real-time by code optimisation and artificial intelligence. Model personalisation is crucial in obtaining physically and physiologically valid predictions. CONCLUSIONS: Recent work has shown that laboratory-quality biomechanical measurements and modelling can be performed outside the laboratory with a small number of wearable sensors or computer vision methods. The next stage is to combine these technologies into well-designed easy to use products.

Limiting the Use of Electromyography and Ground Reaction Force Data Changes the Magnitude and Ranking of Modelled Anterior Cruciate Ligament Forces.

Neuromusculoskeletal models often require three-dimensional (3D) body motions, ground reaction forces (GRF), and electromyography (EMG) as input data. Acquiring these data in real-world settings is challenging, with barriers such as the cost of instruments, setup time, and operator skills to correctly acquire and interpret data. This study investigated the consequences of limiting EMG and GRF data on modelled anterior cruciate ligament (ACL) forces during a drop-land-jump task in late-/post-pubertal females. We compared ACL forces generated by a reference model (i.e., EMG-informed neural mode combined with 3D GRF) to those generated by an EMG-informed with only vertical GRF, static optimisation with 3D GRF, and static optimisation with only vertical GRF. Results indicated ACL force magnitude during landing (when ACL injury typically occurs) was significantly overestimated if only vertical GRF were used for either EMG-informed or static optimisation neural modes. If 3D GRF were used in combination with static optimisation, ACL force was marginally overestimated compared to the reference model. None of the alternative models maintained rank order of ACL loading magnitudes generated by the reference model. Finally, we observed substantial variability across the study sample in response to limiting EMG and GRF data, indicating need for methods incorporating subject-specific measures of muscle activation patterns and external loading when modelling ACL loading during dynamic motor tasks.

Effects of Footwear on Anterior Cruciate Ligament Forces during Landing in Young Adult Females.

Rates of anterior cruciate ligament (ACL) rupture in young people have increased markedly over the past two decades, with females experiencing greater growth in their risk compared to males. In this study, we determined the effects of low- and high-support athletic footwear on ACL loads during a standardized drop-land-lateral jump in 23 late-/post-pubertal females. Each participant performed the task unshod, wearing low- (Zaraca, ASICS) or high- (Kayano, ASICS) support shoes (in random order), and three-dimensional body motions, ground-reaction forces, and surface electromyograms were synchronously acquired. These data were then used in a validated computational model of ACL loading. One-dimensional statistical parametric mapping paired t-tests were used to compare ACL loads between footwear conditions during the stance phase of the task. Participants generated lower ACL forces during push-off when shod (Kayano: 624 N at 71-84% of stance; Zaraca: 616 N at 68-86% of stance) compared to barefoot (770 N and 740 N, respectively). No significant differences in ACL force were observed between the task performed wearing low- compared to high-support shoes. Compared to barefoot, both shoe types significantly lowered push-off phase peak ACL forces, potentially lowering risk of ACL injury during performance of similar tasks in sport and recreation.

Development of predictive statistical shape models for paediatric lower limb bones.

BACKGROUND AND OBJECTIVE: Accurate representation of bone shape is important for subject-specific musculoskeletal models as it may influence modelling of joint kinematics, kinetics, and muscle dynamics. Statistical shape modelling is a method to estimate bone shape from minimal information, such as anatomical landmarks, and to avoid the time and cost associated with reconstructing bone shapes from comprehensive medical imaging. Statistical shape models (SSM) of lower limb bones have been developed and validated for adult populations but are not applicable to paediatric populations. This study aimed to develop SSM for paediatric lower limb bones and evaluate their reconstruction accuracy using sparse anatomical landmarks. METHODS: We created three-dimensional models of 56 femurs, 29 pelves, 56 tibias, 56 fibulas, and 56 patellae through segmentation of magnetic resonance images taken from 29 typically developing children (15 females; 13 ± 3.5 years). The SSM for femur, pelvis, tibia, fibula, patella, haunch (i.e., combined femur and pelvis), and shank (i.e., combined tibia and fibula) were generated from manual segmentation of comprehensive magnetic resonance images to describe the shape variance of the cohort. We implemented a leave-one-out cross-validation method wherein SSM were used to reconstruct novel bones (i.e., those not included in SSM generation) using full- (i.e., full segmentation) and sparse- (i.e., anatomical landmarks) input, and then compared these reconstructions against bones segmented from magnetic resonance imaging. Reconstruction performance was evaluated using root mean squared errors (RMSE, mm), Jaccard index (0-1), Dice similarity coefficient (DSC) (0-1), and Hausdorff distance (mm). All results reported in this abstract are mean ± standard deviation. RESULTS: Femurs, pelves, tibias, fibulas, and patellae reconstructed via SSM using full-input had RMSE between 0.89 ± 0.10 mm (patella) and 1.98 ± 0.38 mm (pelvis), Jaccard indices between 0.77 ± 0.03 (pelvis) and 0.90 ± 0.02 (tibia), DSC between 0.87 ± 0.02 (pelvis) and 0.95 ± 0.01 (tibia), and Hausdorff distances between 2.45 ± 0.57 mm (patella) and 9.01 ± 2.36 mm (pelvis). Reconstruction using sparse-input had RMSE ranging from 1.33 ± 0.61 mm (patella) to 3.60 ± 1.05 mm (pelvis), Jaccard indices ranging from 0.59 ± 0.10 (pelvis) to 0.83 ± 0.03 (tibia), DSC ranging from 0.74 ± 0.08 (pelvis) to 0.90 ± 0.02 (tibia), and Hausdorff distances ranging from 3.21 ± 1.19 mm (patella) to 12.85 ± 3.24 mm (pelvis). CONCLUSIONS: The SSM of paediatric lower limb bones showed reconstruction accuracy consistent with previously developed SSM and outperformed adult-based SSM when used to reconstruct paediatric bones.

Effects of Pubertal Maturation on ACL Forces During a Landing Task in Females.

BACKGROUND: Rates of anterior cruciate ligament (ACL) rupture in young people have increased by >70% over the past two decades. Adolescent and young adult females are at higher risk of ACL injury as compared with their prepubertal counterparts. PURPOSE: To determine ACL loading during a standardized drop-land-lateral jump in females at different stages of pubertal maturation. STUDY DESIGN: Controlled laboratory study. METHODS: On the basis of the Tanner classification system, 19 pre-, 19 early-/mid-, and 24 late-/postpubertal females performed a standardized drop-land-lateral jump while 3-dimensional body motion, ground-reaction forces, and surface electromyography data were acquired. These data were used to model external biomechanics, lower limb muscle forces, and knee contact forces, which were subsequently used in a validated computational model to estimate ACL loading. Statistical parametric mapping analysis of variance was used to compare ACL force and its causal contributors among the 3 pubertal maturation groups during stance phase of the task. RESULTS: When compared with pre- and early-/midpubertal females, late-/postpubertal females had significantly higher ACL force with mean differences of 471 and 356 N during the first 30% and 48% to 85% of stance, and 343 and 274 N during the first 24% and 59% to 81% of stance, respectively, which overlapped peaks in ACL force. At the point of peak ACL force, contributions from sagittal and transverse plane loading mechanisms to ACL force were higher in late-/postpubertal compared with pre- and early-/midpubertal groups (medium effect sizes from 0.44 to 0.77). No differences were found between pre- and early-/midpubertal groups in ACL force or its contributors. CONCLUSION: The highest ACL forces were observed in late-/postpubertal females, consistent with recently reported rises of ACL injury rates in females aged 15 to 19 years. It is important to quantify ACL force and its contributors during dynamic tasks to advance our understanding of the loading mechanism and thereby provide guidance to injury prevention. CLINICAL RELEVANCE: Growth of ACL volume plateaus around 10 years of age, before pubertal maturation, meaning that a late-/postpubertal female could have an ACL of similar size to their less mature counterparts. However, late-/postpubertal females have higher body mass requiring higher muscle forces to accelerate the body during dynamic tasks, which may increase ACL loading. Thus, if greater forces develop in these females, in part because of their increased body mass, these higher forces will be applied to an ACL that is not proportionally larger. This may partially explain the higher rates of ACL injury in late-/postpubertal females.

Mechanism of Anterior Cruciate Ligament Loading during Dynamic Motor Tasks.

INTRODUCTION: This study determined anterior cruciate ligament (ACL) force and its contributors during a standardized drop-land-lateral jump task using a validated computational model. METHODS: Three-dimensional whole-body kinematics, ground reaction forces, and muscle activation patterns from eight knee-spanning muscles were collected during dynamic tasks performed by healthy recreationally active females (n = 24). These data were used in a combined neuromusculoskeletal and ACL force model to determine lower limb muscle and ACL forces. RESULTS: Peak ACL force (2.3 ± 0.5 bodyweight) was observed at ~14% of stance during the drop-land-lateral jump. The ACL force was primarily generated through the sagittal plane, and muscle was the dominant source of ACL loading. The main ACL antagonists (i.e., loaders) were the gastrocnemii and quadriceps, whereas the hamstrings were the main ACL agonists (i.e., supporters). CONCLUSION: Combining neuromusculoskeletal and ACL force models, the roles of muscle in ACL loading and support were determined during a challenging motor task. Results highlighted the importance of the gastrocnemius in ACL loading, which could be considered more prominently in ACL injury prevention and rehabilitation programs.

Modelling the loading mechanics of anterior cruciate ligament.

BACKGROUND AND OBJECTIVES: The anterior cruciate ligament (ACL) plays a crucial role in knee stability and is the most commonly injured knee ligament. Although ACL loading patterns have been investigated previously, the interactions between knee loadings transmitted to ACL remain elusive. Understanding the loading mechanism of ACL during dynamic tasks is essential to prevent ACL injuries. Therefore, we propose a computational model that predicts the force applied to ACL in response to knee loading in three planes of motion. METHODS: First, a three-dimensional (3D) computational model was developed and validated using available cadaveric experimental data to predict ACL force. This 3D model was then combined with a neuromusculoskeletal model of lower limb and used to estimate in vivo ACL forces during a standardised drop-landing task. The neuromusculoskeletal model utilised movement data collected from female participants during a dynamic task and calculated lower limb joint kinematics and kinetics, as well as muscle forces. RESULTS: The total ACL force predicted by the 3D computational ACL force model was in good agreement with cadaveric data, as strong correlation (r2 = 0.96 and P < 0.001), minimal bias, and narrow limits of agreement were observed. The combined model further illustrated that the ACL is primarily loaded through the sagittal plane, mainly due to muscle loading. CONCLUSIONS: The proposed computational model is the first validated model that can provide an accessible tool to develop and test knee ACL injury prevention programs for people with normal ACL. This method can be extended to study the abnormal ACL upon the availability of relevant experimental data.

Effects of creatine supplementation along with resistance training on urinary formaldehyde and serum enzymes in wrestlers.

BACKGROUND: Formaldehyde is a cytotoxic agent produced from creatine through a metabolic pathway, and in this regard, it has been claimed that creatine supplementation could be cytotoxic. Even though the cytotoxic effects of creatine supplementation have been widely studied, yet little is known about how resistance training can alter these toxic effects. This study aimed to determine the effects of short-term creatine supplementation plus resistance training on the level of urinary formaldehyde and concentrations of serum enzymes in young male wrestlers. METHODS: In a double-blind design twenty-one subjects were randomized into creatine supplementation (Cr), creatine supplementation plus resistance training (Cr + T) and placebo plus resistance training (Pl + T) groups. Participants ingested creatine (0.3 g/kg/day) or placebo for 7 days. The training protocol consisted of 3 sessions in one week, each session including three sets of 6-9 repetitions at 80-85% of one-repetition maximum for whole-body exercise. Urine and blood samples were collected at baseline and at the end of the supplementation. RESULTS: Creatine supplementation significantly increased the excretion rate of urinary formaldehyde in the Cr and Cr + T groups by 63.4% and 30.4%, respectively (P<0.05), indicating that resistance training could partially lower this rate by 17.7%. No significant differences were detected in the levels of serum enzymes across time and groups (P>0.05). CONCLUSIONS: These findings indicate that resistance training may lower the increase of urinary formaldehyde excretion induced by creatine supplementation, suggesting that creatine consumption could be relatively less toxic when combined with resistance training.

Effects of resistance exercise and the use of anabolic androgenic steroids on hemodynamic characteristics and muscle damage markers in bodybuilders.

BACKGROUND: Anabolic androgenic steroids (AAS), synthetic compounds of testosterone commonly used as sport performance enhancers, could cause cardiovascular dysfunction and cell damage. Even though the side effects of AAS intake have been widely studied, yet little is known about how resistance exercise can alter these side effects. This study aimed to determine the effects of one session resistance exercise and the use of AAS on hemodynamic characteristics and muscle damage markers in professional bodybuilders. METHODS: Sixteen bodybuilders were divided into two groups: bodybuilders using AAS for at least 5 years (users; N.=8) and AAS-free bodybuilders (non-users; N.=8). The exercise protocol was a circuit strength training session involved three sets of 8-9 repetitions at 80-85% of 1-RM. Heart rate (HR), blood pressure (BP) and concentrations of serum creatine kinase (CK) and lactate dehydrogenase (LDH) were measured at three different time points, immediately before and after the exercise session and 24 hours following the exercise session. RESULTS: The users group showed greater basal levels of hemodynamic characteristics (i.e. HR and BP) and cell damage markers (i.e. CK and LDH) compared to those in the non-users group (all P<0.05). Furthermore, the exercise session significantly increased the levels of HR (P=0.02) and CK (P=0.01) in the users group compared to those in the non-users group immediately after the exercise. No significant differences were observed in BP and LDH responses to exercise between the users and the non-users groups (P>0.05). CONCLUSIONS: These findings indicate that the use of AAS could be potentially harmful as it enhances the levels of the hemodynamic characteristics and the muscle enzymes. These harmful effects of AAS intake could be more evident in response to resistance exercise.