Demonstrating the utility of Instrumented Gait Analysis in the treatment of children with cerebral palsy.

BACKGROUND: Instrumented gait analysis (IGA) has been around for a long time but has never been shown to be useful for improving patient outcomes. In this study we demonstrate the potential utility of IGA by showing that machine learning models are better able to estimate treatment outcomes when they include both IGA and clinical (CLI) features compared to when they include CLI features alone. DESIGN: We carried out a retrospective analysis of data from ambulatory children diagnosed with cerebral palsy who were seen at least twice at our gait analysis center. Individuals underwent a variety of treatments (including no treatment) between sequential gait analyses. We fit Bayesian Additive Regression Tree (BART) models that estimated outcomes for mean stance foot progression to demonstrate the approach. We built two models: one using CLI features only, and one using CLI and IGA features. We then compared the models' performance in detail. We performed similar, but less detailed, analyses for a number of other outcomes. All results were based on independent test data from a 70%/30% training/testing split. RESULTS: The IGA model was more accurate than the CLI model for mean stance-phase foot progression outcomes (RMSEIGA = 11∘, RMSECLI = 13∘) and explained more than 1.5 × as much of the variance (R2IGA = .45, R2CLI = .28). The IGA model outperformed the CLI model for every level of treatment complexity, as measured by number of simultaneous surgeries. The IGA model also exhibited superior performance for estimating outcomes of mean stance-phase knee flexion, mean stance-phase ankle dorsiflexion, maximum swing-phase knee flexion, gait deviation index (GDI), and dimensionless speed. INTERPRETATION: The results show that IGA has the potential to be useful in the treatment planning process for ambulatory children diagnosed with cerebral palsy. We propose that the results of machine learning outcome estimators-including estimates of uncertainty-become the primary IGA tool utilized in the clinical process, complementing the standard medical practice of conducting a through patient history and physical exam, eliciting patient goals, reviewing relevant imaging data, and so on.

A framework based on subject-specific musculoskeletal models and Monte Carlo simulations to personalize muscle coordination retraining.

Excessive loads at lower limb joints can lead to pain and degenerative diseases. Altering joint loads with muscle coordination retraining might help to treat or prevent clinical symptoms in a non-invasive way. Knowing how much muscle coordination retraining can reduce joint loads and which muscles have the biggest impact on joint loads is crucial for personalized gait retraining. We introduced a simulation framework to quantify the potential of muscle coordination retraining to reduce joint loads for an individuum. Furthermore, the proposed framework enables to pinpoint muscles, which alterations have the highest likelihood to reduce joint loads. Simulations were performed based on three-dimensional motion capture data of five healthy adolescents (femoral torsion 10°-29°, tibial torsion 19°-38°) and five patients with idiopathic torsional deformities at the femur and/or tibia (femoral torsion 18°-52°, tibial torsion 3°-50°). For each participant, a musculoskeletal model was modified to match the femoral and tibial geometry obtained from magnetic resonance images. Each participant's model and the corresponding motion capture data were used as input for a Monte Carlo analysis to investigate how different muscle coordination strategies influence joint loads. OpenSim was used to run 10,000 simulations for each participant. Root-mean-square of muscle forces and peak joint contact forces were compared between simulations. Depending on the participant, altering muscle coordination led to a maximum reduction in hip, knee, patellofemoral and ankle joint loads between 5 and 18%, 4% and 45%, 16% and 36%, and 2% and 6%, respectively. In some but not all participants reducing joint loads at one joint increased joint loads at other joints. The required alteration in muscle forces to achieve a reduction in joint loads showed a large variability between participants. The potential of muscle coordination retraining to reduce joint loads depends on the person's musculoskeletal geometry and gait pattern and therefore showed a large variability between participants, which highlights the usefulness and importance of the proposed framework to personalize gait retraining.

Neuromechanics of finger hangs with arm lock-offs: analyzing joint moments and muscle activations to improve practice guidelines for climbing.

Introduction: Climbing imposes substantial demands on the upper limbs and understanding the mechanical loads experienced by the joints during climbing movements is crucial for injury prevention and optimizing training protocols. This study aimed to quantify and compare upper limb joint loads and muscle activations during isometric finger hanging exercises with different arm lock-off positions. Methods: Seventeen recreational climbers performed six finger dead hangs with arm lock-offs at 90° and 135° of elbow flexion, as well as arms fully extended. Upper limb joint moments were calculated using personalized models in OpenSim, based on three-dimensional motion capture data and forces measured on an instrumented hang board. Muscle activations of upper limb muscles were recorded with surface electromyography electrodes. Results: Results revealed that the shoulder exhibited higher flexion moments during arm lock-offs at 90° compared to full extension (p = 0.006). The adduction moment was higher at 135° and 90° compared to full extension (p < 0.001), as well as the rotation moments (p < 0.001). The elbows exhibited increasing flexion moments with the increase in the arm lock-off angle (p < 0.001). Muscle activations varied across conditions for biceps brachii (p < 0.001), trapezius (p < 0.001), and latissimus dorsi, except for the finger flexors (p = 0.15). Discussion: Our findings indicate that isometric finger dead hangs with arms fully extended are effective for training forearm force capacities while minimizing stress on the elbow and shoulder joints. These findings have important implications for injury prevention and optimizing training strategies in climbing.

Influence of femoral anteversion angle and neck-shaft angle on muscle forces and joint loading during walking.

Femoral deformities, e.g. increased or decreased femoral anteversion (AVA) and neck-shaft angle (NSA), can lead to pathological gait patterns, altered joint loads, and degenerative joint diseases. The mechanism how femoral geometry influences muscle forces and joint load during walking is still not fully understood. The objective of our study was to investigate the influence of femoral AVA and NSA on muscle forces and joint loads during walking. We conducted a comprehensive musculoskeletal modelling study based on three-dimensional motion capture data of a healthy person with a typical gait pattern. We created 25 musculoskeletal models with a variety of NSA (93°-153°) and AVA (-12°-48°). For each model we calculated moment arms, muscle forces, muscle moments, co-contraction indices and joint loads using OpenSim. Multiple regression analyses were used to predict muscle activations, muscle moments, co-contraction indices, and joint contact forces based on the femoral geometry. We found a significant increase in co-contraction of hip and knee joint spanning muscles in models with increasing AVA and NSA, which led to a substantial increase in hip and knee joint contact forces. Decreased AVA and NSA had a minor impact on muscle and joint contact forces. Large AVA lead to increases in both knee and hip contact forces. Large NSA (153°) combined with large AVA (48°) led to increases in hip joint contact forces by five times body weight. Low NSA (108° and 93°) combined with large AVA (48°) led to two-fold increases in the second peak of the knee contact forces. Increased joint contact forces in models with increased AVA and NSA were linked to changes in hip muscle moment arms and compensatory increases in hip and knee muscle forces. Knowing the influence of femoral geometry on muscle forces and joint loads can help clinicians to improve treatment strategies in patients with femoral deformities.

The gait pattern and not the femoral morphology is the main contributor to asymmetric hip joint loading.

Gait asymmetry and skeletal deformities are common in many children with cerebral palsy (CP). Changes of the hip joint loading, i.e. hip joint contact force (HJCF), can lead to pathological femoral growth. A child's gait pattern and femoral morphology affect HJCFs. The twofold aim of this study was to (1) evaluate if the asymmetry in HJCFs is higher in children with CP compared to typically developing (TD) children and (2) identify if the bony morphology or the subject-specific gait pattern is the main contributor to asymmetric HJCFs. Magnetic resonance images (MRI) and three-dimensional gait analysis data of twelve children with CP and fifteen TD children were used to create subject-specific musculoskeletal models and calculate HJCF using OpenSim. Root-mean-square-differences between left and right HJCF magnitude and orientation were computed and compared between participant groups (CP versus TD). Additionally, the influence on HJCF asymmetries solely due to the femoral morphology and solely due to the gait pattern was quantified. Our findings demonstrate that the gait pattern is the main contributor to asymmetric HJCFs in CP and TD children. Children with CP have higher HJCF asymmetries which is probably the result of larger asymmetries in their gait pattern compared to TD children. The gained insights from our study highlight that clinical interventions should focus on normalizing the gait pattern and therefore the hip joint loading to avoid the development of femoral deformities.

Intra- and inter-subject variability of femoral growth plate stresses in typically developing children and children with cerebral palsy.

Little is known about the influence of mechanical loading on growth plate stresses and femoral growth. A multi-scale workflow based on musculoskeletal simulations and mechanobiological finite element (FE) analysis can be used to estimate growth plate loading and femoral growth trends. Personalizing the model in this workflow is time-consuming and therefore previous studies included small sample sizes (N < 4) or generic finite element models. The aim of this study was to develop a semi-automated toolbox to perform this workflow and to quantify intra-subject variability in growth plate stresses in 13 typically developing (TD) children and 12 children with cerebral palsy (CP). Additionally, we investigated the influence of the musculoskeletal model and the chosen material properties on the simulation results. Intra-subject variability in growth plate stresses was higher in cerebral palsy than in typically developing children. The highest osteogenic index (OI) was observed in the posterior region in 62% of the TD femurs while in children with CP the lateral region was the most common (50%). A representative reference osteogenic index distribution heatmap generated from data of 26 TD children's femurs showed a ring shape with low values in the center region and high values at the border of the growth plate. Our simulation results can be used as reference values for further investigations. Furthermore, the code of the developed GP-Tool ("Growth Prediction-Tool") is freely available on GitHub (https://github.com/WilliKoller/GP-Tool) to enable peers to conduct mechanobiological growth studies with larger sample sizes to improve our understanding of femoral growth and to support clinical decision making in the near future.

Imaging-based musculoskeletal models alter muscle and joint contact forces but do not improve the agreement with experimentally measured electromyography signals in children with cerebral palsy.

BACKGROUND: Musculoskeletal simulations are used to estimate muscle-tendon and joint contact forces (JCF). Personalizing the model's femoral geometry has been shown to improve the accuracy of JCF calculations. It is, however, unknown if the personalized geometry improves the agreement between estimated muscle activations and experimentally measured electromyography (EMG) signals. RESEARCH QUESTION: Does personalizing the musculoskeletal geometry improve the agreement between estimated muscle activations and EMG signals in terms of timing? METHODS: We retrospectively analysed data from Bosmans et al. [5], which included three-dimensional motion capture data, EMG signals of eight lower limb muscles on each leg, and magnetic resonance imaging (MRI) data from seven children with cerebral palsy. For each patient we created a generic-scaled model and MRI-based model, which accounted for the subject-specific musculoskeletal geometry. We calculated muscle activations, muscle-tendon forces and JCF. Muscle activations were compared to the EMG signals using coefficient of determination and cosines similarity. RESULTS: MRI-based models altered the magnitude of muscle activations and had a large impact on JCF but did not change the muscle activations profiles and therefore did not improve the agreement with EMG signals. SIGNIFICANCE: MRI-based models do not alter the shape of muscle activations. Hence, if detailed muscle activations are a desired output of the simulations, EMG-informed modeling approaches should be used for musculoskeletal simulation in children with cerebral palsy. Furthermore, our study highlighted that altered JCF does not necessarily mean accurate muscle activations. To improve patient-specific simulations, future work should focus on developing methods to estimate cost functions representative for the neural control of children with cerebral palsy.

Quantifying Muscle Forces and Joint Loading During Hip Exercises Performed With and Without an Elastic Resistance Band.

An increase in hip joint contact forces (HJCFs) is one of the main contributing mechanical causes of hip joint pathologies, such as hip osteoarthritis, and its progression. The strengthening of the surrounding muscles of the joint is a way to increase joint stability, which results in the reduction of HJCF. Most of the exercise recommendations are based on expert opinions instead of evidence-based facts. This study aimed to quantify muscle forces and joint loading during rehabilitative exercises using an elastic resistance band (ERB). Hip exercise movements of 16 healthy volunteers were recorded using a three-dimensional motion capture system and two force plates. All exercises were performed without and with an ERB and two execution velocities. Hip joint kinematics, kinetics, muscle forces, and HJCF were calculated based on the musculoskeletal simulations in OpenSim. Time-normalized waveforms of the different exercise modalities were compared with each other and with reference values found during walking. The results showed that training with an ERB increases both target muscle forces and HJCF. Furthermore, the ERB reduced the hip joint range of motion during the exercises. The type of ERB used (soft vs. stiff ERB) and the execution velocity of the exercise had a minor impact on the peak muscle forces and HJCF. The velocity of exercise execution, however, had an influence on the total required muscle force. Performing hip exercises without an ERB resulted in similar or lower peak HJCF and lower muscle forces than those found during walking. Adding an ERB during hip exercises increased the peak muscle and HJCF but the values remained below those found during walking. Our workflow and findings can be used in conjunction with future studies to support exercise design.

Torsion Tool: An automated tool for personalising femoral and tibial geometries in OpenSim musculoskeletal models.

Common practice in musculoskeletal modelling is to use scaled musculoskeletal models based on a healthy adult, but this does not consider subject-specific geometry, such as tibial torsion and femoral neck-shaft and anteversion angles (NSA and AVA). The aims of this study were to (1) develop an automated tool for creating OpenSim models with subject-specific tibial torsion and femoral NSA and AVA, (2) evaluate the femoral component, and (3) release the tool open-source. The Torsion Tool (https://simtk.org/projects/torsiontool) is a MATLAB-based tool that requires an individual's tibial torsion, NSA and AVA estimates as input and rotates corresponding bones and associated muscle points of a generic musculoskeletal model. Performance of the Torsion Tool was evaluated comparing femur bones as personalised with the Torsion Tool and scaled generic femurs with manually segmented bones as golden standard for six typically developing children and thirteen children with cerebral palsy. The tool generated femur geometries closer to the segmentations, with lower maximum (-19%) and root mean square (-18%) errors and higher Jaccard indices (+9%) compared to generic femurs. Furthermore, the tool resulted in larger improvements for participants with higher NSA and AVA deviations. The Torsion Tool allows an automatic, fast, and user-friendly way of personalising femoral and tibial geometry in an OpenSim musculoskeletal model. Personalisation is expected to be particularly relevant in pathological populations, as will be further investigated by evaluating the effects on simulation outcomes.

ESB Clinical Biomechanics Award 2020: Pelvis and hip movement strategies discriminate typical and pathological femoral growth - Insights gained from a multi-scale mechanobiological modelling framework.

BACKGROUND: Many children with cerebral palsy (CP) develop skeletal deformities during childhood. So far, it is unknown why some children with CP develop bony deformities whereas others do not. The aims of this study were to (i) investigate what loading characteristics lead to typical and pathological femoral growth, and (ii) evaluate why some children with CP develop femoral deformities whereas other do not. METHODS: A multi-scale mechanobiological modelling workflow was used to simulate femoral growth based on three-dimensional motion capture data of six typically developing children and 16 children with CP. Based on the growth results, the participants with CP were divided into two groups: typical growth group and pathological growth group. Gait kinematics and femoral loading were compared between simulations resulting in typical growth and those resulting in pathologic growth. FINDINGS: Hip joint contact forces were less posteriorly-oriented in the pathological growth simulations compared to the typical ones. Compared to the typically developing participants, the CP group with pathological femoral growth presented increased knee flexion and no hip extension. The CP group with simulated typical growth presented similar sagittal plane joint kinematics but differed in the frontal plane pelvic and hip movement strategy, which normalized the hip joint contact force and therefore contributed to typical femoral growth trends. INTERPRETATION: Our simulation results identified specific gait features, which may contribute to pathological femoral growth. Furthermore, the hip joint contact force orientation in the sagittal plane seems to be the dominant factor for determining femoral growth simulations.

Generic scaled versus subject-specific models for the calculation of musculoskeletal loading in cerebral palsy gait: Effect of personalized musculoskeletal geometry outweighs the effect of personalized neural control.

BACKGROUND: Musculoskeletal modelling is used to assess musculoskeletal loading during gait. Linear scaling methods are used to personalize generic models to each participant's anthropometry. This approach introduces simplifications, especially when used in paediatric and/or pathological populations. This study aimed to compare results from musculoskeletal simulations using various models ranging from linear scaled to highly subject-specific models, i.e., including the participant's musculoskeletal geometry and electromyography data. METHODS: Magnetic resonance images (MRI) and gait data of one typically developing child and three children with cerebral palsy were analysed. Musculoskeletal simulations were performed to calculate joint kinematics, joint kinetics, muscle forces and joint contact forces using four modelling frameworks: 1) Generic-scaled model with static optimization, 2) Generic-scaled model with an electromyography-informed approach, 3) MRI-based model with static optimization, and 4) MRI-based model with an electromyography-informed approach. FINDINGS: Root-mean-square-differences in joint kinematics and kinetics between generic-scaled and MRI-based models were below 5° and 0.15 Nm/kg, respectively. Root-mean-square-differences over all muscles was below 0.2 body weight for every participant. Root-mean-square-differences in joint contact forces between the different modelling frameworks were up to 2.2 body weight. Comparing the simulation results from the typically developing child with the results from the children with cerebral palsy showed similar root-mean-square-differences for all modelling frameworks. INTERPRETATION: In our participants, the impact of MRI-based models on joint contact forces was higher than the impact of including electromyography. Clinical reasoning based on overall root-mean-square-differences in musculoskeletal simulation results between healthy and pathological participants are unlikely to be affected by the modelling choice.

The importance of a consistent workflow to estimate muscle-tendon lengths based on joint angles from the conventional gait model.

BACKGROUND: Musculoskeletal models enable us to estimate muscle-tendon length, which has been shown to improve clinical decision-making and outcomes in children with cerebral palsy. Most clinical gait analysis services, however, do not include muscle-tendon length estimation in their clinical routine. This is due, in part, to a lack of knowledge and trust in the musculoskeletal models, and to the complexity involved in the workflow to obtain the muscle-tendon length. RESEARCH QUESTION: Can the joint angles obtained with the conventional gait model (CGM) be used to generate accurate muscle-tendon length estimates? METHODS: Three-dimensional motion capture data of 15 children with cerebral palsy and 15 typically developing children were retrospectively analyzed and used to estimate muscle-tendon length with the following four modelling frameworks: (1) 2392-OSM-IK-angles: standard OpenSim workflow including scaling, inverse kinematics and muscle analysis; (2) 2392-OSM-CGM-angle: generic 2392-OpenSim model driven with joint angles from the CGM; (3) modif-OSM-IK-angles: standard OpenSim workflow including inverse kinematics and a modified model with segment coordinate systems and joint degrees-of-freedom similar to the CGM; (4) modif-OSM-CGM-angles: modified model driven with joint angles from the CGM. Joint kinematics and muscle-tendon length were compared between the different modelling frameworks. RESULTS: Large differences in hip joint kinematics were observed between the CGM and the 2392-OpenSim model. The modif-OSM showed similar kinematics as the CGM. Muscle-tendon length obtained with modif-OSM-IK-angles and modif-OSM-CGM-angles were similar, whereas large differences in some muscle-tendon length were observed between 2392-OSM-IK-angles and 2392-OSM-CGM-angles. SIGNIFICANCE: The modif-OSM-CGM-angles framework enabled us to estimate muscle-tendon lengths without the need for scaling a musculoskeletal model and running inverse kinematics. Hence, muscle-tendon length estimates can be obtained simply, without the need for the complexity, knowledge and time required for musculoskeletal modeling and associated software. An instruction showing how the framework can be used in a clinical setting is provided on https://github.com/HansUniVie/MuscleLength.

3D free-hand ultrasound to register anatomical landmarks at the pelvis and localize the hip joint center in lean and obese individuals.

3D free-hand ultrasound (3DFUS) is becoming increasingly popular to assist clinical gait analysis because it is cost- and time-efficient and does not expose participants to radiation. The aim of this study was to evaluate its reliability in localizing the anterior superior iliac spine (ASIS) at the pelvis and the hip joint centers (HJC). Additionally, we evaluated its accuracy to get a rough estimation of the potential to use of 3DFUS to segment bony surface. This could offer potential to register medical images to motion capture data in future. To evaluate reliability, a test-retest study was conducted in 16 lean and 19 obese individuals. The locations of the ASIS were determined by manual marker placement (MMP), an instrumented pointer technique (IPT), and with 3DFUS. The HJC location was also determined with 3DFUS. To quantify reliability, intraclass correlation coefficients (ICCs), the standard error of measurement (SEm), among other statistical parameters, were calculated for the identified locations between the test and retest. To assess accuracy, the surface of a human plastic pelvic phantom was segmented with 3DFUS in a distilled water bath in 27 trials and compared to a 3D laser scan of the pelvis. Regarding reliability, the MMP, but especially the IPT showed high reliability in lean (SEm: 2-3 mm) and reduced reliability in obese individuals (SEm: 6-15 mm). Compared to MMP and IPT, 3DFUS presented lower reliability in the lean group (SEm: 2-4 mm vs. 2-8 mm, respectively) but slightly better values in the obese group (SEm: 7-11 mm vs. 6-16 mm, respectively). Correlations between test-retest reliability and torso body fat mass (% of body mass) indicated a moderate to strong relationship for MMP and IPT but only a weak correlation for the 3DFUS approach. The water-bath experiments indicated an acceptable level of 3.5 (1.7) mm of accuracy for 3DFUS in segmenting bone surface. Despite some difficulties with single trials, our data give further rise to the idea that 3DFUS could serve as a promising tool in future to inform marker placement and hip joint center location, especially in groups with higher amount of body fat.

Impact of scaling errors of the thigh and shank segments on musculoskeletal simulation results.

BACKGROUND: Musculoskeletal simulations are widely used in the research community. The locations of surface markers are mostly used to scale a generic model to the participant's anthropometry. Marker-based scaling approaches include errors due to inaccuracies in marker placements. RESEARCH QUESTION: How do scaling errors of the thigh and shank segments influence simulation results? METHODS: Motion capture data and magnetic resonance images from a child with cerebral palsy and a typically developing child were used to create a subject-specific reference model for each child. These reference models were modified to mimic scaling errors due to inaccurately placed lateral epicondyle markers, which are frequently used to scale the thigh and shank segments. The thigh length was altered in 1 % steps from the original length and the shank length was accordingly adjusted to keep the total leg length constant. Thirty additional models were created, which included models with an altered thigh length of ±15 %. Subsequently, musculoskeletal simulations with OpenSim were performed with all models. Joint kinematics, joint kinetics, muscle forces and joint contact forces (JCF) were compared between the reference and altered models. RESULTS: The investigated scaling error influenced joint kinematics and joint kinetics by up to 9.4° (hip flexion angle) and 0.15 Nm/kg (knee flexion moment), respectively. Maximum muscle and JCF differences of 46 % (medial gastrocnemius) and 72 % (hip JCF) bodyweight, respectively, were observed between the reference and altered models. Scaling errors mainly changed the magnitude but not the shape of most analyzed parameters. The influence of scaling errors on simulation results were similar in both participants. SIGNIFICANCE: Scaling errors of the thigh segment influence simulation results at all joints due to the global optimization approach used in musculoskeletal simulations. Our findings can be used to estimate potential errors due to marker-based scaling approaches in previous and future studies.

The effect of hip muscle weakness and femoral bony deformities on gait performance.

BACKGROUND: Children with cerebral palsy (CP) present with a pathological gait pattern due to musculoskeletal impairments, such as muscle weakness and altered bony geometry. However, the effect of these impairments on gait performance is still unknown. Research aim:This study aimed to explore the effect of hip muscle weakness and femoral deformities on the gait performance of CP and typical developing (TD) subjects. METHODS: 6400 musculoskeletal models were created by weakening the hip extensors, abductors, adductors and flexors from 0% to 75 % and increasing the femoral anteversion angle (FAA) and neck shaft angle (NSA) from 20° to 60° and 120° to 160°, respectively. One TD and five CP gait patterns were imposed to each model and muscle forces were calculated. The effect of weakness and bony deformities on the capability gap (CG) at the hip, i.e. the lack in hip moment generating capacity to perform the gait pattern, was investigated using regression analysis. RESULTS: The CG of apparent equinus, stiff knee gait, TD gait, jump gait and true equinus increased with 0.080, 0.038, 0.015, 0.023 and 0.005 Nm/kg per 10 percent hip abductor weakness increase, with 0.211, 0.130, 0.056, 0.045 and 0.011 Nm/kg per 10 degrees FAA increase and with 0.163, 0.080, 0.036, 0.043 and 0.011 Nm/kg per 10 degrees NSA increase, respectively. Combined weakness and bony deformities explained 96 %, 85 %, 82 %, 65 %, 40 % and 35 % of the variance in the CG of apparent equinus, TD gait, stiff knee gait, jump gait, true equinus and crouch gait, respectively. SIGNIFICANCE: The results suggest that surgical correction of femoral deformities is more likely to be effective than strength training of hip muscles in enhancing CP gait performance. Jump gait, true equinus and especially crouch were more robust, while apparent equinus and stiff knee gait were limited by hip weakness and femoral deformities.

A multi-scale modelling framework combining musculoskeletal rigid-body simulations with adaptive finite element analyses, to evaluate the impact of femoral geometry on hip joint contact forces and femoral bone growth.

Multi-scale simulations, combining muscle and joint contact force (JCF) from musculoskeletal simulations with adaptive mechanobiological finite element analysis, allow to estimate musculoskeletal loading and predict femoral growth in children. Generic linearly scaled musculoskeletal models are commonly used. This approach, however, neglects subject- and age-specific musculoskeletal geometry, e.g. femoral neck-shaft angle (NSA) and anteversion angle (AVA). This study aimed to evaluate the impact of proximal femoral geometry, i.e. altered NSA and AVA, on hip JCF and femoral growth simulations. Musculoskeletal models with NSA ranging from 120° to 150° and AVA ranging from 20° to 50° were created and used to calculate muscle and hip JCF based on the gait analysis data of a typically developing child. A finite element model of a paediatric femur was created from magnetic resonance images. The finite element model was morphed to the geometries of the different musculoskeletal models and used for mechanobiological finite element analysis to predict femoral growth trends. Our findings showed that hip JCF increase with increasing NSA and AVA. Furthermore, the orientation of the hip JCF followed the orientation of the femoral neck axis. Consequently, the osteogenic index, which is a function of cartilage stresses and defines the growth rate, barely changed with altered NSA and AVA. Nevertheless, growth predictions were sensitive to the femoral geometry due to changes in the predicted growth directions. Altered NSA had a bigger impact on the growth results than altered AVA. Growth simulations based on mechanobiological principles were in agreement with reported changes in paediatric populations.

Physics-Based Simulations to Predict the Differential Effects of Motor Control and Musculoskeletal Deficits on Gait Dysfunction in Cerebral Palsy: A Retrospective Case Study.

Physics-based simulations of walking have the theoretical potential to support clinical decision-making by predicting the functional outcome of treatments in terms of walking performance. Yet before using such simulations in clinical practice, their ability to identify the main treatment targets in specific patients needs to be demonstrated. In this study, we generated predictive simulations of walking with a medical imaging based neuro-musculoskeletal model of a child with cerebral palsy presenting crouch gait. We explored the influence of altered muscle-tendon properties, reduced neuromuscular control complexity, and spasticity on gait dysfunction in terms of joint kinematics, kinetics, muscle activity, and metabolic cost of transport. We modeled altered muscle-tendon properties by personalizing Hill-type muscle-tendon parameters based on data collected during functional movements, simpler neuromuscular control by reducing the number of independent muscle synergies, and spasticity through delayed muscle activity feedback from muscle force and force rate. Our simulations revealed that, in the presence of aberrant musculoskeletal geometries, altered muscle-tendon properties rather than reduced neuromuscular control complexity and spasticity were the primary cause of the crouch gait pattern observed for this child, which is in agreement with the clinical examination. These results suggest that muscle-tendon properties should be the primary target of interventions aiming to restore an upright gait pattern for this child. This suggestion is in line with the gait analysis following muscle-tendon property and bone deformity corrections. Future work should extend this single case analysis to more patients in order to validate the ability of our physics-based simulations to capture the gait patterns of individual patients pre- and post-treatment. Such validation would open the door for identifying targeted treatment strategies with the aim of designing optimized interventions for neuro-musculoskeletal disorders.

SimCP: A Simulation Platform to Predict Gait Performance Following Orthopedic Intervention in Children With Cerebral Palsy.

Gait deficits in cerebral palsy (CP) are often treated with a single-event multi-level surgery (SEMLS). Selecting the treatment options (combination of bony and soft tissue corrections) for a specific patient is a complex endeavor and very often treatment outcome is not satisfying. A deterioration in 22.8% of the parameters describing gait performance has been reported and there is need for additional surgery in 11% of the patients. Computational simulations based on musculoskeletal models that allow clinicians to test the effects of different treatment options before surgery have the potential to drastically improve treatment outcome. However, to date, no such simulation and modeling method is available. Two important challenges are the development of methods to include patient-specific neuromechanical impairments into the models and to simulate the effect of different surgical procedures on post-operative gait performance. Therefore, we developed the SimCP framework that allows the evaluation of the effect of different simulated surgeries on gait performance of a specific patient and includes a graphical user interface (GUI) that enables performing virtual surgery on the models. We demonstrated the potential of our framework for two case studies. Models reflecting the patient-specific musculoskeletal geometry and muscle properties are generated based solely on data collected before the treatment. The patient's motor control is described based on muscle synergies derived from pre-operative EMG. The GUI is then used to modify the musculoskeletal properties according to the surgical plan. Since SEMLS does not affect motor control, the same motor control model is used to define gait performance pre- and post-operative. We use the capability gap (CG), i.e., the difference between the joint moments needed to perform healthy walking and the joint moments the personalized model can generate, to quantify gait performance. In both cases, the CG was smaller post- then pre-operative and this was in accordance with the measured change in gait kinematics after treatment.

Selective dorsal rhizotomy improves muscle forces during walking in children with spastic cerebral palsy.

BACKGROUND: Selective dorsal rhizotomy aims to reduce spasticity in children with cerebral palsy. Early investigations indicated postoperative weakness, whereas more recent studies showed that selective dorsal rhizotomy either does not change or improves muscle strength. All previous studies assessed muscle strength in a static position, which did not represent the walking situation. The aim of this study was to analyze the influence of selective dorsal rhizotomy on muscle forces during gait. METHODS: Motion capture data of 25 children with spastic cerebral palsy and 10 typically developing participants were collected. A musculoskeletal OpenSim model was used to calculate joint kinematics, joint kinetics and muscle forces during gait. Static optimization and an electromyography-informed approach to calculate muscle forces were compared. A Muscle-Force-Profile was introduced and used to compare the muscle forces during walking before and after a selective dorsal rhizotomy. FINDINGS: Independent of the approach used (electromyography-informed versus static optimization), selective dorsal rhizotomy significantly normalized forces in spastic muscles during walking and did not reduce the contribution of non-spastic muscles. INTERPRETATION: This study showed that selective dorsal rhizotomy improves dynamic muscle forces in children with cerebral palsy and leads to less gait pathology, as shown in the improvement in joint kinematics and joint kinetics. Individual muscle force analyses using the Muscle-Force-Profile extend standard joint kinematics and joint moment analyses, which might improve clinical-decision making in children with cerebral palsy in the future. The reference data of our participants and MATLAB code for the Muscle-Force-Profile are publicly available on simtk.org/projects/muscleprofile.

The influence of maximum isometric muscle force scaling on estimated muscle forces from musculoskeletal models of children with cerebral palsy.

BACKGROUND: Musculoskeletal models do not include patient-specific muscle forces but rely on a scaled generic model, with muscle forces left unscaled in most cases. However, to use musculoskeletal simulations to inform clinical decision-making in children with cerebral palsy (CP), inclusion of subject-specific muscle forces is of utmost importance in order to represent each child's compensation mechanisms introduced through muscle weakness. RESEARCH AIM: The aims of this study were to (i) evaluate if maximum isometric muscle forces (MIMF) in musculoskeletal models of children with CP can be scaled based on strength measurements obtained with a hand-held-dynamometer (HHD), (ii) evaluate the impact of the HHD based scaling approach and previously published MIMF scaling methods on computed muscle forces during gait, and (iii) compare maximum muscle forces during gait between CP and typically developing (TD) children. METHODS: Strength and motion capture data of six CP and motion capture data of six TD children were collected. The HHD measurements to obtain hip, knee and ankle muscle strength were simulated in OpenSim and used to modify MIMF of the 2392-OpenSim model. These muscle forces were compared to the MIMF scaled on the child's body mass and a scaling approach, which included the body mass and muscle-tendon lengths. OpenSim was used to calculate peak muscle forces during gait. RESULTS: Ankle muscle strength was insufficient to reproduce joint moments during walking when MIMF were scaled based on HHD. During gait, peak hip and knee extensor muscle forces were higher and peak ankle dorsi-flexor forces were lower in CP compared to TD participants. SIGNIFICANCE: HHD measurements can be used to scale MIMF for the hip and knee muscle groups but underestimate the force capacity of the ankle muscle groups during walking. Muscle-tendon-length and mass based scaling methods affected muscle activations but had little influence on peak muscle forces during gait.