To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations?

Proximal femur strength estimates from computed tomography (CT)-based finite element (FE) models are finding clinical application. Published models reached a high in-vitro accuracy, yet many of them rely on nonlinear methodologies or internal best-fitting of parameters. The aim of the present study is to verify to what extent a linear FE modelling procedure, fully based on independently determined parameters, can predict the failure characteristics of the proximal femur in stance and sideways fall loading configurations. Fourteen fresh-frozen cadaver femora were CT-scanned. Seven femora were tested to failure in stance loading conditions, and seven in fall. Fracture was monitored with high-speed videos. Linear FE models were built from CT images according to a procedure already validated in the prediction of strains. An asymmetric maximum principal strain criterion (0.73% tensile, 1.04% compressive limit) was used to define a node-based risk factor (RF). FE-predicted failure load, mode (tensile/compressive) and location were determined from the first node reaching RF=1. FE-predicted and measured failure loads were highly correlated (R(2)=0.89, SEE=814N). In all specimens, FE models correctly identified the failure mode (tensile in stance, compressive in fall) and the femoral region where fracture started (supero-lateral neck aspect). The location of failure onset was accurately predicted in eight specimens. In summary, a simple FE model, adaptable in the future to multiple loads (e.g. including muscles), was highly correlated with experimental failure in two loading conditions on specimens ranging from normal to osteoporotic. Thus, it can be suitable for use in clinical studies.

Multiple loading conditions analysis can improve the association between finite element bone strength estimates and proximal femur fractures: a preliminary study in elderly women.

This is a preliminary case-control study on osteopenic/osteoporotic elderly women, testing the association of proximal femur fracture with minimum femoral strength, as derived from finite element (FE) analysis in multiple loading conditions. Fracture cases (n=22) in acute conditions were enrolled among low-trauma fractures admitted in various hospitals in the Emilia Romagna Region, Italy. Women with no history of low-trauma fractures were enrolled as controls (n=33). Patients were imaged with DXA to obtain aBMD, and with a bilateral full femur CT scan. FE-strength was derived in stance and fall configurations: (i) as the minimum strength among those obtained for multiple loading conditions spanning a domain of plausible force directions, and (ii) as the strength associated to the most commonly used single loading conditions. The association of FE-strength and aBMD with fractures was tested with logistic regression models, deriving odds ratios (ORs) and area under the receiver operating characteristic curve (AUC). FE-strength from multiple loading conditions better classified fracture cases from controls (OR per SD change=9.6, 95% CI=3.0-31.3, AUC=0.87 in stance; OR=9.5, 95% CI=2.9-31.2, AUC=0.88 in fall) compared to aBMD (OR=3.6, 95% CI=1.6-8.2, AUC=0.79 for total femur aBMD), while FE-strength results from the most commonly used single loading conditions were similar to aBMD. Only FE-strength from multiple loading conditions remained significant in age- and aBMD-adjusted models (OR=10.5, 95% CI=1.8-61.3, AUC=0.95). In summary, we highlighted the importance of considering different loading conditions to identify bone weakness, and confirmed that femoral FE-strength estimates may add value to aBMD predictions in elderly osteopenic/osteoporotic women.