Lower cervical spine facet cartilage thickness mapping

SummaryObjectiveFinite element (FE) models of the cervical spine have been used with increasing geometric fidelity to predict load transfer and range of motion (ROM) for normal, injured, and treated spines. However, FE modelers frequently treat the facet cartilage as a simple slab of constant thickness, impeding the accuracy of FE analyzes of spine kinematics and kinetics. Accurate prediction of facet joint contact forces and stresses, ROM, load transfer, and the effects of facet arthrosis require accurate representation of the geometry of the articular cartilage of the posterior facets. Previous research has described the orientations of the facet surfaces, their size and aspect ratio, and mean and maximum thickness. However, the perimeter shape of the cartilaginous region and the three-dimensional distribution of cartilage thickness remain ill-defined. As such, it was the intent of this research to further quantify these parameters.MethodVertebrae from seven fresh-frozen unembalmed human cadavers were serially sectioned and the osteochondral interface and the articulating surface of each facet on each slice were identified. The cartilage thickness was recorded at nine equidistant points along the length of each facet. It was observed that facets tended to have elliptic or ovoid shapes, and best-fit ovoid perimeter shapes were calculated for each facet. The thickness distribution data were used to represent the entire three-dimensional cartilage distribution as a function of one variable, and a thickness distribution function was optimized to fit the thickness distribution. The antero-posterior and medial/lateral shifts of the thickness center relative to the geometric were calculated and reported.ResultsHigh correlation was observed between the ovoid perimeter shapes and the measured facet shapes in radial coordinates, indicating that the ovoid approximation is able to accurately represent the range of facet geometries observed. High correlation between the measured and fitted thickness distributions indicates that the fitting function used is able to accurately represent the range of cartilage thickness distributions observed.ConclusionUtilization of a more physiologic cartilage thickness distribution in FE models will result in improved representation of cervical spine kinematics and increased predictive power. The consistency observed in the thickness distribution function in this study indicates that such a representation can be generated relatively easily

Implantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healing

The relationship between modern clinical diagnostic data, such as from radiographs or computed tomography, and the temporal biomechanical integrity of bone fracture healing has not been well-established. A diagnostic tool that could quantitatively describe the biomechanical stability of the fracture site in order to predict the course of healing would represent a paradigm shift in the way fracture healing is evaluated. This paper describes the development and evaluation of a wireless, biocompatible, implantable, microelectromechanical system (bioMEMS) sensor, and its implementation in a large animal (ovine) model, that utilized both normal and delayed healing variants. The in vivo data indicated that the bioMEMS sensor was capable of detecting statistically significant differences (p-value <0.04) between the two fracture healing groups as early as 21 days post-fracture. In addition, post-sacrifice micro-computed tomography, and histology data demonstrated that the two model variants represented significantly different fracture healing outcomes, providing explicit supporting evidence that the sensor has the ability to predict differential healing cascades. These data verify that the bioMEMS sensor can be used as a diagnostic tool for detecting the in vivo course of fracture healing in the acute post-treatment period. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc

Development and biocompatibility characterization of a biomems sensor for monitoring the progression of fracture healing

[No abstract available

Comparison of eight published lumbar spine finite element models

Due to its ability to represent intricate systems with material nonlinearities as well as irregular loading, boundary, geometrical and material domains, the finite element (FE) method has been recognized as an important computational tool in spinal biomechanics. Current FE models generally account for a single distinct spinal geometry with one set of material properties despite inherently large inter-subject variability. The uncertainty and high variability in tissue material properties, geometry, loading and boundary conditions has cast doubt on the reliability of their predictions and comparability with reported in vitro and in vivo values. A multicenter study was undertaken to compare the results of eight well-established models of the lumbar spine that have been developed, validated and applied for many years. Models were subjected to pure and combined loading modes and their predictions were compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges; their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with previously published median in vitro values. However, the ranges of predictions were larger and exceeded the in vitro ranges, especially for facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with in vivo values. The simulations yielded median facet joint forces of 0 N in flexion, 38 N in extension, 14 N in lateral bending and 60 N in axial rotation that could not be validated due to the paucity of in vivo facet joint forces. In light of high inter-subject variability, one must be cautious when generalizing predictions obtained from one deterministic model. This study demonstrates however that the predictive power increases when FE models are combined together. The median of individual numerical results can hence be used as an improved tool in order to estimate the response of the lumbar spine