Medical implants are normally used in clinical practice to treat most orthopaedics situations involving bone fractures, deformities, dislocation, and lengthening. It should be noted that specific measures regarding biomechanical and biomaterial characteristics are required for a successful post-surgery procedure. Biomechanical evaluations on the medical implants could be performed by utilising computer and engineering technology. One of them is in silico studies using finite element method that could be simulated in high-performance computer. However, various assumptions are required in computer simulation, such as the constraints on data input and computer resources. This review paper discusses current approaches of constructing a finite element model of human bone with specific material properties for upper limb such as the shoulder joint, humerus, elbow joint, radius and wrist joint. Previous related literatures were reviewed from selected keywords and search engines. To narrow the literature search in this study, inclusion and exclusion criteria of the literature searching were applied. We looked at the current level of knowledge in this field and offered recommendations for future study. In conclusion, studies from previous literature have demonstrated several ways for developing mathematical models and simulating medical implants.

Introduction: Detecting breast cancer at earlier stage is crucial to increase the survival rate. Mammography as the golden screening tool has shown to be less effective for younger women due to denser breast tissue. Infrared Thermography has been touted as an adjunct modality to mammography. Further investigation of thermal distribution in breast cancer patient is important prior to its clinical interpretation. Therefore, thermal profiling using 3D computational simulation was carried out to understand the effect of changes in size and location of tumour embedded in breast to the surface temperature distribution at different breast densities. Methods: Extremely dense (ED) and predominantly fatty dense (PF) breast models were developed and simulated using finite element analysis (FEA). Pennes’ bioheat equation was adapted to show the heat transfer mechanism by providing appropriate thermophysical properties in each tissue layer. 20 case studies with various tumour size embedded at two asymmetrical positions in the breast models were analysed. Quantitative and qualitative analyses were performed by recording the temperature values along the arc of breast, calculating of temperature difference at the peaks and comparing multiple thermal images. Results: Bigger size of tumour demands a larger increase in breast surface temperatures. As tumour is located far from the centre of the breast or near to the edge, there was a greater shift of temperature peak. Conclusion: Size and location of tumour in various levels of breast density should be considered as a notable factor to thermal profile on breast when using thermography for early breast cancer detection.