Novel experimental and computational methods for identifying at-risk individuals

To address the limitation of current methods for identifying at-risk individuals we propose the development of novel subject specific computational diagnostic tools, validated against dynamic testing protocols where a drop-tower is used to produce a realistic simulation of a side-ways fall on the hip.

This level of analysis has not been previously performed, and along with providing clinically relevant structural information, it will give credibility and confidence to fracture mechanism and structural determinants of failure information derived from the non-invasive computational methods for fracture prediction.

A thorough understanding of the relevant fracture mechanisms, and the potential to develop new insights into possible therapeutic strategies to reduce osteoporotic fracture incidence, will have obvious benefits for both patients and society.