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Microarchitectural finite element models have become a key tool in analyses of trabecular bone. Robust, accurate, and validated constitutive models would enhance confidence in predictive applications of these models, and in their usefulness as accurate assays of tissue properties. Human trabecular bone specimens from the femoral neck (n = 3), greater trochanter (n = 6), and lumbar vertebra (n = 1) of eight different donors were scanned by μ-CT and converted to voxel-based finite element models. Unconfined uniaxial compression and shear loading were simulated for each of three different constitutive models: a principal strain based model, Drucker-Lode, and Drucker-Prager. The latter was applied with both infinitesimal and finite kinematics. Apparent yield strains exhibited minimal dependence on the constitutive model, differing by at most 16.1%, with the kinematic formulation being influential in compression loading. At the tissue level, the quantities and locations of yielded tissue were insensitive to the constitutive model, with the exception of the Drucker-Lode model, suggesting that correlation of microdamage with computational models does not improve the ability to discriminate between constitutive laws. Taken together, it is unlikely that a tissue constitutive model can be fully validated from apparent level experiments alone, as the calculations are too insensitive to identify differences in the outcomes. Rather, any asymmetric criterion with a valid yield surface will likely be suitable for most bone models.

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Traditional orthopaedic devices do not communicate with physicians or patients post-operatively. After implantation, follow-up of traditional orthopaedic devices is generally limited to episodic monitoring. However, the orthopaedic community may be shifting towards incorporation of smart technology. Smart technology in orthopaedics is a term that encompasses a wide range of potential applications. Smart orthopaedic implants offer the possibility of gathering data and exchanging it with an external reader. They incorporate technology that enables automated sensing, measuring, processing, and reporting of patient or device parameters at or near the implant. While including advanced technology in orthopaedic devices has the potential to benefit patients, physicians, and the scientific community, it may also increase the patient risks associated with the implants. Understanding the benefitrisk profile of new smart orthopaedic devices is critical to ensuring their safety and effectiveness. The 2018 FDA public workshop on orthopaedic sensing, measuring, and advanced reporting technology (SMART) devices was held on April 30, 2018, at the FDA White Oak Campus in Silver Spring, MD with the goal of fostering a collaborative dialogue amongst the orthopaedic community. Workshop attendees discussed four key areas related to smart orthopaedic devices: engineering and technology considerations, clinical and patient perspectives, cybersecurity, and regulatory considerations. The workshop presentations and associated discussions highlighted the need for the orthopaedic community to collectively craft a responsible path for incorporating smart technology in musculoskeletal disease care.

Background: Intervertebral body fusion devices (IBFDs) are a widely used type of spinal implant placed between two vertebral bodies to stabilize the spine for fusion in the treatment of spinal pathologies. Assessing mechanical performance of these devices is critical during the design, verification, and regulatory evaluation phases of development. While traditionally evaluated with physical bench testing, empirical assessments are at times supplemented with computational models and simulations such as finite element analysis (FEA). However, unlike many mechanical bench tests, FEA lacks standardized practices and consistency of implementation. Objectives: The objectives of this study were twofold. First, to identify IBFD 510(k) submissions containing FEA and conduct a comprehensive review of the elements provided in the FEA reports. Second, to engage with spinal device manufacturers through an anonymous survey and assess their practices for implementing FEA. Methods: First, a retrospective analysis of 510(k) submissions for IBFDs cleared by the FDA between 2013 and 2017 was performed. The contents of FEA test reports were quantified according to FDA guidance. Second, a survey inquiring about the use of FEA was distributed to industry and academic stakeholders. The survey asked up to 20 questions relating to modeler experience and modeling practices. Results: Significant gaps were present in model test reports that deemed the data unreliable and, therefore, unusable for regulatory decision-making in a high percentage of submissions. Nonetheless, the industry survey revealed most stakeholders employ FEA during device evaluation and are interested in more prescriptive guidelines for executing IBFD models. Conclusions: This study showed that while inconsistencies and gaps in FEA execution do exist within the spinal device community, the stakeholders are eager to work together in developing standardized approaches for executing computational models to support mechanical performance assessment of spinal devices in regulatory submissions.

The skin is a barrier and part of the immune system that protects us from harmful bacteria. Because indwelling medical devices break this barrier, they greatly increase the risk of infection by microbial pathogens. To study how these infections can be prevented through improved clinical practices and medical device technology, it is important to have preclinical models that replicate the early stages of microbial contamination, ingress, and colonization leading up to infection. At present, there are no preclinical ex vivo models specifically developed to simulate conditions for indwelling medical devices. Translocation of pathogens from outside the body across broken skin to normally sterile internal compartments is a rate-limiting step in infectious pathogenesis. In this work, we report a sensitive and reproducible ex vivo porcine skin–catheter model to test how long antimicrobial interventions can delay translocation. Skin preparation was first optimized to minimize tissue damage. The presence of skin dramatically decreased bacterial migration time across the polyurethane catheter interface from > 96 h to 12 h. Using visual colony detection, fluorescence, a luminescent in vitro imaging system, and confocal microscopy, the model was used to quantify time-dependent differences in translocation for eluting and non-eluting antimicrobial catheters. The results show the importance of including tissue in preclinical biofilm models and help to explain current gaps between in vitro testing and clinical outcomes for antimicrobial devices.