Summary: | The influence of mechanical loading on bone modelling and remodelling has been, and still is the subject of many studies. It is widely accepted that the internal structure of long bones is orientated to the strains experienced throughout activities, and the morphometry of the bones are as a result of the loading. Although other influences play a role in bone development including, hormonal, nutritional and genetic. The internal structure is orientated in such a way that it transfers the loads experienced without being excessive in weight, providing an efficient weight bearing structure. Many researchers have analysed the adult femur but little work has been undertaken to understand femoral development in juveniles. Therefore the aim this work was to develop an understanding of the mechanical stresses and strains that the femur experiences during growth. The juvenile femur changes dramatically throughout growth. These changes occur from prenatal through to full maturity. The most notable include the ossification from a highly cartilaginous structure in the early years of development, to bone at ~18 years old, an increase in the length and angle of the neck, a change in the shaft torsion and a change in the bicondylar angle. Similarly, the development of movement patterns and locomotion in humans changes significantly throughout growth. Movement is restricted in utero, in neonates the movement begins to engage muscular activity, at 6 months a baby is usually able to sit upright; 9 months crawling begins; by 1 year old there is the ability to walk without support and at 4 years old an adult like gait pattern has developed. Full adult gait pattern has been documented to be achieved between 8-11 years old. In this work through gait analysis and musculoskeletal modelling the loads which the femur experiences at specific stages/ages of bipedal locomotion are analysed. Finite element analyses were then performed to develop an understanding of the stresses and strains of the proximal juvenile femur in relation to the attainment and development of bipedal gait. This was achieved by evaluating changes in these mechanical stresses and strains throughout different ages, relating them to the variations discovered in the gait patterns. Digitisation of the femora was performed on four specimens; prenatal, 3 years old, 7 years old and an adult. Following the scanning of the specimens in a micro CT scanner, some restoration to the damaged samples was required. Furthermore the dry samples were incomplete, and the models were needed to be modelled to accurately resemble fully intact femurs. The CT scans contained the full shaft however were missing the fully articulated proximal femur, due to the dry nature of the specimens the cartilages were absent. MRI scans which contained the femoral head data but were missing the full shaft were merged with the CT data to create a fully articulated femur for use in subsequent modelling. Gait analysis was performed on five children aged from 3-7 years old, with an average of five adults gait data used for comparison. The analysis showed that kinematic data was similar between all ages, however kinetic results revealed some differences. Ground reaction force in the 3 year old showed a higher heel strike compared to a higher toe off observed in adult during the gait cycle, indicating a lack of control in the 3 year old. Furthermore the 3 year old, compared to the other ages, had different values in joint moments. These joint moment results in particular played a role in the muscle forces produced from the musculoskeletal modelling. To obtain the muscle force data required for the FEA, musculoskeletal models were built. Testing the reliability of the musculoskeletal model was performed comparing the kinematic and kinetic data from the musculoskeletal modelling against the data obtained from the motion capture system. A good agreement was found between these data sets with the kinematics having the largest difference in the ankle plantar flexion of 8.6°. The kinetic results revealed almost exact matches. Further testing was attempted between the muscle force data and collected EMG. The collected EMG matched reported EMG in the literature and the onset and offset times of muscle activity corresponded well to muscle force peaks produced in the musculoskeletal model. Comparisons between the EMG and force through calculating the EMG as a force were inconclusive, although a degree of accuracy was shown but a more comprehensive method is required. It was concluded that with the accuracy of the kinematic and kinetic results the musculoskeletal modelling was accurate enough to give a true representation of physiological muscle forces to be modelled during FEA. Analysis of the musculoskeletal modelling results in the children revealed that the 3 year old had the highest significance between all the age groups. With the greatest significance in the hip flexors and abductors throughout the gait cycle. Joint reaction forces as a percentage of bodyweight were found to be much higher in the juvenile models. The adult model had a value of 265% bodyweight whereas the 3 year old showed a reaction force of 537% bodyweight. These differences observed in the musculoskeletal modelling had a direct effect on the FEA because the loads calculated here were applied to the finite element models to evaluate the effects that these would have on the stresses and strains during growth and development of the femur. FE models were built to represent a 3 year old, 7 year old and adult femur. Age specific loads calculated over 100% of a gait cycle, were applied to the models. The stress/strain analysis revealed some differences between the models but in general the areas exposed to high and low strain levels were similar. The similarities could suggest that each model was structurally adapted to the loads the femur regularly experiences. The thesis was successful in evaluating the stress and strain distribution apparent in the developing femur. However the work would be advanced by evaluating models from age ranges with a much more varied movement pattern i.e. crawling. This would increase an understanding of the structural optimisation of the femur.
|