Cartilage Thickness and Surface Roughness Patterns in Healthy and Osteoarthritis Knees: Novel 3D Analysis of Subjects from the Osteoarthritis Initiative. Issue 7 (18th July 2016)

• Record Type: Journal Article
• Authors: Maerz, Tristan; Newton, Michael Daniel; Osborne, Jeffrey D.; Gawronski, Karissa Marie Bassett; Baker, Kevin; Anderson, Kyle
• Is Part Of: Orthopaedic journal of sports medicine. Volume 4:Issue 7(2016.)Supplement 4
• Publication Date: 2016-07-18
• Subjects: Sports medicine -- Periodicals; Orthopedics -- Periodicals; Arthroscopy -- Periodicals; Arthroplasty -- Periodicals; Knee -- Surgery -- Periodicals; 616.7
• DOI: 10.1177/2325967116S00134
• Languages: English
• ISSNs: 2325-9671

Abstract

Objectives: Three-dimensional (3D) magnetic resonance imaging (MRI) enables characterization of articular cartilage (AC) morphology. AC is traditionally analyzed using mean cartilage thickness (MCT), but OA can occur without drastic changes in MCT due to regions of both thickening and thinning, as shown in recent studies. Our group recently developed a method to assess 3D AC morphology in terms of both MCT and surface roughness (Sa) using mesh parameterization, an image processing technique that projects 3D data onto a 2D domain. The objective of this study was to apply this technique to characterize changes in MCT and Sa in subjects from the Osteoarthritis Initiative (OAI) with varying degrees of OA. Methods: Under institutional approval, image data was obtained from OAI. Inclusion criteria were availability of a baseline 3D double-echo steady state (DESS) MRI of the right knee and Kellgren-Lawrence (KL) score. Exclusion criteria were history of systemic testosterone, estrogen, GNRH, PTH, or bisphosphonate use, prior fracture, knee replacement, hyaluronic acid or steroid injections, and evidence of unreported knee injury or other anomaly on x-ray review. From the resulting pool, 10 subjects (5 men and 5 women) were randomly selected from each KL grade (0 - 4). Using our parameterization method, AC regions of interest were isolated from the MRI stacks and converted to 2D height maps (Figure 1). MCT and normalized surface roughness (Sa) were calculated for the whole femur, whole tibia and individual compartments. Femurs and tibias of KL0, KL2 and KL4 subjects have been analyzed. Analysis of patellae and remaining KL grades is ongoing. Results were compared between groups using t-tests with α = 0.05. Results: Representative KL0 and KL4 AC thickness maps are shown in Fig1A, B. Compared to KL0, KL4 exhibits thinning with adjacent thickening on the medial femoral condyle (MFC). There were no significant differences in MCT between KL grades in any femoral compartment. On the tibia, KL0 exhibits congruent AC with natively-thicker AC at the weight-bearing aspect. KL4 tibiae exhibit global thinning with a zone of severe thinning on the medial plateau (MP). Whole-tibia MCT of KL4 was significantly lower compared to KL2 and KL0 (Fig. 1D). In contrast to MCT, Sa was highly sensitive to compartment-dependent degeneration. In the whole femur, Sa was significantly higher in KL4 compared to both KL2 and KL0. On the MFC, Sa increased steadily with increasing KL grade (Fig1E), and the lateral condyle of KL4 exhibited higher Sa compared to KL0. No differences in Sa were observed on the trochlea. On the tibia, Sa was significantly elevated in KL4 compared to both KL0 and KL2 in all compartments (Fig1F). Conclusion: The presented technique enabled repeatable visualization, compartmental segmentation, and quantification of MCT and Sa of the whole joint. No differences in femoral MCT were found, which can be attributed to adjacent thickening and thinning. Femoral and tibial OA changes were detected more sensitively using Sa, with significant increases observed in the whole femur and both condyles and plateaux. Significant differences in Sa between KL0 and KL2 femurs indicate sensitivity of this technique to subtle changes in early OA. More sensitive characterization of compartmental and sub-compartmental morphologic changes associated with OA can increase our understanding of its progression and facilitate more sensitive early diagnosis.