pQCT bone strength index may serve as a better predictor than bone mineral density for long bone breaking strength

Bone mineral density (BMD) is commonly used to predict osteoporotic fracture risk without considering the geometry of the bone. However, geometric parameters are also important in determination of bone strength. An index including both material and geometric properties may be therefore more relevant in prediction of fracture risk. We studied the correlation between parameters measured by noninvasive peripheral quantitative computed tomography (pQCT) and bone bending strength of the diaphysis of 45 fresh goat humeri and 27 femora. Multislice pQCT was used for measuring volumetric diaphyseal cortical BMD, total BMD, diaphyseal and cortical cross-sectional area (CSA), and cross-sectional moment of inertia (CSMI) and their derived bone strength indices (BSIs), including BSI_CSMI (cortical BMD × CSMI) and BSI_CSA (cortical BMD × cortical CSA). Conventional dual-energy absorptiometry (DXA) was also conducted to measure areal BMD of diaphysis for comparison. Ultimate fracture load was obtained via three-point bending test. Results showed that for femora, fracture load was correlated better with BSI_CSA (r = 0.697, P 0.001) than cortical BMD (r = 0.304, P 0.05) and total BMD (r = 0.387, P 0.05) measured using pQCT and areal BMD (r = 0.612, P 0.001) measured using DXA. For humeri, fracture load was also correlated with BSI_CSA (r = 0.579, P 0.001) but not with other pQCT parameters including cortical BMD and total BMD (r = 0.282 and 0.305, respectively; P 0.05, both). The best correlation was found with areal BMD measured by DXA (r = 0.760, P 0.001). In conclusion, pQCT noninvasive BSI_CSA derived from cortical BMD (material) and its cortical CSA (bone geometry or distribution) may serve as an important noninvasive index for predicting long bone bending strength. The bending strength was also predicted by bone mass (areal BMD) measured by DXA, an integration of bone mineral and geometry. Further clinical studies are needed to validate the predictive value of BSI in long bone osteoporotic fracture.