Otterness I G, Le Graverand M-P H, Eckstein F
Division of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI, USA.
Osteoarthritis Cartilage. 2008 Jan;16(1):34-40. doi: 10.1016/j.joca.2007.05.010. Epub 2007 Jul 5.
To determine if anthropometric factors obtainable on routine examination can be used to estimate premorbid knee total subchondral bone area (tAB), cartilage surface area (AC), cartilage thickness (ThC), and cartilage volume (VC).
Young individuals (21-39 years old) without history of knee joint pain, injury or disease were studied. Magnetic resonance imaging of the right knee was used to determine tAB, AC, ThC and VC for knee cartilage. Multilinear regression and curve fitting by variance minimization were used to model the data.
VC and AC closely depended on tAB(1.5) in both men and women. This relationship subsumed all dependency on sex, height, weight and body mass index. In females, VC depended on height cubed and tAB on height squared. The relationship was much weaker in males. ThC was poorly related to tAB and VC. Confidence limits for VC standardized to tAB(1.5) were narrower than standardization to tAB or height.
The absence of a tight relationship of VC and tAB with height in males suggests that the factors stimulating bone and cartilage growth may be different between sexes. The high correlation between tAB and VC across both sexes suggests, however, that (opposite to measures from routine clinical examination) tAB(1.5) can provide individual reference values for VC, against which changes with age and disease can be estimated with high confidence.
确定在常规检查中可获取的人体测量学因素是否可用于估计病前膝关节全层软骨下骨面积（tAB）、软骨表面积（AC）、软骨厚度（ThC）和软骨体积（VC）。
对无膝关节疼痛、损伤或疾病史的年轻个体（21 - 39岁）进行研究。使用右膝磁共振成像来确定膝关节软骨的tAB、AC、ThC和VC。采用多线性回归和方差最小化曲线拟合对数据进行建模。
男性和女性的VC和AC都紧密依赖于tAB(1.5)。这种关系涵盖了对性别、身高、体重和体重指数的所有依赖性。在女性中，VC依赖于身高的立方，tAB依赖于身高的平方。在男性中这种关系则弱得多。ThC与tAB和VC的相关性较差。以tAB(1.5)标准化的VC的置信区间比以tAB或身高标准化的更窄。
男性中VC和tAB与身高缺乏紧密关系表明，刺激骨骼和软骨生长的因素在性别之间可能不同。然而，两性中tAB和VC之间的高相关性表明，与常规临床检查的测量结果相反，tAB(1.5)可以为VC提供个体参考值，据此可以高度自信地估计随年龄和疾病的变化。
