Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.

The future in action: neurophysiological and behavioral evidence of anticipatory motor simulation.

The motor system can no longer be considered as a mere passive executive system of motor commands generated elsewhere in the brain. On the contrary, it is deeply involved in perceptual and cognitive functions and acts as an “anticipation device”. The present thesis investigates the anticipatory motor mechanisms occurring in two particular instances: i) when processing sensory events occurring within the peripersonal space (PPS); and ii) when perceiving and predicting others’actions. The first study provides evidence that PPS representation in humans modulates neural activity within the motor system, while the second demonstrates that the motor mapping of sensory events occurring within the PPS critically relies on the activity of the premotor cortex. The third study provides direct evidence that the anticipatory motor simulation of others’ actions critically relies on the activity of the anterior node of the action observation network (AON), namely the inferior frontal cortex (IFC). The fourth study, sheds light on the pivotal role of the left IFC in predicting the future end state of observed right-hand actions. Finally, the fifth study examines how the ability to predict others’ actions could be influenced by a reduction of sensorimotor experience due to the traumatic or congenital loss of a limb. Overall, the present work provides new insights on: i) the anticipatory mechanisms of the basic reactivity of the motor system when processing sensory events occurring within the PPS, and the same anticipatory motor mechanisms when perceiving others’ implied actions; ii) the functional connectivity and plasticity of premotor-motor circuits both during the motor mapping of sensory events occurring within the PPS and when perceiving others’ actions; and iii) the anticipatory mechanisms related to others’ actions prediction.