Surgical parameters influence paediatric knee kinematics and cartilage stresses in anterior cruciate ligament reconstruction: Navigating subject-specific variability using neuromusculoskeletal-finite element modelling analysis.

PURPOSE: Anterior cruciate ligament (ACL) rupture is increasingly common in paediatric and adolescent populations, typically requiring surgical ACL reconstruction (ACLR) to restore knee stability. However, ACLR substantially alters knee biomechanics (e.g., motion and tissue mechanics) placing the patient at elevated risk of early-onset knee osteoarthritis. METHODS: This study employed a linked neuromusculoskeletal (NMSK)-finite element (FE) model to determine effects of four critical ACLR surgical parameters (graft type, size, location and pre-tension) on tibial articular cartilage stresses in three paediatric knees of different sizes during walking. Optimal surgical combinations were defined by minimal kinematic and tibial cartilage stress deviations in comparison to a corresponding intact healthy knee, with substantial deviations defined by normalized root mean square error (nRMSE) > 10%. RESULTS: Results showed unique trends of principal stress deviations across knee sizes with small knee showing least deviation from intact knee, followed by large- and medium-sized knees. The nRMSE values for cartilage stresses displayed notable variability across different knees. Surgical combination yielding the highest nRMSE in comparison to the one with lowest nRMSE resulted in an increase of maximum principal stress on the medial tibial cartilage by 18.0%, 6.0% and 1.2% for small, medium and large knees, respectively. Similarly, there was an increase of maximum principal stress on lateral tibial cartilage by 11.2%, 4.1% and 12.7% for small, medium and large knees, respectively. Knee phenotype and NMSK factors contributed to deviations in knee kinematics and tibial cartilage stresses. Although optimal surgical configurations were found for each knee size, no generalizable trends emerged emphasizing the subject-specific nature of the knee and neuromuscular system. CONCLUSION: Study findings underscore subject-specific complexities in ACLR biomechanics, necessitating personalized surgical planning for effective restoration of native motion and tissue mechanics. Future research should expand investigations to include a broader spectrum of subject-specific factors to advance personalized surgical planning. LEVEL OF EVIDENCE: Level III.

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.

Automatic generation of knee kinematic models from medical imaging.

BACKGROUND AND OBJECTIVE: Three-dimensional spatial mechanisms have been used to accurately predict passive knee kinematics, and have shown potential to be used in optimized multibody kinematic models. Such multi-body models are anatomically consistent and can accurately predict passive knee kinematics, but require extensive medical image processing and thus are not widely adopted. This study aimed to automate the generation of kinematic models of tibiofemoral (TFJ) and patellofemoral (PFJ) joints from segmented magnetic resonance imaging (MRI) and compare them against a corresponding manual pipeline. METHODS: From segmented MRI of eight healthy participants (four females; aged 14.0 ± 2.6 years), geometric parameters (i.e., articular surfaces, ligament attachments) were determined both automatically and manually, and then assembled into TFJ and PFJ kinematic models to predict passive kinematics. The TFJ model was a six-link mechanism with deformable ligamentous constraints, whereas PFJ was a modified hinge. The ligament length changes through TFJ flexion were prescribed to literature strain profile. The geometric parameters were optimized to ensure physiological kinematic predictions through a Multiple Objective Particle Swarm Optimization. RESULTS: Geometric parameters showed strong agreement between automatic and manual pipelines (median error of 2.8 mm for anatomical landmarks and 1.5 mm for ligament lengths). Predicted TFJ and PFJ kinematics from the two pipelines were not statistically different, except for tibial superior/inferior translation near terminal TFJ extension. The TFJ kinematics predicted from the automatic pipeline had mean errors of 3.6° and 12.4° for adduction/abduction and internal/external rotation, respectively, and <7 mm mean translational error compared to the manual pipeline. Predicted PFJ had <9° mean rotational errors and <6 mm mean translational errors. CONCLUSIONS: The automatic pipeline developed and presented here can predict passive knee kinematics comparable to a manual pipeline, but removes laborious manual processing and provides a systematic approach to model creation.

A 100-day mentoring program leads to positive shifts in girls' perceptions and attitudes towards biomechanics and related STEM disciplines.

The gender gap in STEM (Science, Technology, Engineering, and Mathematics) is among the widest across education and professional fields, with an underrepresentation of girls and women, particularly in engineering and biomechanics. This issue begins early in education and worsens as females progress into more senior roles. To address this gap, we designed and implemented the Biomechanics Research and Innovation Challenge (BRInC), a 100-day STEM program focused on mentoring and role modelling to engage high school girls and early-career biomechanists at key phases where they most commonly disengage in STEM. We evaluated the influence of the program on (i) identity and perceptions towards science, engineering, and biomechanics; (ii) attitudes towards biomechanics, maths and science; and (iii) attitudes towards gender bias, education and career aspirations in STEM, within high school girls following participation in the BRInC program. We observed significant and positive shifts in girls' perceptions of both biomechanics and engineering. Participation in the program appeared to lead to favourable shifts in attitudes towards biomechanics, maths, and science and fostered a positive influence on girls' education and career aspirations, igniting an interest in future research opportunities. Innovative STEM engagement programs, such as BRInC, highlight the promising potential of targeted and bespoke approaches to address the underrepresentation of females in biomechanics and STEM-related education and careers. Future programs should strive to enhance socioeconomic and cultural diversity, employ whole of life-cycle approaches by offering programs for girls and women at various phases of the STEM pathway, and prioritize impact assessments to effectively monitor progress.

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.

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.

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.

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.

Dependency of lower limb joint reaction forces on femoral version.

BACKGROUND: Musculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an individual's anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral version angle. RESEARCH QUESTION: How are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral version? METHODS: We developed a bone-deformation tool in MATLAB (shared at https://simtk.org/projects/bone_deformity) and used it to create a set of seven OpenSim models spanning from 2˚ femoral retroversion to 40˚ anteversion. We used these models to simulate the gait of an elderly individual with an instrumented prosthesis implanted at their knee joint (5th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint. RESULTS: Hip and knee JRF magnitudes were affected by the femoral version with variations from the unmodified generic model up to 17.9 ±â€¯4.5% at the hip and 43.4 ±â€¯27.1% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370 ±â€¯0.068 body weight, coefficient of determination: 0.757 ±â€¯0.104, peak error range: 0.09-0.42 body weight) were those with femoral anteversion angle closer to that measured on the segmented bone of the individual. SIGNIFICANCE: Femoral version substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JRFs with these models.

Bisect offset ratio and cartilaginous sulcus angle are good combined predictors of recurrent patellar dislocation in children and adolescents.

OBJECTIVES: Recurrent patellar dislocation (RPD) is found most commonly in the juvenile population. While risk factors have been well-established in adults, there remains a paucity in radiographical data to define normal and pathoanatomical juvenile cohorts. The objectives of this paper were to elucidate the differences in the patellofemoral joint between RPD and typically developed (TD) juvenile populations, using MRI measurements, and determine the best independent and combined predictors of RPD. METHODS: A prospective, cross-sectional study was conducted with 25 RPD and 24 TD participants aged between 8 and 19 years. MR images were obtained to assess common measures of lower limb alignment, patellofemoral alignment, and trochlear dysplasia. RESULTS: Significant differences were evident for acetabular inclination, tibial-femoral torsion, tibial tubercle-to-trochlear groove (TT-TG) distance, lateral patellar tilt (LPT), cartilaginous sulcus angle (CSA) and bisect offset ratio (BOR). CSA and BOR were included in the final predictive model, which correctly classified 89.4% of RPD cases. CONCLUSION: Radiographical parameters that stratify risk of RPD in adults are also able to predict RPD in the pediatric population (TT-TG, LPT, CSA and BOR). Together, CSA and BOR accurately identified 89.4% of RPD. These measures should be included in the evaluation of pediatric patients who present with patellar dislocation. LEVEL OF EVIDENCE: Level II.

Best methods and data to reconstruct paediatric lower limb bones for musculoskeletal modelling.

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.

Rotational Malalignment of the Knee Extensor Mechanism: Defining Rotation of the Quadriceps and Its Role in the Spectrum of Patellofemoral Joint Instability.

Osseous rotational malalignment of the lower limb is widely accepted as a factor contributing to patellofemoral instability, particularly in pediatric patients. Patellar instability occurs when the lateral force vector generated by the quadriceps exceeds the restraints provided by osseous and soft-tissue anatomy. The anatomy and activation of the quadriceps are responsible for the force applied across the patellofemoral joint, which has previously been measured using the quadriceps (Q)-angle. To our knowledge, the contribution of the quadriceps anatomy in generating a force vector in the axial plane has not previously been assessed. The primary aim of this study was to introduce the quadriceps torsion angle, a measure of quadriceps rotational alignment in the juvenile population. The secondary aims of this study were to determine the inter-assessor and intra-assessor reliability of the quadriceps torsion angle in the juvenile population and to investigate whether a large quadriceps torsion angle is a classifier of patellar dislocator group membership in a mixed cohort of patellar dislocators and typically developing controls. METHODS: Participants between the ages of 8 and 19 years were recruited as either controls or recurrent patellar dislocators. A total of 58 knees in both groups were assessed from magnetic resonance imaging scans of the entire lower limbs. Axial cuts midway between the superior aspect of the femoral head and the articular surface of the medial femoral condyle were used to calculate the proximal reference for the quadriceps torsion angle. The quadriceps torsion angle was defined as the angle between the line connecting the anterior aspect of the sartorius and the junction of the anterior and posterior compartments at the lateral intermuscular septum and the posterior condylar axis line. Inter-assessor reliability was calculated using the intraclass correlation coefficient. The relationship between the quadriceps torsion angle and the femoral torsion was assessed in the entire cohort. These values were compared between the control group and the dislocator group to determine if the raw values or an interplay between the 2 factors played a role in the pathoanatomy of recurrent patellofemoral dislocation. RESULTS: The quadriceps torsion angle was a reproducible assessment in both inter-assessor and intra-assessor reliability analyses. A moderate positive correlation (r = 0.624; p < 0.01) was found between the femoral torsion and the quadriceps torsion angle. Although the quadriceps torsion angle was a fair classifier of patellar dislocation group membership, femoral torsion was not. CONCLUSIONS: This study has quantified the rotational alignment of the extensor mechanism using the quadriceps torsion angle. The measurement is shown to be reliable and reproducible and a fair classifier of patellofemoral instability. CLINICAL RELEVANCE: This article introduces an objective measure of soft-tissue rotational malalignment in the pathogenesis of recurrent patellar dislocation.

Development and validation of subject-specific pediatric multibody knee kinematic models with ligamentous constraints.

Computational knee models that replicate the joint motion are important tools to discern difficult-to-measure functional joint biomechanics. Numerous knee kinematic models of different complexity, with either generic or subject-specific anatomy, have been presented and used to predict three-dimensional tibiofemoral (TFJ) and patellofemoral (PFJ) joint kinematics of cadavers or healthy adults, but not pediatric populations. The aims of this study were: (i) to develop subject-specific TFJ and PFJ kinematic models, with TFJ models having either rigid or extensible ligament constraints, for eight healthy pediatric participants and (ii) to validate the estimated joint and ligament kinematics against in vivo kinematics measured from magnetic resonance imaging (MRI) at four TFJ flexion angles. Three different TFJ models were created from MRIs and used to solve the TFJ kinematics: (i) 5-rigid-link parallel mechanism with rigid surface contact and isometric anterior cruciate (ACL), posterior cruciate (PCL) and medial collateral (MCL) ligaments (ΔLnull), (ii) 6-link parallel mechanism with minimized ACL, PCL, MCL and lateral collateral ligament (LCL) length changes (ΔLmin) and (iii) 6-link parallel mechanism with prescribed ACL, PCL, MCL and LCL length variations (ΔLmatch). Each model's geometrical parameters were optimized using a Multiple Objective Particle Swarm algorithm. When compared to MRI-measured data, ΔLnull and ΔLmatch performed the best, with average root mean square errors below 6.93° and 4.23 mm for TFJ and PFJ angles and displacements, respectively, and below 2.01 mm for ligament lengths (<4.32% ligament strain). Therefore, within these error ranges, ΔLnull and ΔLmatch can be used to estimate three-dimensional pediatric TFJ, PFJ and ligament kinematics and can be incorporated into lower-limb models to estimate joint kinematics and kinetics during dynamic tasks.