Predicting knee osteoarthritis

Treatment options for osteoarthritis (OA) beyond pain relief or total knee replacement are very limited. Because of this, attention has shifted to identifying which factors increase the risk of OA in vulnerable populations in order to be able to give recommendations to delay disease onset or to slow disease progression. The gold standard is then to use principles of risk management, first to provide subject-specific estimates of risk and then to find ways of reducing that risk. Population studies of OA risk based on statistical associations do not provide such individually tailored information. Here we argue that mechanistic models of cartilage tissue maintenance and damage coupled to statistical models incorporating model uncertainty, united within the framework of structural reliability analysis, provide an avenue for bridging the disciplines of epidemiology, cell biology, genetics and biomechanics. Such models promise subject-specific OA risk assessment and personalized strategies for mitigating or even avoiding OA. We illustrate the proposed approach with a simple model of cartilage extracellular matrix synthesis and loss regulated by daily physical activity

Subject-specific finite element analysis to characterize the influence of geometry and material properties in Achilles tendon rupture

Achilles tendon injuries including rupture are one of the most frequent musculoskeletal injuries, but the mechanisms for these injuries are still not fully understood. Previous in vivo and experimental studies suggest that tendon rupture mainly occurs in the tendon mid-section and predominantly more in men than women due to reasons yet to be identified. Therefore we aimed to investigate possible mechanisms for tendon rupture using finite element (FE) analysis. Specifically, we have developed a framework for generating subject-specific FE models of human Achilles tendon. A total of ten 3D FE models of human Achilles tendon were generated. Subject-specific geometries were obtained using ultrasound images and a mesh morphing technique called Free Form Deformation. Tendon material properties were obtained by performing material optimization that compared and minimized difference in uniaxial tension experimental results with model predictions. Our results showed that both tendon geometry and material properties are highly subject-specific. This subject-specificity was also evident in our rupture predictions as the locations and loads of tendon ruptures were different in all specimens tested. A parametric study was performed to characterize the influence of geometries and material properties on tendon rupture. Our results showed that tendon rupture locations were dependent largely on geometry while rupture loads were more influenced by tendon material properties. Future work will investigate the role of microstructural properties of the tissue on tendon rupture and degeneration by using advanced material descriptions

MRI Integrated with Computational Methods for Determining Internal Soft Tissue Loads as Related to Chronic Wounds

Excessive and prolonged internal soft tissue loads are one of the main factors responsible for the initiation of internal injuries that may, if ignored or untreated, escalate into chronic wounds. Since internal tissue loads cannot be measured in vivo, computational methods that incorporate the actual anatomy of the living body, are currently the best available resource for acquiring internal mechanical knowledge. In this chapter we discuss various methods that use computational modeling integrated with anatomical data, scanned by magnetic resonance imaging (MRI) in order to determine internal soft tissue loads. Specifically we will elaborate on linear and non-linear finite element (FE) methods and hyperelastic warping