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 patellofemoral instability, which is a common knee problem, caused by the abnormal movement of the patella (kneecap). Manual kinematic parameter calculations across time steps in a dynamic volumetric data set are time-consuming and prone to errors as well as inconsistencies. To overcome these limitations, the proposed approach supports automatic tracking of identified features of interest (FOIs) in the time domain and, thus, facilitates quantitative analysis processes in a semiautomatic manner. Moreover, it allows us to visualize the movement of the patella 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 patellofemoral data, discuss its benefits with respect to quantification as well as medical reporting, and describe how to generalize it to other complex joint movements.