Prevention of osteoporotic fractures requires accurate methods to detect the increase in bone fragility at an early disease stage as well as effective therapies to reduce the risk of bone fractures. Presently the prediction of the patient-specific bone fracture risk is primarily based on bone density, since this is the only parameter which can routinely be measured in vivo. However, these predictions might not always be precise because the fracture risk is also determined by the bone microarchitecture and the bone's loading conditions. The aim of this paper is to introduce and evaluate new methods which could contribute to a better quantification of bone fracture risk. Recently, a new approach, combining computational engineering methods (finite element (FE) method) and 3D high-resolution imaging techniques, has been introduced which c! an account not only for bone density but also for microarchitecture and loading conditions. High-resolution imaging techniques allow acquisition of 3D images of the bone microarchitecture, whereas FE methods applied to these images allow very precise calculation of the mechanical properties of bone. However, such a detailed FE analysis was not feasible for bone in vivo mainly because the resolution was not sufficient to measure the bone microarchitecture. It is shown here, from preliminary results, that the FE approach based on high-resolution images from a new CT scanner now allows prediction of the mechanical behavior of peripheral bones in vivo. It is expected that, eventually, the FE approach will lead to a better patient-specific fracture risk prediction than earlier methods based on bone density alone. Hence, with this new approach, it might be possible to detect the increase in bone fragility at an early stage of osteoporosis and it might also be possible to evaluate ! treatments more accurately.
|Technology and Health Care
|Published - 1998