METHODOLOGICAL CHALLENGES FOR BIOMECHANICAL APPOACHES IN WINTER SPORTS

Many research questions related to performance or to injury prevention require biomechanical approaches and study plans that provide the best achievable compromise between internal and external validity. This is especially true for winter sport activities like skiing or snowboarding which cannot adequately be reproduced under laboratory conditions. The keynote presentation will illustrate how these methodological challenges have been addressed to answer three research questions related to injury prevention and the development of safety gear in winter sports: (1) the loading of the hip joint at different skiing manoeuvers (to answer the question if skiing is recommendable sport for people with hip replacement), (2) the effectiveness of wrist guards for the prevention of wrist or lower arm fractures in snowboarding (3) the development of algorithms for mechatronic ski bindings with the target to reduce the unchanged high rate of knee injuries

Generalised ligament model for finite element modelling of the knee

Introduction: A general ligament model for the tibiofemoral joint would pave the way for the use of finite element (FE) models in preoperative planning software as well as for the development of future implant designs for a variety of knee geometries. The aim was to develop a general ligament model applicable to knees from different specimens. Method: A FE model of the knee was developed containing the 3D geometries of the anterior and posterior cruciate ligaments (ACL, PCL) and the medial and lateral collateral ligaments (MCL, LCL). Beidokhti et al. showed that modelling the ligaments as a continuum leads to more accurate contact modelling. The material model of the ligaments was a multilinear elastic model based on a tensile test on a LCL with a variable strain offset as calibration parameter. In addition, an initial strain was assigned to the ligaments to avoid compressive forces and provide stability to the knee. A holistic approach to the ligament model was to consider the ligament forces, which is the ligament’s output affecting the tibiofemoral joint kinematics. Thus, the goal was to determine a set of forces as a general ligament model. The force set was based on seven different knee FE models that were independently calibrated based on robotic laxity testing of knee cadavers. The target forces were then applied to six new FE models. Results and discussion: For the ACL, the LCL and the MCL, the calibration forces were defined at 0° flexion and were 15N, 49N and 23N, respectively. For the PCL, the force was 35N at 90° flexion. Interestingly, the ligaments can exhibit large differences in forces at the flexion angles other than the one of calibration (Figure 2). In Figure 3, the different stress-strain curves are shown, which led to the targeted forces for the different knee models. These differences are due to the factors listed subsequently. Factors influencing ligament behaviour: • Subject-specific differences • Correct segmentation • Definition of attachment points • Different initial positions due to MRI • Ligament positioning e.g. larger knees produce a larger lever arm for the ligament • The smaller the cross-section of the ligament, the higher the stress in the ligament for the same force output → Challenges of a generalised material model Conclusions: The pitfall of a generalised ligament model is that it is generalised and that it does not fit the subject as good as possible. Hence subject-specific properties need to be considered as it would improve the predicted kinematics already shown by Beidokhti et al. A possibility would be to have a loose and stiff ligament force set, which could be applied according to subjectspecific laxity tests. A viable strategy for preoperative planning would also be to have a generative ligament geometry because segmenting the geometry is a time intensive procedure. This would be a compromise between subject-specific geometries and springs

Development of scalable finite element models based on knee laxity tests on cadavers

Aim of the study: The aim of the project was to use the results of laxity tests on cadaver knees to create scalable, subject-specific finite element (FE) models. The models were used to improve the surface geometry of unicondylar knee prostheses using optimization techniques. Material and methods: For the experimental tests, the alignment of the knee and the robot was defined by inserting carbon rods through the bones, recording CT data and then designing bone- and subject-specific 3D prints. As the FE-models rely on MRI images while the experiments use CT coordinate systems, there are differences in their positions. Therefore, a transformation matrix was used to correct the offset of the FE-model. With MeshLab the bones were aligned and then the position offsets calculated. The FE-model was built based on segmented MRI data using Mimics (Materialise NV) with the FE-program Ansys® Academic Research Mechanical (ANSYS Inc.). A multilinear elastic material model was selected as the material model for the ligaments with a uniaxial tensile test of a lateral collateral ligament as input. An initial area and length were assigned to calculate a stress-strain curve. In addition, a strain offset parameter was introduced to handle different strains. An additional internal/external stiffness was added. An important feature of the FE-model was to assign an initial strain to the ligaments. This maintains the actual geometry segmented from the MRI and helps to keep the ligament in tension. The level of detail chosen for the model also meant that there was only one principal ligament per laxity test. Results: This scalable parameter model of knee ligaments build was applied to six knees that had a native geometry and three different unicompartmental knee joint replacement geometries. The difference in position between the experiments and the FE-model could be offset. With knowledge of the transformation matrix, the FE-model could include the same implant position as implanted by the surgeon. Discussion: A reliable framework for the development of knee FE-models based on cadaver laxity testing was demonstrated. An improvement for future FE-models would be to provide fixation so that the MRI and CT scans are taken at the same position or by using fixed bone markers in both scans. Finally, initial stretching could be fixed to a certain strain value; however, the challenge is whether this solution remains scalable

Use of an industrial robot to record human knee kinematics in vitro - evaluation of the test method

Introduction: In vitro experiments using 6-axis industrial robots are a common method for studying human knee kinematics, recording passive path (PP) during flexion, and measuring knee laxity at various angles. There is only limited research on the reliability of this test setup even if it has been used countless times for in vitro experiments. To ensure reliability, the robot should have an automated determination of the forceand torque-free point at 0° flexion, high reproducibility, and sensitivity Method: Test specimens: An anonymized fresh-frozen human cadaveric right knee specimen with medial and lateral unicondylar knee prothesis was tested. Robot set up: All tests were carried out with a 6-df robotic system (KUKA KR 150; KUKA Robotics) equipped with a 6-component force-torque sensor (Omega 160 IP60; ATI Industrial Automation, tolerances: force 2.5N, moment: 0.5Nm). Finding the force and moment free state at 0° flexion: The goal was to develop a Matlab routine that automatically calculates the starting position, where no forces or torques are acting on the knee except for its own weight. The script determines the load on the robot arm and calculates the position where the knee is in a force-free and torque-free state, which will be used as the starting point of PP and the forces and moments will be set to zero. To test the accuracy of the tare program (TP), the tare point was determined 20 times. After each attempt, a manipulation was performed (e.g., internal rotation), and it was checked if the target values for forces and moments were within the measurement tolerances of the robot sensor. Reproducibility of the passive path (PP): The PP from 0° to 60° was repeated 21 times using the same starting point. The leg was unclamped and clamped again after each trial. Mean and standard deviation were determined for anterior-posterior displacement, internal and external rotation as well as varus and valgus moments. Results: Validation of tare program: The TP works well and has a hit rate of 90% across all force and moment directions. The most inaccurate is the regulation of the varus and valgus moments where five measurements were outside the tolerance. Reproducibility of passive path: Even with the same starting point 21 repetitions of PP cannot hit the same path twice. The largest range of correct solutions is observed for internal and external rotation. Discussion: TP can determine knee force- and moment-free state at desired knee angle reliably and is more accurate than a manual search. The reproducibility study of PP showed that many solutions exist for finding force and moment-free state for a knee flexion. This finding is particularly important for studies comparing cadaver knee prosthesis kinematics to the native state. Therefore, analyse absolute, not relative values when measuring laxity. Further, ligament tension and thus the knee stiffness decreases with each pass of passive pathway due to both increased ligament stretching and temperature changes in the specimen and room. Conditioning of the leg according to the same protocol before the test is therefore recommended

The ataxia (axJ) mutation causes abnormal GABAA receptor turnover in mice

Ataxia represents a pathological coordination failure that often involves functional disturbances in cerebellar circuits. Purkinje cells (PCs) characterize the only output neurons of the cerebellar cortex and critically participate in regulating motor coordination. Although different genetic mutations are known that cause ataxia, little is known about the underlying cellular mechanisms. Here we show that a mutated ax(J) gene locus, encoding the ubiquitin-specific protease 14 (Usp14), negatively influences synaptic receptor turnover. Ax(J) mouse mutants, characterized by cerebellar ataxia, display both increased GABA(A) receptor (GABA(A)R) levels at PC surface membranes accompanied by enlarged IPSCs. Accordingly, we identify physical interaction of Usp14 and the GABA(A)R alpha1 subunit. Although other currently unknown changes might be involved, our data show that ubiquitin-dependent GABA(A)R turnover at cerebellar synapses contributes to ax(J)-mediated behavioural impairment