STATIC AND FATIGUE FAILURE PROPERTIES OF THORACIC AND LUMBAR VERTEBRAL BODIES AND THEIR RELATION TO REGIONAL DENSITY

This study investigated (1) whether a characterization of the macroscopic architecture within the vertebral centrum would improve predictions of vertebral strength, (2) if regions in the centrum where least bone loss with age occurs are more predictive of vertebral strength, and (3) whether different patterns of the macroscopic architecture are predictive of static as compared to fatigue strength. To characterize the vertebral macroscopic architecture, a regional bone mineral density (rBMD) technique was used that estimated the cancellous density distribution (in 18 specific regions of the vertebral centrum) for vertebrae T7-L4, from spines of 20 female cadavers. Static and fatigue failure properties of whole vertebrae were obtained, and predictive models of static and fatigue failure properties of whole vertebrae were examined. We found that (1) vertebral failure properties were better predicted by combinations of vertebral regional cancellous density (multiple linear regressions) rather than by any individual region of cancellous density alone (simple linear regressions); (2) models using regions of density that demonstrated minimum decline with age [from the data of Flynn and Cody (Calcif. Tissue Int. 53, S170-S175 (1993))] resulted in better correlations with ex vivo vertebral static failure properties than models using density regions that showed maximum decline with age, and (3) static and fatigue characteristics required different density regions to reach significance. (A comparison of models predictive of static and fatigue failure properties revealed that anterior density regions were most often included in predictive models of the static properties while posterior regions were more predictive of the fatigue properties). The role of the distribution of cancellous density in contributing to vertebral strength has been demonstrated, and these results may be useful in future studies focused on disease processes such as osteoporosis.