RESUMO
The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. We show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.
RESUMO
For Ti6Al4V orthopedic and spinal implants, osseointegration is often achieved using complex porous geometries created via additive manufacturing (AM). While AM porous titanium (pTi) has shown clinical success, concerns regarding metallic implants have spurred interest in alternative AM biomaterials for osseointegration. Insights regarding the evaluation of these new materials may be supported by better understanding the role of preclinical testing for AM pTi. We therefore asked: (a) What animal models have been most commonly used to evaluate AM porous Ti6Al4V for orthopedic bone ingrowth; (b) What were the primary reported quantitative outcome measures for these models; and (c) What were the bone ingrowth outcomes associated with the most frequently used models? We performed a systematic literature search and identified 58 articles meeting our inclusion criteria. We found that AM pTi was evaluated most often using rabbit and sheep femoral condyle defect (FCD) models. Additional ingrowth models including transcortical and segmental defects, spinal fusions, and calvarial defects were also used with various animals based on the study goals. Quantitative outcome measures determined via histomorphometry including ''bone ingrowth'' (range: 3.92-53.4% for rabbit/sheep FCD) and bone-implant contact (range: 9.9-59.7% for rabbit/sheep FCD) were the most common. Studies also used 3D imaging to report outcomes such as bone volume fraction (BV/TV, range: 4.4-61.1% for rabbit/sheep FCD), and push-out testing for outcomes such as maximum removal force (range: 46.6-3092 N for rabbit/sheep FCD). Though there were many commonalities among the study methods, we also found significant heterogeneity in the outcome terms and definitions. The considerable diversity in testing and reporting may no longer be necessary considering the reported success of AM pTi across all model types and the ample literature supporting the rabbit and sheep as suitable small and large animal models, respectively. Ultimately, more standardized animal models and reporting of bone ingrowth for porous AM materials will be useful for future studies.
