Peripheral quantitative computed tomography (pQCT)-based finite element analysis provides enhanced diagnostic performance in identifying non-vertebral fracture patients compared with dual-energy X-ray absorptiometry

Due to limitations of the predominant clinical method for diagnosing osteoporosis, an engineering model based on a dedicated CT scanner for bone density and structure was applied in fracture patients and controls. Improved diagnostic performance was observed, which supports its potential use in future research and clinical practice.

Introduction: Dual-energy X-ray absorptiometry (DXA), the predominant clinical method for diagnosing osteoporosis, has limitations in identifying individuals with increased fracture risk. Peripheral quantitative computed tomography (pQCT) provides additional information and can be used to generate finite element (FE) models from which bone strength properties can be estimated. We investigated the ability of pQCT-FE properties to distinguish peripheral low-trauma fracture patients from healthy controls, by comparison with DXA and standard pQCT.

Methods: One hundred and eight fracture patients (77 females aged 67.7 ± 7.9 years, 31 males aged 69.7 ± 8.9 years) were recruited from a hospital fracture liaison service. One hundred and twenty healthy community controls (85 females aged 69.8 ± 8.5 years, 35 males aged 68.9 ± 7.2 years) were recruited.

Results: Significant differences between groups were observed in pQCT-FE properties, especially at the 4% tibia site. Fracture odds increased most per standard deviation decrease in pQCT-FE at this location [shear stiffness estimate, k_shear, in females, OR = 10.34, 95% CI (1.91, 43.98); bending stiffness estimate, k_bend, in males, OR = 8.32, 95% CI (4.15, 33.84)]. Area under the receiver operating characteristics curve (AUROC) was observed to be highest with pQCT-FE properties at 4% the tibia site. In females, this was 0.83 for the pQCT-FE variable k_shear, compared with 0.72 for DXA total hip bone density (TH aBMD) and 0.76 for pQCT tibia trabecular density (Trb vBMD); in males, this was 0.81 for the pQCT-FE variable k_bend at the 4% tibia site, compared with 0.62 for TH aBMD and 0.71 for Trb vBMD. There were significant differences in AUROC between DXA and pQCT-FE variables in both females (p = 0.02) and males (p = 0.03), while no difference was observed in AUROC between primary pQCT and pQCT-FE variables.

Conclusions: pQCT-FE modeling can provide enhanced diagnostic performance compared with DXA and, given its moderate cost, may be useful in clinical settings.