Distal radius fractures are one of the most common types of fractures to occur in older adults. Bone strength (e.g., failure load) of the distal radius can be estimated using finite element (FE) models generated from high-resolution peripheral quantitative computed tomography (HR-pQCT) images; however, these models are limited because they determine failure load under pure compressive loading conditions and neglect off-axis loads that occur during a fall on an outstretched hand. The objective of this research was to identify moment arms in a HR-pQCT distal radius FE model that best predicted off-axis experimental failure load with highest explained variance and least error.
We scanned the distal radius (9.5 mm site) of 21 fresh-frozen cadaveric forearms from female donors (82, SD 9 years) using HR-pQCT. We tested the specimens until fracture in a testing configuration set to simulate a fall on an outstretched hand to obtain experimental failure load. We created FE models which simulated off-axis loading. Specifically, we applied a point load at different medial-dorsal and lateral-dorsal moment arm combinations to determine predicted offaxis failure loads for different failure volumes and different failure criterion. We report the moment arm combination with the highest explained variance (R²) and lowest root mean squared error (RMSE%) in experimental failure loads.
When incorporating off-axis loading, applying a 1 mm dorsal moment arm explained up to 79% of variance in experimental failure load, improving explained variance from pure compressive loading by 4%. These findings suggest that accounting for off-axis loading in current HR-pQCT FE models appear to offer modest improvement to the prediction of distal radius failure load which may potentially help to improve identification of individuals at risk of wrist fracture, and prevention and treatment therapies.