Prediction of individual knee motion: an in-vivo validation under physiological load

Quantification of individual joint motion may help understanding the articular physiology and designing better treatments and devices. Measurements of such a motion are nowadays invasive or imprecise [1]. We present a numerical model that allows prediction of individual joint motion from the shape of articular surfaces. We hypothesize that the articulations are shaped by an adaptation process to optimally distribute contact loads [2-4]. Individual knee motion under physiological loads can thus be obtained by minimizing a measure of peak contact pressure such as joint congruence [5]: the more congruent the articular surfaces, the smaller the peak contact pressure. This concept was previously applied and validated for cadaveric tibiotalar [6] and knee [7] joints. In this study, the model is validated in vivo on seven knees during weight bearing MRI.