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. 2001 Feb;9(2):101-11.
doi: 10.1053/joca.2000.0365.

Interindividual variability and correlation among morphological parameters of knee joint cartilage plates: analysis with three-dimensional MR imaging

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Free article

Interindividual variability and correlation among morphological parameters of knee joint cartilage plates: analysis with three-dimensional MR imaging

F Eckstein et al. Osteoarthritis Cartilage. 2001 Feb.
Free article

Abstract

Objective: To determine the range and variability of the cartilage volume, thickness, and articular surface areas in the knee joints of healthy male subjects, the association of these parameters within and between the knee joint cartilage plates, and their correlation with anthropometric variables.

Method: The right knees of 27 individuals (age 23 to 64 years) without cartilage damage were examined. Sagittal magnetic resonance imaging was with a fat-suppressed gradient echo sequence (resolution 2 x 0.31 x 0.31 mm(3)), quantitative parameters being computed for all cartilage plates.

Results: The total knee joint cartilage volume ranged from 16.6 to 31.4 ml, the size of the articular surfaces from 102 to 163 cm(2), and the mean cartilage thickness from 1.57 to 2.43 mm. The mean and maximal cartilage thickness were highest in the patella (2.76 and 5.72 mm). There was a significant correlation of the cartilage volume with the mean thickness (R=0.80) and with the joint surface areas (R=0.56), but not between the thickness and surface area (R=0.37). The association among the patella, tibia, and femur was 0.16 to 0.72 for volumes, 0.08 to 0.78 for thickness, and 0.24 to 0.62 for surfaces. The knee joint cartilage volume and the surface areas were significantly associated with the body height (R=0.51 and 0.57), but not the cartilage thickness (R=0.22).

Conclusion: There is a surprisingly high variability of the quantitative distribution of cartilage within the knee joint, with only moderate correlations between knee joint cartilage plates, and this variability cannot be adequately predicted based on anthropometric variables.

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