Prediction of Individual Knee Kinematics From an MRI Representation of the Articular Surfaces

Objective: The knowledge of individual joint motion may help to understand the articular physiology and to design better treatments and medical devices. Measurements of in-vivo individual motion are nowadays invasive/ionizing (fluoroscopy) or imprecise (skin markers). We propose a new approach to derive the individual knee natural motion from a three-dimensional representation of articular surfaces. Methods: We hypothesize that tissue adaptation shapes articular surfaces to optimize load distribution. Thus, the knee natural motion is obtained as the envelope of tibiofemoral positions and orientations that minimize peak contact pressure, i.e. that maximize joint congruence. We investigated four in-vitro and one in-vivo knees. Articular surfaces were reconstructed from a reference MRI. Natural motion was computed by congruence maximization and results were validated versus experimental data, acquired through bone implanted markers, in-vitro, and single-plane fluoroscopy, in-vivo. Results: In two cases, one of which in-vivo, maximum mean absolute error stays below 2.2° and 2.7 mm for rotations and translations, respectively. The remaining knees showed differences in joint internal rotation between the reference MRI and experimental motion at 0° flexion, possibly due to some laxity. The same difference is found in the model predictions, which, however, still replicate the individual knee motion. Conclusion: The proposed approach allows the prediction of individual joint motion based on non-ionizing MRI data. Significance: This method may help to characterize healthy and, by comparison, pathological knee behavior. Moreover, it may provide an individual reference motion for the personalization of musculoskeletal models, opening the way to their clinical application.