Today, different implant designs exist in the market; however, there is not a
clear understanding of which are the best implant design parameters to achieve
mechanical optimal conditions. Therefore, the aim of this project was to
investigate if the geometry of a commercial short stem hip prosthesis can be
further optimized to reduce stress shielding effects and achieve better short-
stemmed implant performance. To reach this aim, the potential of machine
learning techniques combined with parametric Finite Element analysis was used.
The selected implant geometrical parameters were: total stem length (L),
thickness in the lateral (R1) and medial (R2) and the distance between the
implant neck and the central stem surface (D). The results show that the total
stem length was not the only parameter playing a role in stress shielding. An
optimized implant should aim for a decreased stem length and a reduced length
of the surface in contact with the bone. The two radiuses that characterize
the stem width at the distal cross-section in contact with the bone were less
influential in the reduction of stress shielding compared with the other two
parameters; but they also play a role where thinner stems present better
results
