Finite element modeling of meniscal tears using continuum damage mechanics and digital image correlation

Meniscal tears are a common, painful, and debilitating knee injury with limited treatment options. Computational models that predict meniscal tears may help advance injury prevention and repair, but first these models must be validated using experimental data. Here we simulated meniscal tears with finite element analysis using continuum damage mechanics (CDM) in a transversely isotropic hyperelastic material. Finite element models were built to recreate the coupon geometry and loading conditions of forty uniaxial tensile experiments of human meniscus that were pulled to failure either parallel or perpendicular to the preferred fiber orientation. Two damage criteria were evaluated for all experiments: von Mises stress and maximum normal Lagrange strain. After we successfully fit all models to experimental force-displacement curves (grip-to-grip), we compared model predicted strains in the tear region at ultimate tensile strength to the strains measured experimentally with digital image correlation (DIC). In general, the damage models underpredicted the strains measured in the tear region, but models using von Mises stress damage criterion had better overall predictions and more accurately simulated experimental tear patterns. For the first time, this study has used DIC to expose strengths and weaknesses of using CDM to model failure behavior in soft fibrous tissue.

Guidelines for Accurate Multi-Temporal Model Registration of 3D Scanned Objects

Changes in object morphology can be quantified using 3D optical scanning to generate 3D models of an object at different time points. This process requires registration techniques that align target and reference 3D models using mapping functions based on common object features that are unaltered over time. The goal of this study was to determine guidelines when selecting these localized features to ensure robust and accurate 3D model registration. For this study, an object of interest (tibia bone replica) was 3D scanned at multiple time points, and the acquired 3D models were aligned using a simple cubic registration block attached to the object. The size of the registration block and the number of planar block surfaces selected to calculate the mapping functions used for 3D model registration were varied. Registration error was then calculated as the average linear surface variation between the target and reference tibial plateau surfaces. We obtained very low target registration errors when selecting block features with an area equivalent to at least 4% of the scanning field of view. Additionally, we found that at least two orthogonal surfaces should be selected to minimize registration error. Therefore, when registering 3D models to measure multi-temporal morphological change (e.g., mechanical wear), we recommend selecting multiplanar features that account for at least 4% of the scanning field of view. For the first time, this study has provided guidelines for selecting localized object features that can provide accurate 3D model registration for 3D scanned objects.

In vitro method to quantify and visualize mechanical wear in human meniscus subjected to joint loading

The mechanical wear and tear of soft connective tissue from repetitive joint loading is a primary factor in degenerative joint disease, and therefore methods are needed to accurately characterize wear in joint structures. Here, we evaluate the accuracy of using a structured light 3D optical scanning system and modeling software to quantify and visualize volume loss in whole human meniscus subjected to in vitro joint loading. Using 3D printed meniscus replicas with known wear volumes, we determined that this novel imaging method has a mean accuracy of approximately 13 mm3, corresponding to a mean error of less than 7% when measuring meniscal volumetric changes of 0.2 cm3 (size of a pea). The imaging method was then applied to measure the in vitro wear of whole human menisci at four time points when a single cadaveric knee was subjected to one million cycles of controlled joint loading. The medial and lateral menisci reached steady state volumetric reductions of 0.72 cm3 and 0.34 cm3 per million cycles, respectively. Colorimetric maps of linear wear depth revealed high wear and deformation in the posterior regions of both the medial and lateral menisci. For the first time, this study has developed a method to accurately characterize volume loss in whole meniscus subjected to in vitro joint loading. This 3D scanning method offers researchers a new investigative tool to study mechanical wear and joint degeneration in meniscus, and other soft connective tissues.