Altered mechanical loading is a widely suggested, but poorly understood potential cause of cartilage degeneration in osteoarthritis. In rodents, osteoarthritis is induced following destabilization of the medial meniscus (DMM). This study estimates knee kinematics and contact forces in rats with DMM to gain better insight into the specific mechanisms underlying disease development in this widely-used model. Unilateral knee surgery was performed in adult male Sprague-Dawley rats (n=5 with DMM, n=5 with sham surgery). Radio-opaque beads were implanted on their femur and tibia. 8 weeks following knee surgery, rat gait was recorded using the 3D²YMOX setup (Sanctorum et al. 2019, simultaneous acquisition of biplanar XRay videos and ground reaction forces). 10 trials (1 per rat) were calibrated and processed in XMALab (Knörlein et al. 2016). Hindlimb bony landmarks were labeled on the XRay videos using transfer learning (Deeplabcut, Mathis et al. 2019; Laurence-Chasen et al. 2020). A generic OpenSim musculoskeletal model of the rat hindlimb (Johnson et al. 2008) was adapted to include a 3-degree-of-freedom knee. Inverse kinematics, inverse dynamics, static optimization of muscle forces, and joint reaction analysis were performed. In rats with DMM, knee adduction was lower compared to sham surgery. Ground reaction forces were less variable with DMM, resulting in less variability in joint external moments. The mediolateral ground reaction force was lower, resulting in lower hip adduction moment, thus less force was produced by the rectus femoris. Rats with DMM tended to break rather than propel, resulting in lower hip flexion moment, thus less force was produced by the semimembranosus. These results are consistent with lower knee contact forces in the anteroposterior and axial directions. These preliminary data indicate no overloading of the knee joint in rats with DMM, compared with sham surgery. We are currently expanding our workflow to finite element analysis, to examine mechanical cues in the cartilage of these rats (Fig1G).
Last decade, a shift towards operative treatment of midshaft clavicle fractures has been observed [T. Huttunen et al., Injury, 2013]. Current fracture fixation plates are however suboptimal, leading to reoperation rates up to 53% [J. G. Wijdicks et al., Arch. Orthop. Trauma Surg, 2012]. Plate irritation, potentially caused by a bad geometric fit and plate prominence, has been found to be the most important factor for reoperation [B. D. Ashman et a.l, Injury, 2014]. Therefore, thin plate implants that do not interfere with muscle attachment sites (MAS) would be beneficial in reducing plate irritation. However, little is known about the clavicle MAS variation. The goal of this study was therefore to assess their variability by morphing the MAS to an average clavicle. 14 Cadaveric clavicles were dissected by a medical doctor (MH), laser scanned (Nikon, LC60dx) and a photogrammetry was created with Agisoft photoscan (Agisoft, Russia). Subsequently a CT-scan of these bones was acquired and segmented in Mimics (Materialise, Belgium). The segmented bone was aligned with the laser scan and MAS were indicated in 3-matic (Materialise, Belgium). Next, a statistical shape model (SSM) of the 14 segmented clavicles was created. The average clavicle from the SSM was then registered to all original clavicle meshes. This registration assures correspondences between source and target mesh. Hence, MAS of individual muscles of all 14 bones were indicated on the average clavicle. Mean area is 602 mm2 ± 137 mm2 for the deltoid muscle, 1022 mm2 ±207 mm2 for the trapezius muscle, and 683 mm2 ± 132 mm2 for the pectoralis major muscle. The sternocleidomastoid muscle has a mean area of 513 mm2 ± 190 mm2 and the subclavius muscle had the smallest mean area of 451 mm2 ± 162 mm2. Visualization of all MAS on the average clavicle resulted in 72% coverage of the surface, visualizing only each muscle's largest MAS led to 52% coverage. The large differences in MAS surface areas, as shown by the standard deviation, already indicate their variability. Difference between coverage by all MAS and only the largest, shows that MAS location varies strongly as well. Therefore, design of generic plates that do not interfere with individual MAS is challenging. Hence, patient-specific clavicle fracture fixation plates should be considered to minimally interfere with MAS.
Addressing posterior tibial plateau fractures is increasingly recognized as an important prognostic factor for functional outcome. The treatment of posterior tibial plateau fractures is rather demanding and the implants are still standard, off-the-shelf implants. This emphasizes the need for a more thorough morphological study of the posterior tibial plateau, in order to treat these posterior fractures more adequately. We aimed to demonstrate anatomical variations of the tibia in order to develop better implants. After approval of the ethical committee 22 historically available CT scans of intact left tibia”s were segmented using Mimics (Materialise, Belgium). In order to perform principal component analysis, corresponding meshes are necessary. Mesh correspondence was achieved by deforming one selected source tibia to every other target tibia, through non rigid registration. The non-rigid registration algorithm was based on the algorithm described by Amberg et al (ref). After performing the non-rigid registration, principal component analysis was performed in Matlab (Mathworks, USA).Purpose
Method
Modification in joint loading, and specifically shear stress, is found to be an important mechanical factor in the development of osteoarthritis (OA). Cartilage shear stresses can be investigated using finite element (FE) modelling, where typically in vivo joint loading as measured by an instrumented hip prosthesis is used as boundary condition. However, subject-specific gait characteristics substantially affect joint loading. The goal of this study is to investigate the effect of subject-specific joint loading as calculated using a subject-specific musculoskeletal model and integrated motion capture data on acetabular shear stress. Three healthy control subjects walked at self-selected speed while measuring marker trajectories (Vicon, Oxford Metrics, UK) and force data (two AMTI force platforms; Watertown, MA). A subject-specific MRI-based musculoskeletal model consisting of 14 segments, 19 degrees of freedom and 88 musculotendon actuators, and including wrapping surfaces around the hip joint, was used. All analyses were performed in OpenSim 3.1. The model was scaled to the dimensions of each subject using the marker positions of a static pose. A kalman smoother procedure was used to calculate joint angles. Muscle forces were calculated using static optimization, minimizing the sum of squared muscle activations, and hip contact forces (HCF) were calculated and normalized to body weight (BW). To calculate shear stress, HCFs and joint angles calculated during the stance phase of gait were imposed to a hip finite element model (hip_n10rb) using FFEbio 2.5. In the model, femoral and acetabular cartilage were represented using the Mooney-Rivlin formulation (c1=6.817, bulk modulus=1358.86) and the pelvis and femur bones as rigid bodies. Peak HCF as well as maximal acetabular shear stress, magnitude and location, and the HCF at the time of maximal shear stress were compared between subjects.Introduction
Methods
