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.

Objective: Early detection of degenerative changes in the cartilage matrix composition is essential for evaluating early interventions that slow down osteoarthritis (OA) initiation. T1rho and T2 relaxation times were found to be effective for detecting early changes in proteoglycan and collagen content. To use these magnetic resonance imaging (MRI) methods, it is important to document the topographical variation in cartilage thickness, T1rho and T2 relaxation times in a healthy population. As OA is partially mechanically driven, the relation between these MRI-based parameters and localized mechanical loading during walking was investigated. Design: MR images were acquired in 14 healthy adults and cartilage thickness and T1rho and T2 relaxation times were determined. Experimental gait data was collected and processed using musculoskeletal modeling to identify weight-bearing zones and estimate the contact force impulse during gait. Variation of the cartilage properties (i.e., thickness, T1rho, and T2) over the femoral cartilage was analyzed and compared between the weight-bearing and non-weight-bearing zone of the medial and lateral condyle as well as the trochlea. Results: Medial condyle cartilage thickness was correlated to the contact force impulse (r = 0.78). Lower T1rho, indicating increased proteoglycan content, was found in the medial weight-bearing zone. T2 was higher in all weight-bearing zones compared with the non-weight-bearing zones, indicating lower relative collagen content. Conclusions: The current results suggest that medial condyle cartilage is adapted as a long-term protective response to localized loading during a frequently performed task and that the weight-bearing zone of the medial condyle has superior weight bearing capacities compared with the non-weight-bearing zones.

Finite element modeling (FEM) can predict hip cartilage contact mechanics. This study investigated how subject-specific boundary conditions and joint geometry affect acetabular cartilage contact mechanics using a multi-scale workflow. For two healthy subjects, musculoskeletal models calculated subject-specific hip kinematics and loading, which were used as boundary conditions for FEM. Cartilage contact mechanics were predicted using either generic or subject-specific FEM and boundary conditions. A subject-specific mesh resulted in a more lateral contact. Effects of subject-specific boundary conditions varied between both subjects. Results highlight the complex interplay between loading and kinematics and their effect on cartilage contact mechanics.

Background: Deviations in knee joint geometry and alignment were previously related to an increased risk for knee OA. These were hypothesized to influence the load distribution over the articular cartilage. Therefore, this study evaluated the effect of altered knee joint geometry and alignment in the coronal and transverse plane on the medial–lateral load distribution and ligament strain using a musculoskeletal modeling approach. Methods: Joint kinematics during gait were measured in 15 healthy adults. Using different musculoskeletal models with altered geometry of the tibia plateau or knee joint malalignment in the coronal and transverse plane, the resulting muscle, ligament and contact forces were calculated. Next, the distribution of the load over the medial and lateral condyle was analyzed and compared to the reference loading distribution, with neutral geometry and alignment, using repeated-measures ANOVA and individual t-tests, with a Bonferroni-corrected alpha level. Results: Coronal plane malalignment significantly affected the load distribution. Small changes in coronal tibial slope had less pronounced effects on the load distribution, but increased ligament strains. Transverse plane malalignment only minimally affected the load distribution. Conclusion: Coronal plane knee malalignment affected knee loading, with increased varus alignment resulting in increased medial loading. This confirms a causal relation between coronal malalignment and increased medial compartment loading and suggests a potential role of aberrant coronal plane alignment on OA initiation. Altered coronal tibial slope induced increased ligament strains, potentially contributing to a cascade of knee laxity and subsequently more extreme knee malalignment.

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.

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.