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Musculoskeletal modelling pipelines typically use generic models scaled to individual's anthropometry. The ability to represent variations in bone or joint geometry and alignment is highly limited. This may have a large effect, particularly when modelling contact between articular surfaces such as for the knee where articular contact mechanics are used to determine joint kinematics and the resulting cartilage contact pressures and locations. Here we describe a developed open-source framework for the personalisation of such models and compare dynamic simulation outputs. The framework involves three main steps: (1) positions personalised geometries from magnetic resonance imaging and replaces generic bone and contact geometries. (2) Repositions muscle and ligament attachments and via points and optimisation of wrapping surfaces to ensure physiological lengthening behaviour. Finally, (3) muscle and ligament properties are calibrated to ensure physiological behaviour. Following model creation, dynamic simulations from a single participant and gait trial were compared. Small changes in knee adduction/abduction and rotation angles were observed between models. Joint moment differences however were present in not only the knee but also hip and ankle joints. These differences resulted in changes in both the magnitude and location of knee joint contact pressure. The framework developed is automated and requires only minimal user interaction and is built using open-source software packages which can be freely downloaded and installed. The adoption of such personalised modelling approaches facilitates patient specific modelling and may provide more detailed information regarding disease progression, patient stratification and facilitate personalised rehabilitation and treatment planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Anatomical knee joint features and osteoarthritis (OA) severity are associated, however confirming causals link to altered knee loading is challenging. This study leverages statistical shape models (SSM) to investigate the relationship between joint shape/alignment and knee loading during gait in knee OA (KOA) patients to understand their contribution to elevated medial knee loading in OA. Musculoskeletal (MSK) models were created for the mean as well as the first eight SSM principal modes of variation (-3,-2,-1, +1, +2, +3 standard deviations for each mode) and used as input to a MSK modeling framework. Using an identical KOA gait pattern (i.e., joint kinematics and ground reaction forces), we ran simulations for each MSK model and evaluated medial compartment loading magnitude and contact distribution at the instant of first and second peak of knee joint loading. An increase in external rotation, posterior tibia translation and a decrease in medial joint space and medial femoral condylar size predisposed the medial compartment knee joint to overloading during gait. This was coupled with an anterior and medial shift in contact location with increasing external rotated tibial position and increasing posterior tibial translation with respect to the femur. Next, results also highlighted a posterior shift of the medial compartment loading location with decreasing medial joint space. This study provides important population-based insights on how knee shape and alignment predispose individuals with KOA to elevated medial compartmental knee loading. This information can be crucial in assessing the risk for medial KOA development and progression., (© 2024 Orthopaedic Research Society.)

Background: The complex anatomical structure of the foot-ankle imposes challenges to accurately quantify detailed hindfoot kinematics and estimate musculoskeletal loading parameters. Most systems used to capture or estimate dynamic joint function oversimplify the anatomical structure by reducing its complexity., Research Question: Can four dimensional computed tomography (4D CT) imaging in combination with an innovative foot manipulator capture in vivo hindfoot kinematics during a simulated stance phase of walking and can talocrural and subtalar articular joint mechanics be estimated based on a detailed in silico musculoskeletal foot-ankle model., Methods: A foot manipulator imposed plantar/dorsiflexion and inversion/eversion representing a healthy stance phase of gait in 12 healthy participants while simultaneously acquiring 4D CT images. Participant-specific 3D hindfoot rotations and translations were calculated based on bone-specific anatomical coordinate systems. Articular cartilage contact area and contact pressure of the talocrural and subtalar joints were estimated using an extended foot-ankle model updated with an elastic foundation contact model upon prescribing the participant-specific rotations measured in the 4D CT measurement., Results: Plantar/dorsiflexion predominantly occurred at the talocrural joint (RoM 15.9±3.9°), while inversion/eversion (RoM 5.9±3.9°) occurred mostly at the subtalar joint, with the contact area being larger at the subtalar than at the talocrural joint. Contact pressure was evenly distributed between the talocrural and subtalar joint at the beginning of the simulated stance phase but was then redistributed from the talocrural to the subtalar joint with increasing dorsiflexion., Significance: In a clinical case study, the healthy participants were compared with four patients after surgically treaded intra-articular calcaneal fracture. The proposed workflow was able to detect small but meaningful differences in hindfoot kinematics and kinetics, indicative of remaining hindfoot pathomechanics that may influence the onset and progression of degenerative joint diseases., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Barbara Postolka reports financial support was provided by the Swiss National Science Foundation [grant number 500PM 214210]. Hannelore Boey reports financial support was provided by the Research Foundation Flanders [grant number 1S36519N]. Jos Vander Sloten & Ilse Jonkers report financial support was provided by the Berghmans-Dereymaeker research chair on Foot & Ankle Biomechanics. The other authors declare to have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Corrective shoe insoles are prescribed for a range of foot deformities and are typically designed based on a subjective assessment limiting personalization and potentially leading to sub optimal treatment outcomes. The incorporation of in silico techniques in the design and customization of insoles may improve personalized correction and hence insole efficiency. Methods: We developed an in silico workflow for insole design and customization using a combination of measured motion capture, inverse musculoskeletal modelling as well as forward simulation approaches to predict the kinematic response to specific insole designs. The developed workflow was tested on twenty-seven participants containing a combination of healthy participants (7) and patients with flatfoot deformity (20). Results: Average error between measured and simulated kinematics were 4.7 ± 3.1, 4.5 ± 3.1, 2.3 ± 2.3, and 2.3 ± 2.7° for the chopart obliquity, chopart anterior-posterior axis, tarsometatarsal first ray, and tarsometatarsal fifth ray joints respectively. Discussion : The developed workflow offers distinct advantages to previous modeling workflows such as speed of use, use of more accessible data, use of only open-source software, and is highly automated. It provides a solid basis for future work on improving predictive accuracy by adapting the currently implemented insole model and incorporating additional data such as plantar pressure., Competing Interests: Author SV and FB were employed by the company Materialise. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Killen, Van Rossom, Burg, Vander Sloten and Jonkers.)

The purpose of this study was to determine the effect of donor muscle morphology following tendon harvest in anterior cruciate ligament (ACL) reconstruction on muscular support of the tibiofemoral joint during sidestep cutting. Magnetic resonance imaging (MRI) was used to measure peak cross-sectional area (CSA) and volume of the semitendinosus (ST) and gracilis (GR) muscles and tendons (bilaterally) in 18 individuals following ACL reconstruction. Participants performed sidestep cutting tasks in a biomechanics laboratory during which lower-limb electromyography, ground reaction loads, whole-body motions were recorded. An EMG driven neuro-musculoskeletal model was subsequently used to determine force from 34 musculotendinous units of the lower limb and the contribution of the ST and GR to muscular support of the tibiofemoral joint based on a normal muscle-tendon model (Standard model). Then, differences in peak CSA and volume between the ipsilateral/contralateral ST and GR were used to adjust their muscle-tendon parameters in the model followed by a recalibration to determine muscle force for 34 musculotendinous units (Adjusted model). The combined contribution of the donor muscles to muscular support about the medial and lateral compartments were reduced by 52% and 42%, respectively, in the adjusted compared to standard model. While the semimembranosus (SM) increased its contribution to muscular stabilisation about the medial and lateral compartment by 23% and 30%, respectively. This computer simulation study demonstrated the muscles harvested for ACL reconstruction reduced their support of the tibiofemoral joint during sidestep cutting, while the SM may have the potential to partially offset these reductions. This suggests donor muscle impairment could be a factor that contributes to ipsilateral re-injury rates to the ACL following return to sport., Competing Interests: The authors declare that no competing interests exist., (Copyright: © 2023 Konrath et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Flatfoot deformity is a prevalent hind- and midfoot disorder. Given its complexity, single-plane radiological measurements omit case-specific joint interaction and bone shape variations. Three-dimensional medical imaging assessment using statistical shape models provides a complete approach in characterizing bone shape variations unique to flatfoot condition. This study used statistical shape models to define specific bone shape variations of the subtalar, talonavicular, and calcaneocuboid joints that characterize flatfoot deformity, that differentiate them from healthy controls. Bones of the aforementioned joints were segmented from computed tomography scans of 40 feet. The three-dimensional hindfoot alignment angle categorized the population into 18 flatfoot subjects (≥7° valgus) and 22 controls. Statistical shape models for each joint were defined using the entire study cohort. For each joint, an average weighted shape parameter was calculated for each mode of variation, and then compared between flatfoot and controls. Significance was set at p < 0.05, with values between 0.05 ≤ p < 0.1 considered trending towards significance. The flatfoot population showed a more adducted talar head, inferiorly inclined talar neck, and posteriorly orientated medial subtalar articulation compare to controls, coupled with more navicular eversion, shallower navicular cup, and more prominent navicular tuberosity. The calcaneocuboid joint presented trends of a more adducted calcaneus, more abducted cuboid, narrower calcaneal roof, and less prominent cuboid beak compared to controls. Statistical shape model analysis identified unique shape variations which may enhance understanding and computer-aided models of the intricacies of flatfoot, leading to better diagnosis and, ultimately, surgical treatment., (© 2022 American Association of Clinical Anatomists and British Association of Clinical Anatomists.)

Introduction: Knee osteoarthritis (KOA) is characterized by articular cartilage degeneration. It has been widely accepted that the mechanical joint environment plays a significant role in the onset and progression of this disease. In silico models have been used to study the interplay between mechanical loading and cartilage degeneration, hereby relying mainly on two key mechanoregulatory factors indicative of collagen degradation and proteoglycans depletion. These factors are the strain in collagen fibril direction (SFD) and maximum shear strain (MSS) respectively. Methods: In this study, a multi-scale in silico modeling approach was used based on a synergy between musculoskeletal and finite element modeling to evaluate the SFD and MSS. These strains were evaluated during gait based on subject-specific gait analysis data collected at baseline (before a 2-year follow-up) for a healthy and progressive early-stage KOA subject with similar demographics. Results: The results show that both SFD and MSS factors allowed distinguishing between a healthy subject and a KOA subject, showing progression at 2 years follow-up, at the instance of peak contact force as well as during the stance phase of the gait cycle. At the peak of the stance phase, the SFD were found to be more elevated in the KOA patient with the median being 0.82% higher in the lateral and 0.4% higher in the medial compartment of the tibial cartilage compared to the healthy subject. Similarly, for the MSS, the median strains were found to be 3.6% higher in the lateral and 0.7% higher in the medial tibial compartment of the KOA patient compared to the healthy subject. Based on these intersubject SFD and MSS differences, we were additionally able to identify that the tibial compartment of the KOA subject at risk of progression. Conclusion/discussion: We confirmed the mechanoregulatory factors as potential biomarkers to discriminate patients at risk of disease progression. Future studies should evaluate the sensitivity of the mechanoregulatory factors calculated based on this multi-scale modeling workflow in larger patient and control cohorts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Mohout, Elahi, Esrafilian, Killen, Korhonen, Verschueren and Jonkers.)

In this review, we elaborate on how musculoskeletal (MSK) modeling combined with dynamic movement simulation is gradually evolving from a research tool to a promising in silico tool to assist medical doctors and physical therapists in decision making by providing parameters relating to dynamic MSK function and loading. This review primarily focuses on our own and related work to illustrate the framework and the interpretation of MSK model-based parameters in patients with 3 different conditions, that is, degenerative joint disease, cerebral palsy, and adult spinal deformities. By selecting these 3 clinical applications, we also aim to demonstrate the differing levels of clinical readiness of the different simulation frameworks introducing in silico model-based biomarkers of motor function to inform MSK rehabilitation and treatment, with the application for adult spinal deformities being the most recent of the 3. Based on these applications, barriers to clinical integration and positioning of these in silico technologies within standard clinical practice are discussed in the light of specific challenges related to model assumptions, required level of complexity and personalization, and clinical implementation.

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.

Neuromusculoskeletal models are a powerful tool to investigate the internal biomechanics of an individual. However, commonly used neuromusculoskeletal models are generated via linear scaling of generic templates derived from elderly adult anatomies and poorly represent a child, let alone children with a neuromuscular disorder whose musculoskeletal structures and muscle activation patterns are profoundly altered. Model personalization can capture abnormalities and appropriately describe the underlying (altered) biomechanics of an individual. In this work, we explored the effect of six different levels of neuromusculoskeletal model personalization on estimates of muscle forces and knee joint contact forces to tease out the importance of model personalization for normal and abnormal musculoskeletal structures and muscle activation patterns. For six children, with and without cerebral palsy, generic scaled models were developed and progressively personalized by (1) tuning and calibrating musculotendon units' parameters, (2) implementing an electromyogram-assisted approach to synthesize muscle activations, and (3) replacing generic anatomies with image-based bony geometries, and physiologically and physically plausible muscle kinematics. Biomechanical simulations of gait were performed in the OpenSim and CEINMS software on ten overground walking trials per participant. A mixed-ANOVA test, with Bonferroni corrections, was conducted to compare all models' estimates. The model with the highest level of personalization produced the most physiologically plausible estimates. Model personalization is crucial to produce physiologically plausible estimates of internal biomechanical quantities. In particular, personalization of musculoskeletal anatomy and muscle activation patterns had the largest effect overall. Increased research efforts are needed to ease the creation of personalized neuromusculoskeletal models., (© 2022. The Author(s).)

Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R 2 between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach.

Background: Anterior cruciate ligament reconstruction (ACLR) together with concomitant meniscal injury are risk factors for the development of tibiofemoral (TF) osteoarthritis (OA), but the potential effect on the patellofemoral (PF) joint is unclear. The aim of this study was to: (i) investigate change in patellar cartilage morphology in individuals 2.5 to 4.5 years after ACLR with or without concomitant meniscal pathology and in healthy controls, and (ii) examine the association between baseline patellar cartilage defects and patellar cartilage volume change., Methods: Thirty two isolated ACLR participants, 25 ACLR participants with combined meniscal pathology and nine healthy controls underwent knee magnetic resonance imaging (MRI) with 2-year intervals (baseline = 2.5 years post-ACLR). Patellar cartilage volume and cartilage defects were assessed from MRI using validated methods., Results: Both ACLR groups showed patellar cartilage volume increased over 2 years (p < 0.05), and isolated ACLR group had greater annual percentage cartilage volume increase compared with controls (mean difference 3.6, 95% confidence interval (CI) 1.0, 6.3%, p = 0.008) and combined ACLR group (mean difference 2.2, 95% CI 0.2, 4.2%, p = 0.028). Patellar cartilage defects regressed in the isolated ACLR group over 2 years (p = 0.02; Z = - 2.33; r = 0.3). Baseline patellar cartilage defect score was positively associated with annual percentage cartilage volume increase (Regression coefficient B = 0.014; 95% CI 0.001, 0.027; p = 0.03) in the pooled ACLR participants., Conclusions: Hypertrophic response was evident in the patellar cartilage of ACLR participants with and without meniscal pathology. Surprisingly, the increase in patellar cartilage volume was more pronounced in those with isolated ACLR. Although cartilage defects stabilised in the majority of ACLR participants, the severity of patellar cartilage defects at baseline influenced the magnitude of the cartilage hypertrophic response over the subsequent ~ 2 years., (© 2021. The Author(s).)

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., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Computational modelling is an invaluable tool for investigating features of human locomotion and motor control which cannot be measured except through invasive techniques. Recent research has focussed on creating personalised musculoskeletal models using population-based morphing or directly from medical imaging. Although progress has been made, robust definition of two critical model parameters remains challenging: (1) complete tibiofemoral (TF) and patellofemoral (PF) joint motions, and (2) muscle tendon unit (MTU) pathways and kinematics (i.e. lengths and moment arms). The aim of this study was to develop an automated framework, using population-based morphing approaches to create personalised musculoskeletal models, consisting of personalised bone geometries, TF and PF joint mechanisms, and MTU pathways and kinematics. Informed from medical imaging, personalised rigid body TF and PF joint mechanisms were created. Using atlas- and optimisation-based methods, personalised MTU pathways and kinematics were created with the aim of preventing MTU penetration into bones and achieving smooth MTU kinematics that follow patterns from existing literature. This framework was integrated into the Musculoskeletal Atlas Project Client software package to create and optimise models for 6 participants with incrementally increasing levels of personalisation with the aim of improving MTU kinematics and pathways. Three comparisons were made: (1) non-optimised (Model 1) and optimised models (Model 3) with generic joint mechanisms; (2) non-optimised (Model 2) and optimised models (Model 4) with personalised joint mechanisms; and (3) both optimised models (Model 3 and 4). Following optimisation, improvements were consistently shown in pattern similarity to cadaveric data in comparison (1) and (2). For comparison (3), a number of comparisons showed no significant difference between the two compared models. Importantly, optimisation did not produce statistically significantly worse results in any case.

Background: Studies of walking in those with femoroacetabular impingement syndrome have found altered pelvis and hip biomechanics. But a whole body, time-contiuous, assessment of biomechanical parameters has not been reported. Additionally, larger cam morphology has been associated with more pain, faster progression to end-stage osteoarthritis and increased cartilage damage but differences in walking biomechanics between large compared to small cam morphologies have not been assessed., Research Question: Are trunk, pelvis and lower limb biomechanics different between healthy pain-free controls and individuals with FAI syndrome and are those biomechanics different between those with larger, compared to smaller, cam morphologies?, Methods: Twenty four pain-free controls were compared against 41 participants with FAI syndrome who were stratified into two groups according to their maximum alpha angle. Participants underwent three-dimensional motion capture during walking. Trunk, pelvis, and lower limb biomechanics were compared between groups using statistical parametric mapping corrected for walking speed and pain., Results: Compared to pain-free controls, participants with FAI syndrome walked with more trunk anterior tilt (mean difference 7.6°, p < 0.001) as well as less pelvic rise (3°, p < 0.001), hip abduction (-4.6°, p < 0.05) and external rotation (-6.5°, p < 0.05). They also had lower hip flexion (-0.06Nm⋅kg -1 , p < 0.05), abduction (-0.07Nm⋅kg -1 , p < 0.05) and ankle plantarflexion moments (-0.19Nm⋅kg -1 , p < 0.001). These biomechanical differences occurred throughout the gait cycle. There were no differences in walking biomechanics according to cam morphology size., Significance: Results do not support the hypothesis that larger cam morphology is associated with larger differences in walking biomechanics but did demonstrate general differences in trunk, pelvis and lower limb biomechanics between those with FAI sydrome and pain-free controls. Altered external biomechanics are likely the result of complex sensory-motor strategy resulting from pain inhibition or impingement avoidance. Future studies should examine internal loading in those with FAI sydnrome., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In biomechanical simulations, generic linearly scaled musculoskeletal anatomies are commonly used to represent children, often neglecting or oversimplifying subject-specific features that may affect model estimates. Inappropriate bone sizing may influence joint angles due to erroneous joint centre identification. Alternatively, subject-specific image-based musculoskeletal models allow for more realistic representations of the skeletal system. To this end, statistical shape modelling (SSM) and morphing techniques may help to reconstruct bones rapidly and accurately. Specifically, the musculoskeletal atlas project (MAP) Client, which employs magnetic resonance imaging (MRI) and/or motion capture data to inform SSM and nonrigid morphing techniques, proved able to accurately reconstruct adult pelvis and femur bones. Nonetheless, to date, the above methods have never been applied to paediatric data. In this study, pelvis, femurs and tibiofibular bones of 18 typically developing children were reconstructed using the MAP Client. Ten different combinations of SSM and morphing techniques, i.e. pipelines, were developed. Generic bone geometries from the gait2392 OpenSim model were linearly scaled for comparisons. Jaccard index, root mean square distance error and Hausdorff distance were computed to quantify reconstruction accuracy. For the pelvis bone, colour maps were produced to identify areas prone to inaccuracies and hip joint centres (HJC) location was compared. Finally, per cent difference between MRI- and MAP-measured left-to-right HJC distances was computed. Pipelines informed by MRI data, alone or in combination with motion capture data, accurately reconstructed paediatric lower limb bones (i.e. Jaccard index > 0.8). Scaled OpenSim geometries provided the least accurate reconstructions. Principal component-based scaling methods produced size-dependent results, which were worse for smaller children.

Many biomedical, orthopaedic, and industrial applications are emerging that will benefit from personalized neuromusculoskeletal models. Applications include refined diagnostics, prediction of treatment trajectories for neuromusculoskeletal diseases, in silico design, development, and testing of medical implants, and human-machine interfaces to support assistive technologies. This review proposes how physics-based simulation, combined with machine learning approaches from big data, can be used to develop high-fidelity personalized representations of the human neuromusculoskeletal system. The core neuromusculoskeletal model features requiring personalization are identified, and big data/machine learning approaches for implementation are presented together with recommendations for further research.

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., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Musculoskeletal models are important tools for studying movement patterns, tissue loading, and neuromechanics. Personalising bone anatomy within models improves analysis accuracy. Few studies have focused on personalising foot bone anatomy, potentially incorrectly estimating the foot's contribution to locomotion. Statistical shape models have been created for a subset of foot-ankle bones, but have not been validated. This study aimed to develop and validate statistical shape models of the functional segments in the foot: first metatarsal, midfoot (second-to-fifth metatarsals, cuneiforms, cuboid, and navicular), calcaneus, and talus; then, to assess reconstruction accuracy of these shape models using sparse anatomical data., Methods: Magnetic resonance images of 24 individuals feet (age = 28 ± 6 years, 52% female, height = 1.73 ± 0.8 m, mass = 66.6 ± 13.8 kg) were manually segmented to generate three-dimensional point clouds. Point clouds were registered and analysed using principal component analysis. For each bone segment, a statistical shape model and principal components were created, describing population shape variation. Statistical shape models were validated by assessing reconstruction accuracy in a leave-one-out cross validation. Statistical shape models were created by excluding a participant's bone segment and used to reconstruct that same excluded bone using full segmentations and sparse anatomical data (i.e. three discrete points on each segment), for all combinations in the dataset. Tali were not reconstructed using sparse anatomical data due to a lack of externally accessible landmarks. Reconstruction accuracy was assessed using Jaccard index, root mean square error (mm), and Hausdorff distance (mm)., Results: Reconstructions generated using full segmentations had mean Jaccard indices between 0.77 ± 0.04 and 0.89 ± 0.02, mean root mean square errors between 0.88 ± 0.19 and 1.17 ± 0.18 mm, and mean Hausdorff distances between 2.99 ± 0.98 mm and 6.63 ± 3.68 mm. Reconstructions generated using sparse anatomical data had mean Jaccard indices between 0.67 ± 0.06 and 0.83 ± 0.05, mean root mean square error between 1.21 ± 0.54 mm and 1.66 ± 0.41 mm, and mean Hausdorff distances between 3.21 ± 0.94 mm and 7.19 ± 3.54 mm. Jaccard index was higher ( P < 0.01) and root mean square error was lower ( P < 0.01) in reconstructions from full segmentations compared to sparse anatomical data. Hausdorff distance was lower ( P < 0.01) for midfoot and calcaneus reconstructions using full segmentations compared to sparse anatomical data., Conclusion: For the first time, statistical shape models of the primary functional segments of the foot were developed and validated. Foot segments can be reconstructed with minimal error using full segmentations and sparse anatomical landmarks. In future, larger training datasets could increase statistical shape model robustness, extending use to paediatric or pathological populations., Competing Interests: The authors declare that they have no competing interests., (© 2020 Grant et al.)

Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p = <0.001) and regression (31.2 ± 15 mm, p = <0.001) methods. The addition of complete pelvis imaging data to the shape modelling workflow further reduced HJC error estimates compared to no imaging (6.6 ± 3.1 mm, p = 0.002). Average RMSE were greatest for the hip flexor and extensor muscle groups using the functional (16.71 mm and 8.87 mm respectively) and regression methods (16.15 mm and 9.97 mm respectively). The effects on moment-arms were less substantial for the shape modelling methods, ranging from 0.05 to 3.2 mm. Shape modelling methods improved HJC location and muscle moment-arm estimates compared to linear scaling of musculoskeletal models in patients with hip osteoarthritis., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Accurate representation of subject-specific bone anatomy in lower-limb musculoskeletal models is important for human movement analyses and simulations. Mathematical methods can reconstruct geometric bone models using incomplete imaging of bone by morphing bone model templates, but the validity of these methods has not been fully explored. The purpose of this study was to determine the minimal imaging requirements for accurate reconstruction of geometric bone models. Complete geometric pelvis and femur models of 14 healthy adults were reconstructed from magnetic resonance imaging through segmentation. From each complete bone segmentation, three sets of incomplete segmentations (set 1 being the most incomplete) were created to test the effect of imaging incompleteness on reconstruction accuracy. Geometric bone models were reconstructed from complete sets, three incomplete sets, and two motion capture-based methods. Reconstructions from (in)complete sets were generated using statistical shape modelling, followed by host-mesh and local-mesh fitting through the Musculoskeletal Atlas Project Client. Reconstructions from motion capture-based methods used positional data from skin surface markers placed atop anatomic landmarks and estimated joint centre locations as target points for statistical shape modelling and linear scaling. Accuracy was evaluated with distance error (mm) and overlapping volume similarity (%) between complete bone segmentation and reconstructed bone models, and statistically compared using a repeated measure analysis of variance (p<0.05). Motion capture-based methods produced significantly higher distance error than reconstructions from (in)complete sets. Pelvis volume similarity reduced significantly with the level of incompleteness: complete set (92.70±1.92%), set 3 (85.41±1.99%), set 2 (81.22±3.03%), set 1 (62.30±6.17%), motion capture-based statistical shape modelling (41.18±9.54%), and motion capture-based linear scaling (26.80±7.19%). A similar trend was observed for femur volume similarity. Results indicate that imaging two relevant bone regions produces overlapping volume similarity >80% compared to complete segmented bone models, and improve analyses and simulation over current standard practice of linear scaling musculoskeletal models., Competing Interests: The authors have declared that no competing interests exist.

The tibiofemoral joint (TFJ) experiences large compressive articular contact loads during activities of daily living, caused by inertial, ligamentous, capsular, and most significantly musculotendon loads. Comparisons of relative contributions of individual muscles to TFJ contact loading between walking and sporting movements have not been previously examined. The purpose of this study was to determine relative contributions of individual lower-limb muscles to compressive articular loading of the medial and lateral TFJ during walking, running, and sidestepping. The medial and lateral compartments of the TFJ were loaded by a combination of medial and lateral muscles. During all gait tasks, the primary muscles loading the medial and lateral TFJ were the vastus medialis (VM) and vastus lateralis (VL) respectively during weight acceptance, while typically the medial gastrocnemii (MG) and lateral gastrocnemii (LG) dominated medial and lateral TFJ loading respectively during midstance and push off. Generally, the contribution of the quadriceps muscles were higher in running compared to walking, whereas gastrocnemii contributions were higher in walking compared to running. When comparing running and sidestepping, contributions to medial TFJ contact loading were generally higher during sidestepping while contributions to lateral TFJ contact loading were generally lower. These results suggests that after orthopaedic procedures, the VM, VL, MG and LG should be of particular rehabilitation focus to restore TFJ stability during dynamic gait tasks., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: The muscle-tendon properties of the semitendinosus (ST) and gracilis (GR) are substantially altered following tendon harvest for the purpose of anterior cruciate ligament reconstruction (ACLR). This study adopted a musculoskeletal modelling approach to determine how the changes to the ST and GR muscle-tendon properties alter their contribution to medial compartment contact loading within the tibiofemoral joint in post ACLR patients, and the extent to which other muscles compensate under the same external loading conditions during walking, running and sidestep cutting., Materials and Methods: Motion capture and electromyography (EMG) data from 16 lower extremity muscles were acquired during walking, running and cutting in 25 participants that had undergone an ACLR using a quadruple (ST+GR) hamstring auto-graft. An EMG-driven musculoskeletal model was used to estimate the medial compartment contact loads during the stance phase of each gait task. An adjusted model was then created by altering muscle-tendon properties for the ST and GR to reflect their reported changes following ACLR. Parameters for the other muscles in the model were calibrated to match the experimental joint moments., Results: The medial compartment contact loads for the standard and adjusted models were similar. The combined contributions of ST and GR to medial compartment contact load in the adjusted model were reduced by 26%, 17% and 17% during walking, running and cutting, respectively. These deficits were balanced by increases in the contribution made by the semimembranosus muscle of 33% and 22% during running and cutting, respectively., Conclusion: Alterations to the ST and GR muscle-tendon properties in ACLR patients resulted in reduced contribution to medial compartment contact loads during gait tasks, for which the semimembranosus muscle can compensate.

Purpose: To investigate differences in anterior cruciate ligament-reconstructed (ACLR) and healthy individuals in terms of the magnitude of the tibiofemoral contact forces, as well as the relative muscle and external load contributions to those contact forces, during walking, running, and sidestepping gait tasks., Methods: A computational EMG-driven neuromusculoskeletal model was used to estimate the muscle and tibiofemoral contact forces in those with single-bundle combined semitendinosus and gracilis tendon autograft ACLR (n = 104, 29.7 ± 6.5 yr, 78.1 ± 14.4 kg) and healthy controls (n = 60, 27.5 ± 5.4 yr, 67.8 ± 14.0 kg) during walking (1.4 ± 0.2 m·s), running (4.5 ± 0.5 m·s) and sidestepping (3.7 ± 0.6 m·s). Within the computational model, the semitendinosus of ACLR participants was adjusted to account for literature reported strength deficits and morphological changes subsequent to autograft harvesting., Results: ACLR had smaller maximum total and medial tibiofemoral contact forces (~80% of control values, scaled to bodyweight) during the different gait tasks. Compared with controls, ACLR were found to have a smaller maximum knee flexion moment, which explained the smaller tibiofemoral contact forces. Similarly, compared with controls, ACLR had both a smaller maximum knee flexion angle and knee flexion excursion during running and sidestepping, which may have concentrated the articular contact forces to smaller areas within the tibiofemoral joint. Mean relative muscle and external load contributions to the tibiofemoral contact forces were not significantly different between ACLR and controls., Conclusions: ACLR had lower bodyweight-scaled tibiofemoral contact forces during walking, running, and sidestepping, likely due to lower knee flexion moments and straighter knee during the different gait tasks. The relative contributions of muscles and external loads to the contact forces were equivalent between groups.