Effects of loading rate on the of mechanical behavior of the femur in falling condition

The Surgeon General estimates that by 2020, half of all Americans could have weak bones due to bone loss. Osteoporosis causes more than 1.5 million fractures every year. Identifying effective interventions based on individual patient characteristics remains a major challenge. Proximal femur fractures are common and devastating events for individuals with osteoporosis. Since fracture is primarily a mechanical event, noninvasive predictions of fracture strength and location would be useful both for identifying at-risk individuals and evaluating treatment effects. However, bone fracture prediction is complicated due to the complex microstructure and nanostructure of bone. Bone is a highly heterogeneous material with rate-dependent mechanical behavior and large inter-individual variation. In this study, we designed two mechanical test procedures to understand the mechanical response of bone under impact and quasi-static load tests. The boundary conditions of the tests were designed in a way to simulate a fall to the side. The present study consists of three main parts: cadaver testing, quantitative image analysis, and finite element (FE) modeling. We obtained ten human femur bones and used high-resolution CT to quantify the microstructure and density of each sample. Specimen-specific FE models were created to evaluate the ability of various failure criteria to predict experimental fracture. Afterward, the samples were tested and their failure patterns were recorded. The fractured samples were rescanned to analyze the fractured surfaces. Our experimental results show that the loading necessary to fracture the femur samples is much higher in the impact tests. However, the toughening mechanisms are more pronounced in quasi-static tests. We found that FE model formulations were able to accurately predict femur stiffness and strength for quasi-static and impact conditions separately, but that no single formulation could account for the rate-dependent outcomes.