Torsional stiffness and strength of the proximal tibia are better predicted by finite element models than DXA or QCT

Individuals with spinal cord injury experience a rapid loss of bone mineral below the neurological lesion. The clinical consequence of this bone loss is a high rate of fracture around regions of the knee. The ability to predict the mechanical competence of bones at this location may serve as an important clinical tool to assess fracture risk in the spinal cord injury population. The purpose of this study was to develop, and statistically compare, non-invasive methods to predict torsional stiffness (K) and strength (T_ult) of the proximal tibia. Twenty-two human tibiae were assigned to either a "training set" or a "test set" (11 specimens each) and mechanically loaded to failure. The training set was used to develop subject-specific finite element (FE) models, and statistical models based on dual energy x-ray absorptiometry (DXA) and quantitative computed tomography (QCT), to predict K and T_ult; the test set was used for cross-validation. Mechanical testing produced clinically relevant spiral fractures in all specimens. All methods were accurate and reliable predictors of K (cross-validation r²≥0.91; error≤13%), however FE models explained an additional 15% of the variance in measured T_ult and illustrated 12-16% less error than DXA and QCT models. Given the strong correlations between measured and FE predicted K (cross-validation r²=0.95; error=10%) and T_ult (cross-validation r²=0.91; error=9%), we believe the FE modeling procedure has reached a level of accuracy necessary to answer clinically relevant questions.