Osteoarthritis (OA) is a highly multifactorial disorder that largely lacks information for proper patient stratification. The core pathophysiology of the disorder consists in a disregulation of articular chondrocyte activity. The later becomes catabolic and contributes to the destruction of the articular cartilage that induces, in turn, undue stimulations of the articular catabolic cartilages, feeding a vicious circle of feedback looped degenerative processes. Mechanical factors are thought to be important players and are transmitted down to the cells depending on patient morphology and body dynamics. Though they might provide important descriptors to classify population at risk to develop accelerated and most severe forms of OA, they cannot be measured clinically.
Finite element modelling has the potential to translate body mass and motion and joint morphological information into stress, strain and fluid velocity fields inside cartilage tissues, which will be exploited into this TFG. Specifically, the work will consist in the generation and analysis of personalised finite element models of the knee joints in a clinical cohort of 80 patients acquired in collaboration with the Rheumatology Service of the Hospital del Mar. An existing mesh scaling algorithm will be applied to personalise a full knee joint nonlinear finite element model from a collection of knee joint MRI. Then, the joint models will be mechanically loaded according to available information of patient gait analysis, and the typical stressors of cell mechanotransduction receptors will be extracted and classified in the light of the available patient information. Impact of tissue cartilage composition effect will be also assessed, based on a reduced set of histochemical analyses of patient knee joint cartilage, performed at IMIM.
Supervision: Jérôme Noailly, Carlos Ruiz Wills