Meniscal tear and extrusion are strongly associated with progression of symptomatic knee osteoarthritis as assessed by quantitative magnetic resonance imaging.

BACKGROUND: The relation between knee meniscal structural damage and cartilage degradation is plausible but not yet clearly proven. OBJECTIVES: To quantitate the cartilage volume changes in knee osteoarthritis using magnetic resonance imaging (MRI), and determine whether meniscal alteration predicts cartilage volume loss over time. METHODS: 32 patients meeting ACR criteria for symptomatic knee osteoarthritis were studied. MRI knee acquisitions were done every six months for two years. The cartilage volumes of different knee regions were measured. Three indices of structural change in the medial and lateral menisci were evaluated--degeneration, tear, and extrusion--using a semiquantitative scale. RESULTS: 24 patients (75%) had mild to moderate or severe meniscal damage (tear or extrusion) at baseline. A highly significant difference in global cartilage volume loss was observed between severe medial meniscal tear and absence of tear (mean (SD), -10.1 (2.1)% v -5.1 (2.4)%, p = 0.002). An even greater difference was found between the medial meniscal changes and medial compartment cartilage volume loss (-14.3 (3.0)% in the presence of severe tear v -6.3 (2.7)% in the absence of tear; p<0.0001). Similarly, a major difference was found between the presence of a medial meniscal extrusion and loss of medial compartment cartilage volume (-15.4 (4.1)% in the presence of extrusion v -4.5 (1.7)% with no extrusion; p<0.001). CONCLUSIONS: Meniscal tear and extrusion appear to be associated with progression of symptomatic knee osteoarthritis.

A model for global symmetry detection in dense images.

In this paper, a model is proposed for bilateral symmetry detection in images consisting of dense arrangements of local features. The model is elaborated on the basis of a psychophysical experiment showing that grouping precedes and facilitates symmetry detection. The proposed computational model consists of three stages: a grouping stage, a symmetry-detection stage, and a symmetry-subsumption stage. Reliance upon a preliminary grouping stage enables a significant reduction of the computational load for detecting symmetry. An implementation of the model is described, and results are presented, showing a good agreement of the model performance with human symmetry perception.