Clinical Measurements of Bone Tissue Mechanical Behavior Using Reference Point Indentation

Abstract

Over the last thirty years, it has become increasingly clear the amount of bone (e.g. ‘bone quantity’) and the quality of the bone matrix (e.g. ‘bone quality’) both critically contribute to bone’s tissue-level mechanical behavior and the subsequent ability of bone to resist fracture. Although determining the tissue-level mechanical behavior of bone through mechanical testing is relatively straightforward in the laboratory, the destructive nature of such testing is unfeasible in humans and in animal models requiring longitudinal observation. Therefore, surrogate measurements are necessary for quantifying tissue-level mechanical behavior for the pre-clinical and clinical evaluation of bone strength and fracture risk in vivo. A specific implementation of indentation known as reference point indentation (RPI) enables the mechanical testing of bone tissue without the need to excise and prepare the bone surface. However, this compromises the ability to carefully control the specimen geometry that is required to define the bone tissue material properties. Yet the versatility of such measurements in clinical populations is provocative, and to date there are a number of promising studies that have utilized this tool to discern bone pathologies and to monitor the effects of therapeutics on bone quality. Concurrently, on-going efforts continue to investigate the aspects of bone material behavior measured by RPI, and the compositional factors that contribute to these measurements. There are currently two variants, cyclic- and impact- RPI, that have been utilized in pre-clinical and clinical studies. This review surveys clinical studies that utilize RPI, with particular emphasis on the clinical instrument, as well as the endeavors to understand the fundamental mechanisms of such measurements. Ultimately, an improved awareness in the tradeoffs and limitations of in vivo RPI is critical towards the effective and successful utilization of this tool for the overall improvement of fragility determination in the clinic.

Added Value of Impact Microindentation in the Evaluation of Bone Fragility: A Systematic Review of the Literature

“…Two hundred and seventy-seven duplicate articles in ≥2 electronic data bases were excluded, and 281 unique studies were further assessed; (Figure 2). Two hundred and forty-three of these were excluded on the basis of title and abstract: 218 studies were not using the OsteoProbe R , eight were using the OsteoProbe R either in animal studies (12)(13)(14) or in ex vivo human bone (15)(16)(17)(18)(19), two described primarily technical (21)(22)(23)(24)(25)(26)(27)(28), and seven specifically on RPI (7,9,20,(29)(30)(31)(32). Included in the final evaluation were 31 original articles and seven studies published only as meeting abstracts using the OsteoProbe R microindentation device in vivo in humans.…”

Inhibition of vascular endothelial growth factor in young adult mice causes low bone blood flow and bone strength with no effect on bone mass in trabecular regions

“…This BMD/fracture risk gap has led to the study of bone quality as a bone mass-independent contributor to fracture risk ( Fonseca et al, 2014 ). Bone properties that may influence fracture risk independent of bone mass can be assessed by various non-invasive imaging techniques (bone geometry, trabecular microarchitecture, and cortical microstructure) ( Manhard et al, 2017 ), a minimally invasive indentation method ( Chang et al, 2018 ); serum biomarkers of bone turnover, collagen cross-linking, and protein glycation ( Garnero, 2012 ); and analysis of bone biopsies (bone matrix composition, collagen fiber orientation, and degree of bone mineralization ( Roschger et al, 2014 ).…”

Uncertainty optimization of dental implant based on finite element method, global sensitivity analysis and support vector regression

“…5,6 Thus, more recent works are moving to develop new devices or techniques to obtain more accurate material parameters including elastic modulus and Poisson’s ratio. 7,8 The last area is the analysis and optimization of bio-implants through FEM. The main purpose is to study the interactions between biological tissues and implants, and the effect of design variables on the mechanical performance of bio-implants such as the stress at implant–bone interface, 9 the volume of implant 10 and the fatigue probability of implant auxiliary components.…”