Addressing the bone risk of fracture of the subject with osteoporosis throughout bone composition

Osteoporotic hip fracture represents a high social and economic burden. Advanced algorithms based on homogenization theory allow us to estimate bone principal composition volume fractions, i.e. organic, hydroxyapatite, and water. Nevertheless, the power of discrimination of such fractions remains unexplored. The project consists of implementing an algorithm developed by the biomechanics and mechanobiology team of BCN MedTech to obtain the volume fraction of a clinical cohort and use statistical tools to discriminate fracture and non-fracture cases. The candidate will use a Matlab
code, statistical software, and finite element 3D models. The data consists of 128 subject-specific 3D models from dual x-ray absorptiometry (DXA) acquisitions. The candidate will have the support of all team members of the Biomechanics and Mechanobiology group.

 

Supervisors: Carlos Ruiz, Elham Alizadeh