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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.

No abstract

The menisci are fibrocartilaginous soft tissues that act to absorb and distribute load across the surface of the knee joint. As a result of mechanical wear and large repetitive loading, meniscus tissue can begin to breakdown, or degenerate. Meniscus degeneration increases the risk of tearing, weakened tissue integrity, and the progression of osteoarthritis. Therefore, it is imperative to understand the wear behavior of whole human meniscus to identify conditions that may significantly increase the risk of degeneration. The objective of this study is to develop and validate an in vitro methodology for characterizing volumetric wear behavior in whole human meniscus using a 3D optical scanning system. This study was done in three parts. Part I and II consisted of assessing the accuracy and repeatability of the proposed methodology for meniscus tissue. Two surrogate models were developed for this purpose: (1) Simple Surrogate: Geometric Blocks and (2) Complex Surrogate: Menisci & Tibia Replicas. Part III utilized the method to quantify wear in whole human meniscus subjected to physiological loading conditions. One fresh-frozen cadaveric knee joint was potted in a custom designed and built knee simulator and subjected to four loading stages of 250,000 cycles. A 3D optical scanner was used to generate 3D renderings for pre- and post-wear conditions for both surrogates and human meniscus. An open-source software, CloudCompare, was then used to computationally evaluate volume loss. For the surrogate models, the process was repeated at varying wear depths, and the percentage error between real-life measured volumes and CloudCompare calculated volumes was determined. The human meniscus followed the same scanning procedure for pre- and post-wear; however, post-wear volume was recorded following each loading stage. Results from the simple surrogate model showed that the method was capable of measuring wear with < 2% error when detecting volumetric changes of 1.08 cm3 ; however, as defect depth decreased, the absolute mean percentage error increased (p < 0.001). The complex surrogate model showed significant difference when measuring wear in the lateral and medial meniscus (p < 0.05) with percentage errors of less than 7.9% when detecting volumetric changes of 0.4 cm3. The results obtained from whole human meniscus testing indicate that with an increase in loading cycles, a higher degree of meniscal wear and deformation is present. For the first time, this study provides a methodology to identify volumetric loss due to wear behavior in whole human meniscus. This is also the first study to provide comprehensive visualization and identification of global defects within the meniscus tissue. Results of this study have the potential to help identify the physical and biochemical factors that lead to meniscus degeneration thereby advancing fundamental knowledge of the etiology of degenerative wear within articulating soft tissue.