Quantitative Analysis of Knee Movement Patterns Through Comparative Visualization

In this paper, we present a novel visualization approach for the quantitative analysis of knee movement patterns in time-varying data sets. The presented approach has been developed for the analysis of patello-femoral instability, which is a common knee problem, caused by the abnormal movement of the patella (kneecap). Currently, patello-femoral analysis is based on acquisitions performed during a 30 or 45 degrees of knee flexion, which is analyzed in so-called Skyline or Merchant views. Because of the limited range of considered knee flexions, this technique does not adequately reveal the instability of the kneecap at full extension. While 3D imaging of the straight knee can help to improve the diagnostic process, its static nature does not permit the analysis of the dynamics of the patellar under functional movements. Recently, 4D CT imaging has become available as a new modality for kinetic joint movement analysis. The inclusion of the time domain in 4D CT scans enables the acquisition of the kinematic behavior of joints under natural conditions. However, quantitative analysis on such 4D CT scans is challenging. Our approach investigates the quantitative kinematic analysis of complex joint movements in time series data. By supporting the ability to track features of interest (FOIs) in the time domain, the quantitative analysis process can be facilitated in a semi-automatic manner. Moreover, it allows us to visualize the movement of the patellar in the femoral groove during an active flexion and extension movement, which is essential to assess kinematics with respect to knee flexions. To further support quantitative analysis, we propose kinematic plots and time-angle profiles, which enable comparative dynamics visualization. As a result, our proposed visualization approach facilitates better understanding of the effects of surgical interventions by quantifying and comparing the dynamics before and after the operations. We demonstrate our approach using clinical time-varying patello-femoral data, discuss its benefits with respect to quantification as well as medical reporting, and describe how to generalize it to other complex joint movements.