Patient specific prognosis of disease progression in osteoarthritis
Reza Hosseini, PhD
Osteoarthritis (OA) involves degeneration of articular cartilage and changes to underlying bone. Because cartilage has limited repair capacity, it is believed that earlier intervention improves long-term clinical outcome. A key factor for early intervention to be successful is to establish whether for a particular patient, OA progression will be aggressive or mild, and under which circumstances adaptive or degenerative responses would prevail. We set out to develop a tool that can assist in making such difficult prognostic evaluations. Hypothesis: The premise is that in addition to biological factors, mechanical loading importantly determines OA progression. Excessive mechanical stimulation causes cartilage wear, inappropriate mechanical environments induce cell-mediated tissue differentiation, unfortunate load transfer between bone and cartilage induces sclerosis and osteophyte formation. These changes may result in a new equilibrium, or accelerate progression of OA. Past performance: Computational models have matured where it has become possible to predict locations of loading-induced cartilage damage, time courses of tissue differentiation and bone adaptation under (patho)physiological conditions. Together they capture essential aspects of progressive OA. In the ongoing GARP study (LUMC), prospective clinical and imaging data of OA progression at various stages are being collected.
Our objective is to develop and validate a computational tool that can be used to objectively predict the time course of OA progression in a patient-specific manner. Approach: Relevant parts of established numerical models will be put together to constitute an OA progression model. Simulations of OA progression are performed, starting with patient-specific input data. For tuning and subsequent validation, computed predictions of structural and compositional changes in cartilage and bone are corroborated against this patient’s own prospective data (GARP-study). End-product: The result is a validated predictive tool that assists in discriminating between mild and aggressive OA at an earlier stage than currently possible. In the future it may assist in identifying which patient would respond best to which joint-loading modification. This prediction does not directly interfere with the patient. Hence, there is no objective against immediate clinical implementation through our clinical collaborators.
Hosseini, S.M. (2014). Towards a damage model for articular cartilage. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: prof.dr. K. Ito & dr. C.C. van Donkelaar).