Abstract

Photo-diagnosis of knee diseases can providenoninvasive, contrasted, deep penetrating and higher resolution optical and temperature images. In this study knee joint were modeled and simulated using finite element method, optical images and temperature images were generated for injured, osteoarthritis (OA) and normal knee conditions. Monte Carlo and diffusion approximation equation were used for absorption mapping and bioheat transfer equation to generate temperature information. Furthermore, the results found by Monte Carlo and diffusion approximation equation for the same parameters were compared. The results obtained in both Monte Carlo and diffusion approximation revealed that temperature mapping is capable of for differentiating injuries of knee, OA and normal knee joints compared with optical absorption images. In study the average net temperature rise scored 0.12 Kelvin for normal and 0.13 Kelvin for OA joints which is very significant at 3µs which become significant at its logarithmic value to produce temperature images and small to produce thermal damage on the tissue. To conclude, photo diagnosis knee joint model mimics for detecting injuries and analyzing diseases of knee and other similar boney-ligament/cartilage complex body structures in diagnostic imaging and monitoring procedures by using the combination of thermal and optical absorption properties of joints. This work has valuable impact for optical diagnostic imaging.

Keywords

osteoarthritis, monte carlo algorithm, diffusion approximation, medial, collateral, ligament, anterior cruciate ligament, bioheat transfer equation, lateral collateral ligament, finite element method, posterior cruciate ligament