RELATIONS OF MECHANICAL-PROPERTIES TO DENSITY AND CT NUMBERS IN HUMAN BONE
RELATIONS OF MECHANICAL-PROPERTIES TO DENSITY AND CT NUMBERS IN HUMAN BONE
复制标题
DOI：
10.1016/1350-4533(95)97314-f
复制
发表时间：
1995-07-01
影响因子：
2.2
通讯作者：
ASHMAN, RB
中科院分区：
文献类型：
--
作者：
RHO, JY;HOBATHO, MC;ASHMAN, RB
8名受试者的皮质骨和松质骨的力学特性采用超声传输技术测定。从水中骨骼扫描获得的原始计算机断层扫描（CT）值被校正为Hounsfield单位。CT数与皮质骨力学性能的相关性较低（r(2)0.6）。这些结果表明，CT值可能仅用于预测松质骨的力学特性。模量在径向和周向之间的相关性很差。而松质骨的前后方向或中外侧方向的模量与S-I方向的模量之间存在良好的相关性。这些结果表明。皮质骨的S-I方向模量不能预测桡骨或周向，但松质骨可以预测。单独评估松质骨的线性模型和功率模型的预测能力大致相等。然而，幂函数在低密度和高密度值处给出了更好的数据拟合。根据骨的类型，从密度和CT数预测弹性模量的具体关系建议适用于人、皮质骨和松质骨。这些特定的相关性可能有助于许多研究人员开发更准确的模型；然而，这些假设需要进一步的研究来证明。
Mechanical properties of cortical and cancellous bone from eight human subjects were determined using art ultrasonic transmission technique Raw computerized tomography (CT) values obtained from scans of the bones in water were corrected to Hounsfield units. The correlations between CT numbers and mechanical property estimated from cortical bone were found to be low (r(2)0.6). These results suggest that CT values may be useful in predicting mechanical properties only for cancellous bone.Poor correlations were found between modulus in the radial or circumferential direction. and modulus in the superior-inferior direction for cortical bone whereas good correlations were found between modulus in the anterior-posterior direction or medial-lateral direction, and modulus in the S-I direction for cancellous bone. These results indicate that modulus in. the radial or circumferential direction could not be predicted from modulus in the S-I direction for cortical bone, but could be predicted for cancellous bone.The predictive capabilities of linear and power models evaluated for cancellous bone alone were approximately equal. However, the power function gives a better fit of data at the low and high density values.The specific relationships, depending on the types of bone, that Predict elastic modulus from density and CT numbers were suggested for human, cortical and cancellous bone. These specific correlations may help a number of researchers develop more accurate models; however, these hypotheses should be proven by further study.