The early detection of Osteoarthritis (OA) treatment efficacy requires monitoring of small changes in cartilage morphology. Current approaches rely in carefully monitoring global cartilage parameters. However, they are not very sensitive to the detection of focal morphological changes in cartilage structure. This work presents the use of the statistical parametric mapping (SPM) for the detection and quantification of changes in cartilage morphology. The SPM is computed by first registering the baseline and the follow-up three dimensional (3D) reconstructions of the cartilage tissue. Once the registration is complete, the thickness changes for every cartilage point is computed which is followed by a model based estimation of the variance of thickness error. The cartilage thickness change and the variance estimations are used to compute the z-score map. The map is used to visualize and quantify significant changes in cartilage thickness. The z-map quantification provides the area of significant changes, the associated volume of changes as well as the average thickness of cartilage loss. Furthermore, thickness change distributions functions are normalized to provide the probability distribution functions (PDF). The PDF can be used to understand and quantify the differences among different treatment groups. The performance of the approach on simulated data and real subject data will be presented.

Date Published: 5 March 2007
PDF: 12 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651248 (5 March 2007); doi: 10.1117/12.710152

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)