Computer simulating a clinical trial of a load-bearing implant: example of an intramedullary prosthesis

Abstract

Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted in an idealized or `average? patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population?effectively simulating a clinical trial. Specifically we hypothesise an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or `average? patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young?s modulus implant () to one with a higher Young?s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis in an idealized of `average? patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance?simulating a clinical trial?presents a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.