Automatic measurement and visualization of focal femoral cartilage thickness in stress-based regions of interest using three-dimensional knee models


Purpose: Thinning of cartilage is a common manifestation of osteoarthritis. This study addresses the need of measuring the focal femoral cartilage thickness at the weight bearing regions of the knee by developing a reproducible and automatic method from MR images. Methods: 3D models derived from semi-automatic MR image segmentations were used in this study. Two different methods were examined for identifying the mechanical loading of the knee articulation. The first was based on a generic weight bearing regions definition, derived from gait characteristics and cadaver studies. The second used a physically based simulation to identify the patient-specific stress distribution of the femoral cartilage, taking into account the forces and movements of the knee. For this purpose, four different scenarios were defined in our 3D finite element (FE) simulations. The radial method was used to calculate the cartilage thickness in stress-based regions of interest and a study was performed to validate the accuracy and suitability of the radial thickness measurements. Results: Detailed focal maps using our simulation data and regional measurements of cartilage thickness are given. We present the outcome of the different simulation scenarios and discuss how the internal/external rotations of the knee alter the overall stress distribution and affect the shape and size of the calculated weight bearing areas. The use of FE simulations allows for a patient-specific calculation of the focal cartilage thickness. Conclusions: It is important to assess the quantification of focal knee cartilage morphology to monitor the progression of joint diseases or related treatments. When this assessment is based on MR images, accurate and robust tools are required. In this paper we presented a set of techniques and methodologies in order to accomplish this goal and move toward personalized medicine.

In International Journal of Computer Assisted Radiology and Surgery, DOI:10.1007/s11548-015-1257-3