Hayes W C, Piazza S J, Zysset P K
Harvard Medical School, Boston, Massachusetts.
Radiol Clin North Am. 1991 Jan;29(1):1-18.
In this review, we have made use of some simple engineering concepts to summarize current efforts relating QCT measures to bone density and strength. From a variety of in vitro experiments on cadaveric vertebrae and femora, it is evident that both apparent and ash densities are strong linear functions of QCT measures, with coefficients of determination ranging from 0.49 to 0.90 and relative errors from 44.9% to 7.1%. QCT data also can be used (with somewhat less confidence) to determine the compressive modulus (R2s from 0.36 to 0.68, relative errors from 45.0% to 35.5%) and compressive strength (R2s from 0.58 to 0.70, relative errors from 56.5% to 39.9%) of trabecular bone from the proximal femur and vertebral body. In cortical bone, material properties are only correlated weakly with QCT measures. Experiments designed to relate QCT data to failure loads for the proximal femur and vertebral body have been remarkably successful. Coefficients of determination have ranged from 0.32 to 0.93, with relative errors from 31.1% to 13.9%. However, when the in vitro failure loads determined in these experiments are compared against available estimates of in vivo loads on the spine and hip, it is apparent, at least in the elderly, that in vivo loads are relatively close to those that cause fracture in vitro. To assess the possibility of developing QCT-based clinical predictors of fracture risk for individual patients, we have introduced the concept factor of risk often used in engineering design to account for uncertainties in estimates of service loads and component strength. The factor of risk for a particular loading condition is defined as the ratio of expected service loads to the known failure loads. To extend this concept to densitometric fracture risk prediction in vivo, it is important to recognize that densitometric data must not only be used to predict the ultimate load carrying capacity of the region of interest, but that this ultimate load must then be compared to the forces expected in vivo under comparable loading conditions. One difficulty with this approach is that little is known about the in vivo forces that are associated with atraumatic age-related fractures of the hip and vertebrae and even less about the forces applied to the hip and spine during traumatic events such as falls. However, from available estimates of in vivo loads during bending and lifting, it is apparent that in the elderly, factors of risk for the spine can easily approach 1.(ABSTRACT TRUNCATED AT 400 WORDS)
在本综述中,我们运用了一些简单的工程学概念来总结当前将定量计算机断层扫描(QCT)测量值与骨密度和强度相关联的研究成果。从对尸体椎骨和股骨进行的各种体外实验可知,表观密度和灰密度均为QCT测量值的强线性函数,决定系数范围为0.49至0.90,相对误差为44.9%至7.1%。QCT数据还可用于(可信度稍低)确定股骨近端和椎体小梁骨的压缩模量(决定系数R²从0.36至0.68,相对误差从45.0%至35.5%)和抗压强度(决定系数R²从0.58至0.70,相对误差从56.5%至39.9%)。在皮质骨中,材料特性与QCT测量值的相关性较弱。旨在将QCT数据与股骨近端和椎体的破坏载荷相关联的实验取得了显著成功。决定系数范围为0.32至0.93,相对误差为31.1%至13.9%。然而,当将这些实验中确定的体外破坏载荷与脊柱和髋部体内载荷的现有估计值进行比较时,很明显,至少在老年人中,体内载荷相对接近体外导致骨折的载荷。为了评估开发基于QCT的个体患者骨折风险临床预测指标的可能性,我们引入了工程设计中常用的风险系数概念,以考虑服役载荷和部件强度估计中的不确定性。特定载荷条件下的风险系数定义为预期服役载荷与已知破坏载荷的比值。为了将这一概念扩展到体内骨密度骨折风险预测,重要的是要认识到,骨密度数据不仅必须用于预测感兴趣区域的极限承载能力,而且必须将该极限载荷与在类似载荷条件下体内预期的力进行比较。这种方法的一个困难在于,对于与髋部和椎体无创伤性年龄相关性骨折相关的体内力知之甚少,对于诸如跌倒等创伤事件期间施加于髋部和脊柱的力了解更少。然而,从弯曲和举升过程中体内载荷的现有估计值来看,很明显,在老年人中,脊柱的风险系数很容易接近1。(摘要截断于400字)